Master
2021/2022![Learning Objectives](/f/src/global/i/edu/objectives.svg)
![Expected Learning Outcomes](/f/src/global/i/edu/results.svg)
![Course Contents](/f/src/global/i/edu/sections.svg)
![Bibliography](/f/src/global/i/edu/library.svg)
Computer Molecular Biology and Medicine
Category 'Best Course for New Knowledge and Skills'
Type:
Elective course (Systems Analysis and Mathematical Technologies)
Area of studies:
Applied Mathematics and Informatics
Delivered by:
School of Applied Mathematics
When:
1 year, 1, 2 module
Mode of studies:
offline
Open to:
students of all HSE University campuses
Instructors:
Roman Efremov
Master’s programme:
Systems Analysis and Mathematical Technologies
Language:
English
ECTS credits:
6
Contact hours:
60
Course Syllabus
Abstract
The course covers: basic physical principles of molecular simulations, mathematical algorithms and computationalprotocols employed to study supramolecular biological objects in the framework of classicalmechanics and empirical force fields; the methods of molecular mechanics, molecular dynamics, Monte Carlo,structuralbioinformatics and molecular docking along with their theoretical foundations and employedphysical models and mathematical algorithms; -Combined approaches to rational design of computational experiments with the help of in silicotechnologies; efficient application of the macroscopic approximation and classical mechanics in detailedanalysis of complex microscopic phenomena –individual molecules and their ensembles
Learning Objectives
- The purpose of learning the discipline “Computer molecular biology and medicine” is the students’ introduction into modern methods of computer modeling of complex -multicomponent and mesoscopic -biomolecular systems. The modeling is carried out in the framework of classical Newtonian mechanics, using empirical energy functions -so-called force fields
Expected Learning Outcomes
- be capable of: Analyzing scientific problems and physical processes, realizing in practice fundamentalknowledge obtained in the course of training; Adaptation new problematics, knowledge, scientific terminology and methodology, topossess the skills of independent learning; Application in the given subject area statistical methods of processing experimentaldata, numerical methods, methods of mathematical and computational modeling of complexsystems;
- get experience in: Formulation of computational tasks in studies of complex biomolecular systems; Preparing and running computer simulations of various biomolecular systems, includingsmall molecules, proteins, membranes and their complexes; Correct processing of modeling results and their comparison with available experimentaland literature data; Theoretical analysis of real problems related to atomic-scale studies of molecularsystems and their functioning mechanisms
- be capable of: Understanding meaning of the tasks appearing in the course of professional activity and employment the related physico-mathematical apparatus for description and solving the abovetasks; Using the knowledge of physical and mathematical subjects for further learningaccording to the training profile; Practical working with modern software in the field of computer modeling of complexsystems
- will know: Basic computer technologies of the experimental data processing; Modern methods of computational analysis and prediction of properties and functioningmechanisms of the studied complex biomolecular systems and constructs; Basic physical models describing structural and dynamic properties of biomolecularsystems; Basic principles of computer-aided drug design and multiscale modeling;
Course Contents
- Introduction: “Classical mechanics and in silico modeling in solving modern biomedical tasks (brief overview)”
- Biomolecular simulations with empirical force fields
- Molecular dynamics (MD)
- Monte Carlo (MC) technique in biomolecular modeling
- Methods of free energy calculations in molecular systems
- Solvation effects in biomolecular simulations.
- Molecular modeling of biomembranes.
- Modern computational techniques for assessment of hydrophobic properties of molecular systems
- Numerical experiment in molecular biology and biophysics: modern possibilities and perspectives
Bibliography
Recommended Core Bibliography
- Finkelstein A.V., Ptitsyn O.B. Protein Physics: A Course of Lectures. –Academic Press, 2002.
- Frenkel D., Smit B. Understanding Molecular Simulation: From Algorithms to Applications. –Elsevier, 2002.
- Snurr, Randall Q, Adjiman, Claire, Kofke, David A.Foundations of Molecular Modeling and Simulation. –Springer, 2016.
Recommended Additional Bibliography
- Rapaport, D. C. The art of molecular dynamics simulation. –Cambridge university press, 2004.