Evidence map›Paper›PMID 42470104›Full record

ArticleBiophysical journal2026

Dynamical-nonequilibrium alanine scanning for identifying allosteric positions in proteins.

Balazs Balega, Michael Beer, Dan T S Pike, James Spencer, A Sofia F Oliveira, Adrian J Mulholland

Abstract read
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Article in Biophysical journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Balazs BalegaCentre for Computational Chemistry, School of Chemistry, University of Bristol, Bristol, UK.
Michael BeerCentre for Computational Chemistry, School of Chemistry, University of Bristol, Bristol, UK.
Dan T S PikeCentre for Computational Chemistry, School of Chemistry, University of Bristol, Bristol, UK.
James SpencerSchool of Biochemistry and Cellular and Molecular Medicine, University of Bristol, Bristol, UK.
A Sofia F OliveiraCentre for Computational Chemistry, School of Chemistry, University of Bristol, Bristol, UK. Electronic address: sofia.oliveira@bristol.ac.uk.
Adrian J MulhollandCentre for Computational Chemistry, School of Chemistry, University of Bristol, Bristol, UK. Electronic address: adrian.mulholland@bristol.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Allosteric effects are widespread in proteins, but predicting the impact of sequence substitutions at positions distant from ligand-binding or enzyme active sites remains challenging, as their effects are mediated through complex dynamical networks. Pinpointing such positions experimentally is labor intensive and low throughput. Equilibrium molecular dynamics (MD) simulations are useful: analysis methods can identify functional distal sites and networks, while free energy simulations can predict effects on stability or binding, given sufficient sampling; such simulations are typically time-consuming, requiring extensive simulation of each individual mutant. Here, we introduce a dynamical-nonequilibrium MD (D-NEMD) protocol using alanine substitutions as targeted perturbations to identify distal positions that influence enzyme function. Using the well characterized class A β-lactamase KPC-2 as a test system, we show that D-NEMD distinguishes functional from nonfunctional sites based on whether substitutions generate structured, long-range responses that reach the active site. KPC-2 is clinically important due to its broad substrate spectrum and the emergence of resistance-associated point mutations, many of which act through nonlocal effects on catalytic residues. Alanine substitutions at positions 179 and 164, which disrupt the Ω-loop salt bridge, trigger persistent structural responses propagating through the protein and reach both catalytic residues and the oxyanion hole backbone. Likewise, alanine substitution at position 220 elicits pronounced responses extending to the active-site β sheet and key loops, consistent with its known role in substrate specificity. In contrast, substitution at position 276-mutations of which have negligible kinetic impact-produces only local displacements with minimal propagation and no effect on catalytically relevant regions. These differential response patterns align with experimentally observed resistance phenotypes. D-NEMD therefore provides a fast, generalizable, and predictive approach for identifying allosterically connected distal positions. The protocol complements equilibrium MD, is straightforward to implement, and offers a tractable route for prioritizing candidate sites for mechanistic study or future mutational scanning efforts.

Indexed as

Alaninebeta-LactamasesMolecular Dynamics SimulationAllosteric RegulationAmino Acid SubstitutionCatalytic DomainAlaninebeta-Lactamases

Identifiers

PMID42470104
PMCPMC13507459

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.