Difference between revisions of "2020 AMS-535 Fall"

Revision as of 10:29, 22 August 2020

Please see http://ringo.ams.sunysb.edu/~rizzo for Rizzo Group Homepage

Instructor	Dr. Robert C. Rizzo [631-632-8519, rizzorc -at- gmail.com] Dr. Guilherme Duarte Ramos Matos [631-632-8519, guilherme dot duarteramosmatos -at- stonybrook dot edu]
TA	John Bickel [631-632-8519, john dot bickel -at- stonybrook dot edu]
Course No.	AMS-535 / CHE-535
Location/Time	Online, Monday and Wednesday 2:40PM - 4:00PM
Office Hours	Anytime by appointment, Math Tower 3-129
Grading	Grades will be based on the quality of: (1) Pre-recorded oral presentations (25%) each student will pre-record 2 ZOOM presentations based on papers in the schedule below (2) Class discussion (30%) at scheduled class times, students will go into ZOOM breakout rooms (3) Take home quizzes (45%) 5 quizzes will be given and the lowest quiz grade will be dropped

Online Syllabus Notes

As a result of the COVID-19 outbreak this course is being offered online. This is a mixed course meaning that there will be both synchronous and asynchronous aspects. Details of this semester are as follows:

Course grading criteria has been modified from previous years (see grading breakdown above).
We will to hold class at the regularly scheduled time however this will all be done online via the Zoom program ( https://it.stonybrook.edu/services/zoom ).
The first 5 lectures will be given by the Instructors at the regularly scheduled class time and these 5 lectures will be recorded and put on the class website.
Students will pre-record 2 ZOOM presentations based on papers in the schedule shown below.
Students will email their pre-recorded presentations to the course Instructors by Friday at 5PM before the week in which their presentations will be discussed.
Course participants will watch the student presentations before the class in which they are to be discussed in the ZOOM breakout rooms.
Course participants will score each student presentation using the following scoring sheet and email their scores to the course Instructors prior to each class.
The Discussion part of the grade will be assessed.
Oral Presentations of Class Projects will be recorded by each participant individually (see Recording Your Oral Presentation Using Zoom section below), at home, and then emailed to the Instructors (see Video Presentation due date below).
Oral Presentations of Class Projects will be evaluated by 3 course participants and a Presentation Assessment Sheet for each talk evaluated will be submitted based on the Reviewer Assignments outlined below.
The Student Accessibility Support Center Statement (see below) has been updated
A Faculty Technical Support Statement (see below) has been added

Recording Your Oral Presentations Using Zoom: It is very straightforward to create a video of yourself giving a PPT presentation using Zoom:

Download the Zoom app ( https://it.stonybrook.edu/services/zoom )
Open the Zoom app
Create a new Zoom meeting with only yourself (make sure audio and video are turned on)
Share your screen
Open your presentation in PPT and put in presentation mode
Start recording and give a short test presentation to make sure that everything is working smoothly (use mouse as necessary to highlight specific regions of your slides)
Stop recording and quit the meeting
Open the newly created video (using QuickTime or some other video player) to make sure that your test presentation has both audio and video and looks good
Follow the above steps to create your "full-length" video presentation (videos should not exceed 20 minutes)
Email your video to the Instructors who will make it available to the class (please name your Zoom video Lastname.mp4)

Oral Presentation Guidelines: Recorded Talks should be presented in PPT format and be between 20 and 25 minutes long. The purpose of your talks is for you to clearly and concisely present the papers assigned to you in the schedule below. Talks should be arranged in the following order:

Introduction/Background (include biological relevance)
Specifics of Your System
Computational Details (theory)
Computational Details (system setup)
Results and Discussion (include a critical interpretation of your results)
Conclusions
Future
Acknowledgments

Video Presentations of Class Projects Must be Emailed to Guilherme by 2:30PM (please name files as "Lastname.mp4")
Project Analysis/Troubleshooting

Each course participant will watch and evaluate 3 Presentations (~ 20 minutes each) based on the Reviewer Assignment schedule below and submit a Presentation Assessment Sheet for each Video (due 1 week from today). Instructors will evaluate 3-4 presentations each.

Date	Topic	Speaker and Presentation	Primary Reference	Secondary Reference
2019.08.24 Mon	Organizational Meeting	-	-	-
2019.08.26 Wed	SECTION I: DRUG DISCOVERY AND BIOMOLECULAR STRUCTURE Drug Discovery 1. Introduction, history, irrational vs. rational 2. 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	-
2019.08.31 Mon	Chemistry Review 1. Molecular structure, bonding, graphical representations 2. Functionality, properties of organic molecules	Rizzo, R.	presentation	-
2019.09.02 Wed	Biomolecular Structure 1. Lipids, carbohydrates 2. Nucleic acids, proteins	Rizzo, R.	presentation	structures of the 20 amino acid side chains
2019.09.07 Mon	No Class: Labor Day	-	-	-
2019.09.09 Wed	Molecular Interactions and Recognition 1. Electrostatics, VDW interactions, hydrophobic effect, molecular recognition (binding energy) 2. Inhibitors types: allosteric, transition state, covalent vs non-covalent, selective, competitive	Rizzo, R.	presentation	-
2019.09.14 Mon	Intro. to Methods in 3-D Structure Determination 1. Crystallography, NMR 2. Structure Quality, PDB in detail	Rizzo, R.	presentation	-
-	-	-	Take home QUIZ for Section 1 starts after today's class (4:00PM) and must be emailed to all Instructors within 24 hours (4:00PM tomorrow)	-
2019.09.16 Wed	SECTION II: MOLECULAR MODELING Classical Force Fields 1. All-atom Molecular Mechanics 2. OPLS	1. last, first 2. last, first	1. Mackerell, A. D., Jr., Empirical force fields for biological macromolecules: overview and issues. J. Comput. Chem. 2004, 25, 1584-604 2. 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	1. van Gunsteren, W. F.; et al., Biomolecular modeling: Goals, problems, perspectives. Angew. Chem. Int. Ed. Engl. 2006, 45, 4064-92 2. 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
2019.09.21 Mon	Classical Force Fields 1. AMBER Explicit Solvent Models 2. Water models (TIP3P, TIP4P, SPC)	1. last, first 2. last, first	1. 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 2. Jorgensen, W. L.; et al., Comparison of Simple Potential Functions for Simulating Liquid Water. J. Chem. Phys. 1983, 79, 926-935	1. 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
2019.09.23 Wed	Explicit Solvent Models 1. Condensed-phase calculations (DGhydration) Continuum Solvent Models 2. Generalized Born Surface Area (GBSA)	1. last, first 2. last, first	1. Jorgensen, W. L.; et al., Monte Carlo Simulation of Differences in Free Energies of Hydration. J. Chem. Phys. 1985, 83, 3050-3054 2. Still, W. C.; et al., Semianalytical Treatment of Solvation for Molecular Mechanics and Dynamics. J. Am. Chem. Soc 1990, 112, 6127-6129	-
2019.09.28 Mon	Continuum Solvent Models 1. Poisson-Boltzmann Surface Area (PBSA) 2. Accuracy of partial atomic changes for GBSA and PBSA	1. last, first 2. last, first	1. Sitkoff, D.; et al., Accurate Calculation of Hydration Free Energies Using Macroscopic Solvent Models. J. Phys. Chem. 1994, 98, 1978-1988 2. Rizzo, R. C.; et al., 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	-
-	-	-	Take home QUIZ for Section 2 starts after today's class (4:00PM) and must be emailed to all Instructors within 24 hours (4:00PM tomorrow)	-
2019.09.30 Wed	SECTION III: SAMPLING METHODS Molecular Conformations 1. Small molecules, peptides, relative energy, minimization methods Sampling Methods for Large Simulations 2. Molecular dynamics (MD)	1. last, first 2. last, first	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 2. Karplus, M.; Petsko, G. A., Molecular dynamics simulations in biology. Nature 1990, 347, 631-9	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
2019.10.05 Mon	Sampling Methods for Large Simulations 1. Monte Carlo (MC) Predicting Protein Structure 2. Ab initio structure prediction (protein-folding)	1. last, first 2. last, first	1. Metropolis Monte Carlo Simulation Tutorial, LearningFromTheWeb.net, Accessed Oct 2008, Luke, B. 1. Jorgensen, W. L.; TiradoRives, J., Monte Carlo vs Molecular Dynamics for Conformational Sampling. J. Phys. Chem. 1996, 100,14508-14513 2. Dill, K. A.; Chan, H. S., From Levinthal to pathways to funnels. Nat. Struct. Biol. 1997, 4, 10-19	1. Metropolis, N.;et al., Equation of State Calculations by Fast Computing Machines. The Journal of Chemical Physics 1953, 21, 1087-1092
2019.10.07 Wed	Predicting Protein Structure 1. Example Trp-cage 2. Comparative (homology) modeling	1. last, first 2. last, first	1. Simmerling, C.;et al., All-atom structure prediction and folding simulations of a stable protein. J. Am. Chem. Soc. 2002, 124,11258-9 2. Marti-Renom, M. A.; et al., Comparative protein structure modeling of genes and genomes. Annu. Rev. Biophys. Biomol. Struct. 2000,29,291-325	1. Daggett, V.; Fersht, A., The present view of the mechanism of protein folding. Nat. Rev. Mol. Cell Biol. 2003, 4, 497-502 2. Fiser, A.; et al., Evolution and physics in comparative protein structure modeling. Acc. Chem. Res. 2002, 35, 413-21
2019.10.12 Mon	Predicting Protein Structure 1. Case studies (CASP) 2. Accelerated MD for Blind Protein Prediction	1. last, first 2. last, first	1. Moult, J., A decade of CASP: progress, bottlenecks and prognosis in protein structure prediction. Curr. Opin. Struct. Biol. 2005,15, 285-9 2. Perez, A.; et al., Blind protein structure prediction using accelerated free-energy simulations. Sci. Adv. 2016, 2	1. Kryshtafovych, A.; et al., Progress over the first decade of CASP experiments. Proteins 2005, 61 Suppl 7, 225-36
2019.10.14 Wed	Predicting Protein Structure 1. MD x-ray refinement 2. Protein Design	1. last, first 2. last, first	1. Brunger, A. T.;Adams, P. D., Molecular dynamics applied to X-ray structure refinement. Acc. Chem. Res. 2002, 35, 404-12 1. Kuhlman, A. T.;et al, Design of a Novel Globular Protein Fold with Atomic-Level Accuracy. Science 2003, 302, 1364-1368	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
-	-	-	Take home QUIZ for Section 3 starts after today's class (4:00PM) and must be emailed to all Instructors within 24 hours (4:00PM tomorrow)	-
2019.10.19 Mon	SECTION IV: LEAD DISCOVERY Docking 1. Introduction to DOCK 2. Test Sets (pose reproduction)	1. last, first 2. last, first	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. Mukherjee, S.; et al., Docking Validation Resources: Protein Family and Ligand Flexibility Experiments. J. Chem. Info. Model. 2010, 50, 1986-2000	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 2. The CCDC/Astex Test Set
2019.10.21 Wed	Docking 1. Test Sets (virtual screening) 2. Test Sets (database enrichment)	1. last, first 2. last, first	1. 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 2. Huang, N.; et al., Benchmarking Sets for Molecular Docking. J. Med. Chem. 2006, 49(23), 6789-6801	1. ZINC Website at UCSF, Shoichet group
2019.10.26 Mon	Docking 1. Footprint-based scoring Discovery Methods 2. Hotspot probes (GRID)	1. last, first 2. last, first	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. 1. Goodford, P. J., A computational procedure for determining energetically favorable binding sites on biologically important macromolecules. J. Med. Chem. 1985, 28, 849-57	-
2019.10.28 Wed	Discovery Methods 1. COMFA 2 Pharmacophores	1. last, first 2. last, first	1. Kubinyi, H., Comparative molecular field analysis (CoMFA). Encyclopedia of Computational Chemistry, Databases and Expert Systems Section, John Wiley & Sons, Ltd. 1998 2. Chang, C.; et al., Pharmacophore-based discovery of ligands for drug transporters. Advanced Drug Delivery Reviews 2006, 58, 1431-1450	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
2019.11.02 Mon	Discovery Methods. 1. Pharmacophores 2. De novo design	1. last, first 2. last, first	1. Alvarez, J.; et al., Pharmacophore-Based Molecular Docking to Account for Ligand Flexibility. Proteins 2003, 51, 172-188 2. Cheron, N.; et al., OpenGrowth: An Automated and Rational Algorithm for Finding New Protein Ligands. J. Med. Chem. 2016, 59, 4171-4188	-
2019.11.04 Wed	Discovery Methods 1. De novo design 2. Genetic Algorithm	1. last, first 2. last, first	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	-
-	-	-	Take home QUIZ for Section 4 starts after today's class (4:00PM) and must be emailed to all Instructors within 24 hours (4:00PM tomorrow)	-
2019.11.09 Mon	SECTION V: LEAD REFINEMENT Free Energy Methods 1. Thermolysin with two ligands (FEP) 2. Fatty acid synthase I ligands (TI)	1. last, first 2. last, first	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 2. 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	1&2. Jorgensen, W. L., Free Energy Calculations: A Breakthrough for Modeling Organic Chemistry in Solution. Accounts Chem. Res. 1989, 22, 184-189 1&2. Kollman, P., Free Energy Calculations: Applications to Chemical and Biochemical Phenomena. Chem. Rev. 1993, 93, 2395-2417 2. 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
2019.11.11 Wed	MM-PB/GBSA 1. Intro to Molecular Mechanics Poisson-Boltzmann / Generalized Born Surface Area Methods MM-GBSA case studies 2. EGFR and mutants	1. last, first 2. last, first	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. Balius, T.E.; Rizzo, R. C. Quantitative Prediction of Fold Resistance for Inhibitors of EGFR. Biochemistry, 2009, 48, 8435-8448
2019.11.16 Mon	MM-GBSA case studies 1. ErbB family selectivity Linear Response 2. Intro to Linear Response (LR method)	1. last, first 2. last, first	1. Huang, Y.; Rizzo, R. C. A Water-based Mechanism of Specificity and Resistance for Lapatinib with ErbB Family Kinases, Biochemistry, 2012, 51, 2390-2406 2. 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	-
2019.11.18 Wed	Linear Response 1. Inhibition of protein kinases (Extended LR method) Properties of Known Drugs 2. Molecular Scaffolds (frameworks) and functionality (side-chains	1. last, first 2. last, first	1. 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 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	-
2019.11.23 Mon	No Class: Thanksgiving	-	-	-
2019.11.23 Wed	No Class: Thanksgiving	-	-	-
2019.11.30 Mon	Properties of Known Drugs 1. Lipinski Rule of Five 2 ADME Prediction	1. last, first 2. last, first	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
2019.12.02 Wed	TBD	-	-	-
2019.12.07 Mon	TBD	-	-	-
-	-	-	Take home QUIZ for Section 5 starts after today's class (4:00PM) and must be emailed to all Instructors within 24 hours (4:00PM tomorrow)	-
-	Final Exam	-	No Final Exam in AMS-535/CHE-535 for Fall 2020	-

@@ Line 31: / Line 31: @@
 == '''Online Syllabus Notes''' ==
-As a result of the COVID-19 outbreak this course is being offered online. It is a mixed course in that it there will be both synchronous and asynchronous aspects. The details are:
+As a result of the COVID-19 outbreak this course is being offered online. This is a mixed course meaning that there will be both synchronous and asynchronous aspects.  Details of this semester are as follows:
-*The course grading criteria has been modified (see grading breakdown above).
+*Course grading criteria has been modified from previous years (see grading breakdown above).
-*The schedule has been revised starting March 23 2020.
+*We will to hold class at the regularly scheduled time however this will all be done online via the Zoom program ( https://it.stonybrook.edu/services/zoom ).
-*We will continue to hold class at the regularly scheduled time however this will now be done online via the Zoom program ( https://it.stonybrook.edu/services/zoom ).
+*The first 5 lectures will be given by the Instructors at the regularly scheduled class time and these 5 lectures will be recorded and put on the class website.
-*AMBER tutorials are being prerecorded by the Instructors and will be uploaded as appropriate into the course schedule as online videos.
+*Students will pre-record 2 ZOOM presentations based on papers in the schedule shown below.
-*AMBER tutorials should be viewed online before each relevant Zoom meetings so that meeting time can be spent troubleshooting and providing other guidance as necessary for class tutorials.
+*Students will email their pre-recorded presentations to the course Instructors by Friday at 5PM before the week in which their presentations will be discussed.
-*Class time normally devoted to watching and evaluating Oral Presentations will instead be used for Zoom meetings devoted to troubleshooting and providing other guidance as necessary for Class Projects.
+*Course participants will watch the student presentations before the class in which they are to be discussed in the ZOOM breakout rooms.
+*Course participants will score each student presentation using the following scoring sheet and email their scores to the course Instructors prior to each class.
+*The Discussion part of the grade will be assessed.
 *Oral Presentations of Class Projects will be recorded by each participant individually (see Recording Your Oral Presentation Using Zoom section below), at home, and then emailed to the Instructors (see Video Presentation due date below).
 *Oral Presentations of Class Projects will be evaluated by 3 course participants and a [http://ringo.ams.sunysb.edu/~rizzo/StonyBrook/teaching/AMS532_AMS535_AMS536/Presentations/2020_ams.536.presentation.assessment.docx Presentation Assessment Sheet] for each talk evaluated will be submitted based on the Reviewer Assignments outlined below.
@@ Line 59: / Line 61: @@
-'''Oral Presentation Guidelines:''' These meetings should be formal and your chance to tell a complete story. Talks should be presented in PPT format and be between 20 and 30 minutes long. The purpose of your talks is for you to clearly and concisely present your overall progress to date including appropriate background material and interpretation of your results. Check our guidelines on [http://ringo.ams.sunysb.edu/~rizzo/StonyBrook/teaching/AMS532_AMS535_AMS536/Projects/how_not_to_make_a_presentation.pdf how not to make a presentation]. Talks should be arranged in the following order:
+'''Oral Presentation Guidelines:''' Recorded Talks should be presented in PPT format and be between 20 and 25 minutes long. The purpose of your talks is for you to clearly and concisely present the papers assigned to you in the schedule below. Talks should be arranged in the following order:
 *Introduction/Background (include biological relevance)
 *Specifics of Your System
@@ Line 68: / Line 71: @@
 *Future
 *Acknowledgments
+'''Video Presentations of Class Projects Must be Emailed to Guilherme by 2:30PM (please name files as "Lastname.mp4")'''<br> Project Analysis/Troubleshooting <br> <br> Each course participant will watch and evaluate 3 Presentations (~ 20 minutes each) based on the Reviewer Assignment schedule below and submit a [http://ringo.ams.sunysb.edu/~rizzo/StonyBrook/teaching/AMS532_AMS535_AMS536/Presentations/2020_ams.536.presentation.assessment.docx Presentation Assessment Sheet] for each Video (due 1 week from today).  Instructors will evaluate 3-4 presentations each.

Difference between revisions of "2020 AMS-535 Fall"

Revision as of 10:29, 22 August 2020

Please see http://ringo.ams.sunysb.edu/~rizzo for Rizzo Group Homepage

Online Syllabus Notes

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