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Xu T, Li Y, Gao X, Zhang L. Understanding the Fast-Triggering Unfolding Dynamics of FK-11 upon Photoexcitation of Azobenzene. J Phys Chem Lett 2024; 15:3531-3540. [PMID: 38526058 DOI: 10.1021/acs.jpclett.4c00091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/26/2024]
Abstract
Photoswitchable molecules can control the activity and functions of biomolecules by triggering conformational changes. However, it is still challenging to fully understand such fast-triggering conformational evolution from nonequilibrium to equilibrium distribution at the molecular level. Herein, we successfully simulated the unfolding of the FK-11 peptide upon the photoinduced trans-to-cis isomerization of azobenzene based on the Markov state model. We found that the ensemble of FK-11 contains five conformational states, constituting two unfolding pathways. More intriguingly, we observed the microsecond-scale conformational propagation of the FK-11 peptide from the fully folded state to the equilibrium populations of the five states. The computed CD spectra match well with the experimental data, validating our simulation method. Overall, our study not only offers a protocol to study the photoisomerization-induced conformational changes of enzymes but also could orientate the rational design of a photoswitchable molecule to manipulate biological functions.
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Affiliation(s)
- Tiantian Xu
- State Key Laboratory of Structural Chemistry, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou, Fujian 350002, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yongfang Li
- State Key Laboratory of Structural Chemistry, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou, Fujian 350002, China
| | - Xin Gao
- Computational Bioscience Research Center, King Abdullah University of Science and Technology (KAUST), Thuwal 23955, Saudi Arabia
- Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955, Saudi Arabia
| | - Lu Zhang
- State Key Laboratory of Structural Chemistry, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou, Fujian 350002, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- Fujian Provincial Key Laboratory of Theoretical and Computational Chemistry, Fuzhou, Fujian 361005, China
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2
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Stenström O, Diehl C, Modig K, Akke M. Ligand-induced protein transition state stabilization switches the binding pathway from conformational selection to induced fit. Proc Natl Acad Sci U S A 2024; 121:e2317747121. [PMID: 38527204 PMCID: PMC10998626 DOI: 10.1073/pnas.2317747121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2023] [Accepted: 02/29/2024] [Indexed: 03/27/2024] Open
Abstract
Protein-ligand complex formation is fundamental to biological function. A central question is whether proteins spontaneously adopt binding-competent conformations to which ligands bind conformational selection (CS) or whether ligands induce the binding-competent conformation induced fit (IF). Here, we resolve the CS and IF binding pathways by characterizing protein conformational dynamics over a wide range of ligand concentrations using NMR relaxation dispersion. We determined the relative flux through the two pathways using a four-state binding model that includes both CS and IF. Experiments conducted without ligand show that galectin-3 exchanges between the ground-state conformation and a high-energy conformation similar to the ligand-bound conformation, demonstrating that CS is a plausible pathway. Near-identical crystal structures of the apo and ligand-bound states suggest that the high-energy conformation in solution corresponds to the apo crystal structure. Stepwise additions of the ligand lactose induce progressive changes in the relaxation dispersions that we fit collectively to the four-state model, yielding all microscopic rate constants and binding affinities. The ligand affinity is higher for the bound-like conformation than for the ground state, as expected for CS. Nonetheless, the IF pathway contributes greater than 70% of the total flux even at low ligand concentrations. The higher flux through the IF pathway is explained by considerably higher rates of exchange between the two protein conformations in the ligand-associated state. Thus, the ligand acts to decrease the activation barrier between protein conformations in a manner reciprocal to enzymatic transition-state stabilization of reactions involving ligand transformation.
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Affiliation(s)
- Olof Stenström
- Division of Biophysical Chemistry, Center for Molecular Protein Science, Department of Chemistry, Lund University, SE-221 00Lund, Sweden
| | - Carl Diehl
- Division of Biophysical Chemistry, Center for Molecular Protein Science, Department of Chemistry, Lund University, SE-221 00Lund, Sweden
| | - Kristofer Modig
- Division of Biophysical Chemistry, Center for Molecular Protein Science, Department of Chemistry, Lund University, SE-221 00Lund, Sweden
| | - Mikael Akke
- Division of Biophysical Chemistry, Center for Molecular Protein Science, Department of Chemistry, Lund University, SE-221 00Lund, Sweden
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3
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Sisk TR, Robustelli P. Folding-upon-binding pathways of an intrinsically disordered protein from a deep Markov state model. Proc Natl Acad Sci U S A 2024; 121:e2313360121. [PMID: 38294935 PMCID: PMC10861926 DOI: 10.1073/pnas.2313360121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Accepted: 11/22/2023] [Indexed: 02/02/2024] Open
Abstract
A central challenge in the study of intrinsically disordered proteins is the characterization of the mechanisms by which they bind their physiological interaction partners. Here, we utilize a deep learning-based Markov state modeling approach to characterize the folding-upon-binding pathways observed in a long timescale molecular dynamics simulation of a disordered region of the measles virus nucleoprotein NTAIL reversibly binding the X domain of the measles virus phosphoprotein complex. We find that folding-upon-binding predominantly occurs via two distinct encounter complexes that are differentiated by the binding orientation, helical content, and conformational heterogeneity of NTAIL. We observe that folding-upon-binding predominantly proceeds through a multi-step induced fit mechanism with several intermediates and do not find evidence for the existence of canonical conformational selection pathways. We observe four kinetically separated native-like bound states that interconvert on timescales of eighty to five hundred nanoseconds. These bound states share a core set of native intermolecular contacts and stable NTAIL helices and are differentiated by a sequential formation of native and non-native contacts and additional helical turns. Our analyses provide an atomic resolution structural description of intermediate states in a folding-upon-binding pathway and elucidate the nature of the kinetic barriers between metastable states in a dynamic and heterogenous, or "fuzzy", protein complex.
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Affiliation(s)
- Thomas R. Sisk
- Department of Chemistry, Dartmouth College, Hanover, NH03755
| | - Paul Robustelli
- Department of Chemistry, Dartmouth College, Hanover, NH03755
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4
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Arbon R, Zhu Y, Mey ASJS. Markov State Models: To Optimize or Not to Optimize. J Chem Theory Comput 2024; 20:977-988. [PMID: 38163961 PMCID: PMC10809420 DOI: 10.1021/acs.jctc.3c01134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 12/10/2023] [Accepted: 12/11/2023] [Indexed: 01/03/2024]
Abstract
Markov state models (MSM) are a popular statistical method for analyzing the conformational dynamics of proteins including protein folding. With all statistical and machine learning (ML) models, choices must be made about the modeling pipeline that cannot be directly learned from the data. These choices, or hyperparameters, are often evaluated by expert judgment or, in the case of MSMs, by maximizing variational scores such as the VAMP-2 score. Modern ML and statistical pipelines often use automatic hyperparameter selection techniques ranging from the simple, choosing the best score from a random selection of hyperparameters, to the complex, optimization via, e.g., Bayesian optimization. In this work, we ask whether it is possible to automatically select MSM models this way by estimating and analyzing over 16,000,000 observations from over 280,000 estimated MSMs. We find that differences in hyperparameters can change the physical interpretation of the optimization objective, making automatic selection difficult. In addition, we find that enforcing conditions of equilibrium in the VAMP scores can result in inconsistent model selection. However, other parameters that specify the VAMP-2 score (lag time and number of relaxation processes scored) have only a negligible influence on model selection. We suggest that model observables and variational scores should be only a guide to model selection and that a full investigation of the MSM properties should be undertaken when selecting hyperparameters.
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Affiliation(s)
- Robert
E. Arbon
- EaStCHEM
School of Chemistry, David Brewster Road, Joseph Black Building, The King’s Buildings, Edinburgh EH9 3FJ, United Kingdom
- Redesign
Science, 180 Varick St., New York, New York 10014, United States
| | - Yanchen Zhu
- EaStCHEM
School of Chemistry, David Brewster Road, Joseph Black Building, The King’s Buildings, Edinburgh EH9 3FJ, United Kingdom
| | - Antonia S. J. S. Mey
- EaStCHEM
School of Chemistry, David Brewster Road, Joseph Black Building, The King’s Buildings, Edinburgh EH9 3FJ, United Kingdom
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5
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Joseph D, Griesinger C. Optimal control pulses for the 1.2-GHz (28.2-T) NMR spectrometers. SCIENCE ADVANCES 2023; 9:eadj1133. [PMID: 37948513 PMCID: PMC10637738 DOI: 10.1126/sciadv.adj1133] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Accepted: 10/12/2023] [Indexed: 11/12/2023]
Abstract
The ability to measure nuclear magnetic resonance (NMR) spectra with a large sample volume is crucial for concentration-limited biological samples to attain adequate signal-to-noise (S/N) ratio. The possibility to measure with a 5-mm cryoprobe is currently absent at the 1.2-GHz NMR instruments due to the exceedingly high radio frequency power demands, which is four times compared to 600-MHz instruments. Here, we overcome the high-power demands by designing optimal control (OC) pulses with up to 20 times lower power requirements than currently necessary at a 1.2-GHz spectrometer. We show that multidimensional biomolecular NMR experiments constructed using these OC pulses can bestow improvement in the S/N ratio of up to 26%. With the expected power limitations of a 5-mm cryoprobe, we observe an enhancement in the S/N ratio of more than 240% using our OC sequences. This motivates the development of a cryoprobe with a larger volume than the current 3-mm cryoprobes.
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Affiliation(s)
- David Joseph
- Max Planck Institute for Multidisciplinary Sciences, Göttingen, Niedersachsen D-37077, Germany
| | - Christian Griesinger
- Max Planck Institute for Multidisciplinary Sciences, Göttingen, Niedersachsen D-37077, Germany
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6
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Pasarkar AP, Bencomo GM, Olsson S, Dieng AB. Vendi sampling for molecular simulations: Diversity as a force for faster convergence and better exploration. J Chem Phys 2023; 159:144108. [PMID: 37823459 DOI: 10.1063/5.0166172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 09/25/2023] [Indexed: 10/13/2023] Open
Abstract
Molecular dynamics (MD) is the method of choice for understanding the structure, function, and interactions of molecules. However, MD simulations are limited by the strong metastability of many molecules, which traps them in a single conformation basin for an extended amount of time. Enhanced sampling techniques, such as metadynamics and replica exchange, have been developed to overcome this limitation and accelerate the exploration of complex free energy landscapes. In this paper, we propose Vendi Sampling, a replica-based algorithm for increasing the efficiency and efficacy of the exploration of molecular conformation spaces. In Vendi sampling, replicas are simulated in parallel and coupled via a global statistical measure, the Vendi Score, to enhance diversity. Vendi sampling allows for the recovery of unbiased sampling statistics and dramatically improves sampling efficiency. We demonstrate the effectiveness of Vendi sampling in improving molecular dynamics simulations by showing significant improvements in coverage and mixing between metastable states and convergence of free energy estimates for four common benchmarks, including Alanine Dipeptide and Chignolin.
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Affiliation(s)
- Amey P Pasarkar
- Vertaix, Department of Computer Science, Princeton University, 35 Olden Street, Princeton, New Jersey 08544, USA
| | - Gianluca M Bencomo
- Department of Computer Science, Princeton University, 35 Olden Street, Princeton, New Jersey 08544, USA
| | - Simon Olsson
- Department of Computer Science and Engineering, Chalmers University of Technology, Rännvägen 6, 41258 Gothenburg, Sweden
| | - Adji Bousso Dieng
- Vertaix, Department of Computer Science, Princeton University, 35 Olden Street, Princeton, New Jersey 08544, USA
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7
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Sisk T, Robustelli P. Folding-upon-binding pathways of an intrinsically disordered protein from a deep Markov state model. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.21.550103. [PMID: 37546728 PMCID: PMC10401938 DOI: 10.1101/2023.07.21.550103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
A central challenge in the study of intrinsically disordered proteins is the characterization of the mechanisms by which they bind their physiological interaction partners. Here, we utilize a deep learning based Markov state modeling approach to characterize the folding-upon-binding pathways observed in a long-time scale molecular dynamics simulation of a disordered region of the measles virus nucleoprotein NTAIL reversibly binding the X domain of the measles virus phosphoprotein complex. We find that folding-upon-binding predominantly occurs via two distinct encounter complexes that are differentiated by the binding orientation, helical content, and conformational heterogeneity of NTAIL. We do not, however, find evidence for the existence of canonical conformational selection or induced fit binding pathways. We observe four kinetically separated native-like bound states that interconvert on time scales of eighty to five hundred nanoseconds. These bound states share a core set of native intermolecular contacts and stable NTAIL helices and are differentiated by a sequential formation of native and non-native contacts and additional helical turns. Our analyses provide an atomic resolution structural description of intermediate states in a folding-upon-binding pathway and elucidate the nature of the kinetic barriers between metastable states in a dynamic and heterogenous, or "fuzzy", protein complex.
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Affiliation(s)
- Thomas Sisk
- Dartmouth College, Department of Chemistry, Hanover, NH, 03755
| | - Paul Robustelli
- Dartmouth College, Department of Chemistry, Hanover, NH, 03755
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8
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Pandey PR, Rózycki B, Weikl TR. Molecular Dynamics Simulations of Immune Receptors and Ligands. Methods Mol Biol 2023; 2654:51-59. [PMID: 37106175 DOI: 10.1007/978-1-0716-3135-5_4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/29/2023]
Abstract
Molecular dynamics simulations of immune receptor and ligand proteins in their native membrane environment allow to determine the orientational and structural variability of the proteins and protein complexes. The simulations complement the static, "membrane-free" structural information obtained from cryo-EM structures of transmembrane proteins in detergent micelles or from crystal structures of extracellular protein domains. Here we describe how to set up and perform simulations of transmembrane receptors, ligands, and receptor-ligand complexes.
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Affiliation(s)
- Prithvi R Pandey
- Max Planck Institute of Colloids and Interfaces, Potsdam, Germany
| | - Bartosz Rózycki
- Institute of Physics of the Polish Academy of Sciences, Warszawa, Poland
| | - Thomas R Weikl
- Max Planck Institute of Colloids and Interfaces, Potsdam, Germany.
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