alexa New Applications Of Boxed Molecular Dynamics: Atomistic Simulations Of Atomic Force Microscopy Experiments And Peptide Cyclization | 72369
ISSN: 0974-276X

Journal of Proteomics & Bioinformatics
Open Access

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9th International Conference on Structural Biology
September 18-20, 2017 Zurich, Switzerland

Dmitrii V Shalashilin
University of Leeds, UK
ScientificTracks Abstracts: J Proteomics Bioinform
DOI: 10.4172/0974-276X-C1-100
Abstract
New applications of Boxed Dynamics (BXD), an efficient technique to extend the time scale of molecular dynamics and simulate rare events, will be presented. BXD allows analysis of thermodynamics and kinetics in complicated molecular systems. It is a fully atomistic multiscale technique, in which thermodynamics and long-time dynamics are recovered from a set of short-time molecular dynamics simulations. BXD is many orders of magnitude faster than standard MD and can produce well converged results. Previously BXD has been applied to peptide cyclization, solution-phase organic reaction dynamics, and desorption of ions from self-assembled monolayers (SAMs). Here two new applications of BXD will be reported. First atomistic simulations of protein pulling with Atomic Force Microscope AFM) will be presented, where BXD is able to reproduce correctly the Potential of Mean Force (PMF) of a protein pulled in AFM experiments, the experimentally observed force profile and its relationship with the protein structure. Second, an application of BXD to enzymatic peptide cyclization will also be presented, where BXD predicts correctly the cyclizable peptide sequences. All such sequences have a conformation with their C and N termini close to each other. In both applications calculations were done with standard force field without any adjustment of the force field parameters. Thus, BXD proves to be a good predictive tool. It is implemented in CHARMM molecular dynamics code and can be used for many other applications.
Biography

Dmitrii V Shalashilin is a Professor of Computational Chemistry at the University of Leeds. His research is focused on the development of efficient computational techniques for quantum and classical simulations in chemistry and their applications.

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