Literature DB >> 34621251

The Role of Hydrophobic Nodes in the Dynamics of Class A β-Lactamases.

Edgar Olehnovics1, Junqi Yin2, Adrià Pérez3, Gianni De Fabritiis3,4, Robert A Bonomo5,6,7,8,9,10,11, Debsindhu Bhowmik12, Shozeb Haider1.   

Abstract

Class A β-lactamases are known for being able to rapidly gain broad spectrum catalytic efficiency against most β-lactamase inhibitor combinations as a result of elusively minor point mutations. The evolution in class A β-lactamases occurs through optimisation of their dynamic phenotypes at different timescales. At long-timescales, certain conformations are more catalytically permissive than others while at the short timescales, fine-grained optimisation of free energy barriers can improve efficiency in ligand processing by the active site. Free energy barriers, which define all coordinated movements, depend on the flexibility of the secondary structural elements. The most highly conserved residues in class A β-lactamases are hydrophobic nodes that stabilize the core. To assess how the stable hydrophobic core is linked to the structural dynamics of the active site, we carried out adaptively sampled molecular dynamics (MD) simulations in four representative class A β-lactamases (KPC-2, SME-1, TEM-1, and SHV-1). Using Markov State Models (MSM) and unsupervised deep learning, we show that the dynamics of the hydrophobic nodes is used as a metastable relay of kinetic information within the core and is coupled with the catalytically permissive conformation of the active site environment. Our results collectively demonstrate that the class A enzymes described here, share several important dynamic similarities and the hydrophobic nodes comprise of an informative set of dynamic variables in representative class A β-lactamases.
Copyright © 2021 Olehnovics, Yin, Pérez, De Fabritiis, Bonomo, Bhowmik and Haider.

Entities:  

Keywords:  Markov state model; class A; deep learning; hydrophobic nodes; molecular dynamics; β-lactamase

Year:  2021        PMID: 34621251      PMCID: PMC8490755          DOI: 10.3389/fmicb.2021.720991

Source DB:  PubMed          Journal:  Front Microbiol        ISSN: 1664-302X            Impact factor:   5.640


  65 in total

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