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Credit:
1 course unit
Elective course
Catalog Description:
This course aims to provide theoretical, conceptual, and hands-on modeling experience on three different length and time scales that are crucial to biochemical phenomena in cells and to nanotechnology applications. Special Emphasis will be on cellular signal transduction. 60% lectures, 40% computational laboratory. No programming skills required.
Prerequisites:
None*
*Undergraduates who have taken BE324 or equivalent courses in Quantum Mechanics and/or Statistical Physics need no permission. Others, email instructor rradhak@seas.upenn.edu for permission.
Textbook(s) and/or
other Required Material:
Course notes, online
manuals, journal articles, review articles
Reference Textbooks:
Molecular Modeling and Simulation:An Interdisciplinary
Guide, T. Schlick, 2002
Course Objectives:
To provide
theoretical, conceptual, and hands-on modeling experience on three
different length and time scales -- (1) electronic structure (Å,ps), (2)
molecular mechanics (100Å,ns), and (3) deterministic & stochastic
approaches for microscale systems (µm,sec). Students will gain hands-on
experience, i.e., running codes (Gaussian, Gamess, CPMD, CHARMM, MC,
Kinetikit, STOCKS) on real applications together with the following
theoretical formalisms: Hartree-Fock, density functional theory,
semi-empirical methods, molecular dynamics, Monte Carlo, free energy
methods, deterministic and stochastic modeling of differential equations
for systems biology.
Topics Covered:
- Motivation for Computational Biology (1 lecture)
- Interactions (1 lecture)
- Master Equation, Markov Models, Monte Carlo, Kinetic Monte Carlo (2 lectures)
- Applications (student presentations) (1 lecture)
- Monte Carlo Lab (lab+assignment)
- Systems Biology Lab (lab+demos)
- Protein and Nucleic Acid Interaction
- Cellular Signals, Second Messengers
- Receptor Signaling
- Nuclear Signaling
- Cell Cycle
- Cell Cycle Deregulation and Cancer
- Equilibrium and Stability (2 lectures)
- Molecular Dynamics (1-2 lecture)
- Forcefields, long-range interactions (1-2 lecture)
- Student Presentations (Ewald Summation, Nose-Hoover, Nose-Hoover Chain)
- Biomolecular Dynamics (Lab+ Assignment)
- Multiscale Modeling Techniques
- Free Energy Methods
- Applications (Student Presentations): protein-ligand design, protein folding
- Transition Path Sampling
- Applications: Protein conformational changes
- Linear response and Fluctuation Dissipation Theorem
- Applications (Student Presentations)
- Integrating Molecular dynamics and Continuum Mechanics
- Application Wetting of drop on a surface, endocytosis, biological adhesion
Class/Laboratory Schedule:
Lecture: 3 hr/week
Contribution towards Professional Component:
100% Engineering science
Contribution towards
Program Outcomes:
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Multidisciplinary
Ability |
High |
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Problem Solving
Approach |
High |
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Problem Solving
Methods |
High |
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Experimentation |
Low |
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Design |
Low |
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Professional
Orientation |
Low |
Person(s) Preparing Description and Date:
Ravi Radhakrishnan
July 2007
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