the many roles of computational science in drug design and analysis
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The Many Roles of Computational Science in Drug Design and Analysis. Mala L. Radhakrishnan Department of Chemistry, Wellesley College June 17, 2008 DOE CSGF Fellows Conference, Washington, D.C. …target rapidly mutates!. Amprenavir bound to HIV-1 protease. (HIV). - PowerPoint PPT PresentationTRANSCRIPT
The Many Roles of Computational Science in Drug
Design and Analysis
Mala L. RadhakrishnanDepartment of Chemistry, Wellesley College
June 17, 2008DOE CSGF Fellows Conference, Washington, D.C.
Amprenavir bound to HIV-1 protease
(HIV)
Kim et al, J. Am . Chem . Soc. 117:1181, 1995
Shafer, Clinical Microbiology Rev., 15:247, 2002
…target rapidly mutates!
Understanding binding specificity and promiscuity
Developing methods for optimal drug cocktail design
Designing broadly-binding HIV-1 protease inhibitors
HIV−1 Protease
Ligand (drug)
Receptor (target)
Goal: create a high-affinity interaction low G
Ligand (drug)
Receptor (target)
“Reality”:
Quantum mechanics
Statistical Mechanics
Model:
Atoms as spheres
Point charges
(Rigid Binding)
Ligand (drug)
Receptor (target)
Model:
Atoms as spheres
Point charges
(Rigid Binding)
+
+
-
-Ligand (drug)
Receptor (target)
+ -
+
+
-
-Drug
Target
+ -
+
+−+
+−++
−
++ −
++
−
++
−
+
+−
++−
++
−
+
+−+ +
−+
+−
+
+ −++
−
Interactions with solvent
+
+
-
-
+ -
Loss of solvation FAVORS LOW CHARGE MAGNITUDES
Drug-target interaction FAVORS HIGH CHARGE MAGNITUDES
+
+ −+
+−
++
−
+ +−
++−
++
−
++
−
++−
+
+
-
-
+ -
Our Model
“solvent continuum”: high dielectric + mobile ions
Designing Toward Multiple Targets
+-
+-
-+
+
-
++
-
?Physical Properties Tailored Recognition
Theoretical Framework
+
L R C
Solvent continuum
Kangas and Tidor, J Chem Phys, 109:7522-7545, 1998
Gbind = vdW + SASA + qLTLqL + qR
TRqR + qRTCqL
G
charge value
The binding profile looks like a paraboloid.
+ …+--
+ +
- -
- +
+ +
- -+
+
--
Theoretical Framework
A promiscuous ligand A specific ligand
Radhakrishnan and Tidor, J. Phys. Chem. B, 111:13419-13435, 2007
Model Systems
Radhakrishnan and Tidor, J. Phys. Chem. B, 111:13419-13435, 2007
• Smaller ligands are more promiscuous than larger ligands
Theory and Model Systems Agree:
Drug charge distribution
Numerical ExperimentTheory
G
qR
Binding profile for a big ligand
Binding profile for a small ligand
black:small red: big
Some Other Insights
• Smaller ligands are more promiscuous
• Hydrophobic ligands are more promiscuous because they are near the center of biological charge space
• Hydrophobic ligands are more promiscuous because they are not as sensitive to shape differences
• Flexibility makes polar and charged ligands more specific, but allows for greater overall binding affinity to multiple partners.
• Asymmetric groups can lead to increased promiscuity
Radhakrishnan and Tidor, J. Phys. Chem. B, 111:13419-13435, 2007
HIV−1 Protease
Understanding binding promiscuity
Developing methods for optimal drug cocktail design
Designing broadly-binding HIV-1 protease inhibitors
Rational Cocktail Design
Drug 2
Drug 1
target variants
decoy
Cocktail Design as an Optimization Problem
Can also combinatorially design individual molecular members simultaneously
Minimize # drugs in cocktail
All targets covered by at least one drug
All targets covered by at least one drug
Minimize sum of binding energies
Size of cocktail is optimal
E
drugs
targ
ets+
de
coy
s
affinity thresholds A
drugs
targ
ets
A’1 0 0 0 1 1 ...
pre-process out decoys
(mxn)
Optimally covering model ensembles
---
-
0 0.5
0.5 -0.5
0 -0.5
0 0Radhakrishnan and Tidor, J. Chem. Inf. Model . 48:1055-1073, 2008
Tiling the Mutation Space
-0.5 0.5
0.5 -0.5
0 -0.5
0 -0.5
0 0.5
0 0.5
0.5 -0.5
-0.5 0.5
q(target,1)
q(t
arg
et,2
)
q(target,1)
q(t
arg
et,2
)
0 0
0 0
HIV−1 Protease
Understanding binding promiscuity
Developing methods for optimal drug cocktail design
Designing broadly-binding HIV-1 protease inhibitors
Designing into Multiple Targets: HIV-protease
Wild Type V82AI84VD30NL90MI50V
L63P, V82T, I84V
Methods:
Molecular “scaffolds”
F
OH
Functional groups
F
Michael Altman et al. J. Amer. Chem Soc., 130: 6099-6113, 2008
G, fast energy function
G,High resolution energy function
Dead-End Elimination, A*:
List of tight-binding compounds
Design of Broadly−Binding HIV−1 Protease Inhibitors
Wild Type
V82AI84VD30NL90MI50V
L63P, V82T, I84V
Physical Properties
0 70
7
Energy threshold (kcal/mol)
Siz
e o
f o
pti
mal
co
ckt
ail
Michael Altman et al. J. Amer. Chem Soc., 130: 6099-6113, 2008
Summary
• Physical Framework for Binding Promiscuity and Specificity
• Methods For Designing Toward Target Ensembles
• HIV-1 Protease as a Case Study
The Many Roles of Computation Computation can…
…map out key interactions in a
binding site.
…design drugs. …predict properties that make drugs
specific or “promiscuous.”
…design drug cocktails.
…model cellular events.
…design novel experimental
systems.
…etc. !
…analyze clinical data
Acknowledgements
MIT Wellesley- Bruce Tidor - Bilin Zhuang and Andrea Johnston- Michael Altman- Dave Czerwinski
- Celia Schiffer, Tariq Rana, Michael Gilson and groups.
Funding: DOE CSGF, NIH, Wellesley College