Lecture 6: Computer aided drug design: structure-based approach. Chen Yu Zong Department of Computational Science National University of Singapore

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Lecture 6 Computer aided drug design
structure-based approach.Chen Yu ZongDepartment
of Computational ScienceNational University of
Singapore

• Drug design overview.
• Introduction of methodology.
• Examples drug resistance, toxicity prediction.

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Traditional Drug Design Methods Random screening

• Long design cycle 7-12 years.
• High cost 350 million USD per marketed drug.
• Drug Discovery Today 2, 72-78 (1997)
• Too slow and costly to meet demand.

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Strategies for improving design cycle

• Smart screening
• High-throughput robotic screening.
• Diversity of chemical compounds
• Combinatorial chemistry.
• Nature 384 Suppl., 2-7 (1996)
• High expectation.

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Alternative approach?

• Current situation
• Molecular mechanism of disease processes,
  structural biology.
• Rising cost of experimental equipment and
  resources.
• Computer revolution (low cost, high power).
• Software development.
• Computer approach?

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Strategies for improving design cycle

• Computer-aided drug design
• Receptor 3D structure unknown
• QSAR.
• Pharm. Res. 10, 475-486 (1993).
• Receptor 3D structure known
• Ligand-protein docking.
• Science 257, 1078-1082 (1992)

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Is ligand-protein docking practical?

• 3D structure of proteins and small molecules
• 20,000 protein entries in PDB,
  growth rate 100-200 per
  month.
• 100,000 small molecules in ACD.
• Computation time
• 100,000 small molecules per week.
• Nature 384 Suppl., 23-26 (1996)
• Computer cost
• Decreasing dramatically.

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Success Stories

• HIV-1 Protease Inhibitors
• Inverase (Hoffman-LaRoche, 1995)
• Norvir (Abbot, 1996)
• Crixivan (Merck, 1996)
• Viracept (Agouron, 1997)
• Drug discovery today 2, 261-272 (1997)

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Examples of Other Drugs Designed by
Structure-Based Methods

• Human renin inhibitor
• Antihypertension.
• Collagenase and stromelysin inhibitor Anticancer
  and antiarthritis.
• Purine nucleotide phosphorylase inhibitor
  Antidepressant.
• Thymidylate synthase inhibitor Antiproliferation.
• Nature 384 suppl, 23-26 (1996)

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Favourable Conditions forApplication of
Ligand-Protein Docking

• Human Genome Project
• Protein Crystallography
• Functional Genomics
• Pharmacogenomics
• Molecular Biology
• Modeling Technology
• Information Technology

• ? Ligand-Protein Docking

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Computer-aided drug design in Industry and
Premier Universities

• Pharmaceutical Giants
• Merck, Abbott, Bristol-Myers Squibb, Pfizer,
  Glaxo-Welcome.
• Biotech New and Emerging Stars
• Agouron, Arris, Chiron, ISIS, MetaXen, Vertex.
• Major Universities
• Harvard, UCSF, UC Berkeley, Washington U,
  Cambridge, Columbia.

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Computer-aided drug design in Industry

• Structure-based design viewed as having
  competitive edge
• An indication Companies are withholding 3D
  structures of key proteins.
• Modeling group viewed as a key component in drug
  discovery team
• Many companies have setup modeling group.
• Investment in computer equipment
• An indication Glaxo-welcome bought 100 SGI
  workstations in 1996.

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Ligand-Protein Docking is the Most Rational
ApproachReason Based on receptor structure

• Mechanism of drug action

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Mechanism of drug action
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Mechanism of drug binding
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Ligand binding mechanism
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.
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.
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.
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Scoring Functions in Ligand-Protein Docking

• Potential Energy Description

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Scoring Functions in Ligand-Protein Docking

• Potential Energy Description

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Scoring Functions in Ligand-Protein Docking

• Potential Energy Description
• van der Waals interactions
• Electrostatic interactions
• V ?ligand atoms Aij1/2 Arec- Bij1/2 Brec
  qiQrec

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Modelling Strategy for Ligand-Protein Docking
Average CPU time 5,000 small molecules per week
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The Use of Molecular Mechanics Energy Functions
in Docking Evaluation

• Potential Energy Description
• Hydrogen bonding
• van der Waals interactions
• Electrostatic interactions
• Empirical solvation free energy (energy
  evaluation only)
• V ?H bonds V0 (1-e-a(r-r0) )2 - V0
• ?non bonded Aij/rij12 - Bij/rij6 qiqj
  /?r rij
• ?atoms i Dsi Ai

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Example 1 Study of Drug Resistant Mutations by
Ligand-Protein Docking

• Enzyme-inhibitor PDB Id
  Mutation introduced
• HIV-1 protease MK 639 1HSG V82A, V82F, V82I,
  I84V, V82f/I84V, M46I/L63P,
• 
  V82T/I84V, M46I/L63P/V82T/I84V
• HIV-1 protease Saquinavir 1HXB V82F, V82I,
  I84V, G48V, V82F/I84V, V82T/I84V
• HIV-1 protease SB 203386 1SBG I32V/V47I/I82V
• HIV-1 protease VX 478 1HPV M46I/L63P,
  V82T/I84V, M46I/L63P/V82T/I84V
• HIV-1 protease U89360e 1GNO V82D, V82N,
  V82Q, D30F
• HIV-1 RT Nevirapine 1VRT L100I, K103N, V106A,
  E138K, Y181C, Y188H
• HIV-1 RT TIBO R82913 1TVR L100I, K103N, V106A,
  E138K, Y181C, Y188H
• J. Mol. Graph. Mod. 19, 560-570 (2001).

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Quality of Modelled Structures
Wild type X-ray structure Blue Modelled mutant
Red Mutant X-ray structure Green
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Mutation induced energy change compared with
observed drug resistance data
J. Bio. Chem.271, 31947 (1996) AIDS 12 453
(1998) Biochemistry 37, 8735 (1998)
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Modelling Strategy for Ligand-Protein Induced
Fit Generation of multiple conformations
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Example 2 Prediction of toxicity, side effect,
pharmacokinetics and pharmacogenetics by a
receptor-based approach

• Annu. Rev. Pharmacol Toxicol 2000, 40353-388
• 1997, 37269-296
• Pharmacological Rev. 2000, 52207-236

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Importance of prediction of side effect,
toxicity, pharmacokinetics in early stages of
drug discovery

• Most drug candidates fail to reach market
• Pharmacokinetics (60), side-effect and toxicity
  (40) are the main reason.
• Large portion of money (USD350 million) and time
  (6-12 years) spent on a clinical drug has been
  wasted on failed drugs.
• Drug Discov Today 1997 272

Drug Candidates in Different Stages of
Development Majority of Candidates Fail to Reach
Market Clin Pharmacol Ther. 1991 50471
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Strategy
Proteins 200143217
Science 1992257 1078
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Feasibility

• Proteins
• Database gt20,000 3D structures in PDB.
• Protein diversity 17 in PDB with unique
  sequence.
• Advance in structural genomics 10,000 unique
  proteins within 5 years.
• 
  Ann. Rev. Biophys. Biomol. Struct. 1996 25113
  
• 
  Nature Struct. Biol. 1998 51029
• Method
• Ligand-protein docking docking algorithms capable
  of finding binding conformations.
• 
  Proteins. 1999 361 Proteins 2001 43217
• Additional information
• Rapid accumulation of knowledge in proteomics,
  pathways, protein functions.
• Computer resources
• Increasing power and decreasing cost (Linux PC,
  Multi-processor machines)

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Automated Protein Targets Identification
Software INVDOCK
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INVDOCK Testing on Toxicity Targets
J. Mol. Graph. Mod., 20, 199-218 (2001).
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Toxicity and side effect targets of Aspirin
identified from INVDOCK search of protein
database
J. Mol. Graph. Mod., 20, 199-218 (2001).
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Conclusion

• Structure-based computer aided drug design is a
  promising approach.
• Revolution in molecular biology and computer
  technology sets the stage for this approach.
• Much remains to be done.