1
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Horvath D, Žoldák G. Entropy-Based Strategies for Rapid Pre-Processing and Classification of Time Series Data from Single-Molecule Force Experiments. ENTROPY (BASEL, SWITZERLAND) 2020; 22:e22060701. [PMID: 33286473 PMCID: PMC7517239 DOI: 10.3390/e22060701] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Revised: 06/16/2020] [Accepted: 06/20/2020] [Indexed: 06/12/2023]
Abstract
Recent advances in single-molecule science have revealed an astonishing number of details on the microscopic states of molecules, which in turn defined the need for simple, automated processing of numerous time-series data. In particular, large datasets of time series of single protein molecules have been obtained using laser optical tweezers. In this system, each molecular state has a separate time series with a relatively uneven composition from the point of view-point of local descriptive statistics. In the past, uncertain data quality and heterogeneity of molecular states were biased to the human experience. Because the data processing information is not directly transferable to the black-box-framework for an efficient classification, a rapid evaluation of a large number of time series samples simultaneously measured may constitute a serious obstacle. To solve this particular problem, we have implemented a supervised learning method that combines local entropic models with the global Lehmer average. We find that the methodological combination is suitable to perform a fast and simple categorization, which enables rapid pre-processing of the data with minimal optimization and user interventions.
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2
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Matsunaga Y, Sugita Y. Linking time-series of single-molecule experiments with molecular dynamics simulations by machine learning. eLife 2018; 7:32668. [PMID: 29723137 PMCID: PMC5933924 DOI: 10.7554/elife.32668] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2017] [Accepted: 04/23/2018] [Indexed: 12/27/2022] Open
Abstract
Single-molecule experiments and molecular dynamics (MD) simulations are indispensable tools for investigating protein conformational dynamics. The former provide time-series data, such as donor-acceptor distances, whereas the latter give atomistic information, although this information is often biased by model parameters. Here, we devise a machine-learning method to combine the complementary information from the two approaches and construct a consistent model of conformational dynamics. It is applied to the folding dynamics of the formin-binding protein WW domain. MD simulations over 400 μs led to an initial Markov state model (MSM), which was then "refined" using single-molecule Förster resonance energy transfer (FRET) data through hidden Markov modeling. The refined or data-assimilated MSM reproduces the FRET data and features hairpin one in the transition-state ensemble, consistent with mutation experiments. The folding pathway in the data-assimilated MSM suggests interplay between hydrophobic contacts and turn formation. Our method provides a general framework for investigating conformational transitions in other proteins.
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Affiliation(s)
- Yasuhiro Matsunaga
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Japan.,JST PRESTO, Kawaguchi, Japan
| | - Yuji Sugita
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Japan.,Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Japan.,Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
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3
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Chung HS, Eaton WA. Protein folding transition path times from single molecule FRET. Curr Opin Struct Biol 2017; 48:30-39. [PMID: 29080467 DOI: 10.1016/j.sbi.2017.10.007] [Citation(s) in RCA: 84] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2017] [Revised: 10/03/2017] [Accepted: 10/05/2017] [Indexed: 11/28/2022]
Abstract
The transition path is the tiny segment of a single molecule trajectory when the free energy barrier between states is crossed and for protein folding contains all of the information about the self-assembly mechanism. As a first step toward obtaining structural information during the transition path from experiments, single molecule FRET spectroscopy has been used to determine average transition path times from a photon-by-photon analysis of fluorescence trajectories. These results, obtained for several different proteins, have already provided new and demanding tests that support both the accuracy of all-atom molecular dynamics simulations and the basic postulates of energy landscape theory of protein folding.
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Affiliation(s)
- Hoi Sung Chung
- Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892-0520, United States.
| | - William A Eaton
- Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892-0520, United States.
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4
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Mori T, Saito S. Molecular Mechanism Behind the Fast Folding/Unfolding Transitions of Villin Headpiece Subdomain: Hierarchy and Heterogeneity. J Phys Chem B 2016; 120:11683-11691. [DOI: 10.1021/acs.jpcb.6b08066] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Toshifumi Mori
- Institute for Molecular Science, Myodaiji, Okazaki, Aichi 444-8585, Japan
- School of Physical Sciences, The Graduate University for Advanced Studies, Okazaki, Aichi 444-8585, Japan
| | - Shinji Saito
- Institute for Molecular Science, Myodaiji, Okazaki, Aichi 444-8585, Japan
- School of Physical Sciences, The Graduate University for Advanced Studies, Okazaki, Aichi 444-8585, Japan
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5
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Banushkina PV, Krivov SV. Optimal reaction coordinates. WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE 2016. [DOI: 10.1002/wcms.1276] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Polina V. Banushkina
- Astbury Center for Structural Molecular Biology; Faculty of Biological Sciences, University of Leeds; Leeds UK
| | - Sergei V. Krivov
- Astbury Center for Structural Molecular Biology; Faculty of Biological Sciences, University of Leeds; Leeds UK
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6
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Koorehdavoudi H, Bogdan P. A Statistical Physics Characterization of the Complex Systems Dynamics: Quantifying Complexity from Spatio-Temporal Interactions. Sci Rep 2016; 6:27602. [PMID: 27297496 PMCID: PMC4906350 DOI: 10.1038/srep27602] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2016] [Accepted: 05/20/2016] [Indexed: 12/28/2022] Open
Abstract
Biological systems are frequently categorized as complex systems due to their capabilities of generating spatio-temporal structures from apparent random decisions. In spite of research on analyzing biological systems, we lack a quantifiable framework for measuring their complexity. To fill this gap, in this paper, we develop a new paradigm to study a collective group of N agents moving and interacting in a three-dimensional space. Our paradigm helps to identify the spatio-temporal states of the motion of the group and their associated transition probabilities. This framework enables the estimation of the free energy landscape corresponding to the identified states. Based on the energy landscape, we quantify missing information, emergence, self-organization and complexity for a collective motion. We show that the collective motion of the group of agents evolves to reach the most probable state with relatively lowest energy level and lowest missing information compared to other possible states. Our analysis demonstrates that the natural group of animals exhibit a higher degree of emergence, self-organization and complexity over time. Consequently, this algorithm can be integrated into new frameworks to engineer collective motions to achieve certain degrees of emergence, self-organization and complexity.
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Affiliation(s)
- Hana Koorehdavoudi
- Department of Aerospace and Mechanical Engineering, University of Southern California, Los Angeles, CA 90089-1453, USA
| | - Paul Bogdan
- Department of Electrical Engineering, University of Southern California, Los Angeles, CA 90089-2560, USA
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7
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Banushkina PV, Krivov SV. Nonparametric variational optimization of reaction coordinates. J Chem Phys 2015; 143:184108. [DOI: 10.1063/1.4935180] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Polina V. Banushkina
- Astbury Center for Structural Molecular Biology, Faculty of Biological Sciences, University of Leeds, Leeds LS2 9JT, United Kingdom
| | - Sergei V. Krivov
- Astbury Center for Structural Molecular Biology, Faculty of Biological Sciences, University of Leeds, Leeds LS2 9JT, United Kingdom
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8
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Matsunaga Y, Kidera A, Sugita Y. Sequential data assimilation for single-molecule FRET photon-counting data. J Chem Phys 2015; 142:214115. [DOI: 10.1063/1.4921983] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Affiliation(s)
- Yasuhiro Matsunaga
- Advanced Institute for Computational Science, RIKEN, 7-1-26 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
| | - Akinori Kidera
- Graduate School of Medical Life Science, Yokohama City University, 1-7-29 Suehiro-cho, Tsurumi, Yokohama 230-0045, Japan
| | - Yuji Sugita
- Advanced Institute for Computational Science, RIKEN, 7-1-26 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
- Theoretical Molecular Science Laboratory, RIKEN, 2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan
- iTHES, RIKEN, 2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan
- Quantitative Biology Center, RIKEN, International Medical Device Alliance (IMDA) 6F, 1-6-5 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
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9
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Wu H, Noé F. Gaussian Markov transition models of molecular kinetics. J Chem Phys 2015; 142:084104. [DOI: 10.1063/1.4913214] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Affiliation(s)
- Hao Wu
- Department for Mathematics and Computer Science, FU Berlin, Arnimallee 6, 14195 Berlin, Germany
| | - Frank Noé
- Department for Mathematics and Computer Science, FU Berlin, Arnimallee 6, 14195 Berlin, Germany
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10
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Banushkina PV, Krivov SV. Fep1d: A script for the analysis of reaction coordinates. J Comput Chem 2015; 36:878-82. [DOI: 10.1002/jcc.23868] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2014] [Revised: 01/29/2015] [Accepted: 01/30/2015] [Indexed: 01/23/2023]
Affiliation(s)
- Polina V. Banushkina
- Astbury Center for Structural Molecular Biology, Faculty of Biological Sciences; University of Leeds; Leeds LS2 9JT United Kingdom
| | - Sergei V. Krivov
- Astbury Center for Structural Molecular Biology, Faculty of Biological Sciences; University of Leeds; Leeds LS2 9JT United Kingdom
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11
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Cazade PA, Berezovska G, Meuwly M. Coupled protein-ligand dynamics in truncated hemoglobin N from atomistic simulations and transition networks. Biochim Biophys Acta Gen Subj 2014; 1850:996-1005. [PMID: 25224733 DOI: 10.1016/j.bbagen.2014.09.008] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2014] [Revised: 09/01/2014] [Accepted: 09/03/2014] [Indexed: 11/27/2022]
Abstract
BACKGROUND The nature of ligand motion in proteins is difficult to characterize directly using experiment. Specifically, it is unclear to what degree these motions are coupled. METHODS All-atom simulations are used to sample ligand motion in truncated Hemoglobin N. A transition network analysis including ligand- and protein-degrees of freedom is used to analyze the microscopic dynamics. RESULTS Clustering of two different subsets of MD trajectories highlights the importance of a diverse and exhaustive description to define the macrostates for a ligand-migration network. Monte Carlo simulations on the transition matrices from one particular clustering are able to faithfully capture the atomistic simulations. Contrary to clustering by ligand positions only, including a protein degree of freedom yields considerably improved coarse grained dynamics. Analysis with and without imposing detailed balance agree closely which suggests that the underlying atomistic simulations are converged with respect to sampling transitions between neighboring sites. CONCLUSIONS Protein and ligand dynamics are not independent from each other and ligand migration through globular proteins is not passive diffusion. GENERAL SIGNIFICANCE Transition network analysis is a powerful tool to analyze and characterize the microscopic dynamics in complex systems. This article is part of a Special Issue entitled Recent developments of molecular dynamics.
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Affiliation(s)
- Pierre-André Cazade
- Department of Chemistry, University of Basel, Klingelbergstrasse 80 4056 Basel, Switzerland
| | - Ganna Berezovska
- Department of Chemistry, University of Basel, Klingelbergstrasse 80 4056 Basel, Switzerland
| | - Markus Meuwly
- Department of Chemistry, University of Basel, Klingelbergstrasse 80 4056 Basel, Switzerland; Department of Chemistry, Brown University, Providence/RI, USA.
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12
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D'Onofrio DJ, Abel DL. Redundancy of the genetic code enables translational pausing. Front Genet 2014; 5:140. [PMID: 24904640 PMCID: PMC4033003 DOI: 10.3389/fgene.2014.00140] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2014] [Accepted: 04/28/2014] [Indexed: 11/13/2022] Open
Abstract
The codon redundancy (“degeneracy”) found in protein-coding regions of mRNA also prescribes Translational Pausing (TP). When coupled with the appropriate interpreters, multiple meanings and functions are programmed into the same sequence of configurable switch-settings. This additional layer of Ontological Prescriptive Information (PIo) purposely slows or speeds up the translation-decoding process within the ribosome. Variable translation rates help prescribe functional folding of the nascent protein. Redundancy of the codon to amino acid mapping, therefore, is anything but superfluous or degenerate. Redundancy programming allows for simultaneous dual prescriptions of TP and amino acid assignments without cross-talk. This allows both functions to be coincident and realizable. We will demonstrate that the TP schema is a bona fide rule-based code, conforming to logical code-like properties. Second, we will demonstrate that this TP code is programmed into the supposedly degenerate redundancy of the codon table. We will show that algorithmic processes play a dominant role in the realization of this multi-dimensional code.
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Affiliation(s)
- David J D'Onofrio
- Control Systems Modeling and Simulation, General Dynamics Sterling Heights, MI, USA ; Department of Humanities and Science, Math Department, College of Humanities and Science, University of Phoenix Detroit, MI, USA
| | - David L Abel
- Department of ProtoBioCybernetics/ProtoBioSemiotics, The Gene Emergence Project of The Origin of Life Science Foundation, Inc. Greenbelt, MD, USA
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13
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Berezovska G, Prada-Gracia D, Rao F. Consensus for the Fip35 folding mechanism? J Chem Phys 2014; 139:035102. [PMID: 23883056 DOI: 10.1063/1.4812837] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
Abstract
Recent advances in computational power and simulation programs finally delivered the first examples of reversible folding for small proteins with an all-atom description. But having at hand the atomistic details of the process did not lead to a straightforward interpretation of the mechanism. For the case of the Fip35 WW-domain where multiple long trajectories of 100 μs are available from D. E. Shaw Research, different interpretations emerged. Some of those are in clear contradiction with each other while others are in qualitative agreement. Here, we present a network-based analysis of the same data by looking at the local fluctuations of conventional order parameters for folding. We found that folding occurs through two major pathways, one almost four times more populated than the other. Each pathway involves the formation of an intermediate with one of the two hairpins in a native configuration. The quantitative agreement of our results with a state-of-the-art reaction coordinate optimization procedure as well as qualitative agreement with other Markov-state-models and different simulation schemes provides strong evidence for a multiple folding pathways scenario with the presence of intermediates.
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Affiliation(s)
- Ganna Berezovska
- Freiburg Institute for Advanced Studies, School of Soft Matter Research, Freiburg im Breisgau, Germany
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14
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Pochorovski I, Knehans T, Nettels D, Müller AM, Schweizer WB, Caflisch A, Schuler B, Diederich F. Experimental and computational study of BODIPY dye-labeled cavitand dynamics. J Am Chem Soc 2014; 136:2441-9. [PMID: 24490940 DOI: 10.1021/ja4104292] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Understanding the distance distribution and dynamics between moieties attached to the walls of a resorcin[4]arene cavitand, which is switchable between an expanded kite and a contracted vase form, might enable the use of this molecular system for the study of fundamental distance-dependent interactions. Toward this goal, a combined experimental and molecular dynamics (MD) simulation study on donor/acceptor borondipyrromethene (BODIPY) dye-labeled cavitands present in the vase and kite forms was performed. Direct comparison between anisotropy decays calculated from MD simulations with experimental fluorescence anisotropy data showed excellent agreement, indicating that the simulations provide an accurate representation of the dynamics of the system. Distance distributions between the BODIPY dyes were established by comparing time-resolved Förster resonance energy transfer experiments and MD simulations. Fluorescence intensity decay curves emulated on the basis of the MD trajectories showed good agreement with the experimental data, suggesting that the simulations present an accurate picture of the distance distributions and dynamics in this molecular system and provide an important tool for understanding the behavior of extended molecular systems and designing future applications.
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Affiliation(s)
- Igor Pochorovski
- Laboratorium für Organische Chemie, ETH Zürich , Hönggerberg, HCI, 8093 Zürich, Switzerland
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15
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Brucale M, Schuler B, Samorì B. Single-molecule studies of intrinsically disordered proteins. Chem Rev 2014; 114:3281-317. [PMID: 24432838 DOI: 10.1021/cr400297g] [Citation(s) in RCA: 112] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Affiliation(s)
- Marco Brucale
- Institute for the Study of Nanostructured Materials (ISMN), Italian National Council of Research (CNR) , Area della Ricerca Roma1, Via Salaria km 29.3 00015 Monterotondo (Rome), Italy
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16
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Georgoulia PS, Glykos NM. On the foldability of tryptophan-containing tetra- and pentapeptides: an exhaustive molecular dynamics study. J Phys Chem B 2013; 117:5522-32. [PMID: 23597287 DOI: 10.1021/jp401239v] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Short peptides serve as minimal model systems to decipher the determinants of foldability due to their simplicity arising from their smaller size, their ability to echo protein-like structural characteristics, and their direct implication in force field validation. Here, we describe an effort to identify small peptides that can still form stable structures in aqueous solutions. We followed the in silico folding of a selected set of 8640 tryptophan-containing tetra- and pentapeptides through 15 210 molecular dynamics simulations amounting to a total of 272.46 μs using explicit representation of the solute and full treatment of the electrostatics. The evaluation and sorting of peptides is achieved through scoring functions, which include terms based on interatomic vector distances, atomic fluctuations, and rmsd matrices between successive frames of a trajectory. Highly scored peptides are studied further via successive simulation rounds of increasing simulation length and using different empirical force fields. Our method suggested only a handful of peptides with strong foldability prognosis. The discrepancies between the predictions of the various force fields for such short sequences are also extensively discussed. We conclude that the vast majority of such short peptides do not adopt significantly stable structures in water solutions, at least based on our computational predictions. The present work can be utilized in the rational design and engineering of bioactive peptides with desired molecular properties.
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Affiliation(s)
- Panagiota S Georgoulia
- Department of Molecular Biology and Genetics, Democritus University of Thrace, Alexandroupolis, Greece
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17
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Berezovska G, Prada-Gracia D, Mostarda S, Rao F. Accounting for the kinetics in order parameter analysis: lessons from theoretical models and a disordered peptide. J Chem Phys 2013. [PMID: 23181288 DOI: 10.1063/1.4764868] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Molecular simulations as well as single molecule experiments have been widely analyzed in terms of order parameters, the latter representing candidate probes for the relevant degrees of freedom. Notwithstanding this approach is very intuitive, mounting evidence showed that such descriptions are inaccurate, leading to ambiguous definitions of states and wrong kinetics. To overcome these limitations a framework making use of order parameter fluctuations in conjunction with complex network analysis is investigated. Derived from recent advances in the analysis of single molecule time traces, this approach takes into account the fluctuations around each time point to distinguish between states that have similar values of the order parameter but different dynamics. Snapshots with similar fluctuations are used as nodes of a transition network, the clusterization of which into states provides accurate Markov-state-models of the system under study. Application of the methodology to theoretical models with a noisy order parameter as well as the dynamics of a disordered peptide illustrates the possibility to build accurate descriptions of molecular processes on the sole basis of order parameter time series without using any supplementary information.
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Affiliation(s)
- Ganna Berezovska
- Freiburg Institute for Advanced Studies, School of Soft Matter Research, Freiburg im Breisgau, Germany
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18
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Schuler B, Hofmann H. Single-molecule spectroscopy of protein folding dynamics—expanding scope and timescales. Curr Opin Struct Biol 2013; 23:36-47. [DOI: 10.1016/j.sbi.2012.10.008] [Citation(s) in RCA: 185] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2012] [Accepted: 10/29/2012] [Indexed: 10/27/2022]
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19
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Terentyeva TG, Hofkens J, Komatsuzaki T, Blank K, Li CB. Time-Resolved Single Molecule Fluorescence Spectroscopy of an α-Chymotrypsin Catalyzed Reaction. J Phys Chem B 2013; 117:1252-60. [DOI: 10.1021/jp310663v] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Tatyana G. Terentyeva
- Photochemistry & Spectroscopy, Department of Chemistry, Katholieke Universiteit Leuven, Leuven, Belgium
| | - Johan Hofkens
- Photochemistry & Spectroscopy, Department of Chemistry, Katholieke Universiteit Leuven, Leuven, Belgium
| | - Tamiki Komatsuzaki
- Molecule & Life Nonlinear Sciences, Research Institute for Electronic Science (RIES), Hokkaido University, Sapporo, Japan
| | - Kerstin Blank
- Institute for Molecules and Materials, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Chun-Biu Li
- Molecule & Life Nonlinear Sciences, Research Institute for Electronic Science (RIES), Hokkaido University, Sapporo, Japan
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20
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Prada-Gracia D, Shevchuk R, Hamm P, Rao F. Towards a microscopic description of the free-energy landscape of water. J Chem Phys 2012; 137:144504. [DOI: 10.1063/1.4755746] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023] Open
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21
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Kamagata K, Kawaguchi T, Iwahashi Y, Baba A, Fujimoto K, Komatsuzaki T, Sambongi Y, Goto Y, Takahashi S. Long-Term Observation of Fluorescence of Free Single Molecules To Explore Protein-Folding Energy Landscapes. J Am Chem Soc 2012; 134:11525-32. [DOI: 10.1021/ja3020555] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Affiliation(s)
- Kiyoto Kamagata
- Institute
of Multidisciplinary Research for Advanced Materials, Tohoku University, Katahira 2-1-1, Aoba-ku, Sendai
980-8577, Japan
| | - Toshifumi Kawaguchi
- Institute
of Multidisciplinary Research for Advanced Materials, Tohoku University, Katahira 2-1-1, Aoba-ku, Sendai
980-8577, Japan
| | - Yoshitomo Iwahashi
- Optonica Corporation, 1-26-11, Matsuigaoka, Kyotanabe,
Kyoto 610-0353, Japan
| | - Akinori Baba
- RIKEN Center for Developmental Biology, 2-2-3 Minatojima-minamimachi,
Chuo-ku, Kobe 650-0047, Japan
| | - Kazuya Fujimoto
- Institute for Protein Research, Osaka University, 3-2, Yamadaoka, Suita, Osaka 565-0871, Japan
| | - Tamiki Komatsuzaki
- Molecule & Life Nonlinear Sciences Laboratory, Research Institute for Electronic Science, Hokkaido University, Kita 20 Nishi 10, Kita-ku, Sapporo 001-0020, Japan
- Core Research for Evolutional Science and
Technology, Japan Science and Technology Agency, 4-1-8, Honmachi, Kawaguchi, Saitama 332-0012, Japan
| | - Yoshihiro Sambongi
- Core Research for Evolutional Science and
Technology, Japan Science and Technology Agency, 4-1-8, Honmachi, Kawaguchi, Saitama 332-0012, Japan
- Graduate School of Biosphere Science, Hiroshima University, 1-4-4, Kagamiyama, Higashi-Hiroshima,
Hiroshima 739-8528, Japan
| | - Yuji Goto
- Institute for Protein Research, Osaka University, 3-2, Yamadaoka, Suita, Osaka 565-0871, Japan
| | - Satoshi Takahashi
- Institute
of Multidisciplinary Research for Advanced Materials, Tohoku University, Katahira 2-1-1, Aoba-ku, Sendai
980-8577, Japan
- Core Research for Evolutional Science and
Technology, Japan Science and Technology Agency, 4-1-8, Honmachi, Kawaguchi, Saitama 332-0012, Japan
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22
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Affiliation(s)
- Riccardo Scalco
- Department of Biochemistry, University of Zurich, Winterthurerstrasse
190, CH-8057 Zurich, Switzerland
| | - Amedeo Caflisch
- Department of Biochemistry, University of Zurich, Winterthurerstrasse
190, CH-8057 Zurich, Switzerland
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23
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Understanding biomolecular motion, recognition, and allostery by use of conformational ensembles. EUROPEAN BIOPHYSICS JOURNAL: EBJ 2011; 40:1339-55. [PMID: 22089251 PMCID: PMC3222826 DOI: 10.1007/s00249-011-0754-8] [Citation(s) in RCA: 82] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/24/2011] [Revised: 09/06/2011] [Accepted: 09/14/2011] [Indexed: 10/31/2022]
Abstract
We review the role conformational ensembles can play in the analysis of biomolecular dynamics, molecular recognition, and allostery. We introduce currently available methods for generating ensembles of biomolecules and illustrate their application with relevant examples from the literature. We show how, for binding, conformational ensembles provide a way of distinguishing the competing models of induced fit and conformational selection. For allostery we review the classic models and show how conformational ensembles can play a role in unravelling the intricate pathways of communication that enable allostery to occur. Finally, we discuss the limitations of conformational ensembles and highlight some potential applications for the future.
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Krivov SV. The Free Energy Landscape Analysis of Protein (FIP35) Folding Dynamics. J Phys Chem B 2011; 115:12315-24. [DOI: 10.1021/jp208585r] [Citation(s) in RCA: 49] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Sergei V. Krivov
- Institute of Molecular and Cellular Biology, Leeds University, Leeds, United Kingdom
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Hoefling M, Lima N, Haenni D, Seidel CAM, Schuler B, Grubmüller H. Structural heterogeneity and quantitative FRET efficiency distributions of polyprolines through a hybrid atomistic simulation and Monte Carlo approach. PLoS One 2011; 6:e19791. [PMID: 21629703 PMCID: PMC3101224 DOI: 10.1371/journal.pone.0019791] [Citation(s) in RCA: 101] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2011] [Accepted: 04/05/2011] [Indexed: 11/21/2022] Open
Abstract
Förster Resonance Energy Transfer (FRET) experiments probe molecular distances via distance dependent energy transfer from an excited donor dye to an acceptor dye. Single molecule experiments not only probe average distances, but also distance distributions or even fluctuations, and thus provide a powerful tool to study biomolecular structure and dynamics. However, the measured energy transfer efficiency depends not only on the distance between the dyes, but also on their mutual orientation, which is typically inaccessible to experiments. Thus, assumptions on the orientation distributions and averages are usually made, limiting the accuracy of the distance distributions extracted from FRET experiments. Here, we demonstrate that by combining single molecule FRET experiments with the mutual dye orientation statistics obtained from Molecular Dynamics (MD) simulations, improved estimates of distances and distributions are obtained. From the simulated time-dependent mutual orientations, FRET efficiencies are calculated and the full statistics of individual photon absorption, energy transfer, and photon emission events is obtained from subsequent Monte Carlo (MC) simulations of the FRET kinetics. All recorded emission events are collected to bursts from which efficiency distributions are calculated in close resemblance to the actual FRET experiment, taking shot noise fully into account. Using polyproline chains with attached Alexa 488 and Alexa 594 dyes as a test system, we demonstrate the feasibility of this approach by direct comparison to experimental data. We identified cis-isomers and different static local environments as sources of the experimentally observed heterogeneity. Reconstructions of distance distributions from experimental data at different levels of theory demonstrate how the respective underlying assumptions and approximations affect the obtained accuracy. Our results show that dye fluctuations obtained from MD simulations, combined with MC single photon kinetics, provide a versatile tool to improve the accuracy of distance distributions that can be extracted from measured single molecule FRET efficiencies.
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Affiliation(s)
- Martin Hoefling
- Theoretical and Computational Biophysics Department, Max Planck Institute for Biophysical Chemistry, Göttingen, Germany
| | - Nicola Lima
- Theoretical and Computational Biophysics Department, Max Planck Institute for Biophysical Chemistry, Göttingen, Germany
| | - Dominik Haenni
- Department of Biochemistry, University of Zurich, Zurich, Switzerland
| | - Claus A. M. Seidel
- Institute of Molecular Physical Chemistry (MPC), Heinrich Heine University, Düsseldorf, Germany
| | - Benjamin Schuler
- Department of Biochemistry, University of Zurich, Zurich, Switzerland
| | - Helmut Grubmüller
- Theoretical and Computational Biophysics Department, Max Planck Institute for Biophysical Chemistry, Göttingen, Germany
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Huang D, Caflisch A. The free energy landscape of small molecule unbinding. PLoS Comput Biol 2011; 7:e1002002. [PMID: 21390201 PMCID: PMC3033371 DOI: 10.1371/journal.pcbi.1002002] [Citation(s) in RCA: 87] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2010] [Accepted: 11/18/2010] [Indexed: 11/18/2022] Open
Abstract
The spontaneous dissociation of six small ligands from the active site of FKBP (the FK506 binding protein) is investigated by explicit water molecular dynamics simulations and network analysis. The ligands have between four (dimethylsulphoxide) and eleven (5-diethylamino-2-pentanone) non-hydrogen atoms, and an affinity for FKBP ranging from 20 to 0.2 mM. The conformations of the FKBP/ligand complex saved along multiple trajectories (50 runs at 310 K for each ligand) are grouped according to a set of intermolecular distances into nodes of a network, and the direct transitions between them are the links. The network analysis reveals that the bound state consists of several subbasins, i.e., binding modes characterized by distinct intermolecular hydrogen bonds and hydrophobic contacts. The dissociation kinetics show a simple (i.e., single-exponential) time dependence because the unbinding barrier is much higher than the barriers between subbasins in the bound state. The unbinding transition state is made up of heterogeneous positions and orientations of the ligand in the FKBP active site, which correspond to multiple pathways of dissociation. For the six small ligands of FKBP, the weaker the binding affinity the closer to the bound state (along the intermolecular distance) are the transition state structures, which is a new manifestation of Hammond behavior. Experimental approaches to the study of fragment binding to proteins have limitations in temporal and spatial resolution. Our network analysis of the unbinding simulations of small inhibitors from an enzyme paints a clear picture of the free energy landscape (both thermodynamics and kinetics) of ligand unbinding.
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Affiliation(s)
- Danzhi Huang
- Department of Biochemistry, University of Zürich, Zürich,
Switzerland
| | - Amedeo Caflisch
- Department of Biochemistry, University of Zürich, Zürich,
Switzerland
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