| Knowledge of conformational changes in biomolecules are crucial for understanding diseases. Research in the area of Computational Biophysics has proven to be essential in this regard, accelerating the development of methods for understanding biomolecular motion and its biological functions. Given the endpoints of transition, path sampling algorithms find a set of reaction path(s) of interest. On-the-fly string method is a popular path sampling algorithm for finding the most probable reaction path. Finding reaction paths often require knowledge of a set of reaction coordinates, or collective variables, along which the transition takes place, which is non-trivial. In this work, I propose the use of low frequency normal modes as reaction coordinates. This choice is based on the observation that normal mode analysis can provide the direction of the low frequency motion of interest. As a proof of concept, I applied this method to study isomerization transitions of alanine dipeptide. The algorithms I developed are general and can be readily applied to larger systems. I also show that the choice of the normal modes confers simplifications in the string method itself.;Biomolecular conformational changes of biological relevance take place in the timescale of milliseconds to seconds. Conventional Molecular Dynamics (MD) simulations can only capture timescale of microseconds. Over the last decade, various attempts has been made to overcome the limitations of MD with smart sampling algorithms. Some or all of these algorithms also try to exploit large-scale distributed computing environments. Often, it is not essential to understand structural changes in atomistic detail. Attempts has been made to capture transitions of interest without getting stuck with the computational complexity associated with fine-grained simulations. The main theme of the coarse-grained algorithms lie in the attempt to capture relevant degrees of freedom along which important conformational changes take place. Normal Mode Langevin (NML) is a recently developed coarse-grained integrator which is based on this idea. Replica Exchange Method (REM) is an efficient algorithm which utilizes multiple simulations (replica) in parallel to accelerate sampling.;In this dissertation, I will present results showing evidence that incorporating NML with REM can improve its scalability for large biomolecular systems. |
