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

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.