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Магистратура 2022/2023

Компьютерная молекулярная биология и медицина

Лучший по критерию «Полезность курса для расширения кругозора и разностороннего развития»
Лучший по критерию «Новизна полученных знаний»
Направление: 01.04.02. Прикладная математика и информатика
Когда читается: 1-й курс, 1, 2 модуль
Формат изучения: без онлайн-курса
Охват аудитории: для всех кампусов НИУ ВШЭ
Прогр. обучения: Системный анализ и математические технологии
Язык: английский
Кредиты: 6
Контактные часы: 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

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

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

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
Assessment Elements

Assessment Elements

  • non-blocking Control work
  • non-blocking Homework
  • non-blocking Exam
Interim Assessment

Interim Assessment

  • 2022/2023 2nd module
    0.2 * Control work + 0.2 * Homework + 0.6 * Exam
Bibliography

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.