Title: Tertiary and quaternary structure prediction of full-length human p53 by comparative modelling with structural environment-based alignment method

Authors: Vaijayanthi Raghavan; Maulishree Agrahari; Dhananjaya Kale Gowda

Addresses: Department of Biotechnology, 100 ft. Ring Road, Banashankari 3rd Stage, PES Institute of Technology, Bengaluru 560085, India ' Department of Biotechnology, 100 ft. Ring Road, Banashankari 3rd Stage, PES Institute of Technology, Bengaluru 560085, India; Department of Physiology and Pharmacology, Faculty of Medicine, University of Calgary, Calgary, Canada ' Research & Development Department, R&D, Robust Materials Technology Private Limited, No. 94, Nagarbhavi Main Road, Bengaluru, Karnataka 560072, India

Abstract: One of the fundamental components for a wide range of proteomics research is to determine the 3D structure and properties of proteins. Access to precise and accurate protein models becomes very essential to predict the drug binding region or optimising the stability and selectivity of biologics. Due to biological and technical challenges of p53, the full-length 3D structure is unavailable for the scientific community; thus, there is a need to develop the 3D structure of p53, which is a key player in preventing cancer. Here, we model all the 393 amino acids to generate full-length 3D models of human p53 in both monomeric and tetrameric forms using computational approaches. The 3D model building involved homology-based modelling techniques combined with a refinement approach and use of structural environment-based alignment method for developing quaternary structure of human p53. Our results showed that 3D models are more reliable when iterative modelling was used and structural environment-based alignment method is well-suited to model the tetramer. These structures can be utilised to develop p53 mutants, virtual screening, design/develop small molecules or target-drug interaction studies.

Keywords: homology modelling; human p53; structure prediction; transformation matrices; tumour suppressor protein.

DOI: 10.1504/IJBRA.2018.094961

International Journal of Bioinformatics Research and Applications, 2018 Vol.14 No.4, pp.337 - 356

Received: 16 Jul 2016
Accepted: 26 Oct 2016

Published online: 26 Dec 2017 *

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