# Anharmonic Conformational Analysis of Biomolecular Simulations

PARVATIKAR, AKASH (2018) Anharmonic Conformational Analysis of Biomolecular Simulations. Master's Thesis, University of Pittsburgh. (Unpublished)

 Preview
PDF
Primary Text

## Abstract

Anharmonicity in time-dependent conformational fluctuations is noted to be a key feature of functional dynamics of biomolecules. While anharmonic events are rare, long timescale ($\mu s - ms$ and beyond) simulations facilitate probing of such events. However, automated analysis and visualization of anharmonic events from these long timescale simulations is proving to be a significant bottleneck. Traditional analysis tools for biomolecular simulations have focused on spatial second order statistics. Previous work involved resolving \emph{higher order spatial correlations} through quasi-anharmonic analysis (QAA). In this thesis, we extend this analysis to spatio-temporal domain in the form of anharmonic conformational analysis (ANCA).

We demonstrate ANCA on a publicly available millisecond long trajectory data of the protein Bovine pancreatic trypsin inhibitor (BPTI) using cartesian coordinates of the individual atoms selected for analysis. To overcome the limitation of finding a good reference structure through trajectory alignment, we propose ANCA in the dihedral space to make use of the internal angles derived from the backbone of a fluctuating biomolecule. We test this dihedral angle extension of ANCA on a microsecond long simulation of Drew-Dickerson Dodecamer B-DNA data. Our results indicate that ANCA provides a biophysically meaningful organizational framework for long timescale biomolecular simulations.

We have additionally built a scalable Python package for ANCA, namely pyANCA, with modules that can: (1) measure for anharmonicity in the form of higher order statistics and show its variation as a function of time, (2) output a story board representation of the simulations to identify key anharmonic conformational events, and (3) identify putative anharmonic conformational substates and visualize transitions between these substates. ANCA is available as an open-source Python package under the BSD 3-Clause license. Python tutorial notebooks, documentation and examples can be downloaded from http://csb.pitt.edu/anca.

## Share

Citation/Export: Select format... Citation - Text Citation - HTML Endnote BibTex Dublin Core OpenURL MARC (ISO 2709) METS MODS EP3 XML Reference Manager Refer

## Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
PARVATIKAR, AKASHakp47@pitt.eduakp470000-0002-2912-1813
ETD Committee:
Committee MemberUttam, Shikharshf28@pitt.edushf28
Date: 2 July 2018
Date Type: Publication
Defense Date: 13 April 2018
Approval Date: 2 July 2018
Submission Date: 28 May 2018
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 72
Institution: University of Pittsburgh
Schools and Programs: School of Computing and Information > Information Science
Degree: MS - Master of Science
Thesis Type: Master's Thesis
Refereed: Yes
Uncontrolled Keywords: anharmonicity, higher-order statistics, molecular dynamics, conformational analysis, decorrelations
Date Deposited: 02 Jul 2018 12:55