COMPUTATIONAL BIOPHYSICS : TOOLS and METHODS

AIM

It is aimed to teach the students some widely-used computational techniques such as molecular modeling, molecular docking and molecular dynamics simulations along with the parameters used to optimize simulations. In this way, students are expected to run a molecular dynamics simulation by their own.

CONTENT

This course contains; Introduction to Quantum Chemistry,An overview to the Quantum Chemical Methods,Introduction to Statistical Mechanics,Molecular Dynamics,Force Fields,Solvation Models,Electrostatics in Molecular dynamics,Free Energy Calculations,Enhanced Sampling Techniques,Hybrid Simulation Methods : QM/MM calculations,Coarse Grained Potentials /Transferability of the Coarse Grained Potentials,Molecular Docking,Application of above-mentioned techniques to biological problems -I,Application of above-mentioned techniques to biological problems -II.

1. 1

   1. Different aspects between molecular mechanics and quantum mechanics are understood and the student can decide which method is appropriate for solving a given biological problem.

   Taught by: Discussion Method, Case Study Method, Self Study Method, Question - Answer Technique, Brainstorming Technique, Project Based Learning Model, Simulation Technique, Computer-Internet Supported Instruction · Assessed by: Project Task

2. 2

   2. The force-fields as well as water models which are needed to perform a molecular dynamics simulation can be determined.

   Taught by: Discussion Method, Case Study Method, Self Study Method, Question - Answer Technique, Brainstorming Technique, Project Based Learning Model, Lecture Method · Assessed by: Project Task

3. 3

   3. Knowledge can be gathered related to the basic commands used in Linux.

   Taught by: Self Study Method, Question - Answer Technique, Experiential Learning, Lecture Method · Assessed by: Homework

4. 4

   4. A molecular dynamics simulation can be started on the clusters.

   Taught by: Discussion Method, Self Study Method, Question - Answer Technique, Project Based Learning Model, Experiential Learning, Lecture Method

5. 5

   5. Molecular dynamics simulations can be initiated and the results can be interpreted.

   Taught by: Discussion Method, Self Study Method, Question - Answer Technique, Brainstorming Technique, Project Based Learning Model, Reverse Brainstorming Technique, Experiential Learning · Assessed by: Project Task

6. 6

   6. The optimum technique can be proposed to solve a problem related to computational biophysics.

   Taught by: Discussion Method, Problem Solving Method, Case Study Method, Question - Answer Technique, Project Based Learning Model, Reverse Brainstorming Technique, Simulation Technique, Problem Baded Learning Model, Inquiry-Based Learning · Assessed by: Project Task

WEEKLY PLAN

1. WEEK 1

   Introduction to Quantum Chemistry

2. WEEK 2

   An overview to the Quantum Chemical Methods

3. WEEK 3

   Introduction to Statistical Mechanics

4. WEEK 4

   Molecular Dynamics

5. WEEK 5

   Force Fields

6. WEEK 6

   Solvation Models

7. WEEK 7

   Electrostatics in Molecular dynamics

8. WEEK 8

   Free Energy Calculations

9. WEEK 9

   Enhanced Sampling Techniques

10. WEEK 10

    Hybrid Simulation Methods : QM/MM calculations

11. WEEK 11

    Coarse Grained Potentials /Transferability of the Coarse Grained Potentials

12. WEEK 12

    Molecular Docking

13. WEEK 13

    Application of above-mentioned techniques to biological problems -I

14. WEEK 14

    Application of above-mentioned techniques to biological problems -II

ASSESSMENT

• Rate of Midterm Exam to Success50%
• Rate of Final Exam to Success50%

WORKLOAD

READING

• 1) Frenkel and Smit, Understanding Molecular Simulation : From Algorithms to Applications, , Academic Press, Computational Science Series
• 2) Allen and Tildesley, Computer Simulation of Liquids, Clarendon Press 3) Zhou, Molecular Modeling at the Atomic Scale, CRC Press, Taylor & Francis.

TEACHING STAFF

• Assoc.Prof. Özge ŞENSOYCOORDINATOR
• Assoc.Prof. Özge ŞENSOY