Mapping DHPS evolvability: identification of novel evolutionarily critical sub-structure through evolutionary and structural analyses of DHPS

Tools

Item Type:	Preprint
Title:	Mapping DHPS evolvability: identification of novel evolutionarily critical sub-structure through evolutionary and structural analyses of DHPS
Creators Name:	Sanyal, D., Shivram, A., Banerjee, S., Uversky, V.N., Chivukula, A., Chattopadhyay, K. and Chowdhury, S.
Abstract:	Protein evolution shapes pathogen adaptation-landscape, particularly in developing drug resistance. The rapid evolution of target proteins under antibiotic pressure leads to escape mutations leading to the problem of antibiotic resistance. A deep understanding of the evolutionary dynamics of antibiotic target proteins presents a plausible intervention strategy for disrupting the evolutionary trajectory of resistance. Mutations in Dihydropteroate synthase (DHPS), an essential folate pathway protein and a key target for sulfonamide antibiotics, result in reduced antibiotic binding, leading to resistance. Deploying an array of statistical analyses on the DHPS sequence-space and integrating those with deep mutational analysis and structure-based network-topology models we identified critical DHPS-subsequences. Our analysis of the frustration landscape of DHPS predicts how conformational and mutational changes shift the energy distributions within the DHPS substructures. Combining dimensionality reduction and optimality analysis we identified a substructure critical to DHPS evolvability, and computed its druggablity. Our integrated evolution and structure-informed framework identified a DHPS-substructure with significant evolutionary and structural impact. Targeting this region could constrain DHPS evolvability and disrupt the resistome, presenting a new avenue for antibiotic development and contributing to the broader effort to address the problem of antibiotic resistance.
Keywords:	Protein Evolution, Evolvability, Drug Resistance, Dihydropteroate Synthase (DHPS), Frustration, Escape Mutations, Network-Topology Model
Source:	bioRxiv
Publisher:	Cold Spring Harbor Laboratory Press
Article Number:	2024.10.16.618629
Date:	18 October 2024
Official Publication:	https://doi.org/10.1101/2024.10.16.618629

Repository Staff Only: item control page