Olehnovics, E;
Yin, J;
Perez, A;
De Fabritiis, G;
Bonomo, RA;
Bhowmik, D;
Haider, S;
(2021)
The Role of Hydrophobic Nodes in the Dynamics of Class A beta-Lactamases.
Frontiers in Microbiology
, 12
, Article 720991. 10.3389/fmicb.2021.720991.
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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.
| Type: | Article |
|---|---|
| Title: | The Role of Hydrophobic Nodes in the Dynamics of Class A beta-Lactamases |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.3389/fmicb.2021.720991 |
| Publisher version: | https://doi.org/10.3389/fmicb.2021.720991 |
| Language: | English |
| Additional information: | © 2021 Olehnovics, Yin, Pérez, De Fabritiis, Bonomo, Bhowmik and Haider. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
| Keywords: | β-lactamase, class A, hydrophobic nodes, Markov state model, deep learning, molecular dynamics |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > UCL School of Pharmacy UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > UCL School of Pharmacy > Pharma and Bio Chemistry |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10137138 |
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