1
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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: 72] [Impact Index Per Article: 36.0] [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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2
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López CA, Zhang X, Aydin F, Shrestha R, Van QN, Stanley CB, Carpenter TS, Nguyen K, Patel LA, Chen D, Burns V, Hengartner NW, Reddy TJE, Bhatia H, Di Natale F, Tran TH, Chan AH, Simanshu DK, Nissley DV, Streitz FH, Stephen AG, Turbyville TJ, Lightstone FC, Gnanakaran S, Ingólfsson HI, Neale C. Asynchronous Reciprocal Coupling of Martini 2.2 Coarse-Grained and CHARMM36 All-Atom Simulations in an Automated Multiscale Framework. J Chem Theory Comput 2022; 18:5025-5045. [PMID: 35866871 DOI: 10.1021/acs.jctc.2c00168] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The appeal of multiscale modeling approaches is predicated on the promise of combinatorial synergy. However, this promise can only be realized when distinct scales are combined with reciprocal consistency. Here, we consider multiscale molecular dynamics (MD) simulations that combine the accuracy and macromolecular flexibility accessible to fixed-charge all-atom (AA) representations with the sampling speed accessible to reductive, coarse-grained (CG) representations. AA-to-CG conversions are relatively straightforward because deterministic routines with unique outcomes are achievable. Conversely, CG-to-AA conversions have many solutions due to a surge in the number of degrees of freedom. While automated tools for biomolecular CG-to-AA transformation exist, we find that one popular option, called Backward, is prone to stochastic failure and the AA models that it does generate frequently have compromised protein structure and incorrect stereochemistry. Although these shortcomings can likely be circumvented by human intervention in isolated instances, automated multiscale coupling requires reliable and robust scale conversion. Here, we detail an extension to Multiscale Machine-learned Modeling Infrastructure (MuMMI), including an improved CG-to-AA conversion tool called sinceCG. This tool is reliable (∼98% weakly correlated repeat success rate), automatable (no unrecoverable hangs), and yields AA models that generally preserve protein secondary structure and maintain correct stereochemistry. We describe how the MuMMI framework identifies CG system configurations of interest, converts them to AA representations, and simulates them at the AA scale while on-the-fly analyses provide feedback to update CG parameters. Application to systems containing the peripheral membrane protein RAS and proximal components of RAF kinase on complex eight-component lipid bilayers with ∼1.5 million atoms is discussed in the context of MuMMI.
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Affiliation(s)
- Cesar A López
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States
| | - Xiaohua Zhang
- Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, California 94550, United States
| | - Fikret Aydin
- Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, California 94550, United States
| | - Rebika Shrestha
- NCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, Maryland 21701, United States
| | - Que N Van
- NCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, Maryland 21701, United States
| | - Christopher B Stanley
- Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, United States
| | - Timothy S Carpenter
- Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, California 94550, United States
| | - Kien Nguyen
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States
| | - Lara A Patel
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States.,Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States
| | - De Chen
- NCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, Maryland 21701, United States
| | - Violetta Burns
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States
| | - Nicolas W Hengartner
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States
| | - Tyler J E Reddy
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States
| | - Harsh Bhatia
- Computing Directorate, Lawrence Livermore National Laboratory, Livermore, California 94550, United States
| | - Francesco Di Natale
- Computing Directorate, Lawrence Livermore National Laboratory, Livermore, California 94550, United States
| | - Timothy H Tran
- NCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, Maryland 21701, United States
| | - Albert H Chan
- NCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, Maryland 21701, United States
| | - Dhirendra K Simanshu
- NCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, Maryland 21701, United States
| | - Dwight V Nissley
- NCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, Maryland 21701, United States
| | - Frederick H Streitz
- Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, California 94550, United States
| | - Andrew G Stephen
- NCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, Maryland 21701, United States
| | - Thomas J Turbyville
- NCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, Maryland 21701, United States
| | - Felice C Lightstone
- Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, California 94550, United States
| | - Sandrasegaram Gnanakaran
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States
| | - Helgi I Ingólfsson
- Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, California 94550, United States
| | - Chris Neale
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States
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3
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Kubincová A, Riniker S, Hünenberger PH. Solvent-scaling as an alternative to coarse-graining in adaptive-resolution simulations: The adaptive solvent-scaling (AdSoS) scheme. J Chem Phys 2021; 155:094107. [PMID: 34496576 DOI: 10.1063/5.0057384] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
A new approach termed Adaptive Solvent-Scaling (AdSoS) is introduced for performing simulations of a solute embedded in a fine-grained (FG) solvent region itself surrounded by a coarse-grained (CG) solvent region, with a continuous FG ↔ CG switching of the solvent resolution across a buffer layer. Instead of relying on a distinct CG solvent model, the AdSoS scheme is based on CG models defined by a dimensional scaling of the FG solvent by a factor s, accompanied by an s-dependent modulation of the atomic masses and interaction parameters. The latter changes are designed to achieve an isomorphism between the dynamics of the FG and CG models, and to preserve the dispersive and dielectric solvation properties of the solvent with respect to a solute at FG resolution. This scaling approach offers a number of advantages compared to traditional coarse-graining: (i) the CG parameters are immediately related to those of the FG model (no need to parameterize a distinct CG model); (ii) nearly ideal mixing is expected for CG variants with similar s-values (ideal mixing holding in the limit of identical s-values); (iii) the solvent relaxation timescales should be preserved (no dynamical acceleration typical for coarse-graining); (iv) the graining level NG (number of FG molecules represented by one CG molecule) can be chosen arbitrarily (in particular, NG = s3 is not necessarily an integer); and (v) in an adaptive-resolution scheme, this level can be varied continuously as a function of the position (without requiring a bundling mechanism), and this variation occurs at a constant number of particles per molecule (no occurrence of fractional degrees of freedom in the buffer layer). By construction, the AdSoS scheme minimizes the thermodynamic mismatch between the different regions of the adaptive-resolution system, leading to a nearly homogeneous scaled solvent density s3ρ. Residual density artifacts in and at the surface of the boundary layer can easily be corrected by means of a grid-based biasing potential constructed in a preliminary pure-solvent simulation. This article introduces the AdSoS scheme and provides an initial application to pure atomic liquids (no solute) with Lennard-Jones plus Coulomb interactions in a slab geometry.
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Affiliation(s)
- Alžbeta Kubincová
- Laboratory of Physical Chemistry, Department of Chemistry and Applied Biosciences, ETH Zurich, Vladimir Prelog-Weg 2, CH-8093 Zürich, Switzerland
| | - Sereina Riniker
- Laboratory of Physical Chemistry, Department of Chemistry and Applied Biosciences, ETH Zurich, Vladimir Prelog-Weg 2, CH-8093 Zürich, Switzerland
| | - Philippe H Hünenberger
- Laboratory of Physical Chemistry, Department of Chemistry and Applied Biosciences, ETH Zurich, Vladimir Prelog-Weg 2, CH-8093 Zürich, Switzerland
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4
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Vergadou N, Theodorou DN. Molecular Modeling Investigations of Sorption and Diffusion of Small Molecules in Glassy Polymers. MEMBRANES 2019; 9:E98. [PMID: 31398889 PMCID: PMC6723301 DOI: 10.3390/membranes9080098] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/12/2019] [Revised: 07/22/2019] [Accepted: 07/23/2019] [Indexed: 11/16/2022]
Abstract
With a wide range of applications, from energy and environmental engineering, such as in gas separations and water purification, to biomedical engineering and packaging, glassy polymeric materials remain in the core of novel membrane and state-of the art barrier technologies. This review focuses on molecular simulation methodologies implemented for the study of sorption and diffusion of small molecules in dense glassy polymeric systems. Basic concepts are introduced and systematic methods for the generation of realistic polymer configurations are briefly presented. Challenges related to the long length and time scale phenomena that govern the permeation process in the glassy polymer matrix are described and molecular simulation approaches developed to address the multiscale problem at hand are discussed.
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Affiliation(s)
- Niki Vergadou
- Molecular Thermodynamics and Modelling of Materials Laboratory, Institute of Nanoscience and Nanotechnology, National Center for Scientific Research Demokritos, Aghia Paraskevi Attikis, GR-15310 Athens, Greece.
| | - Doros N Theodorou
- School of Chemical Engineering, National Technical University of Athens, GR 15780 Athens, Greece
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5
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Machado MR, Zeida A, Darré L, Pantano S. From quantum to subcellular scales: multi-scale simulation approaches and the SIRAH force field. Interface Focus 2019; 9:20180085. [PMID: 31065347 PMCID: PMC6501346 DOI: 10.1098/rsfs.2018.0085] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/11/2019] [Indexed: 12/11/2022] Open
Abstract
Modern molecular and cellular biology profits from astonishing resolution structural methods, currently even reaching the whole cell level. This is encompassed by the development of computational methods providing a deep view into the structure and dynamics of molecular processes happening at very different scales in time and space. Linking such scales is of paramount importance when aiming at far-reaching biological questions. Computational methods at the interface between classical and coarse-grained resolutions are gaining momentum with several research groups dedicating important efforts to their development and tuning. An overview of such methods is addressed herein, with special emphasis on the SIRAH force field for coarse-grained and multi-scale simulations. Moreover, we provide proof of concept calculations on the implementation of a multi-scale simulation scheme including quantum calculations on a classical fine-grained/coarse-grained representation of double-stranded DNA. This opens the possibility to include the effect of large conformational fluctuations in chromatin segments on, for instance, the reactivity of particular base pairs within the same simulation framework.
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Affiliation(s)
- Matías R. Machado
- Institut Pasteur de Montevideo, Group of Biomolecular Simulations, Mataojo 2020, CP 11400 Montevideo, Uruguay
| | - Ari Zeida
- Departamento de Bioquímica and Center for Free Radical and Biomedical Research, Facultad de Medicina, Universidad de la República, Montevideo, Uruguay
| | - Leonardo Darré
- Institut Pasteur de Montevideo, Group of Biomolecular Simulations, Mataojo 2020, CP 11400 Montevideo, Uruguay
- Institut Pasteur de Montevideo, Functional Genomics Unit, Mataojo 2020, CP 11400 Montevideo, Uruguay
| | - Sergio Pantano
- Institut Pasteur de Montevideo, Group of Biomolecular Simulations, Mataojo 2020, CP 11400 Montevideo, Uruguay
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6
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Zavadlav J, Marrink SJ, Praprotnik M. SWINGER: a clustering algorithm for concurrent coupling of atomistic and supramolecular liquids. Interface Focus 2019; 9:20180075. [PMID: 31065343 PMCID: PMC6501350 DOI: 10.1098/rsfs.2018.0075] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/01/2019] [Indexed: 12/11/2022] Open
Abstract
In this contribution, we review recent developments and applications of a dynamic clustering algorithm SWINGER tailored for the multiscale molecular simulations of biomolecular systems. The algorithm on-the-fly redistributes solvent molecules among supramolecular clusters. In particular, we focus on its applications in combination with the adaptive resolution scheme, which concurrently couples atomistic and coarse-grained molecular representations. We showcase the versatility of our multiscale approach on a few applications to biomolecular systems coupling atomistic and supramolecular water models such as the well-established MARTINI and dissipative particle dynamics models and provide an outlook for future work.
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Affiliation(s)
- Julija Zavadlav
- Computational Science and Engineering Laboratory, ETH-Zurich, Clausiusstrasse 33, 8092 Zurich, Switzerland
| | - Siewert J. Marrink
- Groningen Biomolecular Sciences and Biotechnology Institute and Zernike Institute for Advanced Materials, University of Groningen, Nijenborgh 7, 9747, AG Groningen, The Netherlands
| | - Matej Praprotnik
- Laboratory for Molecular Modeling, National Institute of Chemistry, Hajdrihova 19, 1001 Ljubljana, Slovenia
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7
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Gunaratne RS, Wilson DB, Flegg MB, Erban R. Multi-resolution dimer models in heat baths with short-range and long-range interactions. Interface Focus 2019; 9:20180070. [PMID: 31065341 PMCID: PMC6501348 DOI: 10.1098/rsfs.2018.0070] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/11/2019] [Indexed: 11/16/2022] Open
Abstract
This work investigates multi-resolution methodologies for simulating dimer models. The solvent particles which make up the heat bath interact with the monomers of the dimer either through direct collisions (short-range) or through harmonic springs (long-range). Two types of multi-resolution methodologies are considered in detail: (a) describing parts of the solvent far away from the dimer by a coarser approach; (b) describing each monomer of the dimer by using a model with different level of resolution. These methodologies are then used to investigate the effect of a shared heat bath versus two uncoupled heat baths, one for each monomer. Furthermore, the validity of the multi-resolution methods is discussed by comparison to dynamics of macroscopic Langevin equations.
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Affiliation(s)
- Ravinda S. Gunaratne
- Mathematical Institute, University of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford OX2 6GG, UK
| | - Daniel B. Wilson
- Mathematical Institute, University of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford OX2 6GG, UK
| | - Mark B. Flegg
- School of Mathematical Sciences, Monash University, 9 Rainforest walk, Clayton campus, Victoria 3168, Australia
| | - Radek Erban
- Mathematical Institute, University of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford OX2 6GG, UK
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8
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Tarenzi T, Calandrini V, Potestio R, Carloni P. Open-Boundary Molecular Mechanics/Coarse-Grained Framework for Simulations of Low-Resolution G-Protein-Coupled Receptor-Ligand Complexes. J Chem Theory Comput 2019; 15:2101-2109. [PMID: 30763087 PMCID: PMC6433333 DOI: 10.1021/acs.jctc.9b00040] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2019] [Indexed: 12/18/2022]
Abstract
G-protein-coupled receptors (GPCRs) constitute as much as 30% of the overall proteins targeted by FDA-approved drugs. However, paucity of structural experimental information and low sequence identity between members of the family impair the reliability of traditional docking approaches and atomistic molecular dynamics simulations for in silico pharmacological applications. We present here a dual-resolution approach tailored for such low-resolution models. It couples a hybrid molecular mechanics/coarse-grained (MM/CG) scheme, previously developed by us for GPCR-ligand complexes, with a Hamiltonian-based adaptive resolution scheme (H-AdResS) for the solvent. This dual-resolution approach removes potentially inaccurate atomistic details from the model while building a rigorous statistical ensemble-the grand canonical one-in the high-resolution region. We validate the method on a well-studied GPCR-ligand complex, for which the 3D structure is known, against atomistic simulations. This implementation paves the way for future accurate in silico studies of low-resolution ligand/GPCRs models.
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Affiliation(s)
- Thomas Tarenzi
- Computation-based Science and Technology Research Center CaSToRC , The Cyprus Institute , 20 Konstaninou Kavafi Street , 2121 Aglantzia, Nicosia , Cyprus
- Departments of Physics , Faculty of Mathematics, Computer Science and Natural Sciences, Aachen University , Otto-Blumenthal Straße , 52062 Aachen , Germany
- Computational Biomedicine, Institute for Advanced Simulations IAS-5 and Institute of Neuroscience and Medicine INM-9 , Forschungszentrum Jülich , 52428 Jülich , Germany
| | - Vania Calandrini
- Computational Biomedicine, Institute for Advanced Simulations IAS-5 and Institute of Neuroscience and Medicine INM-9 , Forschungszentrum Jülich , 52428 Jülich , Germany
| | - Raffaello Potestio
- Department of Physics , University of Trento , via Sommarive 14 Povo , Trento 38123 , Italy
- INFN-TIFPA, Trento Institute for Fundamental Physics and Applications , I-38123 Trento , Italy
| | - Paolo Carloni
- Departments of Physics , Faculty of Mathematics, Computer Science and Natural Sciences, Aachen University , Otto-Blumenthal Straße , 52062 Aachen , Germany
- Computational Biomedicine, Institute for Advanced Simulations IAS-5 and Institute of Neuroscience and Medicine INM-9 , Forschungszentrum Jülich , 52428 Jülich , Germany
- JARA-HPC, Jülich Supercomputing Center , Forschungszentrum Jülich , 52428 Jülich , Germany
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9
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Ciccotti G, Delle Site L. The physics of open systems for the simulation of complex molecular environments in soft matter. SOFT MATTER 2019; 15:2114-2124. [PMID: 30761396 DOI: 10.1039/c8sm02523a] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
Molecular dynamics (MD) has become one of the most powerful tools of investigation in soft matter. Despite such success, simulations of large molecular environments are mostly run using the approximation of closed systems without the possibility of exchange of matter. Due to the molecular complexity of soft matter systems, an optimal simulation strategy would require the application of concurrent multiscale resolution approaches such that each part of a large system can be considered as an open subsystem at a high resolution embedded in a large coarser reservoir of energy and particles. This paper discusses the current capability and the future perspectives of multiscale adaptive resolution MD methods to satisfy the conceptual principles of open systems and to perform simulations of complex molecular environments in soft matter.
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Affiliation(s)
- Giovanni Ciccotti
- Instituto per le Applicazioni del Calcolo, Consiglio Nazionale delle Ricerche, and Universita' La Sapienza, Rome, Italy.
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10
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Zavadlav J, Sablić J, Podgornik R, Praprotnik M. Open-Boundary Molecular Dynamics of a DNA Molecule in a Hybrid Explicit/Implicit Salt Solution. Biophys J 2018; 114:2352-2362. [PMID: 29650370 PMCID: PMC6129463 DOI: 10.1016/j.bpj.2018.02.042] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2017] [Revised: 02/24/2018] [Accepted: 02/28/2018] [Indexed: 12/24/2022] Open
Abstract
The composition and electrolyte concentration of the aqueous bathing environment have important consequences for many biological processes and can profoundly affect the behavior of biomolecules. Nevertheless, because of computational limitations, many molecular simulations of biophysical systems can be performed only at specific ionic conditions: either at nominally zero salt concentration, i.e., including only counterions enforcing the system's electroneutrality, or at excessive salt concentrations. Here, we introduce an efficient molecular dynamics simulation approach for an atomistic DNA molecule at realistic physiological ionic conditions. The simulations are performed by employing the open-boundary molecular dynamics method that allows for simulation of open systems that can exchange mass and linear momentum with the environment. In our open-boundary molecular dynamics approach, the computational burden is drastically alleviated by embedding the DNA molecule in a mixed explicit/implicit salt-bathing solution. In the explicit domain, the water molecules and ions are both overtly present in the system, whereas in the implicit water domain, only the ions are explicitly present and the water is described as a continuous dielectric medium. Water molecules are inserted and deleted into/from the system in the intermediate buffer domain that acts as a water reservoir to the explicit domain, with both water molecules and ions free to enter or leave the explicit domain. Our approach is general and allows for efficient molecular simulations of biomolecules solvated in bathing salt solutions at any ionic strength condition.
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Affiliation(s)
- Julija Zavadlav
- Computational Science & Engineering Laboratory, ETH Zurich, Zurich, Switzerland
| | - Jurij Sablić
- Laboratory for Molecular Modeling, National Institute of Chemistry, Ljubljana, Slovenia
| | - Rudolf Podgornik
- Theoretical Physics Department, J. Stefan Institute, Ljubljana, Slovenia; Department of Physics, Faculty of Mathematics and Physics, University of Ljubljana, Ljubljana, Slovenia
| | - Matej Praprotnik
- Laboratory for Molecular Modeling, National Institute of Chemistry, Ljubljana, Slovenia; Department of Physics, Faculty of Mathematics and Physics, University of Ljubljana, Ljubljana, Slovenia.
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11
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Frederix PWJM, Patmanidis I, Marrink SJ. Molecular simulations of self-assembling bio-inspired supramolecular systems and their connection to experiments. Chem Soc Rev 2018; 47:3470-3489. [PMID: 29688238 PMCID: PMC5961611 DOI: 10.1039/c8cs00040a] [Citation(s) in RCA: 92] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2018] [Indexed: 01/01/2023]
Abstract
In bionanotechnology, the field of creating functional materials consisting of bio-inspired molecules, the function and shape of a nanostructure only appear through the assembly of many small molecules together. The large number of building blocks required to define a nanostructure combined with the many degrees of freedom in packing small molecules has long precluded molecular simulations, but recent advances in computational hardware as well as software have made classical simulations available to this strongly expanding field. Here, we review the state of the art in simulations of self-assembling bio-inspired supramolecular systems. We will first discuss progress in force fields, simulation protocols and enhanced sampling techniques using recent examples. Secondly, we will focus on efforts to enable the comparison of experimentally accessible observables and computational results. Experimental quantities that can be measured by microscopy, spectroscopy and scattering can be linked to simulation output either directly or indirectly, via quantum mechanical or semi-empirical techniques. Overall, we aim to provide an overview of the various computational approaches to understand not only the molecular architecture of nanostructures, but also the mechanism of their formation.
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Affiliation(s)
- Pim W. J. M. Frederix
- Groningen Biomolecular Sciences and Biotechnology Institute and Zernike Institute for Advanced Materials , University of Groningen , Groningen , The Netherlands . ;
| | - Ilias Patmanidis
- Groningen Biomolecular Sciences and Biotechnology Institute and Zernike Institute for Advanced Materials , University of Groningen , Groningen , The Netherlands . ;
| | - Siewert J. Marrink
- Groningen Biomolecular Sciences and Biotechnology Institute and Zernike Institute for Advanced Materials , University of Groningen , Groningen , The Netherlands . ;
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12
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Zavadlav J, Marrink SJ, Praprotnik M. Multiscale Simulation of Protein Hydration Using the SWINGER Dynamical Clustering Algorithm. J Chem Theory Comput 2018; 14:1754-1761. [PMID: 29439560 DOI: 10.1021/acs.jctc.7b01129] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
To perform computationally efficient concurrent multiscale simulations of biological macromolecules in solution, where the all-atom (AT) models are coupled to supramolecular coarse-grained (SCG) solvent models, previous studies resorted to modified AT water models, such as the bundled-simple point charge (SPC) models, that use semiharmonic springs to restrict the relative movement of water molecules within a cluster. Those models can have a significant impact on the simulated biomolecules and can lead, for example, to a partial unfolding of a protein. In this work, we employ the recently developed alternative approach with a dynamical clustering algorithm, SWINGER, which enables a direct coupling of original unmodified AT and SCG water models. We perform an adaptive resolution molecular dynamics simulation of a Trp-Cage miniprotein in multiscale water, where the standard SPC water model is interfaced with the widely used MARTINI SCG model, and demonstrate that, compared to the corresponding full-blown AT simulations, the structural and dynamic properties of the solvated protein and surrounding solvent are well reproduced by our approach.
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Affiliation(s)
- Julija Zavadlav
- Computational Science & Engineering Laboratory , ETH Zurich , Clausiusstrasse 33 , CH-8092 Zurich , Switzerland
| | - Siewert J Marrink
- Groningen Biomolecular Sciences and Biotechnology Institute and Zernike Institute for Advanced Materials , University of Groningen , Nijenborgh 7 , 9747 AG Groningen , The Netherlands
| | - Matej Praprotnik
- Laboratory for Molecular Modeling , National Institute of Chemistry , Hajdrihova 19 , SI-1001 Ljubljana , Slovenia.,Department of Physics, Faculty of Mathematics and Physics , University of Ljubljana , Jadranska 19 , SI-1000 Ljubljana , Slovenia
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Dalla Serra M, Tossi A. Regional Biophysics Conference - RBC2016. EUROPEAN BIOPHYSICS JOURNAL: EBJ 2017; 46:689-690. [PMID: 29128893 DOI: 10.1007/s00249-017-1265-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Affiliation(s)
- Mauro Dalla Serra
- Institute of Biophysics, National Research Council of Italy and Bruno Kessler Foundation, Via Alla Cascata 56/C, 38123, Trento, Italy.
| | - Alessandro Tossi
- Department of Life Sciences, University of Trieste, Via Licio Giorgieri 1, 34127, Trieste, Italy
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