ArticlePLoS computational biology2010
Modeling conformational ensembles of slow functional motions in Pin1-WW.
Article in PLoS computational biology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.
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44 citing papers in PubMed.
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- Unveiling the Conformational Dynamics of the Histone Tails Using Markov State Modeling.Journal of chemical theory and computation · 2025Article
- Targeting Bacterial RNA Polymerase: Harnessing Simulations and Machine Learning to Design Inhibitors for Drug-Resistant Pathogens.Biochemistry · 2025Review
- Exploring transition states of protein conformational changes via out-of-distribution detection in the hyperspherical latent space.Nature communications · 2025Article
- Pin1 WW Domain Ligand Library Synthesized with an Easy Solid-Phase Phosphorylating Reagent.Biochemistry · 2024Article
- Tutorial on how to build non-Markovian dynamic models from molecular dynamics simulations for studying protein conformational changes.The Journal of chemical physics · 2024Article
- Integrative generalized master equation: A method to study long-timescale biomolecular dynamics via the integrals of memory kernels.The Journal of chemical physics · 2023Article
- An Efficient Path Classification Algorithm Based on Variational Autoencoder to Identify Metastable Path Channels for Complex Conformational Changes.Journal of chemical theory and computation · 2023Article
- Disease mutations and phosphorylation alter the allosteric pathways involved in autoinhibition of protein phosphatase 2A.The Journal of chemical physics · 2023Article
- Building insightful, memory-enriched models to capture long-time biochemical processes from short-time simulations.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Markov State Models to Study the Functional Dynamics of Proteins in the Wake of Machine Learning.JACS Au · 2021Review
- Role of bacterial RNA polymerase gate opening dynamics in DNA loading and antibiotics inhibition elucidated by quasi-Markov State Model.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Protein Allostery at Atomic Resolution.Angewandte Chemie (International ed. in English) · 2020Article
- Target search and recognition mechanisms of glycosylase AlkD revealed by scanning FRET-FCS and Markov state models.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Role of Conformational Motions in Enzyme Function: Selected Methodologies and Case Studies.Catalysts (Basel, Switzerland) · 2016Article
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11 authors.
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Abstract
Protein-protein interactions are often mediated by flexible loops that experience conformational dynamics on the microsecond to millisecond time scales. NMR relaxation studies can map these dynamics. However, defining the network of inter-converting conformers that underlie the relaxation data remains generally challenging. Here, we combine NMR relaxation experiments with simulation to visualize networks of inter-converting conformers. We demonstrate our approach with the apo Pin1-WW domain, for which NMR has revealed conformational dynamics of a flexible loop in the millisecond range. We sample and cluster the free energy landscape using Markov State Models (MSM) with major and minor exchange states with high correlation with the NMR relaxation data and low NOE violations. These MSM are hierarchical ensembles of slowly interconverting, metastable macrostates and rapidly interconverting microstates. We found a low population state that consists primarily of holo-like conformations and is a "hub" visited by most pathways between macrostates. These results suggest that conformational equilibria between holo-like and alternative conformers pre-exist in the intrinsic dynamics of apo Pin1-WW. Analysis using MutInf, a mutual information method for quantifying correlated motions, reveals that WW dynamics not only play a role in substrate recognition, but also may help couple the substrate binding site on the WW domain to the one on the catalytic domain. Our work represents an important step towards building networks of inter-converting conformational states and is generally applicable.
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