2009 AMS-535 Fall

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Example Quiz/Exam Questions from Prior Semesters

example.questions.pdf


Course Participants, Topics, References, and Schedule

Date
Topic
Speaker and Presentation
Primary Reference
Secondary Reference
2009.08.31 Mon
  • Organizational Meeting
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2009.09.02 Wed

SECTION I: DRUG DISCOVERY AND BIOMOLECULAR STRUCTURE

  • Drug Discovery
  1. Introduction, history, irrational vs. rational
  2. Viral Target Examples
 Rizzo, R.

1-2. Jorgensen, W. L., The many roles of computation in drug discovery. Science 2004, 303, 1813-8

1-2. Kuntz, I. D., Structure-based strategies for drug design and discovery. Science 1992, 257, 1078-1082

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2009.09.07 Mon
  • No Class: Labor Day
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2009.09.09 Wed
  • Chemistry Review
  1. Molecular structure, bonding, graphical representations
  2. Functionality, properties of organic molecules
Rizzo, R.
presentation
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2009.09.14 Mon
  • Biomolecular Structure
  1. Lipids, carbohydrates
  2. Nucleic acids, proteins
Rizzo, R.
presentation
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2009.09.16 Wed
  • Molecular Interactions and Recognition
  1. Electrostastics, VDW interactions, hydrophobic effect, molecular recognition (binding energy)
  2. Inhibitors types: allosteric, transition state, covalent vs non-covalent, selective, competitive

Rizzo, R.

presentation
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2009.09.21 Mon
  • Intro. to Methods in 3-D Structure Determination
  1. Crystallography, NMR
  2. Structure Quality, PDB in detail


Rizzo, R.
presentation
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2009.09.23 Wed
Quiz Prior Section I


SECTION II: MOLECULAR MODELING

  • Classical Force Fields
  1. All-atom Molecular Mechanics

1. Goyal, R.

1. Mackerell, A. D., Jr., Empirical force fields for biological macromolecules: overview and issues. J. Comput. Chem. 2004, 25, 1584-604

1. van Gunsteren, W. F.; et al., Biomolecular modeling: Goals, problems, perspectives. Angew. Chem. Int. Ed. Engl. 2006, 45, 4064-92

2009.09.28 Mon
  • No Class: Yom Kippur
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2009.09.28 Tues: Correction Day Follow MON Scedule
  • CHE-607 Modern Drug Design and Discovery: Computational Biology Lectures
  1. TBA
  2. TBA

1. Simmerling, C.

2. Rizzo, R.

NOTE:

For today only we will merge with Professor Ojima's "Modern Drug Design and Discovery" class.

CLASS ROOM CHANGE:

Chemistry Department Room 410
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2009.10.08 Wed class ends at 5:00
  • Force Field Development
  1. OPLS
  2. AMBER

1. Au, L.

2. Holden, P.

1. Jorgensen, W. L.; et al., Development and Testing of the OPLS All-Atom Force Field on Conformational Energetics and Properties of Organic Liquids. J. Am. Chem. Soc. 1996, 118, 11225-11236

2. Cornell, W. D.; et al., A Second Generation Force Field For the Simulation of Proteins, Nucleic Acids, and Organic Molecules. J. Am. Chem. Soc. 1995, 117, 5179-5197

1. Jorgensen, W. L.; et al., The Opls Potential Functions For Proteins - Energy Minimizations For Crystals of Cyclic-Peptides and Crambin. J. Am. Chem. Soc. 1988, 110, 1657-1671

2. Bayly, C. I.; et al., A Well-Behaved Electrostatic Potential Based Method Using Charge Restraints For Deriving Atomic Charges - the RESP Model. J. Phys. Chem. 1993, 97, 10269-10280

2009.10.13 Mon
  • Explicit Solvent Models
  1. Water models (TIP3P, TIP4P, SPC)
  2. Condensed-phase calculations (DGhydration)

1. Brody, D.

2. Gettings, J.


1. Jorgensen, W. L.; et al., Comparison of Simple Potential Functions for Simulating Liquid Water. J. Chem. Phys. 1983, 79, 926-935

2. Jorgensen, W. L.; et al., Monte Carlo Simulation of Differences in Free Energies of Hydration. J. Chem. Phys. 1985, 83, 3050-3054

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2009.10.15 Wed
  • Continuum Solvent Models
  1. Generalized Born Surface Area (GBSA)
  2. Poisson-Boltzmann Surface Area (PBSA) vs GBSA

1. Lebarron, J.

2. Rizzo, R.

1. Still, W. C.; et al., Semianalytical Treatment of Solvation for Molecular Mechanics and Dynamics. J. Am. Chem. Soc 1990, 112, 6127-6129

2. Rizzo, R. C. ; Aynechi, T.; Case, D. A.; Kuntz, I. D. Estimation of Absolute Free Energies of Hydration Using Continuum Methods: Accuracy of Partial Charge Models and Optimization of Nonpolar Contributions. J. Chem. Theory Comput. 2006, 2, 128-139


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2009.10.20 Mon
Quiz Prior Section II


SECTION III: SAMPLING METHODS

  • Molecular Conformation
  1. Small molecules, peptides, relative energy, minimization methods

1. Lee, J.

1. Howard, A. E.; Kollman, P. A., An analysis of current methodologies for conformational searching of complex molecules. J. Med. Chem. 1988, 31, 1669-75

1. NIH Online Molecular Modeling Guide

1. Section 4 (PAGES 22-27) Colby College Molecular Mechanics Tutorial Introduction, 2004, Shattuck, T.W., Colby College

1. Holloway, M. K., A priori prediction of ligand affinity by energy minimization. Perspect. Drug Discov. Design 1998, 9-11, 63-84

2009.10.22 Wed
  • Primary Sampling Methods for Computer Simulations
  1. Molecular dynamics (MD)
  2. Monte Carlo (MC)

1. Liao, W.

2. Liverpool, R.

1. Karplus, M.; Petsko, G. A., Molecular dynamics simulations in biology. Nature 1990, 347, 631-9

2. Metropolis Monte Carlo Simulation Tutorial, LearningFromTheWeb.net, Accessed Oct 2008, Luke, B.

2. Jorgensen, W. L.; TiradoRives, J., Monte Carlo vs Molecular Dynamics for Conformational Sampling. J. Phys. Chem. 1996, 100, 14508-14513

2. Metropolis, N.; et al., Equation of State Calculations by Fast Computing Machines. The Journal of Chemical Physics 1953, 21, 1087-1092

2009.10.27 Mon
  • Predicting Protein Structure I.
  1. Ab initio prediction (protein-folding)
  2. Example Trp-cage

1. Lu, Y.

2. Mulundi, P.

1. Dill, K. A.; Chan, H. S., From Levinthal to pathways to funnels. Nat. Struct. Biol. 1997, 4, 10-19

2. Simmerling, C.; et al., All-atom structure prediction and folding simulations of a stable protein. J. Am. Chem. Soc. 2002, 124, 11258-9

1-2. Daggett, V.; Fersht, A., The present view of the mechanism of protein folding. Nat. Rev. Mol. Cell Biol. 2003, 4, 497-502

2009.10.29 Wed
  • Predicting Protein Structure II.
  1. Comparative (homology) modeling
  2. Case studies (CASP)

1. Mwai, A.

2. Ray, N.

1. Marti-Renom, M. A.; et al., Comparative protein structure modeling of genes and genomes. Annu. Rev. Biophys. Biomol. Struct. 2000, 29, 291-325

2. Moult, J., A decade of CASP: progress, bottlenecks and prognosis in protein structure prediction. Curr. Opin. Struct. Biol. 2005, 15, 285-9

1. Fiser, A.; et al., Evolution and physics in comparative protein structure modeling. Acc. Chem. Res. 2002, 35, 413-21

2. Kryshtafovych, A.; et al., Progress over the first decade of CASP experiments. Proteins 2005, 61 Suppl 7, 225-36

2009.11.03 Mon
  • Enhanced Sampling Techniques
  1. Simulated annealing
  2. Replica Exchange

1. Schaefer, K.

2. Seitz, J.

1. Brunger, A. T.; Adams, P. D., Molecular dynamics applied to X-ray structure refinement. Acc. Chem. Res. 2002, 35, 404-12

2. Sugita, Y.; Miyashita, N.; Yoda, T.; Ikeguchi, M.; Toyoshima, C., Structural Changes in the Cytoplasmic Domain of Phospholamban by Phosphorylation at Ser16: A Molecular Dynamics Study. Biochemistry 2006, 45, 11752-11761

1. Adams, P. D.; et al., Extending the limits of molecular replacement through combined simulated annealing and maximum-likelihood refinement. Acta Crystallogr D Biol Crystallogr 1999, 55, 181-90

2. Sugita, Y.; Okamoto, Y., Replica-exchange molecular dynamics method for protein folding. Chem. Phys. Lett. 1999, 314, 141-151

2. Lei, H.; Duan, Y., Improved sampling methods for molecular simulation. Curr Opin Struct Biol 2007, 17, 187-91

2009.11.05 Wed
Quiz Prior Section III


SECTION IV: LEAD DISCOVERY

  • Docking I.
  1. Introduction to DOCK

Guest Lecture

1. Mukherjee, S.

1. Ewing, T. J.; et al., DOCK 4.0: search strategies for automated molecular docking of flexible molecule databases. J. Comput. Aided Mol. Des. 2001, 15, 411-28

1. Moustakas, D. T.; et al., Development and Validation of a Modular, Extensible Docking program: DOCK 5. J. Comput. Aided Mol. Des. 2006, 20, 601-619

2009.11.10 Mon
  • Docking II.
  1. Test Sets (binding modes)
  2. Test Sets (virtual screening)

Guest Lecture

1. Mukherjee, S.

1. Nissink, J. W. M.; et al., A new test set for validating predictions of protein-ligand interaction. Prot. Struct. Funct. Genetics 2002, 49, 457-471

2. Irwin, J. J.; Shoichet, B. K., ZINC--a free database of commercially available compounds for virtual screening. J. Chem. Inf. Model. 2005, 45, 177-82

1. The CCDC/Astex Test Set

2. ZINC - A free database of commercially-available compounds for virtual screening

2009.11.12 Wed
  • Discovery Methods I.
  1. Hotspot probes (GRID)
  2. COMFA

1. Shang, Y.

2. Tan, L.

1. Goodford, P. J., A computational procedure for determining energetically favorable binding sites on biologically important macromolecules. J. Med. Chem. 1985, 28, 849-57

2. Kubinyi, H., Encyclopedia of Computational Chemistry, Databases and Expert Systems Section, John Wiley & Sons, Ltd. 1998

1. Cramer, R. D.; Patterson, D. E.; Bunce, J. D., Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins. J. Am. Chem. Soc., 1988, 110, 5959-5967

2009.11.17 Mon
  • Discovery Methods II.
  1. Pharmacaphores in drug design
  2. De nova design

1. Wang, H.

2. Wu, J.

1. Chang, C.; et al., Pharmacophore-based discovery of ligands for drug transporters. Advanced Drug Delivery Reviews 2006, 58, 1431-1450

2. Pegg, S. C.; Haresco, J. J.; Kuntz, I. D., A genetic algorithm for structure-based de novo design. J Comput Aided Mol Des 2001, 15, 911-33

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2009.11.19 Wed
  • Discovery Methods Applications
  1. Human Carbonic Anhydrase

1. Yang, M.

1. Gruneberg, S.; Stubbs, M. T.; Klebe, G., Successful virtual screening for novel inhibitors of human carbonic anhydrase: strategy and experimental confirmation. J. Med. Chem. 2002, 45, 3588-602

1. Cramer, R. D.; Patterson, D. E.; Bunce, J. D., Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins. J. Am. Chem. Soc., 1988, 110, 5959-5967

2009.11.24 Mon
Quiz Prior Section IV


SECTION V: LEAD REFINEMENT

  • Free Energy Perturbation (FEP)
  1. Thermolysin with 2 ligands

1. Goyal, R.

1. Bash, P. A.; Singh, U. C.; Brown, F. K.; Langridge, R.; Kollman, P. A., Calculation of the relative change in binding free energy of a protein-inhibitor complex. Science 1987, 235, 574-6

1. Jorgensen, W. L., Free Energy Calculations: A Breakthrough for Modeling Organic Chemistry in Solution. Accounts Chem. Res. 1989, 22, 184-189

1. Kollman, P., Free Energy Calculations: Applications to Chemical and Biochemical Phenomena. Chem. Rev. 1993, 93, 2395-2417

2009.11.26 Wed
  • MM-PBSA, MM-GBSA
  1. Intro to Molecular Mechanics Poisson-Boltzmann / Generalized Born Surface Area Methods
  2. MM-PBSA Validation Study

Guest Lecture

1. Huang, Y.

2. Balius, T.

1. Kollman, P. A.; Massova, I.; Reyes, C.; Kuhn, B.; Huo, S. H.; Chong, L.; Lee, M.; Lee, T.; Duan, Y.; Wang, W.; Donini, O.; Cieplak, P.; Srinivasan, J.; Case, D. A.; Cheatham, T. E., Calculating structures and free energies of complex molecules: Combining molecular mechanics and continuum models. Accounts Chem. Res. 2000, 33, 889-897

2. Kuhn, B.; Gerber, P.; Schulz-Gasch, T.; Stahl, M., Validation and use of the MM-PBSA approach for drug discovery. J. Med. Chem. 2005, 48, 4040-4048

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2009.12.01 Mon
  • MM-GBSA case studies
  1. HIVgp41
  2. influenza

1. Rizzo, R.

1. Strockbine, B.; Rizzo, R. C., Binding of Anti-fusion Peptides with HIVgp41 from Molecular Dynamics Simulations: Quantitative Correlation with Experiment. Prot. Struct. Funct. Bioinformatics 2007, 63, 630-642

2. Chachra, R.; Rizzo, R. C. Origins of Resistance Conferred by the R292K Neuraminidase Mutation via Molecular Dynamics and Free Energy Calculations. J. Chem. Theory Comput. 2008, 4, 1526-1540

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2009.12.03 Wed
  • Linear Response
  1. Intro to Linear Response (LR method)
  2. Inhibition of protein kinases (Extended LR method)

1. Rizzo, R.

1. Aqvist, J.; Mowbray, S. L., Sugar recognition by a glucose/galactose receptor. Evaluation of binding energetics from molecular dynamics simulations. J Biol Chem 1995, 270, 9978-81

2. Rizzo, R. C.; Tirado-Rives, J.; Jorgensen, W. L., Estimation of Binding Affinities for HEPT and Nevirapine Analogues with HIV-1 Reverse Transcriptase via Monte Carlo Simulations. J. Med. Chem. 2001, 44, 145-154

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2009.12.08 Mon
  • Properties of Known Drugs
  1. Estrogen Receptor
  2. Molecular Scaffolds (frameworks) and functionality (side-chains)

Guest Lecture

1. Yang, J.

2. McGillick, B.

1. Waszkowycz, B.; Perkins, T. D. J.; Sykes, R. A.; Li, J., Large-scale virtual screening for discovering leads in the postgenomic era. IBM Systems Journal 2001, 40, 360-376

2. Bemis, G. W.; Murcko, M. A., The properties of known drugs. 1. Molecular frameworks. J. Med. Chem. 1996, 39, 2887-93

2. Bemis, G. W.; Murcko, M. A., Properties of known drugs. 2. Side chains. J. Med. Chem. 1999, 42, 5095-9

2. Lipinski, C. A., Chris Lipinski discusses life and chemistry after the Rule of Five. Drug. Discov. Today 2003, 8, 12-6

2. Lipinski, C. A.; Lombardo, F.; Dominy, B. W.; Feeney, P. J., Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug. Deliv. Rev. 2001, 46, 3-26

2009.12.10 Wed
  • Industry Lecture
  1. Working in a Pharmaceutical Company

Guest Lecture

Dr. Elizabeth Buck

1. OSI Pharmaceuticals

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2009.12.15 Mon
  • No Class: University Correction Day
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2009.12.17 Wed
FINAL EXAM
WED
5:00 - 7:30 PM
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NOTE:

Unless otherwise noted the Final will be given in our regular class room.

FINAL EXAM IS CUMULATIVE

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