ArticleBiophysical journal2019
Cooperative Changes in Solvent Exposure Identify Cryptic Pockets, Switches, and Allosteric Coupling.
Article in Biophysical journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
38 citing papers in PubMed, 72 citations in OpenAlex.
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- Decrypting cryptic pockets with physics-based simulations and artificial intelligence.Current opinion in structural biology · 2026Review
- Dynamic signature of activity-stability tradeoff in lactamase evolution.Nature communications · 2026Article
- Chasing allosteric inhibition of the SARS-CoV-2 PLpro via molecular dynamics simulations with flooding fragments (MDFFr).Journal of computer-aided molecular design · 2025Article
- Identification of Protein Cryptic Sites via Conformational Dynamics Capturing and Water-Based Pocket Characterization in Molecular Dynamics Simulations.Journal of chemical theory and computation · 2025Article
- Opening and closing of a cryptic pocket in VP35 toggles it between two different RNA-binding modes.eLife · 2025Article
- Recent computational advances in the identification of cryptic binding sites for drug discovery.Bioinformatics advances · 2025Review
- Navigating structure-based drug discovery with emerging innovations in physics- and knowledge-based approaches.npj drug discovery · 2025Review
- Exploration of Cryptic Pockets Using Enhanced Sampling Along Normal Modes: A Case Study of KRASJournal of chemical information and modeling · 2024Article
- SWISH-X, an Expanded Approach to Detect Cryptic Pockets in Proteins and at Protein-Protein Interfaces.Journal of chemical theory and computation · 2024Article
- Toward physics-based precision medicine: Exploiting protein dynamics to design new therapeutics and interpret variants.Protein science : a publication of the Protein Society · 2024Review
- PopShift: A Thermodynamically Sound Approach to Estimate Binding Free Energies by Accounting for Ligand-Induced Population Shifts from a Ligand-Free Markov State Model.Journal of chemical theory and computation · 2024Article
- Folding@home: Achievements from over 20 years of citizen science herald the exascale era.Biophysical journal · 2023Review
- Allosteric inhibition of TEM-1 β lactamase: Microsecond molecular dynamics simulations provide mechanistic insights.Protein science : a publication of the Protein Society · 2023Article
- Folding@home: achievements from over twenty years of citizen science herald the exascale era.ArXiv · 2023Article
- Predicting locations of cryptic pockets from single protein structures using the PocketMiner graph neural network.Nature communications · 2023Article
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- Slow Protein Dynamics Elicits New Enzymatic Functions by Means of Epistatic Interactions.Molecular biology and evolution · 2022Article
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
Proteins are dynamic molecules that undergo conformational changes to a broad spectrum of different excited states. Unfortunately, the small populations of these states make it difficult to determine their structures or functional implications. Computer simulations are an increasingly powerful means to identify and characterize functionally relevant excited states. However, this advance has uncovered a further challenge: it can be extremely difficult to identify the most salient features of large simulation data sets. We reasoned that many functionally relevant conformational changes are likely to involve large, cooperative changes to the surfaces that are available to interact with potential binding partners. To examine this hypothesis, we introduce a method that returns a prioritized list of potentially functional conformational changes by segmenting protein structures into clusters of residues that undergo cooperative changes in their solvent exposure, along with the hierarchy of interactions between these groups. We term these groups exposons to distinguish them from other types of clusters that arise in this analysis and others. We demonstrate, using three different model systems, that this method identifies experimentally validated and functionally relevant conformational changes, including conformational switches, allosteric coupling, and cryptic pockets. Our results suggest that key functional sites are hubs in the network of exposons. As a further test of the predictive power of this approach, we apply it to discover cryptic allosteric sites in two different β-lactamase enzymes that are widespread sources of antibiotic resistance. Experimental tests confirm our predictions for both systems. Importantly, we provide the first evidence, to our knowledge, for a cryptic allosteric site in CTX-M-9 β-lactamase. Experimentally testing this prediction did not require any mutations and revealed that this site exerts the most potent allosteric control over activity of any pockets found in β-lactamases to date. Discovery of a similar pocket that was previously overlooked in the well-studied TEM-1 β-lactamase demonstrates the utility of exposons.
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Registered trials
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.