Enhanced Kinetic Sampling Methods for Biomolecular Simulations (TA/FA)

All life processes are based on the fact
that biomolecules can exist in and can switch between different conformations. However,
tracing the structures and the dynamics of proteins and other biomolecules is
expensive and in fact, not possible through experimental means alone in most
cases. Atomistic simulations are playing an increasingly important role in
elucidating molecular processes. However, brute force methods are limited in
the timescales that can be reached. We are primarily interested in developing
methods to bridge the timescale gap between the processes of interest and the
simulation timescales that can be reached in simulations. Our group has already
developed several techniques for enhanced kinetic sampling. This project
involves applying the methods that have been developed to the study of
important problems in molecular biology such as the folding kinetics of
proteins, aggregation,  and the dynamics
of DNA/RNA structures. The student will be exposed to the state-of-art in
molecular dynamics and data science techniques.

 

Skills Required: An interest in modelling and
simulations is required. Expertise in Matlab/python/C/C++  is preferable.








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Proposing Faculty
Research Area
  • Computational Biology