Notice of Computational Biochemistry Course Selection-


Notice of Computational Biochemistry Course Selection

发布日期:2019-01-14 发表者:程心瑛 浏览次数:次

Registration Information for Computational Biochemistry

Computational Biochemistry course will be offered in spring 2019, from March 19 to April 12. It is scheduled to have two lectures and one lab per week. This course introduces the basic knowledge of computational biochemistry, including molecular mechanics and force field, molecular dynamics simulation, and quantum chemistry calculation, etc. Topics include biomolecular 3D structure prediction (homology modeling), prediction of ligand binding modes (molecular docking), 3-D structure simulation (molecular dynamics), and the calculation of interaction energies (MM/GBSA). The laboratory part of this course offers hands-on experience with current modeling and simulation programs.

If you are registering for this class, please contact Dr. XiaocongWang ( with your name, student ID, major and affiliation BEFORE January 24th, 2019.

Best regards,

Wang, Xiaocong

College of Bioinformatics in HZAU


Course Page:

If you like 3D structure and modeling – this is the course for you!

Learn to:

l Predict DNA/RNA and protein structure

l Predict receptor-ligand binding

l Simulate molecular motion

Remember – All function derives from 3D structure and dynamics!

The course uses both lectures and computer laboratory time to provide an understanding of current computational methods, with emphasis on their strengths and limitations. Coursework includes lab projects, presentations, which are performed in both classroom and computer lab during class hours under the supervision of the instructor and qualified TAs. Project 1 will probe the limits of homology modeling, using a small protein test case. Project 2 will examine the ability of computational methods to predict the interaction of protein-ligand complexes. The results of each project will be presented in 10-minute oral presentations. Students will gain hands-on experience with the following programs: AMBER (sander, tLEaP, ptraj), AutoDock, and VMD. A familiarity with protein structure and basic physics or chemistry will be useful, but not required.

Goal for this Course:

1. Understand conformations of biomolecules, sampling of different conformations, and energy potential associated with conformations.

2. Learn the basic theories for molecular mechanics and molecular dynamics.

3. Understand the parameters and conditions in molecular dynamics, select parameters independently with different simulation requests.

4. Learn the bioinformatics tools for representing protein structures, extract information from different database.

5. Perform homology modeling, MD simulation. Learn writing scripts for processing data.

6. Understand interaction energies between biomolecules, and methods for calculating these energies.

7. Learn the basics of quantum chemistry (QM), and its application in biochemistry. Understand theories of QM/MM methods.

8. Learn computational biochemistry in drug design.

Teaching plan:

1 Introductionweek 1

1.1 History of computational biochemistry

1.2 Subject of computational biochemistry

1.3 Methods in computational biochemistry

2 Biomolecular structures database and visualizationweek 1

2.1 Protein Databank (PDB), Nucleic acids databases, and other structure databases

2.2 SCOP& CATH database

2.3 PDB&mmCIF format

2.4 VMD software package and tcl scripts

3 Molecular mechanicsweek 1

3.1 Energy evaluation equation for molecular mechanics

3.2 Velocity and energy

3.3 Force field parameters

3.4 Sampling and energy

4 Potential energy surface week 2

4.1 Intermolecular interactions and potential energy surface

4.2 Valence interactions

4.3 Non-Valence interactions

4.4 Energy minimization

5 Molecular Dynamics Simulation week 2

5.1 Basics in molecular dynamics simulation

5.2 Parameters/Conditions in molecular dynamics simulation

5.3 Water models

5.4 GROMACS and AMBER software packages

6 Interaction Energy Prediction week 3

6.1 Compositions of biomolecular interaction energy

6.2 MM/GB(PB)SA calculation

6.3 Entropy calculation

6.4 Enhanced Sampling Method

7 Introduction to quantum chemistry week 3

7.1 Basics in quantum chemistry

7.2 Self-consistent Field Molecular Orbital Theory

7.3 Density function theory

7.4 Gaussian software package

7.5 Geometry optimization and single point energy calculation

7.6 Transition state and modeling of chemical reaction

8 Enzymatic dynamics & QM/MM method (optional) week 4

8.1 Biological catalysis and enzymes

8.2 QM/MM & QM/MD

8.3 Chemshell software package

8.4 ONIOM method