Abstract

In the current scenario, widespread multidrug resistivity in ESKAPE pathogens demands identification of novel drug targets to keep their infections at bay. For this purpose, we have identified a novel target Hpa2 of A. baumannii, a member of GNAT superfamily of HATs. But due to sequence identity of equal or less than 35%, the correct sequence alignment and construction of 3D monomeric and dimeric models of Hpa2 having optimal structural parameters is a troublesome task. To circumvent these problems, we have designed an easy and optimized protocol for Hpa2 monomer modeling, and for generation of dimeric Hpa2 model using data-driven protein–protein docking experiment. Improvement in the structural features of generated model is an onerous process and generally achieved by paying time and computational cost. Herein, it is achieved by reconciliation of FoldX commands which takes less time in execution. Evaluations performed to validate structural parameters and stability of monomeric and dimeric Hpa2 attests to its quality. Analysis of interfacial residues, energy terms and RMSD values indicated a clear correlation between experimental and theoretical interface properties of the dimers, corroborating to the regime used for Hpa2 dimer generation. Structural information from the refined models was used for virtual screening of substrate-derived library and polyamines to achieve a new platform for developing A. baumannii inhibitory molecules. Molecules showing preferential binding at the dimer interface could be used as allosteric inhibitors. Binding of polyamines with model illustrated the same binding pattern as described experimentally in case of yeast Hpa2.

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