0

CONFORMATIONAL TRANSITIONS IN

DRUG-DNA COMPLEXES

By

Ghazala Yunus

1

CONTENTS

Abbreviations

List of tables

List of figures

CHAPTER 1: Introduction

CHAPTER 2: Theory

CHAPTER 3: Transition & Stability of DNA-Dipyrandium Complex

CHAPTER 4: Thionine Induced Thermal Stability of Natural DNAs

CHAPTER 5: Conclusion

2

ABBREVIATIONS

% Percentage

Conc. Concentration

DNA Deoxyribonucleic acid

DSC Differential scanning calorimetry

ed. Edited

edn. Edition

et al. et alia (Latin: and other)

etc. et cetera

FTIR Fourier transform IR

hr hours

i.e. That is

IR Infrared

ITC Isothermal titration calorimetry

K Kelvin

M Molar

MW Molecular weight

nm Nanometer

ºC Degree centigrade

pH Potential of hydrogen ion

RNA Ribonucleic acid

Temp. Temperature

Tm Melting temperature

3

UV Ultra violet

UV-VIS Ultra violet - visible

viz. vide licet

ΔCp Change in heat capacity

ΔG Changes in free energy

ΔH Changes in Enthalpy

ΔS Changes in Entropy

4

LIST OF TABLES

Table No. Title Page No.

1.1 Thermodynamic parameters for intercalators and

minor groove binders

00

3.1 Transition parameters for dipyrandium binding to

poly d(AT)

00

4.1 Transition parameters for thionine binding to

various natural DNAs

00

5

LIST OF FIGURES

Figure

No. Title Page No.

1.1 DNA structure 00

1.2 Major and minor groove of DNA 00

3.1 Molecular structure of dipyrandium 00

3.2 Heat capacity and transition profiles for unbounded

and bounded DNA with dipyrandium

00

3.3 Half width of the heat capacity curves 00

4.1 Chemical structure of thionine 00

4.2 Heat capacity and transition profiles for thionine

bounded and unbounded CP-DNA. (A) Unbounded

state, (B) Bounded state at saturation

00

4.3 Heat capacity and transition profiles for thionine

bounded and unbounded HT-DNA. (A) Unbounded

state, (B) Bounded state at saturation

00

4.4 Heat capacity and transition profiles (inset) for

thionine bounded and unbounded ML-DNA. (A)

Unbounded state, (B) Bounded state at saturation

00

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CHAPTER 1

INTRODUCTION

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1.1. Introduction

In the present thesis author included detailed study of Drug-DNA

interaction that comprises stability of synthetic and natural DNA on binding with

various drug. The present chapter provides basic information to the next four

chapters, which include the work on theoretical analysis of Dipyrandium and

Thionine binding with synthetic polynucleotide [poly d(AT)] and natural DNA

(CP-DNA, ML-DNA, HT-DNA). The concluding chapter of the thesis provides all

pros and cons of the present work and their significance in the present scenario.

1.2. Drug-DNA interaction: Significance and future

potential

The study of drug-DNA interactions begins around 1960s but the binding

of steroid-diamines and aromatic molecules to synthetic and natural nucleic

acids has received considerable attention over the past several years (Araya et

al., 2007; Bruylants et al., 2005; Gabbay and Glaser, 1971; Gonzalez-ruiz et al.,

2011; Islam et al., 2009; Kunwar et al., 2011; Lane, 2001; Mahler and Dutton,

1964; Mahler et al., 1966; 1968. Paul et al., 2010). Molecular interaction of the

drug with deoxyribonucleic acid (DNA) is a field of high topical interest and may

have a great importance to its biological activity. The molecules can interact

with DNA in a variety of ways such as surface binding to their minor or major

grooves, intercalation between adjacent base pairs, or electrostatic binding.

There are number and variety of techniques devoted to the study of drug-DNA

interactions which are increasing continuously.

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DNA is a molecule of great biological significance in which all the

information governing life processes of the organism are stored (Figure 1.1).

The total DNA content of a cell is termed as genome which is unique for each

and every organism. A segment of DNA that code for a polypeptide is known

as gene which contains the information necessary to produce a functional

product, usually a protein. DNA has two main functions in the cell viz.

transcription and translation. In transcription process, information is retrieved

from the DNA by RNA and utilized to synthesize proteins in the body. During

replication, DNA undergoes self-replication process and regenerates two

identical strains. DNA present in the form of a double helix, where each strand

is composed of a combination of four nucleotides, adenine (A), thymine (T),

guanine (G) and cytosine (C). Within a strand these nucleotides are linked via

phosphodiester linkages. The two strands are held together primarily via

Watson Crick hydrogen bonds where A forms two hydrogen bonds with T and

C forms three hydrogen bonds with G. Specific recognition of DNA sequences

by proteins/ small molecules is achieved via the combination of hydrogen bond

acceptor/donor sites available on the major groove or minor groove of DNA

(Figure 1.2).

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Figure 1.1. DNA structure

Figure 1.2. Major and minor groove of DNA

Transcription and replication plays a vital role in survival and proliferation

of the cell as well as for smooth working of all body processes. DNA starts

transcribing or replicating only when it receives a signal, which is often in the

form of a regulatory protein binding to a particular region of the DNA.

Therefore, if the binding specificity and strength of this regulatory protein can

be imitated by a small molecule, then DNA function can be artificially

modulated, inhibited or activated by binding this molecule instead of the

protein. Hence, this synthetic/natural small molecule can act as a drug when

activation or inhibition of DNA function is required to cure or control a disease.

DNA activation would produce more quantities of the required protein, or could

induce DNA replication; depending on which site the drug is targeted. DNA

inhibition would restrict protein synthesis, or replication, and could induce cell

death (Sheikh et al., 2004). Regions of DNA involved in vital processes such as

origin of replication, promotion of transcription, etc., are of particular interest

10

as targets for a wide range of anticancer and antibiotic drugs (Chaires, 1997,

1998; Haq, 2002; Hurley, 2002.)

1.2.1. Mode of DNA binding with drugs/small molecules

Drugs and/or small molecules bind to DNA both covalently as well as

non-covalently. Covalent binding in DNA is irreversible and invariably leads to

complete inhibition of DNA processes and subsequent cell death. One of the

drug, anticancer antibiotic, covalently bind to DNA is cis-paltin. Non-covalently

bound drugs mostly classified into two classes viz. minor groove binders and

intercalators. Drugs with ability to minor groove binding (minor groove binders)

are usually crescent shaped, which complements the shape of the groove and

facilitates binding by promoting van der Waals interactions. Moreover, these

drugs can form hydrogen bonds to bases, typically to N3 of adenine and O2 of

thymine. Most of the minor groove binding drugs bind to A/T rich sequences.

This preference in addition to the designed propensity for the electronegative

pockets of AT sequences is probably due to better van der Waals contacts

between the ligand and groove walls in this region, since A/T regions are

narrower than G/C groove regions and also because of the steric hindrance in

the latter, presented by the C2 amino group of the guanine base (Sheikh et al.,

2004). Another group of Non-covalently bound drugs, intercalators, introduce

strong structural perturbations in DNA and contain planar heterocyclic groups

which stack between adjacent DNA base pairs. The complex is thought to be

stabilized by π-π stacking interactions between the drug and DNA bases. Non-

covalent binding is reversible and is typically preferred over covalent adduct

11

formation keeping the drug metabolism and toxic side effects in mind. However,

the high binding strength of covalent binders is a major advantage. Some of

the minor groove binders and intercalators are netropsin, berenil, distamycin,

mithramycin, hoechst 33258, pentamidine, nogalamycin and menogaril. As the

number of DNA–drug complex structures that have been solved by X-ray

crystallography and NMR analysis is increasing, it is becoming possible to

identify structural features and their energetic consequences that guide

observed properties like affinity and sequence selectivity.

In drug-DNA interaction, energetics of DNA recognition is not fully

understood at a molecular level, due mainly to the strong electrostatic

interactions prevalent in the system and van der Waals interactions (Jayaram

and Beveridge, 1996; Jayaram et al., 2002). A detailed account and

quantification of these contributions can help in addressing issues of both

practical and fundamental interest (Lazaridis, 2002). The fundamental interest

lies in tackling challenges involved in predicting ligand binding free energies

qualitatively. Among the structural and energetic angles, binding of small

molecules to DNA and proteins differs significantly. Protein–drug binding has

been explained by various popular models such as lock and key model, induced

fit model etc., and it is also believed that hydrophobic effects play an important

role in the binding process. However, a straightforward extrapolation of these

interaction models to DNA–drug systems is not feasible since there is no formal

active site in DNA, unlike enzymes/proteins. Certain base sequence dependent

chemical, structural, and conformational characteristics of DNA double helix,

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nonetheless, carry sufficient information for recognition by regulatory proteins

as well as small molecules (Saenger, 1983; Sinden, 1994), which bind non-

covalently or introduce small covalent modifications. Fairly strong and specific

binding is observed between some ligands and DNA and this is attributed to

various factors like hydrogen bonding etc.

For understanding of DNA–drug interaction, experimental studies plays

basic role. The necessary information on binding constants and corresponding

free energy, entropy, enthalpy, and heat capacity changes on complex

formation can be obtained by thermodynamic studies (Chaires, 1997; Cooper,

1999). This information enormously used to authenticate investigation based

on theoretical predictions and structural analysis. Along with initial studies

focused on thermodynamics of drug-DNA complex formation, Breslauer and his

colleagues recommended significant observation of enthalpy–entropy

compensation in drug-DNA systems and moreover contributed considerably to

developing thermodynamic profiles of these complexes (Zaunczkowski et al.

1987; Chalikian and Breslauer, 1998; Pilch et al., 1999). Among the range of

previous studies in the field of DNA–drug complexes modeling, some of the

initial studies focused on netropsin (Zakrzewska et al., 1984; Caldwell and

Kollman, 1986). These studies proposed models to explain the accurate

functions played by formal charges and hydrogen bonds along with snug fit in

the netropsin–DNA complex. Basically molecular mechanical calculations based

on energy minimization protocols were employed to broaden the horizons and

study different classes of DNA-binding molecules, such as minor groove binding

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netropsin, bisintercalating drug, triostin (Singh et al., 1986), and the covalent

binder acridine (Rao and Singh, 1986). Along with this, the era of free energy

calculations and various components contributing to it became a key area of

interest (Tembe and McCammon, 1984; Jorgensen and Ravimohan, 1985;

Beveridge and DiCapua, 1989). In this regard, results of relative binding free

energies calculation for distamycin and its analog was in good agreement with

experimental one (Singh et al., 1994). However, computation of absolute

binding free energies is a quite complicated assignment and remains semi-

quantitative at present scenario. Out of these some successful attempts have

been reported in which the theoretically determined absolute binding free

energy is in correspondence with experiment (Singh and Kollman, 1999; Pineda

and Zacharias, 2002; Spackova et al., 2003). These theoretical studies on drug-

DNA interactions have resulted in important contributions to the understanding

of binding in a few DNA–drug complexes. Since these studies typically focused

on a single DNA–drug complex (Srivastava et al., 2004 Singh and Kollman,

1999; Pineda and Zacharias, 2002; Spackova et al., 2003), the need to examine

a series of complexes persists to facilitate origin of a set of general principles.

1.2.2. DNA-interactive agents

The polynucleotide, DNA, is also one of the receptors molecule with

which various drugs or small molecules can interact. These DNA-interactive

drugs/agents are generally very toxic to normal cells. Thus, these drugs are

reserved only for life-threatening diseases such as cancers. There are four

general types of compounds that interact with DNA:

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1. Intercalators

2. Groove binders

3. Alkylating agents

4. DNA cleaving agents

In general aromatic or hetero-aromatic molecules bind to DNA by

intercalating between the base pairs of the double helix. The principal driving

forces for intercalation are stacking and charge-transfer interactions, while

hydrogen bonding and electrostatic forces also play a role in stabilization

(Neidle and Abraham, 1984). Additional interactions may further stabilize the

complex but in many cases, no covalent bond is formed. The result of

intercalation is that the DNA double helix becomes geometrically distorted and

the translation of the genetic code may be unable to properly function.

Intercalation, first described in 1961 by Lerman, is a noncovalent interaction in

which the drug is held rigidly perpendicular to the helix axis (Lerman, 1961).

This causes the base pairs to separate vertically, thereby distorting the sugar-

phosphate backbone and decreasing the pitch of the helix. Intercalation is

energetically favored because the energy that holds the intercalated molecule

must be greater than normal base stacking. It is cleared that intercalation does

not disrupt normal DNA hydrogen bonding. However, it can destroy the regular

helical structure by unwinding the DNA at the binding site and importantly,

interferes with DNA-binding enzymes like polymerases. Some examples of the

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intercalators are echinomycin, triostin A, acridine, cis-Platin, daunomycin,

adriamycin, actinomycin D, ethidium and propidium.

Groove binders are highly sequence-specific that interact with DNA

groove, which are recognized by these molecules. The grooves of DNA (major

and minor) differ in hydrogen-bonding, electrostatic potential and degree of

hydration. Most of the large protein molecules exhibit high specific binding with

major groove region of the DNA and small molecules prefer the minor groove.

Minor-groove binding molecules have aromatic rings linked by bonds with

torsional freedom. Because groove-binding agents can extent many nucleic acid

base pairs, they can have highly sequence-specific recognition. Sequence-

specific DNA-binding proteins generally interact with the major groove of B-

DNA, because it exposes more functional groups that identify a base pair.

However, there are some known minor groove DNA-binding ligands such as

netropsin, distamycin, pentamidine etc. (Zimmer and Wahnert, 1986; Dervan,

1986)

Alkylation reaction mostly represents an irreversible binding to DNA

basically with guanine. Alkylating agents add methyl or other alkyl groups onto

molecules where they do not belong. This alkylation proceeds with different

mechanism. In the first mechanism an alkylating agent attaches alkyl groups

to DNA bases and results in DNA fragmented by repair enzymes in their

attempts to replace the alkylated bases. In second mechanism alkylating agents

caused DNA damage due to formation of cross-bridges and bonds between

atoms in the DNA. Cross-linking prevents DNA replication and finally

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transcription. In third type of mechanism, alkylating agents causes the

mispairing of the nucleotides leading to mutations. There are six groups of

alkylating agents viz. nitrogen mustards, ethylenimes, alkylsulfonates,

triazenes, piperazines, and nitrosureas. Cyclosporamide is a classic example

alkylating agent and is one or the most widely used agents.

DNA cleaving agents (strand breaker) initially intercalate into DNA, and

can react in such a way as to generate radicals depending on the local

environmental and cellular metabolism. These radicals typically extract

hydrogen atoms from the DNA sugar-phosphate backbone, leading to scission

of DNA strand. Hence, these DNA-interactive compounds are metabolically

activated radical generators. The anticancer drug bleomycin acts as a strand

breaker and other examples are anthracycline, tirapazamine and enediyne.

Bleomycin is actually a mixture of several glycopeptyde antibiotics isolated from

a strain of the fungus Streptomyces verticellus. Bleomycin cleaves double-

stranded DNA selectively at 5’-GC and 5’-GT sites in the minor groove by a

process that is both metal ion and oxygen dependent (Povirk, 1989; Steighner

and Povirk, 1990; Stubbe, 1996).

1.2.3. Thermodynamics of Drug-DNA Interactions

Nucleic acid-binding drugs are designed to transform gene activity

and/or inhibit protein translation. Therefore, these biomolecules represent a

major target in drug development strategies designed to manufacture next

generation therapeutics for diseases. In order to optimize the clinical efficacy

of drugs and also to discover or design new drugs, it is essential to understand

17

and characterize the molecular basis of drug-DNA interactions, including

structural details and thermodynamics of binding.

Thermodynamic study of drug-DNA interaction determines the forces

involve during the binding of drugs to its target DNA. For the calculation of

observed free energy change (ΔGobs) for a drug-DNA interaction, the following

relationship is used:

𝛥𝐺𝑜𝑏𝑠 = −𝑅𝑇𝑙𝑛𝐾𝐵

Where, R = universal gas constant

T = temperature

KB = equilibrium binding constant (The value of KB

is dependent on pH, salt concentration, and other

experimental parameters)

Isothermal titration calorimetry directly measures the enthalpy of

binding (ΔHB) and equilibrium binding constant (KB), and the entropy change

associated with binding (ΔSB) can also be calculated by using following

equation:

𝛥𝐺𝑜𝑏𝑠 = 𝛥𝐻𝐵 − 𝑇𝛥𝑆𝐵

To determine KB and ΔGobs experimentally, a number of methods are

available. These methods include isothermal titration calorimetry and

spectroscopic techniques. In addition to KB and ΔGobs, it is also important to

18

determine ΔHB and ΔSB for a binding interaction. Isothermal titration

calorimetry is the only experimental method available to directly measure ΔHB.

The driving forces involve in drug-DNA interaction depends on the nature of

reaction. When enthalpy is favorable, the driving forces are hydrogen bonding,

van der Waals interactions, and electrostatic interactions. When entropy is

favorable, binding is driven by hydrophobic interactions, whereas unfavorable

entropic changes are due to loss of conformational degrees of freedom.

Change in heat capacity (ΔCp) due to binding of drugs can also be

calculated by isothermal titration calorimetry, by determining the dependence

of ΔH on temperature. The heat capacity change can also be estimated from

change in accessible surface area (ΔASA), and one can correlate calculated heat

capacity values to experimentally-determined values. There are number of

reports on energetic contributions to the binding free energy for drug-DNA

interactions in which free energy was calculated by the data obtained from

isothermal titration calorimetry (Chaires, 1998a; 1998b; Haq and Ladbury,

2000; Haq et al., 2000; Haq, 2002). It is required to keep experimental

conditions in mind as the observed binding constant and ΔGobs is dependent

these conditions such as buffer, ionic strength, temperature and concentration.

For drug-DNA interactions following five free energy components have been

identified:

1. Unfavorable contribution from conformational changes in the drug or

DNA due to binding (ΔGconf).

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2. Unfavorable contribution due to loss of rotational and translational

degrees of freedom upon binding (ΔGr+t).

3. Contribution from hydrophobic transfer of the unbound drug to the

DNA binding site (ΔGhyd). This value can be determined from heat

capacity change.

4. Contribution from coupled polyelectrolyte effects due to binding of

cationic ligands (ΔGpe). Binding constant and observed ΔG are

dependent on salt concentration. ΔGpe can be determined

experimentally by measuring the binding constant at different salt

concentrations.

5. Contribution due to non-covalent interactions, such as hydrogen

bond formation and van der Waals interactions (ΔGmol).

These free energy terms can be experimentally determined by

isothermal titration calorimetry, in combination with recognized empirical

relationships from other experimental data. This information is used to modify

drug structure to improve binding affinity and specificity of the drug.

Differential scanning calorimetry is also used to study the binding of

various drugs to synthetic and natural DNA (Marky, et al., 1983a; Marky, et al.,

1983b; Leng, et al., 1998; 2003). UV melting profiles and DSC have been used

to measure the binding affinity of a new bisintercalating antibiotic, while other

methods were not successful. DSC was also used to characterize the binding of

echinomycin to DNA, a bisintercalator that is difficult to study due to its poor

solubility (Leng et al., 2003). Thermodynamic parameters for some of the

20

intercalators and minor groove binders are given in table 1.1. On addition of

drug to DNA, the transition midpoint (Tm) increases, and when drug

concentration is high enough to saturate the binding sites on the DNA, McGhee

(McGhee and von Hippel, 1974) showed that:

1

𝑇𝑚0 −

1

𝑇𝑚=

𝑅

𝛥𝐻𝐷𝑁𝐴ln[(1 + 𝐾ℎ𝐿)

1/𝑛]

where 𝑇𝑚0 and 𝑇𝑚 are the melting temperature of drug-free and drug-bound

DNA, respectively,

1.2.4. Heat capacity changes associated with Nucleic acid folding

transitions

Besides the changes in free energy (ΔG), enthalpy (ΔH), and entropy

(ΔS) during the nucleic acid structures modification, heat capacity (CP) are also

changes significantly and affect the overall energetics of folding. Heat capacity

is defined as the amount of heat required to increase the temperature of a

substance by a unit degree and can be presented by:

𝐶𝑃 = [𝜕𝑞

𝜕𝑇]𝑃

Table 1.1. Thermodynamic parameters for intercalators and minor groove

binders

Drugs T ΔCp ΔGobs ΔHB TΔSB Reference

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Intercalators:

Ethidium 25 -140 -6.7 -9.0 -2.3 Chaires, 1998b

Actinomycin 10 -364 -8.5 -2.7 +5.8 Chaires, 1998b

Doxorubicin 20 -150 -8.9 -7.4 +1.5 Chaires, 1998b

Daunorubicin 20 -160 -7.9 -9.0 +1.1 Chaires, 1998b

Propidium 25 -150 -7.5 -6.8 +0.7 Chaires, 1998b

Minor Groove Binders:

Netropsin 25 -213 -8.7 -5.8 +2.9 Haq, 2002

Distamycin 20 NA -10.1 -12.3 -2.2 Chaires, 1998b

Berenil 25 -146 -8.0 +0.6 +8.6 Haq, 2002

Hoechst 33258 25 -330 -7.7 +4.4 +12.1 Haq et al., 1997

NA=Not available

Heat capacity is related to other fundamental thermodynamic

parameters also. Accordingly, different expressions relating CP to these other

parameters may be selected as a function of experimental ease or to highlight

some physical aspect of the system. For example, the most commonly

employed relationships of CP are

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𝐶𝑃 = [𝜕𝐻

𝜕𝑇]𝑃= [

𝜕𝑆

𝜕𝑇]𝑃

Hence, CP can be calculated as the temperature dependence of the

entropy or enthalpy. Changes in heat capacity (ΔCP), associated with the folding

or unfolding of a biopolymer can be expressed as:

𝛥𝐶𝑃 = [𝜕𝛥𝐻

𝜕𝑇]𝑃= [

𝜕𝛥𝑆

𝜕𝑇]𝑃

The above equation demonstrates the most common experimental

method for determining ΔCP, by measuring ΔH as a function of temperature.

The same equation also implies that ΔH and ΔS for a given transition change

together and in the same direction as a function of the ΔCP. Additionally, to

describe ΔCP with respect to ΔH and ΔS, we can also calculate change in heat

capacity with respect to ΔG that may be calculated as:

𝛥𝐶𝑃 = [−𝑇𝜕2𝛥𝐺

𝜕𝑇2]𝑃

Change in heat capacity is the second derivative of ΔG with respect to

temperature. Therefore, folding transitions associated with large ΔCP values

should exhibit significant curve in a plot of ΔG versus temperature. In terms of

physical origins, the heat capacity changes of a nucleic acid in solution derives

from a combination of solvent interactions (both solute–solvent and solvent–

solvent) and internal solute effects, such as conformational entropy,

electrostatics, vibrational modes, and others (sturtevant, 1977).

23

To find the impact of heat capacity changes on nucleic acid folding we

must go through the basics of heat capacity and its relation with the change in

temperature. In the absence of a ΔCP, the free energy associated with nucleic

acid unfolding is linear with temperature, as expressed by the Gibbs equation:

𝛥𝐺 = 𝛥𝐻 − 𝑇𝛥𝑆

However, introduction of a ΔCP introduces curvature in the temperature-

dependent stability profile, as reflected by the fact that CP is the second

derivative of G with respect to temperature. In the case of nucleic acid folding

transitions, it is highly likely that ΔCP itself significantly depends on temperature.

To accommodate a temperature-dependent ΔCP, the Gibbs law can be

modified:

∆𝐺 = (𝑇𝑟𝑒𝑓 − 𝑇

𝑇𝑟𝑒𝑓)∆𝐻𝑟𝑒𝑓 +∫ ∆𝐶𝑃𝑑𝑇

𝑇

𝑇𝑟𝑒𝑓−∫ ∆𝐶𝑃𝑑(𝑙𝑛𝑇)

𝑇

𝑇𝑟𝑒𝑓

where ΔHref is the change in enthalpy upon unfolding at an arbitrary reference

temperature (Tref) which is often set at the high-temperature melting midpoint

(TM) for convenience. Two related consequences of the temperature-dependent

curvature in ΔG imparted by ΔCP are i) that there exists a temperature of

maximum stability, Tmax, and ii) that unfolding can in principle be induced by

sufficiently deviating in temperature either above or below Tmax. The

phenomenon of cold unfolding or cold denaturation has been sufficiently

demonstrated for proteins and linked to the presence of a large, positive ΔCP

for unfolding (Privalov, 1990).

24

Since temperature-dependent changes in ΔH and ΔS largely offset one

another in ΔG, the zero ΔCP approximation is usually adequate for routine

stability estimations of short stretches of duplex at 37°C. The same may not be

true for applications that require high-precision estimates of ΔG for

hybridization of short duplexes. The temperature dependence of ΔCP conferred

by linked single strand equilibria further complicates the prediction of folding

energetic at temperatures distant from those at which parameter data are

collected. Predicted values of ΔH and ΔS are less accurate than those for ΔG

and vary especially between oligomeric and polymeric duplexes; inclusion of

ΔCP within stability calculations can reconcile these differences. A more recent

study found that explicit consideration of ΔCP was necessary to calculate

adequate differential thermodynamic parameters between various duplexes in

an effort to understand the physical basis of their different stabilities

(Tikhomirova et al., 2004; Mikulecky and Feig, 2006). Change in heat capacity

for nucleic acid structural changes have been obtained by different methods.

One of the methods is purely computational method with hydration of solvent

accessible surfaces. Some of the major experimental approaches used to

determine ΔCP are van’t Hoff method, differential scanning calorimetry (DSC)

method and isothermal titration calorimetry (ITC) method.

1.2.5. Thermodynamics in Drug Design

Drugs that interact with DNA have clinical significance especially for the

treatment of solid tumors, lymphoma, and leukemia. The interruption of DNA

replication is effective against rapidly reproducing cancer cells. More efficient

25

and targeted DNA-binding drugs can be achieved by designing new compounds

with multiple binding moieties that bind to specific DNA sequences. Application

of calorimetric methods to study the thermodynamics of nucleic acid-folding

transitions has gradually been improved in recent years. These improvements

escort to the production of high-precision microcalorimeters. Therefore, the

amount of high-resolution structural results about nucleic acids has developed

and clarified the physico–chemical interactions, which force the formation of

nucleic acid structures (Mikulecky and Feig, 2006; Gill et al., 2010). DSC

monitors the excess Cp of a nucleic acid in solution, and the temperature is

increased or decreased with a constant rate. Measuring the differential heat

flow between the sample and a reference accomplishes the excess Cp. When

sample and reference are scanned simultaneously, folding and unfolding

reactions occur in the nucleic acid as a consequence of absorbed or released

heat. This differential heat is gained with subtraction from the reference

thermal profile. Peaks obtained from types of DSC thermograms represent

folding transitions, and melting points of the transition occur near the jump

point of the curve. The melting point corresponds to a single molecular

transition, where ΔCp is equal to zero (Mikulecky and Feig, 2006). Peak results

are fitted in such ways that accommodate Limited ΔCp or ignore them. The later

leads to ΔHVH. The ratio of ΔHcal to ΔHVH could be used for study of intermediate

folding states, which occur near the melting point (Pilch, 2000; Breslauer et al.,

1992). Therefore, the DSC calorimeter is ideal for determining ΔCp and

measuring Cp directly (Mikulecky and Feig, 2006).

26

Latest drug discovery efforts have been dominated by structure-based

design concepts in which lead compounds are sought by attempting to match

their shapes with the complementary shapes of active sites of receptors using

known structures obtained by X-ray crystallography. However, it was formerly

noted that thermodynamic studies are an essential and necessary complement

to structural studies in drug design (Henry, 2001). Structural data alone, even

when coupled with the most sophisticated current computational methods,

cannot fully define the driving forces for binding interactions. Thermodynamics

provides quantitative data of use in elucidating these driving forces and for

evaluating and understanding at a deeper level the effects of substituent

changes on binding affinity (Weber and Salemme, 2003; Chaires, 2008).

1.3. Previous research work done

Ligands that can bind to nucleic acids have been the subject of much

research for the past five decade because DNA/RNA has been presumed to be

the intracellular targets for various small ligands and the ligand-nucleic acid

interaction creates the potential for regulating gene expression resulting in

therapeutic treatment for tumors and other bacterial and viral diseases.

Single strand nucleic acids do not form unique structure but rather

partially stacked helixes or random coils (Fresco and Klempere,r 1959; Saenger,

1984), with the degree of stacking being strongly temperature, ion-strength or

27

pH dependent (Fresco and Klempere,r 1959; Saenger, 1984). Among those

single nucleic acids, poly(A) and poly(U) have attracted much attention due to

their ability to form higher order or other secondary nucleic acid structures, and

the importance of their biological functions in cell growth. It is known that

poly(A) structure play an important role in gene expression in eukaryotic cells.

All mRNAs in eukaryotic cells contain a poly(A) tail at the 3’ end that is important

for the maturation and stability of mRNA and for the initiation of translation

(Zarudnaya and Hovorun, 1999; Munroe and Jacobson, 1990). Post-

translational polyadenylation of mRNA is catalyzed by the enzyme poly(A)

polymerase. Recent studies have found that neoPAP, a human polyadenylic

polymerase, is significantly over-expressed in human cancer cells (Topalian et

al., 2001; 2002). Thus, the new cancer therapeutic agents can be developed,

ones that bind to the poly(A) tail of mRNA and thereafter interfering with mRNA

processing by polyadenylic polymerase. However, very few molecules are

known to bind to a poly(A) single structure or to stabilize the poly(A)•poly(A)

duplex at neutral pH. Of this small number of ligands, berberine (Yadav et al.,

2005), coralyne (Xing et al., 2005, and palmatine (Giri et al., 2006) have been

studied.

The various conformations that DNA can adopt exhibit different binding

properties upon interacting with small ligands. As discussed previously, the

small ligands bind to duplex DNA/RNA mainly via intercalation and groove

binding. Since the major groove is larger than the minor groove, the majority

of groove binders selectively bind to the minor groove because their charges

28

and shapes are complementary. In addition to the groove size, the binding of

small ligands to the duplex is also sequence dependent. For example, Hoechst

33258 prefers AT-rich duplexes (Harshman and Dervan, 1985), with imidazole-

pyrrole-pyrrole (Bremer et al., 2000) recognizes the GC base pair. For most

drug-DNA interactions, these small molecules essentially act as a rigid body,

with little conformational change upon binding. However, the DNA/RNA duplex

conformation may be changed upon binding. In describing the B-form DNA

minor groove recognition, the lexitropson family of compounds, typically

netropsin and distamycin, have been studied extensively due to their inherent

high affinity for DNA duplex. Because of the changes in the minor groove width

and the unusually flexible TpA base step, the particularly binding preference for

these compounds is 5’-AATT and 5’-ATAT rather than 5’-TTAA and 5’-TATA

(Abu-Daya et al., 1995; Lane et al., 1993). Structural analyses obtained through

NMR and crystallographic studies have indicated that the recognition of a ligand

by DNA arises from H-bonded contacts with A/T, electrostatic interaction with

the backbone of the DNA, and the van der Waals interaction with the floor and

the walls of the groove. It has also been observed that the stacking interaction

between the O4’ atom of sugar and the pyrrole ring of the ligand contributes

to the stability of the complex formation (Pelton and Wemmer, 1988). In

addition to the structural findings, binding of lexitropsin with the DAN minor

groove is also accompanied by high binding affinity, favorable enthalpy changes

and binding entropy (Marky and Breslauer 1987).

29

The thermodynamics of drug-DNA interaction has been the focus of

much past research; however, the recent introduction of the high sensitive

micro-calorimetric technique has made this study in this yield more

straightforward. Consistent with other minor groove binding ligands, the

interaction between lexitropson and DNA are characterized by enthalpy-entropy

compensation mechanisms. Studies have shown that netropsin has a binding

affinity of 4.3×107 M-1 at 1:1 binding to the A3T2T3 oligomer, with the entropy

change contributing more to the binding free energy than enthalpy (Rentzeperis

et al., 1995). However, significant differential effects have been observed in

the binding of netropsin to poly(dA)•poly(dT) and poly(dA-dT)2 duplex systems,

suggesting that conformational change plays an important role in the binding

(poly(dA).poly(dT) experiences a conformational change) (Marky and Kupke,

1989). Additional classic B form DNA minor groove binders such as berenil,

Hoechst 33258, and propamidine have also been studied, results indicating

binding affinities in the range of 105 – 107M-1 and the heat capacity changes

(ΔCp) in the range of -150 ~ -400 cal/mol.K. The ΔCp value for minor groove

binders is typically higher than for intercalators, for which this value is usually

less than -200 cal/mol.K (Lane and Jenkins, 2000). Recently, the study

developed in Arya’s laboratories has found B-form DNA recognized by

aminoglycosides, which were previously thought to have no effect on B-form

DNA. This recognition, specifically dual recognition, was achieved by

synthesizing the neomycin-Hoechst 33258 conjugate (Willis and Arya, 2006) or

the neomycin-neomycin dimer (Arya et al., 2004) and then binding them to the

B-form duplex, in particular the AT-rich sequences. It was found that this

30

binding affinity is significantly higher than the classic B-form DNA binders

mentioned previously. These findings open the door for the development of

compounds that target the B-form DNA duplex. Recognition of A-form nucleic

acid, in particular the RNA duplex, by small ligands, however, exhibits a higher

binding affinity than the B-form DNA systems. A good example is the 16S A site

rRNA interaction with aminoglycosides (Kaul and Pilch, 2002). As discussed

above, this system was found to achieve a high binding affinity in the

nanomolar range, but different from the B-form DNA-minor groove binder

system, this binding is predominately enthalpy driven and the binding site is

within the major groove of the RNA. Very few small molecules, however, have

been found to be able to bind to the DNA•RNA hybrid duplex. Recent report

has shown that ethidium bromide is the preferred catalyst for this hybrid

recognition (Ren and Chaires, 2001). The binding affinity is in low micromolar

range. Aminoglycosides, were also found by Arya to bind to this hybrid in the

100 nM range. The methidium-Neomycin conjugate was subsequently

synthesized to achieve a high binding affinity and specificity of drug binding to

DNA•RNA hybrid. Initial results have shown the powerfulness of this conjugate,

which binds to the DNA•RNA hybrid specifically at an affinity of approximately

0.1 nm.

To date, the only full and detailed conformational information about the

DNA triplex comes from NMR studies. In addition to the conformational change,

the stability of the triplex has found to be much lower than its corresponding

duplex because of the charge neutralization resulting from the high

31

electronegative potential formed when three backbones are associated with

one another. Bringing in a positive charge on the third strand (Plum and

Breslauer, 1995), replacing the phosphodiester with a peptide at the backbone

(Cherny et al., 1993), introducing the ionic strength of the solution (Cheng and

Pettitt, 1992), and applying polycations (aminoglycosides) (Arya et al., 2001),

all have been shown to increase the stability of the triplex effectively. Even

though the formation of triplex is slow and less stable than the formation of

duplex, this structure has received much attention as an antigene strategy.

Triplex forming oligonucleotide has served as a potential genetic drug

regulating the gene expression after binding. Triplex formation also performs

numerous functions in biological systems. The replication of polynucleotide is

inhibited by the third-strand binding. In addition, HIV DNA has been reported

to be inhibited from integrating into host genomes (Bouziane et al., 1996).

Cooney and his coworkers have demonstrated the specific inhibition of

transcription by means of triplex formation at the poly(purine).poly(pyrimidine)

sites in the promoter regions (Cooney et al., 1988). Because of the numerous

activities the triplex may exhibit in the biological systems, increasing its stability

has been the focus of much research, with many endeavors being conducted

using small ligands. Intercalators such as acridines, ethidium, proflavine, and

ruthenium complexes (Wilson et al.,1994; Cassidy et al., 1994; Choi et al.,

1997; Mergny, et al., 1991), as well as DNA minor groove-binding ligands such

as berenil, netropsin, and Hoechst 33258 (Durand et al., 1994a; Park and

Breslauer, 1992; Durand et al, 1994b), have been shown to bind to DNA triplex.

However, those ligands do not bind to the triplex selectively, and some of them

32

even destabilize it. Benzo(e)pyridoindole, the first triplex-specific ligand

described (Mergny et al., 1992), binds to the triplex through an intercalation

mechanism, increasing the melting temperature of triplex over the duplex

significantly. Aminoglycosides have been shown in Arya’s laboratories to

stabilize triplex nucleic acids both selectively and significantly. Among these

aminoglycosides, neomycin exhibits the most potent effect, while, neomycin is

the first groove-binding ligand to result in triplex stabilization effect. Molecular

modeling has suggested that neomycin binds within the Watson-Hoogsteen

groove (Arya et al., 2003) formed between the third strand and the pyrimidine

strand.

The formation of a tetraplex or a quadruplex DNA structure has been

suggested as a potential chemotherapeutic target of a new antitumor

compound. This structure is formed from the tandemly repeating guanine

clusters, present primarily in the single stranded segment at the 3’ ends of

chromosomal DNA and characterized by a stacked arrangement of several G4

planar tetrads in which each G interacts with the adjacent one via forces of the

Hoogsteen bonds. These G-rich sequences occur frequently in human genomes

and in many other organisms (Huppert and Balasubramanian, 2005; Todd et

al., 2005). The formation of G-tetraplex has been reported to exhibit many

biological functions. For example, G-tetraplex has been found to exist at the

promoter region of oncogenes such as c-myc (Simonsson et al., 1998). Of the

many G-rich sequences in the organisms, telomere has been the primary focus

over the past few years due to its important biological role and its potential as

33

an antitumor target. Targeting the G-tetraplex with small ligands to improve its

stability has been the subject of much recent research. One of the first studies

involved the binding of ethidium bromide to the G-tetraplex d(T4G4)4 (Guo et

al., 1992). Arya’s laboratory has studied the binding of aminoglycosides,

specifically neomycin, to the G-tetraplex d(T2G20T2)4 using sodium and a pH of

6.8.

A huge number of studies have been reported on vibrational dynamics

of biopolymer system having different confirmations (Prasad et al., 1996; Gupta

et al., 2008; Srivastav et al., 1997; Krishnan and Gupta, 1970a, 1970b; Singh

and Gupta, 1971; Dwivedi and Gupta, 1972; Gupta et al., 1973; Burman et al.,

1995a, 1995b; Gupta et al., 1995). The analysis in most of these cases is based

on separation of the vibrational spectrum into group and skeletal vibrations.

The former are taken from computationally fitted IR and Raman data and the

latter by using the two-parameter Tarasov model (Wunderlich and Bu, 1987)

and fitting to low temperature heat capacities. The vibrational dynamics of

poly(L-glutamine) was interpreted by LaVerne and coworkers from the

dispersion and dispersion profile of the normal modes of poly(L-glutamine) as

obtained by Higg’s method for infinite systems (LaVerne et al., 2009).

Additionally, the dispersion curves give information of the degree of coupling

and the dependence of the frequency of a given mode on the sequence length

of ordered conformation. These curves also facilitate a correlation of the

microscopic properties, such as specific heat, free energy and enthalpy.

1.4. Methods used in previous studies and in present work

34

Advancement in the innovation of nucleic acid binding drugs obviously

relies on the availability of analytical methods or procedures that judge the

efficiency and nature of interactions between nucleic acids and their putative

ligands. A range of novel methods for these studies have emerged in current

years, and methods for studying DNA/Drug interactions highlights new and

non-conventional methods for exploring nucleic acid/ligand interactions. The

structure of these systems can be studied experimentally as well as

theoretically. From the conventional UV-VIS spectrophotometry to the

improved gel mobility electrophoresis assay or the powerful HPLC-MS, the

number of novel specific assays and methodologies is overwhelming (Tian et

al., 2005). Her, I will describe some of the most useful techniques used for

drug-DNA interaction studies. Vibrational spectroscopy such as Infrared

spectroscopy (IR) has been widely used for the structural analysis of DNA

because it can distinguish among A-, B-, and Z-forms of DNA, triple stranded

helices, and other structural motifs. It has also been a useful tool to study

interactions of nucleic acids with drugs and the effects of such interactions in

the structure of DNA, providing some insights about the mechanism of drug

action. A major advantage is that samples can be analyzed in different

aggregation states as solids or crystals, and also in solution. In addition, small

quantities of sample are needed and collection of spectra is very fast. The

region of interest in IR studies dealing with DNA in aqueous solutions is

between 1800 and 800 cm-1. Due to interfering absorption bands of water at

1650 cm-1 and below 950 cm-1, spectra are generally recorded in D2O, where

these bands move to 1200 cm-1, and below 750 cm-1. Fourier transform IR

35

(FTIR) has been used alone or supporting other techniques to determine drug

binding sites and sequence preference, as well as conformational changes due

to drug-DNA interaction (Jangir et al., 2010; Mandeville et al., 2010; Neault and

Tajmir-Riahi, 1996). Raman spectroscopy also depends on the vibrational

frequencies of characteristic groups and has been used sometimes in

conjunction with infrared spectra to study DNA-drug interactions.

Nuclear Magnetic Resonance (NMR) spectroscopy is based on the fact

that atomic nuclei endowed with a property called nuclear spin will align with

an applied magnetic field. The degree of this alignment depends not only on

the strength of the magnetic field, but also on the type of nucleus and its

chemical environment. Every nucleus with spin gives rise to a signal or peak

which represents a transition between a ground and an excited state. Each

magnetically active nucleus is characterized by different parameters such as

chemical shift, multiplicity, J-couplings and relaxation data that can be used to

obtain detailed structural information about the molecule under study. Among

the atomic nuclei available for the study of DNA (1H, 13C, 15N and 31P), 1H is

the most common, but 31P NMR is especially useful for studying the effects of

ligand binding on the phosphate groups of DNA. NMR experiments are very

versatile and the information can be obtained at different temperatures,

solvents, pH values, ionic strengths and dielectric constants. DNA-binding drugs

specific for the minor groove of DNA generally prefer AT-rich, rather than GC-

rich regions of DNA. These drugs are usually planar with crescent shapes. The

DNA minor groove possesses an electrostatic potential minimum attractive to

36

many such ligands. Many anti-tumour drugs bind to the major groove, and they

usually do it covalently through N-7 of guanine but their modes of interaction

have been studied with techniques different from NMR (González-Ruiz et al.,

2011).

The interaction of drugs with DNA can be also detected by UV-VIS

absorption spectroscopy on the basis of absorption properties of the drug or

the DNA molecules. The UV-VIS absorption spectrum of DNA exhibits a broad

band (200-350 nm) in the UV region with a maximum absorbance at 260 nm.

This maximum absorbance is a result of the chromophoric groups present in

purine and pyrimidine moieties responsible for the electronic transitions. The

application of this versatile and simple technique allows estimating the molar

concentration of DNA on the basis of the measurement of the absorbance value

at 260 nm. In practice, the molar concentration of DNA is evaluated in terms

of the concentration of base pairs. The absorbance ratios (A260/A280) can also

characterize the DNA molecules (Paul et al., 2010). Slight changes in the

absorption maximum as well as the molar absorptivity can be appreciated with

the variations in pH or ionic strength of the media. The ε values (λmax= 260

nm) of free oligonucleotides are higher than the ones corresponding to the

same oligonucleotides in single strand DNA (ss-DNA) and double strand DNA

(ds-DNA) because base-base stacking results in a hypochromic effect. This

behavior can be exploited to verify denaturalization of DNA by measuring its

absorbance values before and after denaturing treatment. The hypochromic

effect can also be employed to verify the existence of drug-DNA interactions,

37

due to the fact that the monitoring of the absorbance values allows studying

the melting behaviour of DNA. Melting temperature (Tm) is the temperature

value corresponding to the conversion of 50 % of the double strands into single

strands. An increase in the absorbance value with the increase of temperature

is observed because the ε (260 nm) of ss-DNA is higher than the ε (260 nm) of

ds-DNA. When a drug–DNA interaction exists, Tm is shifted to values different

from native ds-DNA. The magnitude of the shift depends on the type of

interaction. Thus, for intercalating agents the increase observed in the Tm value

is higher than in the case of agents interacting through the DNA minor or major

grooves (González-Ruiz et al., 2011). The changes in the Tm value can be

followed by other techniques such as fluorescence, circular dichroism, NMR or

calorimetry, but UV-Vis absorption spectrometry is the most frequently

employed method due to its good sensitivity, versatility and simplicity. Drug-

DNA interactions can be resolved by comparison of UV-VIS absorption spectra

of the free drug and drug-DNA complexes, which are usually different.

Circular dichroism (CD) spectroscopy is valuable techniques to explore

non-covalent drug-DNA interactions, which affect the electronic structure of the

molecules and also modify their electronic spectroscopic behavior. Circular

dichroism spectroscopy allows to rapidly characterize drug-DNA complexes

using a small amount of sample. Circular dichroism is defined as the difference

in absorption of left and right circularly polarised light. Circular dichroism

provides additional structural details of the complex. When electromagnetic

radiation reaches DNA, the macromolecules present a certain degree of

38

alineation in the direction of the electric field vector, and this molecular

alignment is measured by the light polarised absorbance. When a drug binds

to DNA, its spectrum will be modified if this binding causes changes in DNA

conformation. When a drug binds to DNA, an induced CD spectrum is observed

because of the interaction with DNA. This may result from either a geometric

change in the drug or from coupling between its electronic transitions and those

of the DNA. Particularly the electronic CD has become very significant for

qualitative characterization of conducting biopolymers.

Differential scanning calorimetry (DSC) is a technique capable to study

thermally induced transitions and particularly, the conformational transitions of

biological macromolecules. There are number of literature support applications

of this technique (Robertson and Murphy, 1997; Privalov and Potekhin, 1986;

Biltonen and Freire, 1978; Freire, 1995; Lopez and Makhatadze, 2002;

Jelesarov and Bosshard, 1999; Cooper and Johnson, 1994; Hinz and Schwarz,

2001). DSC is used to understand the molecular mechanism and energetics of

drug-DNA interactions. Statistical mechanical theories were developed by

Crothers and McGhee allowing interpretation and calculation of DNA melting

curves in the presence of ligands (Spink and Wellman, 2001; Crothers, 1971;

McGhee, 1976). The combination of DSC and temperature dependent UV

melting methods allowed the first direct determination of the binding enthalpy

for echinomycin (Leng et al., 2003). DSC was also applied to understand

interaction of distamycin with ColE1 DNA, a well characterized plasmid (Ueta et

al., 2001). DSC measurements were conducted to characterize the thermally

39

induced denaturation of the 20-bp duplex with the specific goal of elucidating

the thermal and thermodynamic consequences of modifying and constraining

DNA via a single, site-specific interstrand cross-link of antitumor cis-platin or its

clinically ineffective trans isomer (Hofr and Brabec, 2001). The interaction of

other drugs, like chlorobenzylidin (Zhong et al., 2003), phenoxazone (Veselkov

et al., 2003) or CP-31398 (Rippin et al., 2002), an anticancer drug, with DNA

has been also investigated by differential scanning calorimetry.

In the present work, we have attempted to understand the effect of

drugs/small molecules binding on synthetic and native deoxyribonucleic acids

through the theoretical analysis. We used amended Zimm and Bragg theory,

initially considered for helix coil transitions in polypeptides, to explain lambda

point anomalies in heat capacities and order-disorder transition in drug

bounded and unbounded DNAs (Zimm and Bragg, 1959). The effect of drugs

or small molecules binding is reflected in the change in nucleation parameter,

which is an inverse measure of binding strength. Our study is aimed at

providing such a theoretical protocol for complementing experimental

techniques and facilitating a minute study of the structure-energy relationships

in DNA-drug complexes.

1.5. Chapter wise presentation of the work done

There are total five chapters in the present thesis which compiled all the

methodology and results of the present work including conclusion. Chapter 1

40

consists of detailed introduction of the thesis and chapter 2 comprises complete

experimental and theoretical approaches used in the next three chapters.

The third chapter of this thesis deals with theoretical analysis of steroid

diamine (Dipyrandium), binding with DNA duplex by using an amended Zimm

and Bragg theory, to explain the melting behavior and heat capacity of DNA

with and without dipyrandium binding. The experimental models of Marky and

coworkers (1983) have been used for the study. Chapter 4 of the thesis deals

with the similar work done on theoretical analysis of tricyclic heteroaromatic

molecule (Thionine) binding with natural DNAs of varying base composition by

using an amended Zimm and Bragg theory, to explain the melting behaviour

and heat capacity of DNAs with and without thionine binding. We used

experimental models of Paul et al. for implementing this study (Paul et al.,

2010). Chapter five presented the conclusion of the entire work. This is the last

chapter which includes all the pros and cons of the present work.

41

References:

Abu-Daya A., Brown P.M. and Fox K.R. (1995). Nucleic Acids Res., 23: 3385-

92.

Araya F., Huchet G., Mcgroarty I., Skellern G.G. and Waigh R.D. (2007).

Methods, 42: 141–149.

Arya D.P., Coffee R.L., Jr. and Xue L. (2004). Bioorg. Med. Chem. Lett., 14:

4643-6.

Arya D.P., Micovic L., Charles I., Coffee R.L., Jr., Willis B. and Xue L. (2003).

Journal of the American Chemical Society., 125: 3733-3744.

Arya D.P., R.Lane Coffee J., Willis B. and Abramovitch A.I. (2001). J. Am. Chem.

Soc., 123: 5385-5395.

Beveridge D.L. and DiCapua F.M. (1989). Annu. Rev. Biophys. Biophys.Chem.,

18: 431–492.

Biltonen R.L. and Freire E. (1978). CRC Crit. Rev. Biochem., 5: 85.

Bouziane M., Cherny D.I., Mouscadet J.F. and Auclair C. (1996). J. Biol. Chem.

271: 10359-64.

Bremer R.E., Szewczyk J.W., Baird E.E. and Dervan P.B. (2000). Bioorg. Med.

Chem., 8: 1947-55.

Breslauer K.J., Freier E. and Straume M. (1992). Methods Enzymol., 211: 533–

567.

42

Breslauer K.J., Remeta D.P., Chou W.Y., Ferrante R., Curry J., Zaunczkowski

D., Snyder J.G. and Marky L.A. (1987). Proc. Natl. Acad. Sci. USA 84:

8922–8926.

Bruylants G., Wouters J. and Michaux C. (2005). Curr. Med. Chem., 12; 2011–

2020.

Burman L., Tandon P., Gupta V.D., Rastogi S. and Srivastav S. (1995b). Polym.

J., 27: 481.

Burman L., Tandon P., Gupta V.D., Rastogi S., Srivastav S. and Gupta G.P.

(1995a). J. Phys. Soc. Japan, 64: 327.

Caldwell J. and Kollman P.A. (1986). Biopolymers 25: 249.

Cassidy S.A., Strekowski L., Wilson W.D. and Fox, K.R. (1994),

Chaires J.B. (1998a). Curr. Opin. Struct. Biol., 9: 314-320.

Chaires J.B. (1997). Biopolymers., 44: 201–215.

Chaires J.B. (1998). Curr. Opin. Struct. Biol., 8: 314–320.

Chaires J.B. (1998b). Biopolymers, 44: 201-215.

Chaires J.B. (2008). Annu. Rev. Biophys., 37:135-151.

Chalikian T.V. and Breslauer K.J. (1998). Curr. Opin. Struct. Biol., 8: 657–664.

Cheng Y.K. and Pettitt B.M. (1992). Prog. Biophys. Mol. Biol., 58: 225-57.

43

Cherny D.Y., Belotserkovskii B.P., Frank-Kamenetskii M.D., Egholm M.,

Buchardt O., Berg R.H. and Nielsen P.E. (1993). Proc. Natl. Acad. Sci.

U.S.A., 90: 1667-70.

Choi S.D., Kim M.S., Kim S.K., Lincoln P., Tuite E., and Norden B. (1997).

Biochemistry 36: 214-223.

Cooney M., Czernuszewicz G., Postel E.H., Flint S.J. and Hogan M.E. (1988).

Science., 241: 456-9.

Cooper A. (1999). Curr. Opin. Chem. Biol. 3: 557–563.

Cooper A. and Johnson C.M. (1994). Methods Mol. Biol., 22: 125.

Crothers D.M. (1971). Biopolymers,10: 2147.

Dervan P.B. (1986). Science, 232 (4749): 464–71.

Durand M., Thuong N.T. and Maurizot J.C. (1994a). J. Biomol. Struc. Dynam.,

11: 1191-202.

Durand M., Thuong N.T. and Maurizot J.C. (1994b). Biochimie., 76: 181-6.

Dwivedi A.M. and Gupta V.D. (1972) chem. phys. lett., 16: 909.

Freire E. (1995). Methods Mol. Biol., 40: 191.

Fresco J.R., and Klemperer E. (1959). Ann. N. Y. Acad. Sci., 81: 730-41.

Gabbay E.J. and Glaser R. (1971). Biochem., 10: 1665–1674.

44

Gill P., Moghadam T.T. and Ranjbar B. (2010). Journal of Biomolecular

Techniques, 21:167–193.

Giri P., Hossain M., and Kumar G.S. (2006). Bioorg. Med. Chem. Lett., 16: 2364-

8.

Gonzalez-Ruiz V., Olives A.I., Martin M.A., Ribelles P., Ramos M.T. and

Menendez J. C. (2011). An Overview of Analytical Techniques Employed

to Evidence Drug-DNA Interactions. Applications to the Design of

Genosensors. In: M. A. Komorowska and S. Olsztynska-Janus, Eds.,

Biomedical Engineering, Trends, Research and Technologies, InTech,

Castle Rock, pp. 65-90.

Guo Q., Lu M., Marky L.A. and Kallenbach N.R. (1992). Biochemistry, 31: 2451-

5.

Gupta A., Tandon P., Gupta V.D., Rastogi S. and Gupta G.P. (1995). J. Phys

Soc. Japan, 64: 315.

Gupta V.D., Singh R.D. and Dwivedi A.M. (1973). Biopolymers., 12: 1377.

Gupta V.D., Trevino S. and Boutin H. (1968). J. Chem. phys., 48: 3008.

Haq I. (2002). Arch. Biochem. Biophys., 403: 1-15.

Haq I., Jenkins T.C., Chowdhry B.Z., Ren J. and Chaires J.B. (2000). Methods

Enzymol., 323: 373-405.

Haq I., Ladbury J. (2000). J. Mol. Recognit., 13: 188-197.

45

Haq I., Ladbury J.E., Chowdhry B.Z., Jenkins T.C. and Chaires J.B. (1997). J.

Mol. Biol., 271: 244-257.

Harshman K.D. and Dervan P.B. (1985). Nucleic Acids Res., 13: 4825-35.

Henry C.M. (2001). Chem. Eng. News., 79:69–74.

Hinz H.J. and Schwarz F.P. (2001). Pure Appl. Chem., 73: 745.

Hofr C. and Brabec V. (2001). J. Biol. Chem., 276: 9655.

Huppert J. L. and Balasubramanian S. (2005). Nucleic Acids Res., 33: 2908-16.

Hurley L.H. (2002). Nat. Rev. Cancer, 2: 188–200.

Islam, M.M., Chowdhury S.R. and Kumar G.S. (2009). J. Phys. Chem. B., 113:

1210–1224.

Jangir D.K., Tyagi G., Mehrotra R. and Kundu S. (2010). Journal of Molecular

Structure, 969: 126-129.

Jayaram B. and Beveridge D.L. (1996). Annu. Rev. Biophys. Biomol. Struct., 25:

367–394.

Jayaram B., McConnell K.J., Dixit S.B., Das A. and Beveridge D.L. (2002). J.

Comput. Chem., 23: 1–14.

Jelesarov I. and Bosshard H.R. (1999). J. Mol. Recognit., 12: 3.

Jorgensen W.L. and Ravimohan C. (1985). J. Chem. Phys., 83: 3050–3054.

Kaul M. and Pilch D.S. (2002). Biochemistry., 41: 7695-7706.

46

Krishnan M.V. and Gupta V.D. (1970a). Chem. phys. Lett., 7: 285.

Krishnan M.V. and Gupta V.D. (1970b) Chem. phys. Lett., 6: 231.

Kunwar A., Emmanuel S., Singh U., Chittela R.K., Sharma D., Sandur S.K. and

Priyadarsini I.K. (2011). Chem. Biol. Drug Design, 77: 281–287.

Lane A.N. and Jenkins T.C. (2000). Q. Rev. Biophys., 33: 255-306.

Lane A.N., Bauer C.J. and Frenkiel T.A. (1993). Eur. Biophys. J., 21: 425-31.

Lane, A.N. (2001). Nuclear magnetic resonance studies of drug-DNA complexes

in solution. In: Methods in Enzymology, Drug-Nucleic Acid Interactions,

Vol. 340, Chaires, J. B. and M. J. Waring (Eds.), Academic Press, San

Diego, USA.

LaVerne S.J., Srivastav S., Srivastav S. and Gupta V.D. (2009). J. Appl. Poly.

Sci., 113(3): 1406–1414.

Lazaridis T. (2002). Curr. Org. Chem., 6: 1319–1332.

Leng F., Chaires J.B. and Waring M.J. (2003). Nucleic Acids Res., 31: 6191-

6197.

Leng F., Priebe W. and Chaires J.B. (1998). Biochemistry, 37: 1743-1753.

Lerman L.S. (1961). Journal of Molecular Biology, 3: 18.

Lopez M.M. and Makhatadze G.I. (2002). Methods Mol. Biol., 173: 113.

47

Mahler H.R., Goutarel R., Khuong-Huu Q. and Ho M.T. (1966). Biochem., 5:

2177–2191.

Mahler H.R., Green G., Goutarel R. and Khuong-Huu Q.(1968). Biochem., 7:

1568–1582.

Mahler, H.R., G. Dutton, Nucleic acid interactions. V. Effects of cyclobuxine, J.

Mol. Biol., 1964, 10, 157–175.

Mandeville J.S., N’soukpoé-Kossi C.N., Neault J.F. and Tajmir-Riahi H.A. (2010).

Biochem. Cell Biol., 88: 469-477.

Marky L.A. and Breslauer K.J. (1987). Proc. Natl. Acad. Sci. U.S.A. 84: 4359-

63.

Marky L.A. and Kupke D.W. (1989). Biochemistry., 28: 9982-8.

Marky L.A., Blumenfield K.S. and Breslauer K.J. (1983a). Nucleic Acids Res., 11:

2857-2870.

Marky L.A., Snyder J.G. and Breslauer K.J. (1983b). Nucleic Acid Res., 11(16):

5701-5715.

McGhee J.D. (1976) Biopolymers,15: 1345.

McGhee J.D. and von Hippel P.H. (1974). J. Mol. Biol. 86: 469-489.

Menendez J.C. (2011). An overview of analytical techniques employed to

evidence drug-DNA interactions. Applications to the design of

genosensors. In: Biomedical engineering, trends, research and

48

technologies. Komorowska M.A. and Olsztynska-Janus S., eds., InTech,

pp 65–90.

Mergny J.L., Collier D., Rougee M., Montenay-Garestier T. and Helene C.

(1991). Nucleic Acids Res., 19: 1521-6.

Mergny J.L., Duvalvalentin G., Nguyen C.H., Perrouault L., Faucon B., Rougee

M., Montenaygarestier T., Bisagni E. and Helene C. (1992). Science 256:

1681-1684.

Mikulecky P.J. and Feig A.L. (2006). Biopolymers, 81: 38–58.

Munroe D. and Jacobson A. (1990). Mol. Cell. Biol., 10: 3441-55.

Neault J.F. and Tajmir-Riahi H.A. (1996). Journal of Biological Chemistry, 271:

8140-8143.

Neidle S. and Abraham Z. (1984). Critical Reviews In Biochemistry, 17: 73.

Park Y.W. and Breslauer K.J. (1992), PNAS (USA)., 89: 6653-7.

Paul P., Hossain M., Yadav R.C. and Kumar G.S. (2010). Biophysical Chemistry,

148: 93-103.

Pelton J.G. and Wemmer D.E. (1988). Biochemistry, 27: 8088-96.

Pilch D.S., Poklar N., Baird E.E., Dervan P.B. and Breslauer K.J. (1999).

Biochemistry, 38: 2143–2151.

49

Pilch DS. (2000). Calorimetry of nucleic acids. In: Egli M, Herdewijn P, Matsuda

A, et al. (eds): Current Protocols in Nucleic Acid Chemistry. John Wiley

& Sons, New York, NY, USA.

Pineda L.F. and Zacharias M. (2002). J. Mol. Recognit., 15: 209–220.

Plum G.E. and Breslauer K.J. (1995). J. Mol. Biol., 248: 679-95.

Povirk L.F., Han Y.H. and Steighner R.J. (1989). Biochemistry, 28: 5808.

Prasad O., Tandon P., Gupta V.D. and Rastogi S.J. (1996). Polym. sci. B., 34:

1213.

Privalov P.L. (1990). Crit Rev Biochem Mol Biol., 25: 281–305.

Privalov P.L. and Potekhin S.A. (1986). Methods Enzymol., 4: 131.

Rao S.N., Singh U.C. and Kollman P.A. (1986). J. Med. Chem., 29: 2484–2492.

Ren J. and Chaires J.B. (2001). Methods Enzymol., 340: 99-108.

Rentzeperis D., Marky L.A., Dwyer T.J., Geierstanger B.H., Pelton J.G. and

Wemmer D.E. (1995). Biochemistry., 34: 2937-45.

Rippin T.M., Bykov V.J., Freund S.M., Selivanova G., Wiman K.G. and Fersht A.

(2002). R. Oncogene. 21: 2119.

Robertson A.D. and Murphy K.P. (1997). Chem. Rev., 97: 1251.

Saenger W. (1983). Principles of Nucleic-Acid Structure, Springer-Verlag, New

York.

50

Saenger W. (1984). Principles of Nucleic Acid Structure. Springer-Verlag, New

York.

Shaikh S.A., Ahmed S.R. and Jayaram B. (2004). Archives of Biochemistry and

Biophysics, 429: 81–99.

Simonsson T., Pecinka P. and Kubista M. (1998). Nucleic Acids Res., 26: 1167-

72.

Sinden R.R. (1994). DNA Structure and Function, Academic Press, San Diego.

Singh R.D. and Gupta V.D. (1971) Spectrochim. Acta., 27A: 385.

Singh S.B. and Kollman P.A. (1999). J. Am. Chem. Soc., 121: 3267–3271.

Singh S.B., Ajay D.E., Wemmer P.A. and Kollman. (1994). Proc. Natl. Acad. Sci.,

USA 91: 7673–7677.

Singh U.C., Pattabiraman N., Langridge R. and Kollman P.A. (1986). Proc. Natl.

Acad. Sci. USA, 83: 6402–6406.

Spackova N., Cheatham III T.E., Ryjacek F., Lankas F., van Meervelt L., Hobza

P., Sponer J. (2003). J. Am. Chem. Soc., 125: 1759–1769.

Spink C.H. and Wellman S.E. (2001). Methods Enzymol., 340: 193.

Srivastav S., Tandon P., Gupta V.D., Rastogi S. and Mehrotra C. (1997).

Polymer Journal., 29(1): 33-43.

51

Srivastava S., Khan I.A., Srivastava S. and Gupta V.D. (2004). Indian J.

Biochem. Biophys., 41: 305–310.

Steighner R.J. and Povirk L.F. (1990). Proceedings of the National Academy of

Sciences of the United States of America, 87: 8350.

Stubbe J., Kozarich J.W., Wu W. and Vanderwall D.E. (1996). Accounts of

Chemical Research, 29: 322

Sturtevant J.M. (1977). Proc Natl Acad Sci U.S.A., 74: 2236–2240.

Tembe B.L. and McCammon J.A. (1984). Comput. Chem., 8: 281–283.

Tian R., Xu S., Lei X., Jin W., Ye M. and Zou H. (2005). Trends Anal. Chem.,

24: 810-825.

Tikhomirova A., Taulier N., Chalikian T.V. (2004). J Am Chem Soc., 126: 16387–

16394.

Todd A.K., Johnston M. and Neidle S. (2005). Nucleic Acids Res., 33: 2901-7.

Topalian S.L., Gonzales M.I., Ward Y., Wang X. and Wang R.F. (2002). Cancer

Res., 62: 5505-9.

Topalian S.L., Kaneko S., Gonzales M.I., Bond G.L., Ward Y. and Manley J.L.

(2001). Mol. Cell. Biol., 21: 5614-23.

Ueta H., Maeda Y. and Kawai Y. (2001). Biosci. Biotech. Biochem., 65: 1261.

52

Veselkov A.N., Maleev V.Y., Glibin E.N., Karawajew L. and Davies D.B. (2003).

Eur. J. Biochem., 270: 4200.

Weber P.C. and Salemme F.R. (2003). Curr. Opin. Struct. Biol., 13:115–21.

Willis B. and Arya D.P. (2006). Biochemistry., 45: 10217-32.

Wilson W.D., Mizan S., Tanious F.A. and Yao S. (1994). J. Mol. Recognit., 7:

89-98.

Wunderlich B. and Bu HS. (1987). Thermochimica Acta., 119- 225.

Xing F., Song G., Ren J., Chaires J. B. and Qu X. (2005). FEBS Lett., 579: 5035-

9.

Yadav R.C., Kumar G.S., Bhadra K., Giri P., Sinha R., Pal S. and Maiti M. (2005).

Bioorg. Med. Chem., 13: 165-74.

Zakrzewska K., Lavery R. and Pullman B. (1984). Nucleic Acids Res., 11: 8825–

8839.

Zarudnaya M.I. and Hovorun D.M. (1999). IUBMB Life., 48: 581-4.

Zhong W., Yu J.S. and Liang Y. (2003). Spectrochim. Acta A Mol. Biomol.

Spectrosc., 59: 1281.

Zimm B.H., Bragg J.K. and Theory. (1959). J. Chem. Phys., 31: 526-535.

Zimmer C. and Wähnert U. (1986). Prog. Biophys. Mol. Biol., 47 (1): 31–112.

53

CHAPTER 2

THEORY

54

Molecular interaction of the drugs with DNA and peptides is a field of

high topical interest and may have a great importance to its biological activity.

In the present chapter the theoretical methods for phase transition studies are

discussed. In this section the theory for order–disorder phase transition is

given. It includes the theoretical formalism of phase transition in telomeres as

a function of temperature and concomitant changes in the heat capacity at the

transition point which shows lambda anomaly. The study includes methods

involve in theoretical analysis of Dipyrandium and Thionine binding with

different natural and synthetic DNA. We used amended Zimm and Bragg theory

(Zimm and Bragg, 1959), to elucidate the order-disorder phase transition in

drug bounded and unbounded DNA duplexes, which is considered initially for

the helix coil transitions in polypeptides. The effect of drug binding is reflected

in the change in nucleation parameter, which is an inverse measure of binding

strength.

Phase Transition Theory

The models of drug-DNA complex determined by the various techniques

suggest that the Watson-Crick hydrogen bonds are intact in the neighbor-

exclusion complex and that every other set of base pairs partially unstacks and

the drugs are partially inserts at this site. However, the system remains a highly

co-operative one therefore the co-operative transition theory could be applied

to explain the melting profile and temperature dependence of thermodynamical

parameter, such as heat capacity. Briefly, Zimm and Bragg theory consists of

55

writing an Ising matrix for a two-phase system, the bounded state and

unbounded state. The Ising matrix M can be written as:

𝑓𝑟 𝑓𝑘 𝑓ℎ

M =

𝑓𝑟𝑓𝑘𝑓ℎ

|

𝑓𝑟1/2𝑓𝑟

1/2 𝑓𝑟1/2𝑓𝑘

1/2 0

𝑓𝑟1/2𝑓𝑘

1/2 0 𝑓𝑘1/2𝑓ℎ

1/2

𝑓ℎ1/2𝑓𝑟

1/2 0 𝑓ℎ1/2𝑓ℎ

1/2

| (1)

where fr, fh and fk are corresponding base pair partition functions’ contributions

in the three states i.e. ordered, disordered and boundary or nucleation. The

eigen values of M are given by:

𝜆1 = [(𝑓𝑟+𝑓ℎ) + {(𝑓𝑟−𝑓ℎ)2 + 4𝑓𝑟𝑓𝑘}

1/2]/2

𝜆2 = [(𝑓𝑟+𝑓ℎ) − {(𝑓𝑟−𝑓ℎ)2 + 4𝑓𝑟𝑓𝑘}

1/2]/2𝜆3 = 0

(2)

Since we are dealing with a finite system hence the effect of initial and

final states becomes important. The contribution of the first segment to the

partition function is given by:

𝑈 = (𝑓𝑟1/2, 0,0) (3)

where the column vector V gives the state of the last segment,

V = |

𝑓𝑟1/2

𝑓𝑘1/2

𝑓ℎ1/2

| (4)

The partition function for an N-segment chain is given by;

56

𝑍 = 𝑈𝑀𝑁−1𝑉 (5)

The matrix T which diagnolizes M consists of the column vectors given by:

𝑀𝑋 = 𝜆𝑋 (6)

Where 𝑋 = |𝑋1𝑋2𝑋3

|

By substituting the values of M from Eq. (6), we get:

𝑇 = ||

1 1 1(𝜆1−𝑓𝑟)

(𝑓𝑟1/2

𝑓𝑘1/2

)

(𝜆1−𝑓𝑟)

(𝑓𝑟1/2

𝑓𝑘1/2

)−(𝑓𝑟

1/2𝑓𝑘1/2

)

(𝑓ℎ1/2

𝑓𝑟1/2

)

(𝜆1−𝑓ℎ)

(𝑓ℎ1/2

𝑓𝑟1/2

)

(𝜆1−𝑓ℎ)−(𝑓ℎ

1/2𝑓𝑟1/2

)

|| (7)

Similarly, we get T-1 from the matrix equation

𝑌𝑀 = 𝜆𝑌 (8)

where, 𝑌 = [𝑌1,𝑌2,𝑌3]

Again by substituting the values of M from Eq. (1) in Eq. (8), we get:

𝑇1 =|

|𝐶1

𝐶1(𝑓𝑟1/2

𝑓𝑘1/2

)

𝜆1

𝐶1(𝑓𝑘𝑓𝑟1/2

𝑓ℎ1/2

)

𝜆1(𝜆1−𝑓ℎ)

𝐶2𝐶2(𝑓𝑟

1/2𝑓𝑘1/2

)

𝜆2

𝐶2(𝑓𝑘𝑓𝑟1/2

𝑓ℎ1/2

)

𝜆2(𝜆2−𝑓ℎ)

𝐶3𝐶3(𝑓𝑟

1/2𝑓𝑘1/2

)

𝜆3

𝐶3(𝑓𝑘𝑓𝑟1/2

𝑓ℎ1/2

)

𝜆3(𝜆3−𝑓ℎ)

|

| (9)

The normalization constants are:

57

𝐶1 = (𝜆1 − 𝑓ℎ)/(𝜆1 − 𝜆2), 𝐶2 = (𝜆2 − 𝑓ℎ)/(𝜆2 − 𝜆1), 𝐶3 = 0 (10)

If we let Λ = 𝑇−1𝑀𝑇 be the diagonalized form of M, the partition

function can be written as:

𝑍 = 𝑈𝑇𝛬𝑁−1𝑇−1𝑉 (11)

On substituting the values from Eqs (1), (3), (4), (7), (9) and (10) in

Eq. (11), the partition function becomes:

𝑍 = 𝐶1𝜆1𝑁 + 𝐶2𝜆1

𝑁 (12)

The fraction of the segments in the disordered form is given by

𝑄𝑟 = [𝛿𝑙𝑛𝑍/𝛿𝑙𝑛𝑓𝑟]/𝑁

Solving the above equation, we get:

𝑄𝑟 = 1/2 + (1 − 𝑠)(2𝐴 − 1)/2𝑃 + (1 + 𝑠){(2𝐴 − 1)𝑃 − 1 + 𝑠}/2𝑃2𝑁

……………….(13)

where 𝑃 = (𝜆1 − 𝜆2)/𝑓𝑟 , 𝑠 = 𝑓ℎ/𝑓𝑟 , 𝜎 = 𝑓𝑘/𝑓𝑟 , 𝐴 = [(𝑓𝑟 − 𝑓ℎ)2 +

4𝑓𝑘𝑓𝑟]−2

Here s is propagation parameter, which for simplicity is assumed to be

1. In fact, in most of the systems, it is found to be close to unity. If Ar and Ah

are the absorbance in disordered and ordered states, respectively, the total

absorption can be written as:

58

𝐴 = 𝑄𝑟𝐴𝑟 + (1 − 𝑄𝑟)𝐴ℎ (14)

The extension of this formalism to specific heat (Cv) is straight forward.

The specific heat is related to the molar enthalpy and entropy changes in the

transition from state I to II. From the well-known thermodynamic relations,

free energy and internal energy are 𝐹 = −𝐾𝑇𝑙𝑛𝑍 and𝑈 = −𝑇2(𝛿/𝛿𝑇)(𝐹/

𝑇), respectively. Differentiating internal energy with respect to temperature

we get the specific heat:

𝐶𝑣 = 𝛿𝑈/𝛿𝑇 = 𝑁𝑘(Δ𝐻/𝑅𝑇𝑚)2(𝑆𝛿𝑄𝑟/𝛿𝑆) (15)

Where ∆H is the molar change in enthalpy about the transition point, S is

entropy which is equal toS = exp[(∆H/R){(1/T) − (1/Tm)}], Tm is the

transition temperature, and

𝛿𝑄𝑟/𝛿𝑆 = (1/2𝑃2)[2𝑃(1 − 𝑆)𝛿𝐴/𝛿𝑆 − 𝑃(2𝐴 − 1)− (1 − 𝑆)(2𝐴

− 1)𝛿𝑃/𝛿𝑆] + (1/2𝑃3𝑁)[𝑃{(𝑆 + 1){(2𝐴 − 1)𝛿𝑃/𝛿𝑆

+ 2𝑃𝛿𝐴/𝛿𝑆 + 1} + {(2𝐴 − 1)𝑃 − 1 + 𝑆}} − {(2𝐴 − 1)𝑃

− 1 + 𝑆}2(𝑆 + 1)]

with 𝛿𝐴/𝛿𝑆 = {(𝑆 − 𝜎)𝑁/(𝑍/𝑓𝑟𝑁)2} × (𝜎/𝑃3) × [−2 + {𝑁(𝑆 − 2𝜎 −

1)/𝑆 − 𝜎}]

𝛿𝑃/𝛿𝑆 = (𝑆 − 1)/𝑃 and 𝜎 = 𝑓𝑘/𝑓𝑟; σ is the nucleation parameter

and is a measure of the energy expanded/released in the formation (uncoiling)

of first turn of the ordered/disordered state. It is related to the uninterrupted

59

sequence lengths (Zimm and Bragg, 1959). The volume heat capacity Cv has

been converted into constant pressure heat capacity Cp by using the Nernst-

Lindemann approximation (Roles and Wunderlich, 1991) :

𝐶𝑝 − 𝐶𝑣 = 3𝑅𝐴0(𝐶𝑝2𝑇/𝐶𝑣𝑇𝑚) (16)

where A0 is a constant often of a universal value [3.9×10-9 (Kmol)/J-1] and Tm

is the melting temperature.

References:

Pan R., Verma M.N. and Wunderlich B. (1989). J. Therm. Anal., 35: 955.

Roles K.A. and Wunderlich B. (1991). Biopoly., 31: 477-487.

Tandon P., Gupta V.D., Prasad O., Rastogi S. and Gupta V.P. (1997). J. Polym.

Sc. Part B Polym. Phys. 35: 2281.

Zimm B.H. and Bragg J.K. (1959). J. Chem. Phys., 31: 526-535.

60

CHAPTER 3

TRANSITION AND

STABILITY OF DNA–

DIPYRANDIUM COMPLEX

61

3.1. Introduction

Molecular interaction of the drug with DNA is a field of high topical

interest and may have a great importance to its biological activity. The

molecules can interact with DNA in a variety of ways such as surface binding

to their minor or major grooves, intercalation between adjacent base pairs,

covalent attachments to the double helix, or electrostatic binding. The study of

drug-DNA interactions began since 1960s but the binding of steroid-diamines

to synthetic and natural nucleic acids has received considerable attention over

the past ten years (Mahler and Dutton, 1964; Mahler et al., 1966, 1968; Waring,

1970; Gabbay and Glaser, 1971; Waring and Chisholm, 1972; Lane, 2001;

Bruylants et al., 2005; Araya et al., 2007; Islam et al., 2009; Paul et al., 2010;

Gonzalez-Ruiz, 2011; Kunwar et al, 2011). Thus, some more theoretical and

experimental studies are conducted based on the assumption that the steroid

diamine binding may ‘kink’ DNA as suggested by Sobell et al. (Waring and

Henley, 1975; Sobell, 1977; Saucier, 1977; Dattagupta, 1978; Manning, 1979;

Patel and Canuel, 1979; Patel, 1979; Lane, 2001; Bruylants et al., 2005; Araya

et al., 2007; Islam et al., 2009; Paul, 2010; Gonzalez-Ruiz, 2011; Kunwar et al,

2011). The naturally occurring steroidal diamine, dipyrandium, is amphiphilic in

nature, and its biophysical features include increasing the duplex denaturation

temperature and altering of the UV and CD spectra of DNA.

Dipyrandium (Fig. 3.1) is an aminosteroid neuromuscular blocking agent

that revolutionized the performance of anesthesia. The relaxant action of

dipyrandium chloride in man was studied by (Mushin and Mapleson, 1964). The

62

binding of dipyrandium to DNA is proposed to occur in the minor groove in

conjunction with 5'-d(TA) kinks (Patel and Canuel, 1979). In view of the

potential importance of such a molecular distortion to drug binding, interest in

and investigations of steroid diamine-DNA complexation has greatly increased.

The aminosteroid-DNA complex model suggested that the Watson-Crick

hydrogen bonds are intact in the neighbor-exclusion complex and that every

other set of base pairs partially unstacks and the steroid diamines partially

inserts at this site (Sobell et al., 1976). Hui and his co-workers studied binding

modes analysis of dipyrandium to the double-stranded hexanucleotides

d(TATATA)2, d(ATATAT)2, and d(CGCGCG)2 by the energy minimization

procedure JUMNA. The binding of dipyrandium to d(CGCGCG)2 is found to be

considerably less favourable than for either of the two (AT) sequences (Hui et

al., 1989). The interaction of dipyrandium with DNA and its dependence on the

base sequence was also studied by Vorlícková et al. using circular dichroism

(Vorlícková et al., 1985). They suggested that calf thymus DNA and

polynucleotide duplexes underwent similar alterations in the chiroptical

properties upon binding of dipyrandium. These results recommend that these

DNAs have similar B-type structures which may kink at the dipyrandium binding

sites. Alternatively, poly(dA-dT).poly(dA-dT) and especially poly(dA-

dU).poly(dA-dU) exhibit some features of A-type structure. Poly(dA-

dT).poly(dA-dT) changes its chiroptical properties little when complexed with

dipyrandium, as if it contained some type of kinks as equilibrium structural

elements (Vorlickova et al., 1985).

63

The calorimetric analysis of aminosteroid binding with DNA duplex was

reported for the first time by Marky et al. (1983). They recommended that

increasing the concentration of bound steroid increases the thermal stability of

the duplex and at saturation; the duplex melts with a Tm some 20°C above that

of the free duplex (Marky et al., 1983). They also concluded that dipyrandium

binding to poly d(AT) is an endothermic process and this binding increases the

melting temperature of the duplex. In the present investigation, we have

attempted to understand the effect of steroid diamine binding on a DNA duplex

by using the experimental model of Marky and his coworkers (Marky et al.,

1983) who studied the thermal and thermodynamic behaviour of dipyrandium

binding to poly d(AT). We used amended Zimm and Bragg theory, to elucidate

the order-disorder transition in dipyrandium bounded and unbounded DNA

duplexes, which is considered initially for the helix coil transitions in

polypeptides (Zimm and Bragg, 1959; Srivastava et al., 1999, 2001). We also

explained lambda point anomalies in heat capacities by using the same theory.

The effect of dipyrandium binding is reflected in the change in nucleation

parameter, which is an inverse measure of binding strength.

Figure 3.1. Molecular structure of dipyrandium

64

3.2. Theory

The model proposed by Sobell for the aminosteroid-DNA complex on the

basis of NMR study, as mentioned above, suggested that the Watson-Crick

hydrogen bonds are intact in the neighbor-exclusion complex and that every

other set of base pairs partially unstacks, and the steroid diamines partially

inserts at this site (Sobell et al., 1977). However, the system remains a highly

co-operative one therefore the co-operative transition theory could be applied

to explain the melting profile and temperature dependence of thermodynamical

parameter, such as heat capacity. Therefore, we used amended Zimm and

Bragg theory (1959) which is presented in chapter 2.

3.3. Experimental model

In this study, we used experimental model of Marky et al. (1983) to

understand the effect of dipyrandium binding to poly d(AT).

3.4. Results and discussion

As stated above the DNA structure still remains a very much co-

operative once binds to dipyrandium and consequently two-state theory of

order-disorder transition is applicable. The hypothesis given by Zimm and

Bragg (1959) is amended so as to consider ordered (bounded/unbounded) and

disordered states as the two states which co-exist at the transition position.

The transition is characterized mainly by the nucleation parameter and overall

change of enthalpy/entropy, which are also the main thermodynamic forces

65

driving the transition. The change in enthalpy obtained from differential

scanning calorimetric (DSC) measurements and changes in other transition

parameters, such as nucleation parameter (σ) and melting point (Tm), takes

all this into account. This may be further elaborated that, the enthalpy change

(∆H) on binding of dipyrandium is maximum (7.6 Kcal/M bp) in case of

nucleotide to drug ratio infinity and minimum (5.09 Kcal/M bp) at the ratio of

5:1, as shown in table 3.1. It may also be concluded that by increasing the

drug concentration the change of enthalpy is decreases gradually (Table 3.1).

The stability of duplex may be determined by its melting temperature (Tm) and

it is increases with increasing concentration of bounded dipyrandium. The

melting temperature for free duplex was 46.5°C and when the duplex was

saturated with dipyrandium, it melts with a Tm some 28°C above that of the

unbounded duplex (Table 3.1). The drug-induced increase in the thermal

stability of the duplex is accompanied by a decrease in the overall transition

enthalpy of the duplex. The sharpness of the transition can be looked at in

terms of half width and a sensitivity parameter defined as (∆H/σ). The variation

of these parameters systematically reflects that the transition is sharpest in

case of unbounded state and goes in order to nucleotide to dipyrandium ratio

of 17:1, 10:1 and 5:1. In case of λ-transition, the same trend in the sharpness

of transition is seen between the dipyrandium bounded as well as unbounded

curves. As expected, the sharpness is better in unbounded, as compared to

bounded state. The various parameters, which give transition profiles in best

agreement with the experimental measurements for binding of dipyrandium,

are presented in table 3.1.

66

The heat capacity and transition profiles for unbounded nucleotide, poly

d(AT), and with different concentration of aminosteroid, dipyrandium, are

shown in figure 3.2. In case of heat capacity curve some insignificant

divergence are reported at the tail ends may be due to presence of different

disordered states, as these states cannot be distinctively defined. Additionally,

these variations could also be arises due to the presence of short helical

segments found in the random coil states. The experimental and calculated

transition curves for the duplex to single strand transition of poly d(AT) in the

absence of dipyrandium are shown by the graph ‘A’ in figure 3.2. Similarly,

graph ‘B’ and ‘C’ shows the transition in the presence of dipyrandium at

nucleotide to drug ratios of 17:1 and 10:1, respectively.

67

Table 3.1. Transition parameters for dipyrandium binding to poly d(AT)

Parameters

Phosphate/Drug (P/D) ratio

∞* 17/1 10/1 5/1

Melting Temperature (K)

319.5 323.2 331.57 347.5

∆H Kcal/M bp 7.6 6.61 6.43 5.09

σ 4x10-4 1x10-3 3x10-3 3.5x10-3

N 106 106 106 50

Ah 0 0 0 0

Ar 1 1 1 1

Sensitivity

parameter (∆H/σ)

19000 6610 2143.33 1454.28

*Unbounded

68

Fig. 3.2. Heat capacity and transition profiles (inset) for unbounded and

bounded DNA with dipyrandium. (A) Unbounded state, (B) Bounded state with

P/D ratio 17/1, (C) Bounded state with P/D ratio 10/1, (D) Bounded state with

P/D ratio 5/1. [(—) calculated and (••••) experimental values].

69

In figure 3.2, graph ‘D’ shows the poly d(AT) transition when the duplex

is saturated with dipyrandium (nucleotide to drug ratio of 5:1). There is a

cooperative transition profile in between calculated and experimental data that

was anticipated from the results. The results presumed from the theoretical

data is reliable with the experimental data of Marky et al. (1983) that was

directly measured binding enthalpy through differential scanning calorimetric

method. The presented data of theoretical analysis also demonstrated that

dipyrandium binding to DNA duplex is an endothermic process and this binding

increases the melting temperature of the duplex as supported by differential

scanning calorimetric measurement. Marky and coworkers have used DSC to

investigate the binding of dipyrandium to the poly d(AT) duplex (Marky et al.,

1983). However, Patel and Canuel used NMR for the same study (Patel and

Canuel, 1979).

In view of that, we can interpret our theoretical analysis results in the

perspective of the particular structural features of the drug-DNA complex as

deduced from their experimental data obtained through DSC/NMR study. It is

evident from figure 3.2 (graph A and D) that the transition of the dipyrandium

saturated DNA duplex is significantly broader than the transition of the

dipyrandium free DNA duplex. Therefore, it is clear that besides affecting the

enthalpy and melting temperature, binding of dipyrandium also alters the

nature of the transition as reflected by the increase in transition width in

experimental as well as calculated data (Figure 3.2). Heat capacity is a second

derivative of the free energy and has been calculated by using equation 15

70

(described in chapter 2). By using heat capacity, the dynamical and

conformational states of a macromolecular system are characterized. The heat

capacity curves, obtained from theoretical and experimental data, along with

their transition profile are shown in figure 3.2. From these curves it may be

concluded that the theoretically obtained heat capacity profiles agreed with

the experimentally reported ones and could be brought almost into coincidence

with the use of scaling factors, which is very close to one in transition profiles

and slightly higher for the heat capacity curves. In addition, the sharpness of

the transition can also be characterized by the half width of the heat capacity

curves. The half width of these heat capacity curves are also calculated which

is in good agreement in both theoretical and experimental graphs (Figure 3.3).

Fig. 3.3. Half width of the heat capacity curves

2

3

6.5

8.5

2

3

6.5

8.5

0

1

2

3

4

5

6

7

8

9

10

∞ 17/1 10/1 5/1

Half w

idth

valu

e

P/D ratio

Half width (Exp.)

Half width (Theo.)

71

3.5. Conclusion

In recent years, the study of nucleic acid interaction with molecules is of

high interest (Araya et al., 2007; Gonzalez-Ruiz et al., 2011; Islam et al., 2009;

Kunwar et al., 2011; Paul et al., 2010). The present study concluded that the

DNA molecule is an extremely co-operative structure and when dipyrandium

binds to it the co-operativity of DNA is not so much disturbed. Therefore, the

amended Zimm and Bragg theory can be effectively applied to it. It generates

the experimental transition profile and λ-point heat capacity anomaly

successfully. The results obtained will allow us to evaluate the thermodynamic

profile of dipyrandium interaction with DNA (dipyrandium-DNA complex). This

theoretical analysis of steroid diamine binding with nucleotide is being extended

to other synthetic and natural DNA polymers. This theoretical analysis can also

be useful in order to understand bimolecular interaction and thus can be applied

in the process of drug design and development.

72

References:

Araya F., Huchet G., McGroarty I., Skellern G.G. and Waigh R.D. (2007).

Methods, 42:141-149.

Bruylants G., Wouters J., Michaux C. (2005). Curr. Med. Chem., 12:2011-2020.

Dattagupta N., Hogan M., Crothers D.M. (1978). Proc. Natl. Acad. Sci. USA,

75:4286-4290.

Gabbay E.J., Glaser R. (1971). Biochem., 10:1665-1674.

Gonzalez-Ruiz V., Olives A.I., Martin M.A., Ribelles P., Ramos M.T., Menendez

J.C. (2011). Biomedical engineering, trends, research and technologies.

Komorowska, M.A. and S. Olsztynska-Janus (eds.), InTech, pp 65-90.

Hui X.W., Gresh N., Pullman B., (1989). Nucleic Acids Res., 17(11):4177-87.

Islam M.M., Chowdhury S.R., Kumar G.S. (2009). J. Phys. Chem. B, 113:1210-

1224.

Kunwar A., Emmanuel S., Singh U., Chittela R.K., Sharma D., Sandur S.K.,

Priyadarsini I.K. (2011). Chem. Biol. Drug Design, 77:281–287.

Lane A.N. (2001). Nuclear magnetic resonance studies of drug-DNA complexes

in solution. In: Methods in Enzymology, Drug-Nucleic Acid Interactions,

Vol. 340, Chaires, J. B. and M. J. Waring (Eds.). Academic Press, San

Diego, USA.

Mahler H.R., Dutton G. (1964). J. Mol. Biol., 10:157-175.

73

Mahler H.R., Goutarel R., Khuong-Huu Q., Ho M.T. (1966). Biochem., 5:2177-

2191.

Mahler H.R., Green G., Goutarel R., Khuong-Huu Q. (1968). Biochem., 7:1568-

1582.

Manning G.S. (1979). Biopolymers, 18:2357-2358.

Marky L.A., Snyder J.G., Breslauer K.J. (1983). Nucleic Acid Res., 11(16):5701-

5715.

Mushin WW, Mapleson WW. (1964). Br. J. Anaesth., 36:761-8.

Patel D.J. (1979). Acc. Chem. Res., 12:118-125.

Patel D.J., Canuel L.L. (1979). Proc. Natl. Acad. Sci. USA, 76:24-28.

Paul P., Hossain M., Yadav R.C., Kumar G.S. (2010). Biophys. Chem., 148:93-

103.

Poklar N., Pilch D.S., Lippard S.J., Redding E.A., Dunham S.U., Breslauer K.J.

(1996). Proc. Natl. Acad. Sci. USA, 93: 7606-7611.

Roles K.A., Wunderlich B. (1991). Biopolymers, 31: 477-487.

Saucier J.M. (1977). Biochem., 16:5879-5889.

Sobell H.M., Tsai C.C., Gilbert S.G., Jain S.C., Sakore T.D. (1976). Proc. Natl.

Acad. Sci. USA, 73: 3068-3072.

74

Sobell H.M., Tsai C.C., Jain S.C., Gilbert S.G. (1977). J. Mol. Biol., 114: 333-

365.

Srivastava S., Gupta V.D., Tandon P., Singh S., Katti S.B. (1999). J. Macromol.

Sci. Phys., 38:349-366.

Srivastava S., Khan I.A., Srivastava S., Gupta V.D. (2004). Indian J. Biochem.

Biophys., 41:305-310.

Srivastava S., Srivastava S., Singh S., Gupta V.D. (2001). J. Macromol. Sci.

Phys., 40(1):1-14.

Vorlickova M., Kypr J., Kleinwächter V. (1985). Biochim. Biophys. Acta.,

838(2):236-43.

Waring M. (1970). J. Mol. Biol., 54: 247-279.

Waring M.J., Chisholm J.W. (1972). Biochim. Biophys. Acta., 262: 18-23.

Waring M.J., Henley S.M. (1975). Nucleic Acids Res., 2:567-585.

Zimm B.H., Bragg J.K. (1959). J. Chem. Phys., 31:526-535.

75

CHAPTER 4

THIONINE INDUCED

THERMAL STABILITY OF

NATURAL DNAS

76

4.1. Introduction

In recent years the study of small molecules interaction with

deoxyribonucleic acids is a research area of prominent interest. There are

number and variety of techniques devoted to evidence drug-DNA interactions

which are increasing continuously (Perez-Montoto et al., 2009; Gonzalez-Diaz

et al., 2009; Panigrahi and Desiraju, 2007; Rohs et al., 2005). To understand

the interactions between small molecules and biomacromolecules, Tian et al.

summarize some general methodology used in these studies (Tian et al., 2005).

Over the past several years, the interaction of aromatic heterocyclic molecules

with deoxyribonucleic acids has received considerable attention due to their

relevance in a range of biological applications including cancer chemotherapy

(Hurley, 2001, 2002; Martinez and Chacon-Garcia, 2005; Palchaudhuri and

Hergenrother, 2007; Maiti and Kumar, 2007; Paul, et al., 2010; Bhadra and

Kumar, 2011). Accordingly, a number of experimental studies are conducted to

understand the nature and thermodynamics of heterocyclic aromatic molecules

and nucleic acid interaction (Ihaya and Nakamura, 1971; Kumar and Asuncion,

1993; Tuite and Kelly, 1993, 1995; Jockusch, et al., 1996; Dohno, et al., 2003;

Du et al., 2005; Xu, 2006).

Thionine (3,7-Diamino-5- phenothiazinium), a tricyclic heteroaromatic

molecule (Fig. 4.1), has been studied for its intercalative binding with DNA

duplex (Tuite and Kelly, 1995) and its photo-induced mutagenic actions on

binding to DNA (Dohno et al., 2003). According to Chang et al. (2005) thionine

binds specifically with guanine–cytosine (GC) content of DNA duplex as

77

suggested by satellite hole spectroscopy study. However, Tuite and Kelly (1995)

recommended that (GC) specificity of thionine binding was not very marked.

The other study suggested that thionine exists in two different tautomeric forms

viz. amino form and imino form and only amino form is intercalated while the

imino form is not (Hecht et al., 2004, 2005). Another study carried out through

pressure tuning hole burning spectroscopy has conclusively shown an external

stacking mode of thionine binding to quadruplex structures (Hecht et al., 2004).

All these studies provide somewhat contradicting data on the GC specificity of

thionine binding to linear double stranded DNA. Although some structural data

is available, the same is not conclusive and the thermodynamics of thionine

binding to DNA was not elucidated. Recently, the calorimetric analysis of

thionine binding to natural DNAs of varying base composition along with the

structural and thermodynamic aspects of the interaction has been reported by

Paul et al. (2010). These authors recommended strong binding of thionine with

DNAs which increases the thermal stability of the duplex. They also concluded

that binding of thionine to DNA of varying base composition is an exothermic

process and there is involvement of multiplicity of non-covalent interactions in

the binding process. In the present study, we have attempted to understand

the effect of thionine binding on native deoxyribonucleic acids through the

theoretical analysis using the experimental model of Paul et al. who studied the

thermal and thermodynamic behaviour of thionine binding to three natural

DNAs of varying base composition (Paul et al., 2010). We used amended Zimm

and Bragg theory, initially considered for helix coil transitions in polypeptides,

to explain lambda point anomalies in heat capacities and order-disorder

78

transition in thionine bounded and unbounded DNAs (Zimm and Bragg, 1959;

Srivastava et al., 1999, 2001). The effect of thionine binding is reflected in the

change in nucleation parameter, which is an inverse measure of binding

strength.

Fig. 4.1. Chemical structure of thionine

4.2. Theory

The spectroscopic and calorimetric study, carried out by Paul et al.

(2010) for the complex formation between thionine and three natural DNAs of

varying base composition, concluded that thionine binds strongly with DNAs of

different GC content (Clostridium perfringenes DNA, herring testes DNA and

Micrococcus lysodeikticus DNA) which resulted in thermal stabilization of the

complex. The binding of thionine to the DNAs was intercalative and was non-

cooperative that resulted in significant perturbation of the conformation of the

DNA as well as thermal stabilization (Paul et al., 2010). However, the system

remains a highly co-operative one; therefore the co-operative transition theory

could be applied to elucidate the melting profile and temperature dependence

79

of thermodynamic parameters, such as heat capacity. Therefore, amended

Zimm and Bragg theory (1959) may be used theoretical approach which is

described in chapter 2.

4.3. Experiment model

In this study, we used experimental model of Paul et al. (2010) to

understand the effect of thionine binding to natural DNA of various base

specificity.

4.4. Results and discussion

The spectroscopic and fluorescence studies of binding affinity of

thionine with Clostridium perfringenes DNA (Type XII, 27 mol% GC), herring

testes DNA (Type XIV, 41 mol% GC) and Micrococcus lysodeikticus DNA (Type

XI, 72 mol% GC) showed strong intercalative binding and enabled the

assumption of two state systems consisting of bound and free thionine (Paul

et al., 2010). When thionine, a phenothiazinium dye, binds with natural DNAs

of varying base composition as mentioned above, the structure of DNAs duplex

still remains a highly co-operative and thus two-state theory of order-disorder

transition is applicable. The Zimm and Bragg theory (1959) is amended so as

to consider ordered (bounded/unbounded) and disordered states as the two

states which co-exist at the transition point. The transition is characterized

mainly by the nucleation parameter and overall change of enthalpy/entropy,

which are also the main thermodynamic forces driving the transition. The

change in enthalpy obtained from differential scanning calorimetric (DSC)

80

measurements takes all this into account. This is evident from the change in

enthalpy and other transition parameters, such as nucleation parameter (σ)

and melting point as shown in table 4.1. The results obtained from theoretical

analysis recommended that the binding of thionine increases melting

temperature of DNAs at saturation point.

As shown in table 4.1, the melting point of Clostridium perfringenes DNA

(CP DNA), herring testes DNA (HT DNA) and Micrococcus lysodeikticus DNA

(ML DNA) was increased with 6.5, 9 and 9.7 K, respectively in comparison to

free duplexes. The sharpness of the transition was defined in terms of half

width and a sensitivity parameter (∆H/σ). The variations in half width and

sensitivity parameter scientifically reflect that the transition is sharp in case of

unbounded state of CP DNA, HT DNA and ML DNA; and goes blunt when these

DNAs are saturated with thionine. In case of λ-transition, the similar trends in

the sharpness of transition are also seen between the thionine bounded as

well as unbounded curves. As anticipated, the sharpness of transition is better

in unbounded CP DNA, HT DNA and ML DNA, as compared to bounded state

of these DNAs with thionine. The various parameters, which give transition

profiles in best agreement with the experimental measurements for binding of

thionine to DNAs of various base compositions, are given in Table 4.1.

81

Table 4.1. Transition parameters for thionine binding to various natural DNAs

Parameters CP DNA HT DNA ML DNA

Unbounded Saturated* Unbounded Saturated* Unbounded Saturated*

Tm (K) 345 351.5 353 362 365.5 375.2

∆H Kcal/M bp 3.06x103 3.24x10

3 6.41x10

3 9.72x10

3 4.84x10

3 5.81x10

3

Σ 3x10-4 5x10

-4 9x10

-3 2x10

-2 6x10

-4 7.5x10

-4

N 98 90 28 16 82 66

Ah 0 0 0 0 0 0

Ar 1 1 1 1 1 1

Half width (Exp.) 5 6.5 11 12 4.5 5

Half width (Theo.) 5 6.5 11 12 4.5 5

Sensitivity parameter (∆H/σ) 102x105 648x104 712x103 486x103 807x104 775x104

*Saturated with thionine

82

The transition profiles and heat capacity for unbounded CP DNA, HT DNA

and ML DNA; along with bounded with thionine are shown in figure 4.2, 4.3

and 4.4, respectively. As per transition profiles shown in figure 4.2, 4.3 and 4.4;

there are slight insignificant deviation at the tail ends of profiles that may be

primarily due to the presence of various disordered states and short helical

segments found in the random coil states. The curve ‘A’ in figure 4.2, 4.3 and

4.4, shows experimental and calculated transition curves for the CP DNA, HT

DNA and ML DNA, respectively in the absence of thionine. However, curve ‘B’

in figure 4.2, 4.3 and 4.4, shows the transition when CP DNA, HT DNA and ML

DNA was saturated with thionine in the ratio of thionine/CPDNA=0.4,

thionine/HTDNA=0.5 and thionine/MLDNA=0.5, respectively. As it was

expected, a cooperative transition profiles is obtained with calculated data

obtained through theoretical analysis for all the DNAs of varying base

composition. The results obtained from the theoretical analysis are in good

agreement with the binding enthalpy determined through DSC by Paul et al.

(2010).

83

Fig. 4.2. Heat capacity and transition profiles (inset) for thionine bounded and unbounded CP-DNA. (A) Unbounded state, (B)

Bounded state at saturation. [(—) calculated and (••••) experimental values]

84

Fig. 4.3. Heat capacity and transition profiles (inset) for thionine bounded and unbounded HT-DNA. (A) Unbounded state, (B)

Bounded state at saturation. [(—) calculated and (••••) experimental values]

85

Fig. 4.4. Heat capacity and transition profiles (inset) for thionine bounded and unbounded ML-DNA. (A) Unbounded state, (B)

Bounded state at saturation. [(—) calculated and (••••) experimental values]

86

The conformational and dynamical states of thionine binding to CP DNA,

HT DNA and ML DNA are characterized by heat capacity which is second derivative

of the free energy and has been calculated by using equation 15 (described in

chapter 2). These heat capacity curves along with λ-point anomaly and their

transition profiles for CP DNA, HT DNA and ML DNA are shown in figure 4.2, 4.3

and 4.4, respectively which recommended that the theoretically calculated heat

capacity profile agreed with the experimentally reported ones and could be

brought almost into agreement with the use of scaling factors, which is very close

to one in transition profiles and slightly higher for the heat capacity curves. The

sharpness of the transition can be characterized by the half width of the heat

capacity curves. As shown in table 4.1 and figure 4.2 half width of transition for

unbounded and saturated CP DNA are in good agreement in both experimental

and theoretical graphs. Similar results are also obtained in case of HT DNA and

ML DNA in which half width are in good agreement (table 4.1), as shown in figure

4.3 and 4.4, respectively.

This analysis recommended that natural DNAs viz. CP-DNA, HT-DNA and

ML-DNA are very much co-operative structure and their co-operativity is not

greatly disturbed when thionine bind to these DNAs. Accordingly, the modified

Zimm and Bragg hypothesis can be applied to it which generates the experimental

transition profile and λ-point heat capacity anomaly effectively. The data obtained

by theoretical analysis of thionine binding with CP DNA, HT DNA and ML DNA also

demonstrated that the binding of thionine to DNAs are an endothermic process

and this binding increases the melting temperature of the DNAs as suggested by

Paul et al. (2010) through calorimetric study. The specific binding and intercalation

87

of thionine with DNA have been studied by using spectroscopic methods (Tuite and

Kelly, 1995; Chang et al., 2005). However, Paul et al. used optical melting and DSC

techniques to understand the interaction of thionine with three natural

deoxyribonucleic acid viz. CP DNA, HT DNA and ML DNA containing different

composition of GC contents (Paul et al., 2010). In accordance to the finding of Paul

and coworkers, the present theoretical analysis also suggested that the binding of

thionine stabilized DNAs and the melting temperature (ΔTm) of CP DNA, HT DNA

and ML DNA was increases about 6.5, 9 and 9.7 K, respectively under saturating

condition. Consequently, we can interpret results of our theoretical analysis in the

context of the specific structural features of thionine-DNAs complex as supposed

from the spectroscopic/DSC data of Paul et al. (2010). Assessment of curve ‘A’ and

‘B’ from figures 4.2, 4.3 and 4.4, reveals that the transition of the thionine-

saturated DNAs duplex are significantly broader than the transition of the thionine-

free DNAs. Thus, besides affecting the transition enthalpy and melting

temperature, binding of thionine also alters the nature of the transition as revealed

by the increase in transition width in experimental and calculated (theoretical) both

data. The transition width was increases from 5.0 to 6.5, from 11 to 12 and from

4.5 to 5.0 for CP DNA, HT DNA and ML DNA, respectively in theoretical and

experimental both data.

In recent years, an augmented understanding of the role played by nucleic

acids in biological systems made DNA as an alternative candidate for the

development and formulation of new drugs. The successful applications of

molecular modeling in virtual ligand screening and structure-based design of

organic and inorganic molecules that target specific DNA are highlighted by Ma et

88

al. (2011). The interactions of drugs and calf thymus DNA were also investigated

by using non-linear fit analysis (Yuan et al., 2011). Further recent literatures also

reviewed that the study of DNA interaction with a small molecule is of high interest

(Paul et al., 2010; Araya et al., 2007; Islam et al., 2009; Gonzalez-Ruiz et al., 2011;

Kunwar et al., 2011). Therefore, the theoretical studies of small molecules binding

presented in this study may also be used to other synthetic and natural DNAs and

can be applied to understand bimolecular interactions.

4.5. Conclusion

The present theoretical analysis concluded that these natural DNA

molecules are a highly co-operative structure and when thionine binds to these

DNAs the structure of DNA remains a highly co-operative one. Consequently, the

amended Zimm and Bragg (phase transitions) theory can be successfully applied to

it. These results will allow us to calculate the thermodynamic profile of the binding

process. Thus, the present theoretical studies of thionine (small molecules) binding

are being extended to other synthetic and natural DNAs and can be applied to

understand bimolecular interactions. This study may also be used in the

investigation process of drug development and in biomedical industries.

89

References:

Araya F., Huchet G., McGroarty I., Skellern G.G. and Waigh R.D. (2007). Methods,

42: 141-149.

Bhadra K. and Kumar G.S. (2011). Med. Res. Rev., 31: 821–862.

Chang T.C., Yang Y.P., Huang K.H., Chang C.C. and Hecht C. (2005). Opt. Spectro.,

98: 716– 721.

Dohno C., Stemp E.D.A. and Barton J.K. (2003). J. American Chem. Soc., 125:

9586–9587.

Du J.Y., Huang X.H., Xu F., Feng Y.Y., Xing W. and Lu T.H. (2005). Guang Pu Xue

Yu Guang Pu Fen Xi, 25: 1435-1448.

González-Díaz H., Pérez-Montoto L.G., Duardo-Sanchez A., Paniagua E., Vázquez-

Prieto S., Vilas R., Dea-Ayuela M. A., Bolas-Fernández F., Munteanu C.R.,

Dorado J., Costas J. and Ubeira F.M. (2009). J. Theor. Biol., 7: 136-147.

Gonzalez-Ruiz V., Olives A.I., Martin M.A., Ribelles P., Ramos M.T. and Menendez

J.C. (2011). An overview of analytical techniques employed to evidence

drug-DNA interactions. Applications to the design of genosensors. In:

Biomedical engineering, trends, research and technologies, Komorowska

M.A. and Olsztynska-Janus S. (eds.), InTech, pp 65-90.

Hecht C., Friedrich J. and Chang T.C. (2004). J. Phys. Chem. B., 108: 10241–10244.

Hecht C., Hermann P., Friedrich J. and Chang T.C. (2005). Chem. Phys. Lett., 413:

335-341.

90

Hurley L.H. (2001). Biochem. Soc. Trans., 29: 692–696.

Hurley L.H. (2002). Cancer, 2: 188 – 200.

Ihaya Y.J. and Nakamura T. (1971). Bull. Chem. Soc. Japan, 44: 951–957.

Islam M.M., Chowdhury S.R. and Kumar G.S. (2009). J. Phys. Chem. B, 113: 1210-

1224.

Jockusch S., Lee D., Turro N.J. and Leonard E.F. (1996). Proc Natl. Acad. Sci. USA,

93: 7446–7451.

Kumar C.V. and Asuncion E.H. (1993). J. American Chem. Soc., 115: 8547-8553.

Kunwar A., Emmanuel S., Singh U., Chittela R.K., Sharma D., Sandur S.K. and

Priyadarsini I.K. (2011). Chem. Biol. Drug Des., 77: 281–287.

Ma D.L., Chan D.S., Lee P., Kwan M.H. and Leung C.H. (2011). Biochimie, 93:

1252-1266.

Maiti M. and Kumar G.S. (2007). Med. Res. Rev., 27: 649–695.

Martinez R. and Chacon-Garcia L. (2005). Cur. Med. Chem., 12: 127–151.

Palchaudhuri R. and Hergenrother P.J. (2007). Cur. Opin. Biotech., 18: 497–503.

Panigrahi S.K. and Desiraju G.R. (2007). J. Biosci., 32: 677-691.

Paul P., Hossain M., Yadav R.C. and Kumar G.S. (2010). Biophys. Chem., 148: 93-

103.

91

Perez-Montoto L.G., Santana L. and González-Díaz H. (2009). Eur. J. Med. Chem.,

44; 4461-4469.

Poklar N., Pilch D.S., Lippard S.J., Redding E.A., Dunham S.U. and Breslauer K.J.

(1996). Proc. Natl. Acad. Sci. USA, 93: 7606-7611.

Rohs R., Bloch I., Sklenar H. and Shakked Z. (2005). Nucleic Acids Res. 33: 7048-

7057.

Roles K.A. and Wunderlich B. (1991). Biopoly., 31: 477-487.

Srivastava S., Gupta V.D., Tandon P., Singh S. and Katti S.B. (1999). J. Macromol.

Sci. Phys., 38: 349-366.

Srivastava S., Khan I.A., Srivastava S. and Gupta V.D. (2004). Indian J. Biochem.

Biophys., 41: 305-310.

Srivastava S., Srivastava S., Singh S. and Gupta V.D. (2001). J. Macromol. Sci.

Phys., 40: 1-14.

Tian R., Xu S., Lei X., Jin W., Ye M. and Zou H. (2005). Trends Anal. Chem., 24:

810-825.

Tuite E.M. and Kelly J.M. (1993). J. Photochem. Photobiol. B., 21: 103–124.

Tuite E.M. and Kelly J.M. (1995). Biopoly., 35: 419–433.

Xu Y., Yang L., Ye X., He P. and Fang Y. (2006). Electroanalysis 18: 873–881.

Yuan J., Guo W. and Wang E. (2011). Analitica Chimica Acta, 706: 338-342.

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Yunus G., Srivastava S. and Gupta V.D. (2011). Intl. J. Phys. Sci., 6: 8151–8156.

Zimm B.H. and Bragg J.K. (1959). J. Chem. Phys., 31: 526-535.

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CHAPTER 5

CONCLUSION

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In the previous chapters (Chapter 3 and 4) author included theoretical study

of Drug-DNA interaction that comprises stability of synthetic and natural DNA on

binding with drugs/small molecules. Molecular interaction of the drug with

deoxyribonucleic acid is a field of high topical interest. Therefore, a number of

techniques committed to drug-DNA interactions are evolved. In fact, the

transcription or translation of DNA starts only when it receives a signal, which is

often in the form of a regulatory protein binds to a particular region of the DNA.

Thus, if the binding specificity and strength of this regulatory protein can be

emulated by a small molecule, then DNA function can be artificially modulated,

inhibited or activated. Therefore, this synthetic/natural small molecule can act as

a drug when activation or inhibition of DNA function is required to cure or control

a disease. The specific sites of DNA molecule involved in vital processes, such as

origin of replication etc., are of particular interest as targets for a wide range of

antibiotic and anticancer drugs (Haq, 2002; Hurley, 2002.) Drugs bind to DNA both

covalently as well as non-covalently. Covalent binding of drugs with DNA is

irreversible and inhibit DNA processes that leads to cell death. Non-covalent

binding is reversible and is typically preferred over covalent adduct formation

keeping the drug metabolism and toxic side effects in mind.

In drug-DNA interaction, energetics of DNA recognition is not fully

understood at a molecular level, due mainly to the strong electrostatic interactions

prevalent in the system and van der Waals interactions. Protein–drug binding has

been explained by various popular models but a straightforward extrapolation of

those interaction models to DNA–drug systems is not feasible since there is no

formal active site in DNA, unlike enzymes/proteins. However, for understanding of

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DNA–drug interaction, experimental studies play major role and the essential

information on binding constants and corresponding free energy, entropy,

enthalpy, and heat capacity changes on complex formation can be obtained by

thermodynamic studies. This information extremely used to authenticate

investigation based on theoretical predictions and structural analysis. These

theoretical studies on drug-DNA interactions have resulted in important

contributions to understand binding of DNA–drug complexes.

In the present investigation as described in above chapters (chapter 3 and

4), theoretical analysis of steroid diamine (Dipyrandium) and tricyclic hetero-

aromatic molecule (Thionine) binding with DNA duplex by using an amended Zimm

and Bragg theory are reported. These studies explain the melting behavior and

heat capacity of DNA with and without drugs binding. The results of both the

studies (with Dipyrandium and Thionine) suggested that the DNA molecule is an

extremely co-operative structure and when drugs bind to it the co-operativity is

not so much disturbed. Thus, the amended Zimm and Bragg theory can be

effectively applied to it. It generates the experimental transition profile and λ-point

heat capacity anomaly successfully. The results obtained will allow us to evaluate

the thermodynamic profile of the binding process. This theoretical analysis of small

molecules binding with nucleotide is being extended to other synthetic and natural

DNA and can also be useful in order to understand bimolecular interaction and in

the process of drug development.

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References

Haq I. (2002). Arch. Biochem. Biophys., 403: 1-15.

Hurley L.H. (2002). Nat. Rev. Cancer, 2: 188–200.