Course Identification

Computational Molecular Biophysics
20192112

Lecturers and Teaching Assistants

Prof. Koby Levy
N/A

Course Schedule and Location

2019
Second Semester
Wednesday, 09:15 - 11:00, FGS, Rm 2
27/03/2019

Field of Study, Course Type and Credit Points

Chemical Sciences: Lecture; Elective; 2.00 points
Chemical Sciences (Materials Science Track): Lecture; Elective; 2.00 points

Comments

No lecture on 3/4/2019

Prerequisites

No

Restrictions

30

Language of Instruction

English

Attendance and participation

Required in at least 80% of the lectures

Grade Type

Numerical (out of 100)

Grade Breakdown (in %)

20%
40%
40%

Evaluation Type

Final assignment

Scheduled date 1

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-
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Estimated Weekly Independent Workload (in hours)

2

Syllabus

1.Protein and Nucleic Acids Architecture Primary, secondary, tertiary, and quaternary structures, dihedral angles and Ramachandran plots, "Catalog" of protein interactions
2. Protein Folding Driving forces of protein folding, energy landscapes, folding in the chaperones, protein misfolding and aggregation, relation between function and dynamics, comparison between protein and RNA folding.
3. Modeling Interactions in Proteins: Building a force field bonded and non-bonded interactions, long-range interactions, different force-fields, parametrization
4. Simplified models of biomolecular systems Physical coarse-grained models, lattice models, empirical potential
5. Foundations of Biomolecular Simulations Classical vs. quantum descriptions, assumptions in biomolecular simulations, from all-atom to simplified (coarse grained) models
6. Energy minimization
7. Molecular Dynamics Simulations Idea of MD , Structure of MD code, Numerical integrators, Simulating different ensembles, Langevin dynamics, MD program packages, setting and running MD simulations, solvent models, conformational sampling
8. Monte Carlo Simulations Basics of MC method, MC simulations of lattice protein models
9. Normal Mode Analysis: dynamics of the folded state
10. Analyzing MD simulations time series, multiple histogram methods, Principal Component Analysis
11. Special topics strategies to enhance conformational sampling, steered MD
 

Learning Outcomes

Upon successful completion of the course, the students will be able to:

Demonstrate an understanding of the biophysical concept of biomolecules using computational and theoretical approaches.

Reading List

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Website

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