IN SILICO SCREENING FOR RESVERATROL DERIVATIVES WITH INCREASED BIOAVAILABILITY

AND INCREASED BINDING AFFINITY TO SIRT-1 PROTEIN

Bonafide Work done by

V. Ganesan (07B425)K. R. Manoj Kumar (07B427)

Under the guidance ofDr. Ananthasubramanian

Ms. Kalyani Sen

DEPARTMENT OF BIOTECHNOLOGYPSG COLLEGE OF TECHNOLOGY

(Govt. Aided Autonomous Institution & ISO 9001:2000 Certified)PEELAMEDU, COIMBATORE – 641 004.Phone : 0422 – 2572177, 2572477, 4344777

Fax : 0422 – 2573833, Email : psgct@vsnl.com

PSG COLLEGE OF TECHNOLOGY(Govt. Aided Autonomous Institution & ISO 9001:2000 Certified)

PEELAMEDU, COIMBATORE – 641 004.

IN SILICO SCREENING FOR RESVERATROL DERIVATIVES WITH INCREASED BIOAVAILABILITY

AND INCREASED BINDING AFFINITY TO SIRT-1 PROTEIN

This is a bonafide work done by

V. Ganesan (07B425)K. R. Manoj Kumar (07B427)

October 2009

Dr. Ananthasubramanium Ms. Kalyani Sen Dr.RamamurthyFaculty Guide Faculty Guide Head of the Department

________________________________________________________________________

Certified that the candidate was examined in the viva-voce examination held on

……………………..

………………………….. ...................................

(Internal Examiner) (External Examiner)

CONTENTS

CHAPTER Page No.

Acknowledgement ............................................................................... (i)

Conspectus ............................................................................................... (ii)

List of Abbreviations .......................................................................... (iii)

1. INTRODUCTION ......................................................................... 1

1.1 RESVERATROL

1.2 SIRT-1

1.3 MECHANISM OF ACTION

1.4 BIOAVAILABILITY OF RESVERATROL

1.5 DOCKING

2. LITERATURE REVIEW ............................................................. 2

3. OBJECTIVE .......................................................................

4. MATERIALS AND METHODS...........................................

4.1 ONLINE DATABASE USED

4.2 TOOLS USED

4.3 METHODOLOGY

5. DISCUSSION ...............................................................................

6. CONCLUSION ............................................................................

7. BIBLIOGRAPHY .......................................................................

ACKNOWLEDGEMENT

We wish to express our heart felt gratitude to our Head of the Department,

Dr. Ramamurthy, for extending his full support and giving us this wonderful

opportunity to accomplish this project.

We express our sincere gratitude to our esteemed guides,

Dr. M. Ananthasubramanian, Assistant Professor, Department of Biotechnology, and

Ms. Kalyani Sen, Lecturer, Department of Biotechnology, for their patient suggestions,

constructive criticism and sustained guidance throughout the course of work. It was a

great privilege to have worked under their able guidance. Their unabated seal and timely

help paved a smooth path to complete the work successfully.

We thank all other professors and lecturers of the department for their

guidance throughout the work.

We thank all the lab assistants and junior researchers for rendering all the

possible help whenever required.

We thank our family members and all our friends who were our moral

support throughout the project.

We thank the Almighty for blessing us with strength, wisdom, knowledge

and patience that rendered us to complete this work.

If the words are considered as symbols of approval and token of

acknowledgement, then let the words play the heralding role of expressing gratitude to all

those who have helped us directly of indirectly during this project.

V. Ganesan

K. R. Manoj Kumar

1. INTRODUCTION

1.1 RESVERATROL:

Resveratrol (trans-resveratrol) is a phytoalexin produced naturally by several plants when under attack by pathogens such as bacteria or fungi. Resveratrol has also been produced by chemical synthesis and is sold as a nutritional supplement derived primarily from Japanese knotweed. In mouse and rat experiments, anti-cancer, anti-inflammatory, blood-sugar-lowering and other beneficial cardiovascular effects of resveratrol have been reported. Most of these results have yet to be replicated in humans. In the only positive human trial, extremely high doses (3–5 g) of resveratrol in a proprietary formulation have been necessary to significantly lower blood sugar. Resveratrol is found in the skin of red grapes and is a constituent of red wine, but apparently not in sufficient amounts to explain the French paradox. Experiments have shown that resveratrol treatment extended the life of fruit flies, nematode worms and short living fish, and mice.

FIG 1: STRUCTURE OF RESVERATROL

1.2 SIRT-1:

Sirtuin 1 stands for silent mating type information regulation 2 homolog 1 S. cerevisiae, referring to the fact that its sirtuin homolog in yeast (S. cerevisiae) is Sir2. SIRT1 is an enzyme which deacetylates proteins that contribute to cellular regulation. SIRT1 is one of seven mammalian homologs of Sir2 that catalyzes NAD+ dependent protein deacetylation, yielding nicotinamide and O-acetyl-ADP-ribose. Originally described as a factor regulating longevity, apoptosis and DNA repair.

1.3 MECHANISM OF ACTION:

One of the proposed mechanisms by which resveratrol increases life span is by binding allosterically to SIRT-1 and increases its activity

by as much as 8-fold by lowering the Km value for acetylated substrate PGC-1α which is a transcriptional co activator which has pleiotropic functions most important among which is, it activates genes involved in mitochondrial biogenesis and protects against metabolic diseases and there by increasing life span. SIRT1 physically interacts with and deacetylates PGC-1α at multiple lysine sites, consequently increasing PGC-1α activity leading to the induction of gene transcription involved in mitochondrial biogenesis, metabolism of lipids and glycogen.

1.4 BIOAVAILABILITY OF RESVERATROL:

About 70% of the resveratrol dose given orally as a pill is absorbed; nevertheless, oral bioavailability of resveratrol is low because it is rapidly metabolized in intestines and liver into conjugated forms: glucuronate and sulfonate. Only trace amounts (below 5 ng/mL) of unchanged resveratrol could be detected in the blood after 25 mg oral dose. Even when a very large dose of resveratrol (2.5 and 5 g) was given as an uncoated pill, the concentration of resveratrol in blood failed to reach the level necessary for the systemic effects.

1.5 DOCKING:

In the field of molecular modeling, docking is a method which predicts the preferred orientation of one molecule to a second when bound to each other to form a stable complex. Knowledge of preferred orientation in turn may be used to predict the strength of association or binding affinity between two molecules using for example scoring functions.

Docking is frequently used to predict the binding orientation of small molecule drug candidates to their protein targets in order to predict the affinity and activity of the small molecule. Hence docking plays an important role in rational design of drugs. Given the biological and pharmaceutical significance of molecular docking, considerable efforts have been directed towards improving the methods used to predict docking.

2. LITERATURE REVIEW

Howitz et.al (2003) reported that resveratrol significantly extends the lifespan of the yeast Saccharomyces cerevisiae. Later studies conducted by Sinclair showed that resveratrol also prolongs the lifespan of the worm Caenorhabditis elegans and the fruit fly Drosophila melanogaster.

Valenzano et.al (2006), Italian scientists obtained the first positive result of resveratrol supplementation in a vertebrate. Using a short-lived fish, Nothobranchius furzeri, with a median life span of nine weeks, they found that a maximal dose of resveratrol increased the median lifespan by 56%. The authors noted a slight increase of mortality in young fish caused by resveratrol and hypothesized that it is its weak toxic action that stimulated the defense mechanisms and resulted in the life span extension.

Sinclair et.al (2006) reported that resveratrol counteracted the detrimental effects of a high-fat diet in mice. The high fat diet was compounded by adding hydrogenated coconut oil to the standard diet; it provided 60% of energy from fat, and the mice on it consumed about 30% more calories than the mice on standard diet. Both the mice fed the standard diet and the high-fat diet plus 22 mg/kg resveratrol had a 30% lower risk of death than the mice on the high-fat diet. Gene expression analysis indicated the addition of resveratrol opposed the alteration of 144 out of 155 gene pathways changed by the high-fat diet. Insulin and glucose levels in mice on the high-fat+resveratrol diet were closer to the mice on standard diet than to the mice on the high-fat diet. However, addition of resveratrol to the high-fat diet did not change the levels of free fatty acids and cholesterol, which were much higher than in the mice on standard diet.

Marie Lagouge et.al (2006) Diminished mitochondrial oxidative phosphorylation and aerobic capacity are associated with reduced longevity. They tested whether resveratrol, which is known to extend lifespan, impacts mitochondrial function and metabolic homeostasis. Treatment of mice with RSV significantly increased their aerobic capacity, as evidenced by their increased running time and consumption of oxygen in muscle fibers. RSV’s effects were associated with an induction of genes for oxidative phosphorylation and mitochondrial biogenesis and were largely explained by an RSV-mediated decrease in PGC- 1α acetylation and an increase in PGC-1α activity. This mechanism is consistent with RSV being a known activator of the protein deacetylase.

Thomas Walle et.al (2004) The dietary polyphenol resveratrol has been shown to have chemopreventive activity against cardiovascular disease and a variety of cancers in model systems, but it is not clear whether the drug reaches the proposed sites of action in

vivo after oral ingestion, especially in humans. In this study, they examined the absorption, bioavailability, and metabolism of 14C-resveratrol after oral and i.v. doses in six human volunteers. The absorption of a dietary relevant 25-mg oral dose was at least 70%, with peak plasma levels of resveratrol and metabolites of 491±90 ng/ml and a plasma half-life of 9.2±0.6 h. However, only trace amounts of unchanged resveratrol (<5 ng/ml) could be detected in plasma. Most of the oral dose was recovered in urine, and liquid chromatography/ mass spectrometry analysis identified three metabolic pathways, i.e., sulfate and glucuronic acid conjugation of the phenolic groups and, interestingly, hydrogenation of the aliphatic double bond, the latter likely produced by the intestinal microflora. Extremely rapid sulfate conjugation by the intestine/liver appears to be the rate-limiting step in resveratrol’s bioavailability. Although the systemic bioavailability of resveratrol is very low, accumulation of resveratrol in epithelial cells along the aerodigestive tract and potentially active resveratrol metabolites may still produce cancer preventive and other effects.

Zakeri et.al (2006) In this study they investigate the relationship between the intestinal absorption of structurally diverse model drugs across the rat intestinal mucosa and their molecular properties. Permeability coefficients for 13 compounds were determined in anaesthetized rats. Drug solution in phosphate buffered saline (PBS) was perfused through the intestinal segment with flow rate of 0.21 ml/min and samples were taken from outlet tubing at different time points up to 90 min. The permeability values ranged from 1.6×10-5 to 2 ×10-4 cm/sec for atenolol and ibuprofen respectively. Molecular properties of drugs including the number of hydrogen bond donors and acceptors, log P, logD, topological polar surface area and number of rotatable bonds were considered. The results indicated that compounds which meet 10 or fewer number of rotatable bonds and topological surface area equal to or less than 140 A◦ have a high probability of good intestinal permeability and fraction of dose which is absorbed in human. Moreover the results indicated that lower number of hydrogen bond counts and higher logD and logP values are associated with higher permeability and bioavailabilty of drugs. Therefore the experimental and computational methods could be used for the prediction of intestinal drug permeability.

3. OBJECTIVE

To screen for resveratrol derivatives in silico for increased bioavailability and increased binding affinity to SIRT-1 protein.

4. MATERIALS AND METHODS4.1 ONLINE DATABASE USED:

PubChem:

PubChem provides information on biological activities of small molecules. It is a component of NIH’S molecular libraries initiative.

PubChem includes substance information, compound structures and bioactivity data in three primary databases, pubChem substances, pubChem compound and pudChem bioassay respectively

PubChem substance contains more than 40 million records. PubCoumpound contains more than 19 million unique structures. PubChem bioassay contains more than 1000 bioassays.

PDB:

The protein data bank(pdb) is a repository for 3-D structure of proteins and nucleic acids. These data, typically obtained by x-ray crystallography or NMR spectroscopy and submitted by biologist and biochemists from around the world, are released into the public domain, and can be accesed for free.

This database was found in 1971 by Drs. Edgar Meyer and Walter Hamiton of Brookhaven National Laboratory and the management of the Protein Data Bank was transferred In 1998 to member of Research Collaboratory for Structural Bioinformatics (RCSB). As of 15 April 2008, data base contained 50,277 released atomic coordinate entries (or “structures”), 46,400 of that proteins, the rest being nucleic acid protein complexes and few other molecules. About 5000 new structures are released in each year. It is estimated that the size of the PDB archive will triple to 1,50,000 by the year 2014.

4.2 TOOLS USED:

Swiss-Pdb Viewer(spdbv):

Swiss-Pdb viewer is a application that provides a user friendly interface allowing to analyze several proteins at the same time. The proteins can be super imposed in order

to deduce structural alignments and compare the active sites or any other relevant parts. Amino acid mutations, H- bonds, angles and distances between atoms are easy to obtain.

Q- Site Finder:

Q-Site finder is a new energy-based method for predicting protein-ligand binding sites. The method analyses interaction energies of a methyl probe with a protein using software developed by Jackson. Probes with favorable interaction energies are retained and cluster of these probes are ranked according to their total interaction energies. The energetically most favorable cluster is ranked.

Marvin Sketch:

Marvin sketch is a advanced chemical editor for drawing chemical structures, queries and reactions. It has a rich list of editing features, is chemically aware and it is able to call ChemAxon’s structure based calculation plug-ins for the structures on the canvas.

Argus Lab:

It is a molecular modeling, graphics, and drug design program. It was first introduced by Mark Thompson and Planaria software LLC.

DSSTox:

Distributed structure searchable toxicity database network is a project of EPA’S National Centre For Computational Toxicology, helping to build a public data foundation for improved structure-activity and predictive toxicology capabilities. The DSSTox website provides a public forum for publishing downloadable structure searchable, standardized chemical structure files associated with toxicity data.

LIPINSKI’S RULE OF FIVE:

Lipinski’s rule of five is a thumb rule to evaluate drug likeness, or to determine if a chemical compound with a certain pharmacological or biological activity has properties that would make it a likely orally active drug in humans. The rule was formulated by Christopher A. Lipinski in 1997, based on the observation that most medication drugs are relatively small and lipophilic molecules.

The rule describes molecular properties important for a drug’s pharmacokinetics in human body, including their absorption, distribution, metabolism, and excretion (ADME). However, the rule does not predict if a compound is pharmacologically active.

The rule is important for drug development where a pharmacologically active lead structure is optimized step-wise for increased activity and selectivity, as well as drug-like properties as described by Lipinski’s rule. The modification of the molecular structure often leads to drugs with higher molecular weight, more rings, more rotatable bonds and higher lipophilicity.

Lipinski’s rule of five states that in general, and orally active drug as no more than one violation of following criteria:

Not more than 5 hydrogen bond donors(nitrogen or oxygen atoms with one or more hydrogen atoms).

Not more than 10 hydrogen bond acceptors(nitrogen or oxygen atoms). A molecular weight under 500 g/mol(160-480). A partition coefficient logP less than 5(-0.4 to +5.6).

4.3 METHODOLOGY:

4.3.1 Retrival of Receptor(SIRT-1):

Structure of SIRT-1 NAD dependent deacetylase was obtained from RCSB Protein Data Bank.

The retrieved structure was then visualized using SWISS PDB modeler and the co-crystallized ligand was then deleted by selecting the ligand alone using control panel in windows menu, then it was discarded using File menu.

The structure was then saved as selected layer and it was further used for docking studies.

4.3.2 Ligand Preparation:

From the PubChem compound search the SDF file format of the lead compound Resveratrol was obtained.

Using Marvin Sketch the SDF format was converted into mol2 file format. From the lead molecule resveratrol several derivatives are drawn using Marvin

sketch by altering the side chains and the structures are saved in mol2 format. The mol2 format structures obtained was then used for docking.

4.3.3 Descriptor Calculation:

Molecular descriptors such as logP, polar surface areas, hydrogen bond donors and acceptors are calculated for the lead and derivatives using Marvin sketch descriptor plug-ins in the tools option.

4.3.4 Predicting the Binding Sites:

Using the Q site finder the ten most probable binding sites were identified. The X,Y, Z coordinates for each of the ten sites were noted. These coordinate values were used as input for docking in ArgusLab. The lead was docked in all the ten sites, the site in which the lead bind with least

energy was selected as the binding site for further dockings.

4.3.5 Docking:

Docking was performed using ArgusLab software . Using file menu both receptor and ligand was opened. The ligand and receptor was selected and saved. Then in calculation menu dock a ligand option was selected. Enter the coordinate values of the binding site and start button was clicked. It displays the docking energy in kcal/mol.

4.3.6 DSSTox Analysis:

Ligands in smiles were given as input to DSSTox online server. It lists out coumpounds which exactly matches and which are similar along with

the similarity score.

5. RESULTS AND DISCUSSION

FIG2: RETRIAL OF STRUCTURE FORM RCSB PDB.

FIG3: STRUCTURE OF RESVERATROL AND ITS CALCULATED DISCRIPTORS USING MARVIN SKETCH.

FIG4: Q SITE FINDER.

FIG5: DSSTox ANALYSIS.

TABLE1: RESVERATROL DERIVATIVES WITH DISCRIPTORS.

S.NO MOLECULAR FORMULA

MOLECULAR WEIGHT

LOGP H BOND DONOR

H BOND ACCEPTOR

PSA

1. C20H24 264.405 7.35 0 0 02. C20H18O6 354.53 3.26 0 6 78.93. C20H18O3 306.355 2.69 0 6 51.214. C18H20O 252.351 6.2 1 1 20.235. C18H16O5 312.317 3.3 1 5 72.836. C18H16O3 280.318 3.09 1 5 54.377. C17H18O3 270.23 4 0 3 27.698. C17H18 222.325 6.16 0 0 09. C16H16O3 256.296 3.97 1 3 38.6910. C16H16O2 240.297 5.05 2 2 40.4611. C16H16O 224.298 5.41 1 1 20.2312. C15H14O4 258.269 3.2 3 4 69.913. C15H14O3 242.27 3.94 2 3 49.6914. C15H14O2 226.27 4.66 2 2 40.4615. C14H9N3O9 363.236 5.43 0 15 165.1516. C14H9N3O6 315.328 4.62 0 12 137.4617. C14H12O4 244.43 3.62 4 4 80.9218. C14H12O3 228.243 3.91 3 3 60.69

TABLE2: DERIVATIVES WHICH OBEY LIPINSKI’S RULE OF FIVE

S.NO MOLECULAR FORMULA

MOLECULAR WEIGHT

LOGP

H BOND DONOR

H BOND ACCEPTOR

PSA % SIMILARITY WITH RESVERATROL

1. C20H18O6 354.53 3.26 0 6 78.9 56

2. C20H18O3 306.355 2.69 0 6 51.21 <44

3. C18H16O5 312.317 3.3 1 5 72.83 58.6

4. C18H16O3 280.318 3.09 1 5 54.37 52.40

5. C17H18O3 270.23 4 0 3 27.69 77.20

6. C16H16O3 256.296 3.97 1 3 38.69 79.60

7. C15H14O4 258.269 3.2 3 4 69.9 79.60

8. C15H14O3 242.27 3.94 2 3 49.69 86.30

9. C15H14O2 226.27 4.66 2 2 40.46 88.80

10. C14H12O4 244.43 3.62 4 4 80.92 89.40

TABLE3: DOCKING RESULTS.

S.NO MOLECULAR FORMULA

DOCKING ENERGY(KCAL/MOL)

% SIMILARITY WITH RESVERATROL

1. C20H18O6 -6.4762 56

2. C20H18O3 NA <44

3. C18H16O5 -6.11484 58.6

4. C18H16O3 -6.15654 52.40

5. C17H18O3 -6.84641 77.20

6. C16H16O3 -6.466 79.60

7. C15H14O4 -6.2235 79.60

8. C15H14O3 -7.66755 86.30

9. C15H14O2 -7.97313 88.80

10. C14H12O4 -7.91989 89.40

11. C14H12O3

(RESVERATROL)-7.60864 100

From the docking studies compounds C15H14O2, C15H14O3, C14H12O4 were ligands found to have high binding affinity to SIRT-1.

It has been also observed that molecules with high structural similarity with resveratrol showed higher binding affinity to SIRT-1.

C14H12O4 C15H14O2

C15H14O3

FIG6: POTENTIAL CANDIDATES.

DISCUSSION:

Based on the docking and screening using lipinski’s rule the three compounds out of the eighteen compounds were identified to have better drug like properties and binding affinity to SIRT-1 than Resveratrol. Further wet lab experiments has to be made to check whether these results are reliable.