Date
|
Topic
|
Speaker and Presentation
|
Primary Reference
|
Secondary Reference
|
2011.08.29 Mon
|
- No class: Hurricane Irene
|
-
|
-
|
-
|
2011.08.31 Wed
|
|
-
|
-
|
-
|
2011.09.05 Mon
|
|
-
|
-
|
-
|
2011.09.07 Wed
|
SECTION I: DRUG DISCOVERY AND BIOMOLECULAR STRUCTURE
- Introduction, history, irrational vs. rational
- Viral Target Examples
|
Rizzo, R.
|
1. Jorgensen, W.L., The many roles of computation in drug discovery. Science 2004, 303, 1813-8
2. Kuntz, I. D., Structure-based strategies for drug design and discovery. Science 1992, 257, 1078-1082
|
-
|
2011.09.12 Mon
|
- Molecular structure, bonding, graphical representations
- Functionality, properties of organic molecules
|
Rizzo, R.
|
presentation
|
-
|
2011.09.14 Wed
|
- Lipids, carbohydrates
- Nucleic acids, proteins
|
Rizzo, R.
|
presentation
|
structures of the 20 amino acid side chains
|
2011.09.19 Mon
|
- Molecular Interactions and Recognition
- Electrostastics, VDW interactions, hydrophobic effect, molecular recognition (binding energy)
- Inhibitors types: allosteric, transition state, covalent vs non-covalent, selective, competitive
|
Rizzo, R.
|
presentation
|
-
|
2011.09.21 Wed
|
- Intro. to Methods in 3-D Structure Determination
- Crystallography, NMR
- Structure Quality, PDB in detail
|
Rizzo, R.
|
presentation
|
-
|
2011.09.26 Mon
|
Quiz Prior Section I
SECTION II: MOLECULAR MODELING
- All-atom Molecular Mechanics
|
Guest Lecture
Balius, T.
|
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
|
2011.09.28 Wed
|
- No Class: Follow a Friday Schedule
|
-
|
-
|
-
|
2011.10.03 Mon
|
- OPLS
- AMBER
|
1. Gan, Q.
2. Boyd, R.
|
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
|
2011.10.05 Wed
|
- Water models (TIP3P, TIP4P, SPC)
- Condensed-phase calculations (DGhydration)
|
1. Adewale, B.
2. Choi,W.
|
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
|
-
|
2011.10.10 Mon
|
- Generalized Born Surface Area (GBSA)
- Poisson-Boltzmann Surface Area (PBSA)
|
1. Hwang, G.
2. Groeneveld, K.
|
1. Still, W. C.; et al., Semianalytical Treatment of Solvation for Molecular Mechanics and Dynamics. J. Am. Chem. Soc 1990, 112, 6127-6129
2. Sitkoff, D.; et al., Accurate Calculation of Hydration Free Energies Using Macroscopic Solvent Models. J. Phys. Chem. 1994, 98, 1978-1988
|
-
|
2011.10.12 Wed
|
Quiz Prior Section II
SECTION III: SAMPLING METHODS
- Small molecules, peptides, relative energy, minimization methods
|
1. Kazi, R.
|
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. 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
|
2011.10.17 Mon
|
- Primary Sampling Methods for Computer Simulations
- Molecular dynamics (MD)
- Monte Carlo (MC)
|
1. Chen,J.
2. Kim, E
|
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
|
2011.10.19 Wed
|
- Predicting Protein Structure I.
- Ab initio prediction (protein-folding)
- Example Trp-cage
|
1. Klaritch-Vrana, B.
2. Lazo, E.
|
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
|
2011.10.24 Mon
|
- Predicting Protein Structure II.
- Comparative (homology) modeling
- Case studies (CASP)
|
1.Guest Lecture
Huang,Y.
2. Santa Cruz, A.
|
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
|
2011.10.26 Wed
|
- Enhanced Sampling Techniques
- Simulated annealing
- Protein Design
|
1.Guja, K.
2.Guest Lecture
Au, L.
|
1. Brunger, A. T.;Adams, P. D., Molecular dynamics applied to X-ray structure refinement. Acc. Chem. Res. 2002, 35, 404-12
2. Street, A. G.; Mayo, S. L., Computational protein design. Structure. 1999, 7, 105-9
|
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. Lippow, S. M.; Tidor, B., Progress in computational protein design. Curr. Opin. Biotechnol. 2007, 18, 305-311
|
2011.10.31 Mon
|
Quiz Prior Section III
SECTION IV: LEAD DISCOVERY
- Introduction to DOCK
- Introduction to Virtual Screening
|
Guest Lecture
Mukherjee, S.
|
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
2. Klebe, G.; et al., Virtual ligand screening: strategies, perspectives and limitations. Drug. Disc. Today. 2006, 11, 580-595
|
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
|
2011.11.02 Wed
|
- Hotspot probes (GRID)
- COMFA
|
1.Wei, L.
2. Shi, H.
|
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
|
2011.11.07 Mon
|
- Pharmacophores in drug design #1
- Pharmacophores in drug design #2
|
Guest Lecture Jiang, L.
|
1. Chang, C.; et al., Pharmacophore-based discovery of ligands for drug transporters. Advanced Drug Delivery Reviews 2006, 58, 1431-1450
2. Alvarez, J.; et al., Pharmacophore-Based Molecular Docking to Account for Ligand Flexibility. Proteins 2003, 51, 172-188
|
-
|
2011.11.09 Wed
|
- De novo design #1
- De novo design #2
|
Guest Lecture Allen, W.
|
1. Jorgensen, W.; et al., Efficient drug lead discovery and optimization. Acc. of Chem. Research 2009, 42 (6), 724-733
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
|
-
|
2011.11.14 Mon
|
- Test Sets (binding modes)
- Test Sets (virtual screening)
|
Guest Lecture
Mukherjee, S.
|
1. Mukherjee, S.; et al., Docking Validation Resources: Protein Family and Ligand Flexibility Experiments. J. Chem. Info. Model. 2010, 50, 1986-2000
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 Website at UCSF, Shoichet group
|
2011.11.16 Wed
|
- Database Enrichment
- Footprint-based scoring
|
1. Guest Lecture Balius, T.
|
1. Huang, N.; et al., Benchmarking Sets for Molecular Docking. J. Med. Chem. 2006, 49(23), 6789-6801
1. Balius, T.E.; et al., Implementation and Evaluation of a Docking-Rescoring Method Using Molecular Footprint Comparisons. J. Comput. Chem. 2011, 32, 2273-2289.
|
-
|
2011.11.21 Mon
|
Quiz Prior Section IV
SECTION V: LEAD REFINEMENT
- Free Energy Perturbation (FEP)
- Thermolysin with two ligands
|
1. Sin, J.
|
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
|
2011.11.23 Wed
|
- No Class: Thanksgiving US
|
-
|
-
|
-
|
2011.11.28 Mon
|
- Thermodynamic integration
- MM-PB/GBSA
- H5N1 Avian influenza N1-PVR
- Intro to Molecular Mechanics Poisson-Boltzmann / Generalized Born Surface Area Methods
|
1. Guest Lecture Jiang, L.,
2. Guest Lecture Huang,Y.
|
1. Lawrenz, M.; et al., Independent-Trajectories Thermodynamic-Integration Free-Energy Changes for Biomolecular Systems: Determinants of H5N1 Avian Influenza Virus Neuraminidase Inhibition by Peramivir. J. Chem. Theory Comput. 2009, 5, 1106-1116
2. 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
|
-
|
2011.11.30 Wed
|
- TI and MM-GBSA
- HIVgp41
|
1. Sinayev, R.
2. Wong, A.
|
1. Cai, Y.; Schiffer, C. A.; Decomposing the Energetic Impact of Drug Resistant Mutations in HIV-1 Protease on Binding DRV. J. Chem. Theory Comput. 2010, 6, 1358-1368
2. 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
|
-
|
2011.12.05 Mon
|
- Intro to Linear Response (LR method)
- Inhibition of protein kinases (Extended LR method)
|
1. Xia, Y.
2. Yeasmin, 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. Tominaga, Y.; Jorgensen, W. L.; General model for estimation of the inhibition of protein kinases using Monte Carlo simulations. J. Med. Chem. 2004, 47, 2534-2549
|
-
|
2011.12.07 Wed
|
- Properties of Known Drugs
- Lipinski Rule of Five
- ADME prediction
|
1. Yuan, X.
2. Zhou, Y.
|
1. 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
2. Hou, T. J.; Xu, X. J.; ADME evaluation in drug discovery. J. Mol. Model, 2002, 8, 337-349
|
1. Lipinski, C. A., Chris Lipinski discusses life and chemistry after the Rule of Five. Drug. Discov. Today 2003, 8, 12-6
2. Hou, T. J.; Xu, X. J.; AMDE Evaluation in drug discovery 3. Modeling blood-brain barrier partitioning using simple molecular descriptors. J. Chem. Inf. Comput. Sci., 2003, 43, 2137-2152
|
2011.12.12 Mon
|
- Follow a Wednesday schedule
- Final Exam discussion.
- Final Exam Study Guide Handout
|
1. Jiang, L.
|
1. final_exam_study_guide
|
last day of class
|
2011.12.19 Mon
|
FINAL EXAM
MON
5:15-7:45 PM
|
-
|
NOTE:
Unless otherwise noted the Final will be given in our regular class room.
FINAL EXAM IS CUMULATIVE
|
-
|