Dynamic Differences in Clinically relevant Pen β-Lactamases from Burkholderia spp.

Abstract

Antimicrobial resistance (AMR) is a global threat, with Burkholderia species contributing significantly to difficult-to-treat infections. Ambler Class A Pen {beta}-lactamases are produced by all Burkholderia spp., and their mutation or overproduction leads to the resistance of {beta}-lactam antibiotics. This study investigates the dynamic differences among four Pen {beta}-lactamases (PenA, PenI, PenL and PenP) using machine learning driven enhanced sampling molecular dynamics simulations, Markov State Models (MSMs), convolutional variational autoencoder-based deep learning (CVAE) and the BindSiteS-CNN model. Although sharing the same catalytic mechanisms, these enzymes exhibit distinct dynamic features due low sequence identity, resulting in different substrate profiles and catalytic turnover. The BindSiteS-CNN model further reveals local active site dynamics, offering insights into the Pen {beta}-lactamase evolutionary adaptation. Our findings reported here identify critical mutations and proposes new hotspots affecting Pen {beta}-lactamase flexibility and function, which can be used to fight emerging resistance in these enzymes.