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| '''Current Announcements''' | | '''Current Announcements''' |
| *Posted on 09/26/2013 by Jeewoen | | *Posted on 09/26/2013 by Jeewoen |
− | Future quizzes are going to be based on primary papers and class(presentation). | + | Future quizzes are going to be based on primary papers and classes(presentations). |
| You are not expected to know every detail in papers but you have to understand at least main ideas, methods and results. | | You are not expected to know every detail in papers but you have to understand at least main ideas, methods and results. |
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Future quizzes are going to be based on primary papers and classes(presentations).
You are not expected to know every detail in papers but you have to understand at least main ideas, methods and results.
Date
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Topic
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Speaker and Presentation
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Primary Reference
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Secondary Reference
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2013.08.26 Mon
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2013.08.28 Wed
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SECTION I: DRUG DISCOVERY AND BIOMOLECULAR STRUCTURE
- Introduction, history, irrational vs. rational
- Viral Target Examples
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Rizzo, R.
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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
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2013.09.02 Mon
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2013.09.04 Wed
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- Molecular structure, bonding, graphical representations
- Functionality, properties of organic molecules
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Rizzo, R.
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presentation
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2013.09.09 Mon
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- Lipids, carbohydrates
- Nucleic acids, proteins
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Rizzo, R.
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presentation
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structures of the 20 amino acid side chains
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2013.09.11 Wed
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- Molecular Interactions and Recognition
- Electrostastics, VDW interactions, hydrophobic effect, molecular recognition (binding energy)
- Inhibitors types: allosteric, transition state, covalent vs non-covalent, selective, competitive
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Rizzo, R.
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presentation
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2013.09.16 Mon
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- Intro. to Methods in 3-D Structure Determination
- Crystallography, NMR
- Structure Quality, PDB in detail
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Rizzo, R.
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presentation
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2013.09.18 Wed
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Quiz Prior Section I
SECTION II: MOLECULAR MODELING
- All-atom Molecular Mechanics
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1. Kennedy, C.
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1. Mackerell, A. D., Jr., Empirical force fields for biological macromolecules: overview and issues. J. Comput. Chem. 2004, 25, 1584-604
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1. van Gunsteren, W. F.; et al., Biomolecular modeling: Goals, problems, perspectives. Angew. Chem. Int. Ed. Engl. 2006, 45, 4064-92
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2013.09.23 Mon
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- OPLS
- AMBER
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1. Heymann, J.
2. Lebedev, I.
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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
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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
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2013.09.25 Wed
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- Water models (TIP3P, TIP4P, SPC)
- Condensed-phase calculations (DGhydration)
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1. Li, F.
2. Pulkoski, M.
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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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2013.09.30 Mon
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- Generalized Born Surface Area (GBSA)
- Poisson-Boltzmann Surface Area (PBSA)
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1. Sopp, J.
2. Yu, B.
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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
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2013.10.02 Wed
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Quiz Prior Section II
SECTION III: SAMPLING METHODS
- Small molecules, peptides, relative energy, minimization methods
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1. Bai, L.
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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
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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
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2013.10.07 Mon
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- Primary Sampling Methods for Computer Simulations
- Molecular dynamics (MD)
- Monte Carlo (MC)
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1. Chu, W.
2. Hussein, K.
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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
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2. Metropolis, N.;et al., Equation of State Calculations by Fast Computing Machines. The Journal of Chemical Physics 1953, 21, 1087-1092
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2013.10.09 Wed
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- Predicting Protein Structure I.
- Ab initio prediction (protein-folding)
- Example Trp-cage
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1. Lichtenthal, B.
2. Liu, K.
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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
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1-2. Daggett, V.; Fersht, A., The present view of the mechanism of protein folding. Nat. Rev. Mol. Cell Biol. 2003, 4, 497-502
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2013.10.14 Mon
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- Enhanced Sampling Techniques
- Simulated annealing
- Protein Design
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1. & 2. Guest Lecture
Au, L.
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1. Brunger, A. T.;Adams, P. D., Molecular dynamics applied to X-ray structure refinement. Acc. Chem. Res. 2002, 35, 404-12
2. Looger, L. L.; Hellinga, H. W., Generalized dead-end elimination algorithms make large-scale protein side-chain structure prediction tractable: implications for protein design and structural genomics. J Mol Biol. 2001, 307, 429-45
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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. Desmet, J.; et al., The dead-end elimination theorem and its use in protein side-chain positioning. Nature. 1992, 356, 539-42
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2013.10.16 Wed
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- Predicting Protein Structure II.
- Comparative (homology) modeling
- Case studies (CASP)
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1. Pal, J.
2. Russo, A.
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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
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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
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2013.10.21 Mon
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Quiz Prior Section III
SECTION IV: LEAD DISCOVERY
- Introduction to DOCK
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1. Sun, Y.
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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
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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
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2013.10.23 Wed
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- Test Sets (binding modes)
- Test Sets (virtual screening)
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1. & 2. Guest Lecture
Fochtman, B.
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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
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1. The CCDC/Astex Test Set
2. ZINC Website at UCSF, Shoichet group
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2013.10.28 Mon
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- Database Enrichment
- Footprint-based scoring
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1. & 2. Guest Lecture
Guo, J.
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1. Huang, N.; et al., Benchmarking Sets for Molecular Docking. J. Med. Chem. 2006, 49(23), 6789-6801
2. Balius, T.E.; et al., Implementation and Evaluation of a Docking-Rescoring Method Using Molecular Footprint Comparisons. J. Comput. Chem. 2011, 32, 2273-2289.
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2013.10.30 Wed
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- Hotspot probes (GRID)
- COMFA
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1. Wang, S.
2. Xue, M.
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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
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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
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2013.11.04 Mon
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- Pharmacophores in drug design #1
- Pharmacophores in drug design #2
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1. & 2. Guest Lecture
Jiang, L.
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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
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2013.11.06 Wed
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- De novo design #1
- De novo design #2
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1. & 2. Guest Lecture
Allen, W.
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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
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2013.11.11 Mon
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Quiz Prior Section IV
SECTION V: LEAD REFINEMENT
- Free Energy Perturbation (FEP)
- Thermolysin with two ligands
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1. Zhao, P.
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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
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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
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2013.11.13 Wed
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- Thermodynamic integration
- MM-PB/GBSA
- Free energy calculation using TI
- Intro to Molecular Mechanics Poisson-Boltzmann / Generalized Born Surface Area Methods
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1. Zong, Y.,
2. Zou, J.
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1. Labahn, A.; et al., Free energy calculations on the binding of novel thiolactomycin derivatives to E. coli fatty acid synthase I. Bioorg Med Chem. 2012, 20, 3446-53
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
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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
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2013.11.18 Mon
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- TI and MM-GBSA
- HIVgp41
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1. & 2. Guest Lecture
Rizzo, R.
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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
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2013.11.20 Wed
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- Intro to Linear Response (LR method)
- Inhibition of protein kinases (Extended LR method)
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1. & 2. Guest Lecture
Zhou, Y.
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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
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2013.11.25 Mon
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- Properties of Known Drugs
- Lipinski Rule of Five
- ADME prediction
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1. XXX, X.
2. XXX, X.
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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
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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
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2013.11.27 Wed
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2013.12.02 Mon
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2013.12.04 Wed
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- Final Exam Study Guide Handout
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1. Shin, J.
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1. final_exam_study_guide
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last day of class
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2013.12.10 Tue
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FINAL EXAM
Tuesday
8:30-11:00PM
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NOTE:
Unless otherwise noted the Final will be given in our regular class room.
It is the student’s responsibility to plan a class schedule that avoids exam conflicts and too many exams in the same day.
FINAL EXAM IS CUMULATIVE
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