Difference between revisions of "2024 AMS-535 Fall"
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*''First Day Class'' | *''First Day Class'' | ||
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*''Drug Discovery'' | *''Drug Discovery'' | ||
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*''Chemistry Review'' | *''Chemistry Review'' | ||
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*''Biomolecular Structure'' | *''Biomolecular Structure'' | ||
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*''Molecular Interactions and Recognition'' | *''Molecular Interactions and Recognition'' | ||
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*''Intro. to Methods in 3-D Structure Determination'' | *''Intro. to Methods in 3-D Structure Determination'' | ||
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* ''Classical Force Fields'' | * ''Classical Force Fields'' | ||
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* ''Classical Force Fields'' | * ''Classical Force Fields'' | ||
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*''Explicit Solvent Models'' | *''Explicit Solvent Models'' | ||
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*''Continuum Solvent Models'' | *''Continuum Solvent Models'' | ||
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*''Molecular Conformations'' | *''Molecular Conformations'' | ||
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:1. [https://ringo.ams.stonybrook.edu/~rizzo/StonyBrook/teaching/AMS532_AMS535_AMS536/References/Holloway001.pdf Holloway, M. K., A priori prediction of ligand affinity by energy minimization. ''Perspect. Drug Discov. Design'' '''1998''', ''9-11'', 63-84] | :1. [https://ringo.ams.stonybrook.edu/~rizzo/StonyBrook/teaching/AMS532_AMS535_AMS536/References/Holloway001.pdf 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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*''Sampling Methods for Large Simulations'' | *''Sampling Methods for Large Simulations'' | ||
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*''Predicting Protein Structure'' | *''Predicting Protein Structure'' | ||
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+ | ||<center>'''NO CLASS - FALL BREAK'''</center> | ||
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*''Predicting Protein Structure'' | *''Predicting Protein Structure'' | ||
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*''Predicting Protein Structure'' | *''Predicting Protein Structure'' | ||
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'''SECTION IV: LEAD DISCOVERY''' | '''SECTION IV: LEAD DISCOVERY''' | ||
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*''Docking'' | *''Docking'' | ||
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*''Docking'' | *''Docking'' | ||
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*''Discovery Methods'' | *''Discovery Methods'' | ||
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*''Discovery Methods.'' | *''Discovery Methods.'' | ||
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*''Discovery Methods'' | *''Discovery Methods'' | ||
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*''Free Energy Methods'' | *''Free Energy Methods'' | ||
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*''Thermodynamic Integration'' | *''Thermodynamic Integration'' | ||
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*''MM-GBSA case studies" | *''MM-GBSA case studies" | ||
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*''Linear Response'' | *''Linear Response'' | ||
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*''Properties of Known Drugs'' | *''Properties of Known Drugs'' | ||
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*''Properties of Known Drugs'' | *''Properties of Known Drugs'' | ||
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*''Last Day Class'' | *''Last Day Class'' |
Revision as of 10:25, 8 August 2024
Please see https://ringo.ams.stonybrook.edu/~rizzo for Rizzo Group Homepage
Instructors | Dr. Robert C. Rizzo [631-632-8519, rizzorc -at- gmail.com]
Brock Boysan [631-632-8519, brock dot boysan -at- stonybrook dot edu] |
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Course No. | AMS-535 / CHE-535 |
Location/Time | FREY HALL 326 WESTCAMPUS, MoWe 2:00PM - 3:20PM |
Office Hours | Anytime by appointment, Math Tower 3-129 |
Grading | Grades will be based on the quality of: (1) Oral presentations (25%)
(2) Class discussion (25%)
(3) Quizzes (50%)
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GENERAL INFORMATION: AMS-535 provides an introduction to the field of computational structure-based drug design. The course aims to foster collaborative learning and will consist of presentations by instructors, course participants, and guest lecturers arranged in five major sections outlined below. Presentations should aim to summarize key papers, theory, and application of computational methods relevant to computational drug design. Grade will be based on oral presentations, class discussion/attendance/participation, and quizzes.
Learning Objectives
- (1) Become informed about the field of computational structure-based drug design and the pros and cons of its methods.
- (2) Dissect seminal theory and application papers relevant to computational drug design.
- (3) Gain practice in giving an in-depth oral powerpoint presentation on computational drug design.
- (4) Read, participate in discussion, and be tested across five key subject areas:
- (i) Drug Discovery and Biomolecular Structure:
Drug Discovery, Chemistry Review, Proteins, Carbohydrates, Nucleic acids
Molecular Interactions and Recognition, Experimental Techniques for Elucidating Structure - (ii) Molecular Modeling:
Classical Force Fields (Molecular Mechanics),
Solvent Models, Condensed-phase Calculations, Parameter Development - (iii) Sampling Methods:
Conformational Space, Molecular Dynamics (MD), Metropolis Monte Carlo (MC)
Sampling Techniques, Predicting Protein Structure, Protein Folding - (iv) Lead Discovery:
Docking as a Lead Generation Tool, Docking Algorithms
Discovery Methods I, Discovery Methods II, Applications - (v) Lead Refinement:
Free Energy Perturbation (FEP), Linear Response (LR), Extended Linear Response (ELR)
MM-PBSA, MM-GBSA, Properties of Known Drugs, Property Prediction
- (i) Drug Discovery and Biomolecular Structure:
LITERATURE DISCLAIMER: Hyperlinks and manuscripts accessed through Stony Brook University's electronic journal subscriptions are provided below for educational purposes only.
PRESENTATION DISCLAIMER: Presentations may contain slides from a variety of online sources for educational and illustrative purposes only, and use here does not imply that the presenter is claiming that the contents are their own original work or research.
Syllabus Notes
General Information:
- This is an in-person course. There is no online section.
- Note that course grading criteria has been modified from previous years (see grading breakdown above).
- The first 5 lectures are to help put everyone on an even footing with regards to background material and will be given by the Instructors at the regularly scheduled class time.
- All class correspondence should be addressed to ALL course Instructors.
Oral Presentations:
- Each participant will give 1-2 oral presentations (depending on the class size).
- In-person presentations should be formal (as if at a scientific meeting or job talk), presented in PPT format, and be 20-25 minutes long.
- All presentations will be recorded and posted on the course website.
- References should occur at the bottom of each slide when necessary.
- Presentations should be based mostly on the primary references however secondary references and other sources may be required to make some presentations complete.
- It is the responsibility of each presenter to email a PPT file of their talk by Friday at 5PM before the week in which their talk is being discussed.
- In general, talks will likely be arranged in the following order: (1) Introduction/Background (include biological relevance if applicable), (2) Specifics of the System or General Problem, (3) Computational Methods (theory) and Details (system setup) being used, (4) Results and Discussion (critical interpretation of results and any problems/challenges), (5) Conclusions/Future, and (6) Acknowledgments.
Class Discussion:
- A sizable portion of the course grade is based on participating in Class Discussion. Thus, it is important that everyone attend all of the classes and participate in scientific discussion to receive full credit.
- If a student is unable to attend a specific class for reasons beyond their control they will instead be asked to email the instructor(s) AND submit a one page Paper Summary Sheet answering questions about the papers that were discussed on the day that they missed. The "Paper Summary Sheets" will form the basis of the "Class Discussion" part of their grade for any classes that were missed.
- If a student misses a class they will have 24 hours to submit their Paper Summary Sheets. Late Paper Summary Sheets will not be accepted.
Quizzes:
- Five quizzes will be used to assess student understanding of the course material.
- The quiz format is in-class, closed book.
- Answers to quiz questions should integrate topics, concepts, and outcomes of the different papers covered for the section being tested.
- Students are expected to work alone and do their own work. Representing another person's work as your own is always wrong. The Instructors are required to report any and all suspected instances of academic dishonesty to the students Graduate Program Director.
Class Schedule
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Required Syllabi Statements:
The University Senate Undergraduate and Graduate Councils have authorized that the following required statements appear in all teaching syllabi (graduate and undergraduate courses) on the Stony Brook Campus.. This information is also located on the Provost’s website: https://www.stonybrook.edu/commcms/provost/faculty/handbook/academic_policies/syllabus_statement.php
Student Accessibility Support Center Statement: If you have a physical, psychological, medical, or learning disability that may impact your course work, please contact the Student Accessibility Support Center, 128 ECC Building, (631) 632-6748, or at sasc@stonybrook.edu. They will determine with you what accommodations are necessary and appropriate. All information and documentation is confidential. Students who require assistance during emergency evacuation are encouraged to discuss their needs with their professors and the Student Accessibility Support Center. For procedures and information go to the following website: https://ehs.stonybrook.edu/programs/fire-safety/emergency-evacuation/evacuation-guide-people-physical-disabilities and search Fire Safety and Evacuation and Disabilities.
Academic Integrity Statement: Each student must pursue his or her academic goals honestly and be personally accountable for all submitted work. Representing another person's work as your own is always wrong. Faculty is required to report any suspected instances of academic dishonesty to the Academic Judiciary. Faculty in the Health Sciences Center (School of Health Technology & Management, Nursing, Social Welfare, Dental Medicine) and School of Medicine are required to follow their school-specific procedures. For more comprehensive information on academic integrity, including categories of academic dishonesty please refer to the academic judiciary website at http://www.stonybrook.edu/commcms/academic_integrity/index.html
Critical Incident Management: Stony Brook University expects students to respect the rights, privileges, and property of other people. Faculty are required to report to the Office of Student Conduct and Community Standards any disruptive behavior that interrupts their ability to teach, compromises the safety of the learning environment, or inhibits students' ability to learn. Until/unless the latest COVID guidance is explicitly amended by SBU, during Fall 2021"disruptive behavior” will include refusal to wear a mask during classes. For the latest COVID guidance, please refer to: https://www.stonybrook.edu/commcms/strongertogether/latest.php