1
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Krämer A, Durumeric AEP, Charron NE, Chen Y, Clementi C, Noé F. Statistically Optimal Force Aggregation for Coarse-Graining Molecular Dynamics. J Phys Chem Lett 2023; 14:3970-3979. [PMID: 37079800 DOI: 10.1021/acs.jpclett.3c00444] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Machine-learned coarse-grained (CG) models have the potential for simulating large molecular complexes beyond what is possible with atomistic molecular dynamics. However, training accurate CG models remains a challenge. A widely used methodology for learning bottom-up CG force fields maps forces from all-atom molecular dynamics to the CG representation and matches them with a CG force field on average. We show that there is flexibility in how to map all-atom forces to the CG representation and that the most commonly used mapping methods are statistically inefficient and potentially even incorrect in the presence of constraints in the all-atom simulation. We define an optimization statement for force mappings and demonstrate that substantially improved CG force fields can be learned from the same simulation data when using optimized force maps. The method is demonstrated on the miniproteins chignolin and tryptophan cage and published as open-source code.
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Affiliation(s)
- Andreas Krämer
- Department of Mathematics and Computer Science, Freie Universität Berlin, Arnimallee 12, 14195 Berlin, Germany
| | - Aleksander E P Durumeric
- Department of Mathematics and Computer Science, Freie Universität Berlin, Arnimallee 12, 14195 Berlin, Germany
| | - Nicholas E Charron
- Department of Physics and Astronomy, Rice University, Houston, Texas 77005, United States
- Center for Theoretical Biological Physics, Rice University, Houston, Texas 77251, United States
- Department of Physics, Freie Universität Berlin, Arnimallee 12, 14195 Berlin, Germany
| | - Yaoyi Chen
- Department of Mathematics and Computer Science, Freie Universität Berlin, Arnimallee 12, 14195 Berlin, Germany
- International Max Planck Research School for Biology and Computation (IMPRS-BAC), Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany
| | - Cecilia Clementi
- Department of Physics and Astronomy, Rice University, Houston, Texas 77005, United States
- Center for Theoretical Biological Physics, Rice University, Houston, Texas 77251, United States
- Department of Physics, Freie Universität Berlin, Arnimallee 12, 14195 Berlin, Germany
- Department of Chemistry, Rice University, Houston, Texas 77005, United States
| | - Frank Noé
- Department of Mathematics and Computer Science, Freie Universität Berlin, Arnimallee 12, 14195 Berlin, Germany
- Department of Physics, Freie Universität Berlin, Arnimallee 12, 14195 Berlin, Germany
- Department of Chemistry, Rice University, Houston, Texas 77005, United States
- Microsoft Research AI4Science, Karl-Liebknecht Straße 32, 10178 Berlin, Germany
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2
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Jin J, Pak AJ, Durumeric AEP, Loose TD, Voth GA. Bottom-up Coarse-Graining: Principles and Perspectives. J Chem Theory Comput 2022; 18:5759-5791. [PMID: 36070494 PMCID: PMC9558379 DOI: 10.1021/acs.jctc.2c00643] [Citation(s) in RCA: 80] [Impact Index Per Article: 40.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Indexed: 01/14/2023]
Abstract
Large-scale computational molecular models provide scientists a means to investigate the effect of microscopic details on emergent mesoscopic behavior. Elucidating the relationship between variations on the molecular scale and macroscopic observable properties facilitates an understanding of the molecular interactions driving the properties of real world materials and complex systems (e.g., those found in biology, chemistry, and materials science). As a result, discovering an explicit, systematic connection between microscopic nature and emergent mesoscopic behavior is a fundamental goal for this type of investigation. The molecular forces critical to driving the behavior of complex heterogeneous systems are often unclear. More problematically, simulations of representative model systems are often prohibitively expensive from both spatial and temporal perspectives, impeding straightforward investigations over possible hypotheses characterizing molecular behavior. While the reduction in resolution of a study, such as moving from an atomistic simulation to that of the resolution of large coarse-grained (CG) groups of atoms, can partially ameliorate the cost of individual simulations, the relationship between the proposed microscopic details and this intermediate resolution is nontrivial and presents new obstacles to study. Small portions of these complex systems can be realistically simulated. Alone, these smaller simulations likely do not provide insight into collectively emergent behavior. However, by proposing that the driving forces in both smaller and larger systems (containing many related copies of the smaller system) have an explicit connection, systematic bottom-up CG techniques can be used to transfer CG hypotheses discovered using a smaller scale system to a larger system of primary interest. The proposed connection between different CG systems is prescribed by (i) the CG representation (mapping) and (ii) the functional form and parameters used to represent the CG energetics, which approximate potentials of mean force (PMFs). As a result, the design of CG methods that facilitate a variety of physically relevant representations, approximations, and force fields is critical to moving the frontier of systematic CG forward. Crucially, the proposed connection between the system used for parametrization and the system of interest is orthogonal to the optimization used to approximate the potential of mean force present in all systematic CG methods. The empirical efficacy of machine learning techniques on a variety of tasks provides strong motivation to consider these approaches for approximating the PMF and analyzing these approximations.
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Affiliation(s)
- Jaehyeok Jin
- Department of Chemistry,
Chicago Center for Theoretical Chemistry, Institute for Biophysical
Dynamics, and James Franck Institute, The
University of Chicago, Chicago, Illinois 60637, United States
| | - Alexander J. Pak
- Department of Chemistry,
Chicago Center for Theoretical Chemistry, Institute for Biophysical
Dynamics, and James Franck Institute, The
University of Chicago, Chicago, Illinois 60637, United States
| | - Aleksander E. P. Durumeric
- Department of Chemistry,
Chicago Center for Theoretical Chemistry, Institute for Biophysical
Dynamics, and James Franck Institute, The
University of Chicago, Chicago, Illinois 60637, United States
| | - Timothy D. Loose
- Department of Chemistry,
Chicago Center for Theoretical Chemistry, Institute for Biophysical
Dynamics, and James Franck Institute, The
University of Chicago, Chicago, Illinois 60637, United States
| | - Gregory A. Voth
- Department of Chemistry,
Chicago Center for Theoretical Chemistry, Institute for Biophysical
Dynamics, and James Franck Institute, The
University of Chicago, Chicago, Illinois 60637, United States
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3
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Li K, Oiwa NN, Mishra SK, Heermann DW. Inter-nucleosomal potentials from nucleosomal positioning data. THE EUROPEAN PHYSICAL JOURNAL. E, SOFT MATTER 2022; 45:33. [PMID: 35403917 PMCID: PMC9001623 DOI: 10.1140/epje/s10189-022-00185-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Accepted: 03/17/2022] [Indexed: 06/14/2023]
Abstract
No systematic method exists to derive inter-nucleosomal potentials between nucleosomes along a chromosome consistently across a given genome. Such potentials can yield information on nucleosomal ordering, thermal as well as mechanical properties of chromosomes. Thus, indirectly, they shed light on a possible mechanical genomic code along a chromosome. To develop a method yielding effective inter-nucleosomal potentials between nucleosomes, a generalized Lennard-Jones potential for the parameterization is developed based on nucleosomal positioning data. This approach eliminates some of the problems that the underlying nucleosomal positioning data have, rendering the extraction difficult on the individual nucleosomal level. Furthermore, patterns on which to base a classification along a chromosome appear on larger domains, such as hetero- and euchromatin. An intuitive selection strategy for the noisy optimization problem is employed to derive effective exponents for the generalized potential. The method is tested on the Candida albicans genome. Applying k-means clustering based on potential parameters and thermodynamic compressibilities, a genome-wide clustering of nucleosome sequences is obtained for C. albicans. This clustering shows that a chromosome beyond the classical dichotomic categories of hetero- and euchromatin is more feature-rich.
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Affiliation(s)
- Kunhe Li
- Institute for Theoretical Physics, Heidelberg University, Philosophenweg 19, D-69120, Heidelberg, Germany
| | - Nestor Norio Oiwa
- Department of Basic Science, Universidade Federal Fluminense, Rua Doutor Sílvio Henrique Braune 22, Centro, Nova Friburgo, 28625-650, Brazil
| | - Sujeet Kumar Mishra
- Center for Computational Biology and Bioinformatics, School of Computational and Integrative Sciences (SCIS) Jawaharlal Nehru University, New Delhi, India
| | - Dieter W Heermann
- Institute for Theoretical Physics, Heidelberg University, Philosophenweg 19, D-69120, Heidelberg, Germany.
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4
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Rudzinski JF, Kloth S, Wörner S, Pal T, Kremer K, Bereau T, Vogel M. Dynamical properties across different coarse-grained models for ionic liquids. JOURNAL OF PHYSICS. CONDENSED MATTER : AN INSTITUTE OF PHYSICS JOURNAL 2021; 33:224001. [PMID: 33592598 DOI: 10.1088/1361-648x/abe6e1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Accepted: 02/16/2021] [Indexed: 06/12/2023]
Abstract
Room-temperature ionic liquids (RTILs) stand out among molecular liquids for their rich physicochemical characteristics, including structural and dynamic heterogeneity. The significance of electrostatic interactions in RTILs results in long characteristic length- and timescales, and has motivated the development of a number of coarse-grained (CG) simulation models. In this study, we aim to better understand the connection between certain CG parameterization strategies and the dynamical properties and transferability of the resulting models. We systematically compare five CG models: a model largely parameterized from experimental thermodynamic observables; a refinement of this model to increase its structural accuracy; and three models that reproduce a given set of structural distribution functions by construction, with varying intramolecular parameterizations and reference temperatures. All five CG models display limited structural transferability over temperature, and also result in various effective dynamical speedup factors, relative to a reference atomistic model. On the other hand, the structure-based CG models tend to result in more consistent cation-anion relative diffusion than the thermodynamic-based models, for a single thermodynamic state point. By linking short- and long-timescale dynamical behaviors, we demonstrate that the varying dynamical properties of the different CG models can be largely collapsed onto a single curve, which provides evidence for a route to constructing dynamically-consistent CG models of RTILs.
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Affiliation(s)
| | - Sebastian Kloth
- Institute of Condensed Matter Physics, Technische Universität Darmstadt, Hochschulstr. 6, 64289 Darmstadt, Germany
| | - Svenja Wörner
- Max Planck Institute for Polymer Research, 55128 Mainz, Germany
| | - Tamisra Pal
- Institute of Condensed Matter Physics, Technische Universität Darmstadt, Hochschulstr. 6, 64289 Darmstadt, Germany
| | - Kurt Kremer
- Max Planck Institute for Polymer Research, 55128 Mainz, Germany
| | - Tristan Bereau
- Max Planck Institute for Polymer Research, 55128 Mainz, Germany
- Van 't Hoff Institute for Molecular Sciences and Informatics Institute, University of Amsterdam, Amsterdam 1098 XH, The Netherlands
| | - Michael Vogel
- Institute of Condensed Matter Physics, Technische Universität Darmstadt, Hochschulstr. 6, 64289 Darmstadt, Germany
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5
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Jin J, Han Y, Pak AJ, Voth GA. A new one-site coarse-grained model for water: Bottom-up many-body projected water (BUMPer). I. General theory and model. J Chem Phys 2021; 154:044104. [PMID: 33514116 PMCID: PMC7826168 DOI: 10.1063/5.0026651] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Accepted: 12/14/2020] [Indexed: 12/26/2022] Open
Abstract
Water is undoubtedly one of the most important molecules for a variety of chemical and physical systems, and constructing precise yet effective coarse-grained (CG) water models has been a high priority for computer simulations. To recapitulate important local correlations in the CG water model, explicit higher-order interactions are often included. However, the advantages of coarse-graining may then be offset by the larger computational cost in the model parameterization and simulation execution. To leverage both the computational efficiency of the CG simulation and the inclusion of higher-order interactions, we propose a new statistical mechanical theory that effectively projects many-body interactions onto pairwise basis sets. The many-body projection theory presented in this work shares similar physics from liquid state theory, providing an efficient approach to account for higher-order interactions within the reduced model. We apply this theory to project the widely used Stillinger-Weber three-body interaction onto a pairwise (two-body) interaction for water. Based on the projected interaction with the correct long-range behavior, we denote the new CG water model as the Bottom-Up Many-Body Projected Water (BUMPer) model, where the resultant CG interaction corresponds to a prior model, the iteratively force-matched model. Unlike other pairwise CG models, BUMPer provides high-fidelity recapitulation of pair correlation functions and three-body distributions, as well as N-body correlation functions. BUMPer extensively improves upon the existing bottom-up CG water models by extending the accuracy and applicability of such models while maintaining a reduced computational cost.
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Affiliation(s)
- Jaehyeok Jin
- Department of Chemistry, Chicago Center for Theoretical Chemistry, Institute for Biophysical Dynamics, and James Franck Institute, The University of Chicago, Chicago, Illinois 60637, USA
| | - Yining Han
- Department of Chemistry, Chicago Center for Theoretical Chemistry, Institute for Biophysical Dynamics, and James Franck Institute, The University of Chicago, Chicago, Illinois 60637, USA
| | - Alexander J. Pak
- Department of Chemistry, Chicago Center for Theoretical Chemistry, Institute for Biophysical Dynamics, and James Franck Institute, The University of Chicago, Chicago, Illinois 60637, USA
| | - Gregory A. Voth
- Department of Chemistry, Chicago Center for Theoretical Chemistry, Institute for Biophysical Dynamics, and James Franck Institute, The University of Chicago, Chicago, Illinois 60637, USA
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6
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Rudzinski JF, Bereau T. Coarse-grained conformational surface hopping: Methodology and transferability. J Chem Phys 2020; 153:214110. [DOI: 10.1063/5.0031249] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Affiliation(s)
| | - Tristan Bereau
- Max Planck Institute for Polymer Research, 55128 Mainz, Germany
- Van ’t Hoff Institute for Molecular Sciences and Informatics Institute, University of Amsterdam, Amsterdam 1098 XH, The Netherlands
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7
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Wörner SJ, Bereau T, Kremer K, Rudzinski JF. Direct route to reproducing pair distribution functions with coarse-grained models via transformed atomistic cross correlations. J Chem Phys 2020; 151:244110. [PMID: 31893905 DOI: 10.1063/1.5131105] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Coarse-grained (CG) models are often parameterized to reproduce one-dimensional structural correlation functions of an atomically detailed model along the degrees of freedom governing each interaction potential. While cross correlations between these degrees of freedom inform the optimal set of interaction parameters, the correlations generated from the higher-resolution simulations are often too complex to act as an accurate proxy for the CG correlations. Instead, the most popular methods determine the interaction parameters iteratively while assuming that individual interactions are uncorrelated. While these iterative methods have been validated for a wide range of systems, they also have disadvantages when parameterizing models for multicomponent systems or when refining previously established models to better reproduce particular structural features. In this work, we propose two distinct approaches for the direct (i.e., noniterative) parameterization of a CG model by adjusting the high-resolution cross correlations of an atomistic model in order to more accurately reflect correlations that will be generated by the resulting CG model. The derived models more accurately describe the low-order structural features of the underlying AA model while necessarily generating inherently distinct cross correlations compared with the atomically detailed reference model. We demonstrate the proposed methods for a one-site-per-molecule representation of liquid water, where pairwise interactions are incapable of reproducing the true tetrahedral solvation structure. We then investigate the precise role that distinct cross-correlation features play in determining the correct pair correlation functions, evaluating the importance of the placement of correlation features as well as the balance between features appearing in different solvation shells.
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Affiliation(s)
- Svenja J Wörner
- Max Planck Institute for Polymer Research, 55128 Mainz, Germany
| | - Tristan Bereau
- Max Planck Institute for Polymer Research, 55128 Mainz, Germany
| | - Kurt Kremer
- Max Planck Institute for Polymer Research, 55128 Mainz, Germany
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8
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Patrone PN, Dienstfrey A, McFadden GB. Model reduction of rigid-body molecular dynamics via generalized multipole potentials. Phys Rev E 2019; 100:063302. [PMID: 31962507 PMCID: PMC8020260 DOI: 10.1103/physreve.100.063302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2019] [Indexed: 06/10/2023]
Abstract
Motivated by the challenges of uncertainty quantification for coarse-grained (CG) molecular dynamics, we investigate the role of perturbation theory in model reduction of classical systems. In particular, we consider the task of coarse-graining rigid bodies in the context of generalized multipole potentials that have controllable levels of accuracy relative to their atomistic counterparts. We show how the multipole framework yields a hierarchy of models that systematically connects a CG "point molecule" approximation to the exact dynamics. We use these results to understand when and how the CG models fail to describe atomistic dynamics at the trajectory level and develop asymptotic error estimates for approximate molecular potential energies. Implications for other model-reduction strategies are also discussed. Key findings of this work are that (i) omitting rotational energy introduces significant error when coarse-graining and (ii) attention to symmetry can improve accuracy of "point-molecule" approximations. Analytical derivations and numerical results support these conclusions. Relevance to nonrigid bodies is also discussed.
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Affiliation(s)
- Paul N. Patrone
- National Institute of Standards and Technology, Gaithersburg, Maryland 20899, USA
| | - Andrew Dienstfrey
- National Institute of Standards and Technology, Gaithersburg, Maryland 20899, USA
| | - G. B. McFadden
- National Institute of Standards and Technology, Gaithersburg, Maryland 20899, USA
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9
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Lebold KM, Noid WG. Dual-potential approach for coarse-grained implicit solvent models with accurate, internally consistent energetics and predictive transferability. J Chem Phys 2019; 151:164113. [PMID: 31675902 DOI: 10.1063/1.5125246] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
The dual-potential approach promises coarse-grained (CG) models that accurately reproduce both structural and energetic properties, while simultaneously providing predictive estimates for the temperature-dependence of the effective CG potentials. In this work, we examine the dual-potential approach for implicit solvent CG models that reflect large entropic effects from the eliminated solvent. Specifically, we construct implicit solvent models at various resolutions, R, by retaining a fraction 0.10 ≤ R ≤ 0.95 of the molecules from a simple fluid of Lennard-Jones spheres. We consider the dual-potential approach in both the constant volume and constant pressure ensembles across a relatively wide range of temperatures. We approximate the many-body potential of mean force for the remaining solutes with pair and volume potentials, which we determine via multiscale coarse-graining and self-consistent pressure-matching, respectively. Interestingly, with increasing temperature, the pair potentials appear increasingly attractive, while the volume potentials become increasingly repulsive. The dual-potential approach not only reproduces the atomic energetics but also quite accurately predicts this temperature-dependence. We also derive an exact relationship between the thermodynamic specific heat of an atomic model and the energetic fluctuations that are observable at the CG resolution. With this generalized fluctuation relationship, the approximate CG models quite accurately reproduce the thermodynamic specific heat of the underlying atomic model.
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Affiliation(s)
- Kathryn M Lebold
- Department of Chemistry, Penn State University, University Park, Pennsylvania 16802, USA
| | - W G Noid
- Department of Chemistry, Penn State University, University Park, Pennsylvania 16802, USA
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10
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Dannenhoffer-Lafage T, Wagner JW, Durumeric AEP, Voth GA. Compatible observable decompositions for coarse-grained representations of real molecular systems. J Chem Phys 2019; 151:134115. [PMID: 31594316 DOI: 10.1063/1.5116027] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Coarse-grained (CG) observable expressions, such as pressure or potential energy, are generally different than their fine-grained (FG, e.g., atomistic) counterparts. Recently, we analyzed this so-called "representability problem" in Wagner et al. [J. Chem. Phys. 145, 044108 (2016)]. While the issue of representability was clearly and mathematically stated in that work, it was not made clear how to actually determine CG observable expressions from the underlying FG systems that can only be simulated numerically. In this work, we propose minimization targets for the CG observables of such systems. These CG observables are compatible with each other and with structural observables. Also, these CG observables are systematically improvable since they are variationally minimized. Our methods are local and data efficient because we decompose the observable contributions. Hence, our approaches are called the multiscale compatible observable decomposition (MS-CODE) and the relative entropy compatible observable decomposition (RE-CODE), which reflect two main approaches to the "bottom-up" coarse-graining of real FG systems. The parameterization of these CG observable expressions requires the introduction of new, symmetric basis sets and one-body terms. We apply MS-CODE and RE-CODE to 1-site and 2-site CG models of methanol for the case of pressure, as well as to 1-site methanol and acetonitrile models for potential energy.
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Affiliation(s)
- Thomas Dannenhoffer-Lafage
- Department of Chemistry, James Franck Institute, and Institute for Biophysical Dynamics, University of Chicago, Chicago, Illinois 60637, USA
| | - Jacob W Wagner
- Department of Chemistry, James Franck Institute, and Institute for Biophysical Dynamics, University of Chicago, Chicago, Illinois 60637, USA
| | - Aleksander E P Durumeric
- Department of Chemistry, James Franck Institute, and Institute for Biophysical Dynamics, University of Chicago, Chicago, Illinois 60637, USA
| | - Gregory A Voth
- Department of Chemistry, James Franck Institute, and Institute for Biophysical Dynamics, University of Chicago, Chicago, Illinois 60637, USA
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11
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Sharp ME, Vázquez FX, Wagner JW, Dannenhoffer-Lafage T, Voth GA. Multiconfigurational Coarse-Grained Molecular Dynamics. J Chem Theory Comput 2019; 15:3306-3315. [PMID: 30897328 PMCID: PMC6660024 DOI: 10.1021/acs.jctc.8b01133] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
![]()
Standard low resolution
coarse-grained modeling techniques have difficulty capturing multiple
configurations of protein systems. Here, we present a method for creating
accurate coarse-grained (CG) models with multiple configurations using
a linear combination of functions or “states”. Individual
CG models are created to capture the individual states, and the approximate
coupling between the two states is determined from an all-atom potential
of mean force. We show that the resulting multiconfiguration coarse-graining
(MCCG) method accurately captures the transition state as well as
the free energy between the two states. We have tested this method
on the folding of dodecaalanine, as well as the amphipathic helix
of endophilin.
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Affiliation(s)
- Morris E Sharp
- Department of Chemistry, James Franck Institute, and Institute for Biophysical Dynamics , The University of Chicago , Chicago , Illinois 60637 , United States
| | - Francisco X Vázquez
- Department of Chemistry , St. John's University , Queens , New York 11439 , United States
| | - Jacob W Wagner
- Department of Chemistry, James Franck Institute, and Institute for Biophysical Dynamics , The University of Chicago , Chicago , Illinois 60637 , United States
| | - Thomas Dannenhoffer-Lafage
- Department of Chemistry, James Franck Institute, and Institute for Biophysical Dynamics , The University of Chicago , Chicago , Illinois 60637 , United States
| | - Gregory A Voth
- Department of Chemistry, James Franck Institute, and Institute for Biophysical Dynamics , The University of Chicago , Chicago , Illinois 60637 , United States
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12
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Li Y, Agrawal V, Oswald J. Systematic coarse‐graining of semicrystalline polyethylene. ACTA ACUST UNITED AC 2019. [DOI: 10.1002/polb.24789] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Affiliation(s)
- Yiyang Li
- School for the Engineering of Matter Transport and Energy Arizona State University P.O. Box 876106, Tempe Arizona, 85287‐6106
| | - Vipin Agrawal
- School for the Engineering of Matter Transport and Energy Arizona State University P.O. Box 876106, Tempe Arizona, 85287‐6106
| | - Jay Oswald
- School for the Engineering of Matter Transport and Energy Arizona State University P.O. Box 876106, Tempe Arizona, 85287‐6106
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13
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Wagner JW, Dannenhoffer-Lafage T, Jin J, Voth GA. Extending the range and physical accuracy of coarse-grained models: Order parameter dependent interactions. J Chem Phys 2018; 147:044113. [PMID: 28764380 DOI: 10.1063/1.4995946] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Order parameters (i.e., collective variables) are often used to describe the behavior of systems as they capture different features of the free energy surface. Yet, most coarse-grained (CG) models only employ two- or three-body non-bonded interactions between the CG particles. In situations where these interactions are insufficient for the CG model to reproduce the structural distributions of the underlying fine-grained (FG) model, additional interactions must be included. In this paper, we introduce an approach to expand the basis sets available in the multiscale coarse-graining (MS-CG) methodology by including order parameters. Then, we investigate the ability of an additive local order parameter (e.g., density) and an additive global order parameter (i.e., distance from a hard wall) to improve the description of CG models in interfacial systems. Specifically, we study methanol liquid-vapor coexistence, acetonitrile liquid-vapor coexistence, and acetonitrile liquid confined by hard-wall plates, all using single site CG models. We find that the use of order parameters dramatically improves the reproduction of structural properties of interfacial CG systems relative to the FG reference as compared with pairwise CG interactions alone.
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Affiliation(s)
- Jacob W Wagner
- Department of Chemistry, James Franck Institute, and Institute for Biophysical Dynamics, The University of Chicago, Chicago, Illinois 60637, USA
| | - Thomas Dannenhoffer-Lafage
- Department of Chemistry, James Franck Institute, and Institute for Biophysical Dynamics, The University of Chicago, Chicago, Illinois 60637, USA
| | - Jaehyeok Jin
- Department of Chemistry, James Franck Institute, and Institute for Biophysical Dynamics, The University of Chicago, Chicago, Illinois 60637, USA
| | - Gregory A Voth
- Department of Chemistry, James Franck Institute, and Institute for Biophysical Dynamics, The University of Chicago, Chicago, Illinois 60637, USA
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14
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Dunn NJH, Lebold KM, DeLyser MR, Rudzinski JF, Noid W. BOCS: Bottom-up Open-source Coarse-graining Software. J Phys Chem B 2017; 122:3363-3377. [DOI: 10.1021/acs.jpcb.7b09993] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Affiliation(s)
- Nicholas J. H. Dunn
- Department of Chemistry, The Pennsylvania State University, University Park, Pennsylvania 16802, United States
| | - Kathryn M. Lebold
- Department of Chemistry, The Pennsylvania State University, University Park, Pennsylvania 16802, United States
| | - Michael R. DeLyser
- Department of Chemistry, The Pennsylvania State University, University Park, Pennsylvania 16802, United States
| | - Joseph F. Rudzinski
- Department of Chemistry, The Pennsylvania State University, University Park, Pennsylvania 16802, United States
| | - W.G. Noid
- Department of Chemistry, The Pennsylvania State University, University Park, Pennsylvania 16802, United States
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15
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Parameterization of Coarse-Grained Molecular Interactions through Potential of Mean Force Calculations and Cluster Expansion Techniques. ENTROPY 2017. [DOI: 10.3390/e19080395] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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16
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Chu JW, Yang H. Identifying the structural and kinetic elements in protein large-amplitude conformational motions. INT REV PHYS CHEM 2017. [DOI: 10.1080/0144235x.2017.1283885] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
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17
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Stadlbauer P, Mazzanti L, Cragnolini T, Wales DJ, Derreumaux P, Pasquali S, Šponer J. Coarse-Grained Simulations Complemented by Atomistic Molecular Dynamics Provide New Insights into Folding and Unfolding of Human Telomeric G-Quadruplexes. J Chem Theory Comput 2016; 12:6077-6097. [DOI: 10.1021/acs.jctc.6b00667] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Affiliation(s)
- Petr Stadlbauer
- Institute
of Biophysics, Academy of Sciences of the Czech Republic, Královopolská
135, 612 65 Brno, Czech Republic
- Regional
Centre of Advanced Technologies and Materials, Departments of Physical
Chemistry, Faculty of Science, Palacký University, 17. listopadu
1192/12, 771 46 Olomouc, Czech Republic
| | - Liuba Mazzanti
- Laboratoire
de Biochimie Théorique, IBPC, CNRS UPR9080, Université Sorbonne Paris Cite, Paris Diderot, 13 rue Pierre et Marie Curie, 75005 Paris, France
| | - Tristan Cragnolini
- Department
of Chemistry, Cambridge University, Lensfield Road, Cambridge CB2 1EW, U.K
| | - David J. Wales
- Department
of Chemistry, Cambridge University, Lensfield Road, Cambridge CB2 1EW, U.K
| | - Philippe Derreumaux
- Laboratoire
de Biochimie Théorique, IBPC, CNRS UPR9080, Université Sorbonne Paris Cite, Paris Diderot, 13 rue Pierre et Marie Curie, 75005 Paris, France
| | - Samuela Pasquali
- Laboratoire
de Biochimie Théorique, IBPC, CNRS UPR9080, Université Sorbonne Paris Cite, Paris Diderot, 13 rue Pierre et Marie Curie, 75005 Paris, France
| | - Jiří Šponer
- Institute
of Biophysics, Academy of Sciences of the Czech Republic, Královopolská
135, 612 65 Brno, Czech Republic
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18
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Click TH, Raj N, Chu JW. Calculation of Enzyme Fluctuograms from All-Atom Molecular Dynamics Simulation. Methods Enzymol 2016; 578:327-42. [PMID: 27497173 DOI: 10.1016/bs.mie.2016.05.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/18/2023]
Abstract
In this work, a computational framework is presented to compute the time evolution of force constants for a coarse grained (CG) elastic network model along an all-atom molecular dynamics trajectory of a protein system. Obtained via matching distance fluctuations, these force constants represent strengths of mechanical coupling between CG beads. Variation of coupling strengths with time is hence termed the fluctuogram of protein dynamics. In addition to the schematic procedure and implementation considerations, several ways of combining force constants and data analysis are presented to illustrate the potential application of protein fluctuograms. The unique angle provided by the fluctuogram expands the scope of atomistic simulations and is expected to impact upon fundamental understanding of protein dynamics as well as protein engineering technologies.
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Affiliation(s)
- T H Click
- Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, Taiwan, ROC
| | - N Raj
- Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, Taiwan, ROC
| | - J-W Chu
- Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, Taiwan, ROC; Department of Biological Science and Technology, National Chiao Tung University, Hsinchu, Taiwan, ROC; Institute of Molecular Medicine and Bioengineering, National Chiao Tung University, Hsinchu, Taiwan, ROC.
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19
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Kmiecik S, Gront D, Kolinski M, Wieteska L, Dawid AE, Kolinski A. Coarse-Grained Protein Models and Their Applications. Chem Rev 2016; 116:7898-936. [DOI: 10.1021/acs.chemrev.6b00163] [Citation(s) in RCA: 555] [Impact Index Per Article: 69.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Sebastian Kmiecik
- Faculty
of Chemistry, University of Warsaw, Pasteura 1, 02-093 Warsaw, Poland
| | - Dominik Gront
- Faculty
of Chemistry, University of Warsaw, Pasteura 1, 02-093 Warsaw, Poland
| | - Michal Kolinski
- Bioinformatics
Laboratory, Mossakowski Medical Research Center of the Polish Academy of Sciences, Pawinskiego 5, 02-106 Warsaw, Poland
| | - Lukasz Wieteska
- Faculty
of Chemistry, University of Warsaw, Pasteura 1, 02-093 Warsaw, Poland
- Department
of Medical Biochemistry, Medical University of Lodz, Mazowiecka 6/8, 92-215 Lodz, Poland
| | | | - Andrzej Kolinski
- Faculty
of Chemistry, University of Warsaw, Pasteura 1, 02-093 Warsaw, Poland
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20
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Dunn NJH, Noid WG. Bottom-up coarse-grained models that accurately describe the structure, pressure, and compressibility of molecular liquids. J Chem Phys 2015; 143:243148. [DOI: 10.1063/1.4937383] [Citation(s) in RCA: 76] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Affiliation(s)
- Nicholas J. H. Dunn
- Department of Chemistry, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - W. G. Noid
- Department of Chemistry, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
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21
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Wagner JW, Dama JF, Voth GA. Predicting the Sensitivity of Multiscale Coarse-Grained Models to their Underlying Fine-Grained Model Parameters. J Chem Theory Comput 2015; 11:3547-60. [DOI: 10.1021/acs.jctc.5b00180] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Jacob W. Wagner
- Department of Chemistry,
James Franck Institute, Institute for Biophysical Dynamics, and Computation
Institute, University of Chicago, 5735 South Ellis Avenue, Chicago, Illinois 60637, United States
| | - James F. Dama
- Department of Chemistry,
James Franck Institute, Institute for Biophysical Dynamics, and Computation
Institute, University of Chicago, 5735 South Ellis Avenue, Chicago, Illinois 60637, United States
| | - Gregory A. Voth
- Department of Chemistry,
James Franck Institute, Institute for Biophysical Dynamics, and Computation
Institute, University of Chicago, 5735 South Ellis Avenue, Chicago, Illinois 60637, United States
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22
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Rudzinski JF, Noid WG. Bottom-Up Coarse-Graining of Peptide Ensembles and Helix–Coil Transitions. J Chem Theory Comput 2015; 11:1278-91. [DOI: 10.1021/ct5009922] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Joseph F. Rudzinski
- Department
of Chemistry, The Pennsylvania State University, University Park, Pennsylvania 16802, United States
| | - William G. Noid
- Department
of Chemistry, The Pennsylvania State University, University Park, Pennsylvania 16802, United States
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23
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Persson RAX, Voulgarakis NK, Chu JW. Dynamic mesoscale model of dipolar fluids via fluctuating hydrodynamics. J Chem Phys 2014; 141:174105. [DOI: 10.1063/1.4900498] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Affiliation(s)
- Rasmus A. X. Persson
- Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu 30068, Taiwan
- Department of Biological Science and Technology, National Chiao Tung University, Hsinchu 30068, Taiwan
| | | | - Jhih-Wei Chu
- Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu 30068, Taiwan
- Department of Biological Science and Technology, National Chiao Tung University, Hsinchu 30068, Taiwan
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24
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Rudzinski JF, Noid WG. Investigation of coarse-grained mappings via an iterative generalized Yvon-Born-Green method. J Phys Chem B 2014; 118:8295-312. [PMID: 24684663 DOI: 10.1021/jp501694z] [Citation(s) in RCA: 45] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Low resolution coarse-grained (CG) models enable highly efficient simulations of complex systems. The interactions in CG models are often iteratively refined over multiple simulations until they reproduce the one-dimensional (1-D) distribution functions, e.g., radial distribution functions (rdfs), of an all-atom (AA) model. In contrast, the multiscale coarse-graining (MS-CG) method employs a generalized Yvon-Born-Green (g-YBG) relation to determine CG potentials directly (i.e., without iteration) from the correlations observed for the AA model. However, MS-CG models do not necessarily reproduce the 1-D distribution functions of the AA model. Consequently, recent studies have incorporated the g-YBG equation into iterative methods for more accurately reproducing AA rdfs. In this work, we consider a theoretical framework for an iterative g-YBG method. We numerically demonstrate that the method robustly determines accurate models for both hexane and also a more complex molecule, 3-hexylthiophene. By examining the MS-CG and iterative g-YBG models for several distinct CG representations of both molecules, we investigate the approximations of the MS-CG method and their sensitivity to the CG mapping. More generally, we explicitly demonstrate that CG models often reproduce 1-D distribution functions of AA models at the expense of distorting the cross-correlations between the corresponding degrees of freedom. In particular, CG models that accurately reproduce intramolecular 1-D distribution functions may still provide a poor description of the molecular conformations sampled by the AA model. We demonstrate a simple and predictive analysis for determining CG mappings that promote an accurate description of these molecular conformations.
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Affiliation(s)
- Joseph F Rudzinski
- Department of Chemistry, The Pennsylvania State University , University Park, Pennsylvania 16802, United States
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25
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Lu L, Dama JF, Voth GA. Fitting coarse-grained distribution functions through an iterative force-matching method. J Chem Phys 2014; 139:121906. [PMID: 24089718 DOI: 10.1063/1.4811667] [Citation(s) in RCA: 55] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023] Open
Abstract
An iterative coarse-graining method is developed for systematically converting an atomistic force field to a model at lower resolution that is able to accurately reproduce the distribution functions defined in the coarse-grained potential. The method starts from the multiscale coarse-graining (MS-CG) approach, and it iteratively refines the distribution functions using repeated applications of the MS-CG algorithm. It is justified on the basis of the force matching normal equation, which can be considered a discrete form of the Yvon-Born-Green equation in liquid state theory. Numerical results for molecular systems involving pairwise nonbonded and three-body bonded interactions are obtained, and comparison with other approaches in literature is provided.
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Affiliation(s)
- Lanyuan Lu
- Department of Chemistry, James Franck Institute, Institute for Biophysical Dynamics, and Computation Institute, University of Chicago, 5735 S. Ellis Ave., Chicago, Illinois 60637, USA
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26
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Abstract
By focusing on essential features, while averaging over less important details, coarse-grained (CG) models provide significant computational and conceptual advantages with respect to more detailed models. Consequently, despite dramatic advances in computational methodologies and resources, CG models enjoy surging popularity and are becoming increasingly equal partners to atomically detailed models. This perspective surveys the rapidly developing landscape of CG models for biomolecular systems. In particular, this review seeks to provide a balanced, coherent, and unified presentation of several distinct approaches for developing CG models, including top-down, network-based, native-centric, knowledge-based, and bottom-up modeling strategies. The review summarizes their basic philosophies, theoretical foundations, typical applications, and recent developments. Additionally, the review identifies fundamental inter-relationships among the diverse approaches and discusses outstanding challenges in the field. When carefully applied and assessed, current CG models provide highly efficient means for investigating the biological consequences of basic physicochemical principles. Moreover, rigorous bottom-up approaches hold great promise for further improving the accuracy and scope of CG models for biomolecular systems.
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Affiliation(s)
- W G Noid
- Department of Chemistry, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
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27
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da Silva JAB, Moreira FGB, dos Santos VML, Longo RL. Topological analyses and small-world patterns of hydrogen bond networks in water + t-butanol, water + n-butanol and water + ammonia mixtures. Phys Chem Chem Phys 2014; 16:19479-91. [DOI: 10.1039/c4cp02130d] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
H-bond networks in aqueous mixtures obtained by Monte Carlo simulations and analyzed by statistical mechanics based tools revealed small-word patterns.
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Affiliation(s)
- Juliana Angeiras Batista da Silva
- Núcleo de Formação Docente
- Centro Acadêmico do Agreste
- Universidade Federal de Pernambuco
- Caruaru, Brazil
- Departamento de Química Fundamental
| | | | | | - Ricardo Luiz Longo
- Departamento de Química Fundamental
- Universidade Federal de Pernambuco
- Recife, Brazil
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28
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Abstract
This chapter provides a primer on theories for coarse-grained (CG) modeling and, in particular, reviews several systematic methods for determining effective potentials for CG models. The chapter first reviews a statistical mechanics framework for relating atomistic and CG models. This framework naturally leads to a quantitative criterion for CG models that are "consistent" with a particular atomistic model for the same system. This consistency criterion is equivalent to minimizing the relative entropy between the two models. This criterion implies that a many-body PMF is the appropriate potential for a CG model that is consistent with a particular atomistic model. This chapter then presents a unified exposition of the theory and numerical methods for several approaches for approximating this many-body PMF. Finally, this chapter closes with a brief discussion of a few of the outstanding challenges facing the field of systematic coarse-graining.
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Affiliation(s)
- W G Noid
- Department of Chemistry, The Pennsylvania State University, University Park, PA, USA
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29
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Chang R, Gross AS, Chu JW. Degree of Polymerization of Glucan Chains Shapes the Structure Fluctuations and Melting Thermodynamics of a Cellulose Microfibril. J Phys Chem B 2012; 116:8074-83. [DOI: 10.1021/jp302974x] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Affiliation(s)
- Rakwoo Chang
- Department of Chemistry, Kwangwoon University, Seoul 139-701, Republic of Korea
| | - Adam S. Gross
- Department of Chemical and Biomolecular
Engineering and Energy Biosciences Institute, University of California, Berkeley, 94720, United States
| | - Jhih-Wei Chu
- Department of Chemical and Biomolecular
Engineering and Energy Biosciences Institute, University of California, Berkeley, 94720, United States
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30
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Rudzinski JF, Noid WG. The Role of Many-Body Correlations in Determining Potentials for Coarse-Grained Models of Equilibrium Structure. J Phys Chem B 2012; 116:8621-35. [DOI: 10.1021/jp3002004] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Joseph F. Rudzinski
- Department of Chemistry, The Pennsylvania State University, University Park, Pennsylvania 16802,
United States
| | - William G. Noid
- Department of Chemistry, The Pennsylvania State University, University Park, Pennsylvania 16802,
United States
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31
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32
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Cho HM, Gross AS, Chu JW. Dissecting Force Interactions in Cellulose Deconstruction Reveals the Required Solvent Versatility for Overcoming Biomass Recalcitrance. J Am Chem Soc 2011; 133:14033-41. [DOI: 10.1021/ja2046155] [Citation(s) in RCA: 110] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Affiliation(s)
- Hyung Min Cho
- Department of Chemical and Biomolecular Engineering, Energy Biosciences Institute, University of California, Berkeley, Berkeley, California, United States
| | - Adam S. Gross
- Department of Chemical and Biomolecular Engineering, Energy Biosciences Institute, University of California, Berkeley, Berkeley, California, United States
| | - Jhih-Wei Chu
- Department of Chemical and Biomolecular Engineering, Energy Biosciences Institute, University of California, Berkeley, Berkeley, California, United States
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33
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Silvestre-Ryan J, Lin Y, Chu JW. "Fluctuograms" reveal the intermittent intra-protein communication in subtilisin Carlsberg and correlate mechanical coupling with co-evolution. PLoS Comput Biol 2011; 7:e1002023. [PMID: 21455286 PMCID: PMC3063751 DOI: 10.1371/journal.pcbi.1002023] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2010] [Accepted: 02/13/2011] [Indexed: 11/21/2022] Open
Abstract
The mechanism of intra-protein communication and allosteric coupling is key to understanding the structure-property relationship of protein function. For subtilisin Carlsberg, the Ca2+-binding loop is distal to substrate-binding and active sites, yet the serine protease function depends on Ca2+ binding. The atomic molecular dynamics (MD) simulations of apo and Ca2+-bound subtilisin show similar structures and there is no direct evidence that subtilisin has alternative conformations. To model the intra-protein communication due to Ca2+ binding, we transform the sequential segments of an atomic MD trajectory into separate elastic network models to represent anharmonicity and nonlinearity effectively as the temporal and spatial variation of the mechanical coupling network. In analogy to the spectrogram of sound waves, this transformation is termed the “fluctuogram” of protein dynamics. We illustrate that the Ca2+-bound and apo states of subtilisin have different fluctuograms and that intra-protein communication proceeds intermittently both in space and in time. We found that residues with large mechanical coupling variation due to Ca2+ binding correlate with the reported mutation sites selected by directed evolution for improving the stability of subtilisin and its activity in a non-aqueous environment. Furthermore, we utilize the fluctuograms calculated from MD to capture the highly correlated residues in a multiple sequence alignment. We show that in addition to the magnitude, the variance of coupling strength is also an indicative property for the sequence correlation observed in a statistical coupling analysis. The results of this work illustrate that the mechanical coupling networks calculated from atomic details can be used to correlate with functionally important mutation sites and co-evolution. A hallmark of protein molecules is their machine-like behaviors while carrying out biological functions. At the molecular level, molecular signals such as binding a metal ion at an action site can cause long-range effects and alter protein function. Such phenomena are often referred to as intra-protein communication or allosteric coupling. Elucidating the underlying mechanisms could lead to novel discovery of molecular modulators to regulate protein function in a more specific and effective manner. A long-standing puzzle is the roles of the anharmonicity and nonlinearity in protein dynamics. To incorporate these characters in modeling intra-protein communication, we devise a “fluctuogram” analysis to record the choreography of allosteric coupling in an atomic molecular dynamics simulation. We show that fluctuogram analysis can bridge the results of physics-based simulation and sequence alignment in bioinformatics by capturing the residues that exhibit high correlation in a multiple sequence alignment. We also show that the fluctuograms calculated from atomic details have the potential to be applied as a tool to select mutation sites for modulating protein function.
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Affiliation(s)
- Jordi Silvestre-Ryan
- Department of Bioengineering, University of California, Berkeley, Berkeley, California, United States of America
| | - Yuchun Lin
- Department of Chemical and Biomolecular Engineering, University of California, Berkeley, Berkeley, California, United States of America
| | - Jhih-Wei Chu
- Department of Chemical and Biomolecular Engineering, University of California, Berkeley, Berkeley, California, United States of America
- * E-mail:
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34
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Batista da Silva JA, Moreira FGB, Leite dos Santos VM, Longo RL. On the hydrogen bond networks in the water–methanol mixtures: topology, percolation and small-world. Phys Chem Chem Phys 2011; 13:6452-61. [DOI: 10.1039/c0cp01802c] [Citation(s) in RCA: 52] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
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