1
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Kryś JD, Gront D. Coarse-grained potential for hydrogen bond interactions. J Mol Graph Model 2023; 124:108507. [PMID: 37295157 DOI: 10.1016/j.jmgm.2023.108507] [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] [Received: 01/23/2023] [Revised: 04/12/2023] [Accepted: 04/18/2023] [Indexed: 06/12/2023]
Abstract
Understanding protein structure and dynamics is crucial for investigating numerous biological processes. This however requires proper description of molecular interactions, most notably hydrogen bonds, which are the driving force behind the folding of protein sequences into working molecules. Due to the multi-body character of this interaction, proper mathematical formulation has been a matter of long debate in the literature. This description becomes even more complex in reduced protein models. In this contribution, we propose a novel hydrogen bond energy function definition that is based only on Cα positions and used for coarse-grained simulations. We show that this new method has the capability to recognize hydrogen bonds with over 80% accuracy and can successfully identify β-sheet in β-amyloid peptide simulations.
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Affiliation(s)
- Justyna D Kryś
- Faculty of Chemistry, Biological and Chemical Research Center, University of Warsaw, Pasteura 1, 02-093, Warsaw, Poland.
| | - Dominik Gront
- Faculty of Chemistry, Biological and Chemical Research Center, University of Warsaw, Pasteura 1, 02-093, Warsaw, Poland
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2
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Ledum M, Sen S, Li X, Carrer M, Feng Y, Cascella M, Bore SL. HylleraasMD: A Domain Decomposition-Based Hybrid Particle-Field Software for Multiscale Simulations of Soft Matter. J Chem Theory Comput 2023; 19:2939-2952. [PMID: 37130290 DOI: 10.1021/acs.jctc.3c00134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
We present HylleraasMD (HyMD), a comprehensive implementation of the recently proposed Hamiltonian formulation of hybrid particle-field molecular dynamics. The methodology is based on a tunable, grid-independent length-scale of coarse graining, obtained by filtering particle densities in reciprocal space. This enables systematic convergence of energies and forces by grid refinement, also eliminating nonphysical force aliasing. Separating the time integration of fast modes associated with internal molecular motion from slow modes associated with their density fields, we enable the first time-reversible, energy-conserving hybrid particle-field simulations. HyMD comprises the optional use of explicit electrostatics, which, in this formalism, corresponds to the long-range potential in particle-mesh Ewald. We demonstrate the ability of HyMD to perform simulations in the microcanonical and canonical ensembles with a series of test cases, comprising lipid bilayers and vesicles, surfactant micelles, and polypeptide chains, comparing our results to established literature. An on-the-fly increase of the characteristic coarse-grain length significantly speeds up dynamics, accelerating self-diffusion and leading to expedited aggregation. Exploiting this acceleration, we find that the time scales involved in the self-assembly of polymeric structures can lie in the tens to hundreds of picoseconds instead of the multimicrosecond regime observed with comparable coarse-grained models.
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Affiliation(s)
- Morten Ledum
- Department of Chemistry and Hylleraas Centre for Quantum Molecular Sciences, University of Oslo, PO Box 1033 Blindern, 0315 Oslo, Norway
| | - Samiran Sen
- Department of Chemistry and Hylleraas Centre for Quantum Molecular Sciences, University of Oslo, PO Box 1033 Blindern, 0315 Oslo, Norway
| | - Xinmeng Li
- Department of Chemistry and Hylleraas Centre for Quantum Molecular Sciences, University of Oslo, PO Box 1033 Blindern, 0315 Oslo, Norway
| | - Manuel Carrer
- Department of Chemistry and Hylleraas Centre for Quantum Molecular Sciences, University of Oslo, PO Box 1033 Blindern, 0315 Oslo, Norway
| | - Yu Feng
- Berkeley Center for Cosmological Physics and Department of Physics, University of California, Berkeley, California 94720, United States
| | - Michele Cascella
- Department of Chemistry and Hylleraas Centre for Quantum Molecular Sciences, University of Oslo, PO Box 1033 Blindern, 0315 Oslo, Norway
| | - Sigbjørn Løland Bore
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, United States
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3
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Giulini M, Rigoli M, Mattiotti G, Menichetti R, Tarenzi T, Fiorentini R, Potestio R. From System Modeling to System Analysis: The Impact of Resolution Level and Resolution Distribution in the Computer-Aided Investigation of Biomolecules. Front Mol Biosci 2021; 8:676976. [PMID: 34164432 PMCID: PMC8215203 DOI: 10.3389/fmolb.2021.676976] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2021] [Accepted: 05/06/2021] [Indexed: 12/18/2022] Open
Abstract
The ever increasing computer power, together with the improved accuracy of atomistic force fields, enables researchers to investigate biological systems at the molecular level with remarkable detail. However, the relevant length and time scales of many processes of interest are still hardly within reach even for state-of-the-art hardware, thus leaving important questions often unanswered. The computer-aided investigation of many biological physics problems thus largely benefits from the usage of coarse-grained models, that is, simplified representations of a molecule at a level of resolution that is lower than atomistic. A plethora of coarse-grained models have been developed, which differ most notably in their granularity; this latter aspect determines one of the crucial open issues in the field, i.e. the identification of an optimal degree of coarsening, which enables the greatest simplification at the expenses of the smallest information loss. In this review, we present the problem of coarse-grained modeling in biophysics from the viewpoint of system representation and information content. In particular, we discuss two distinct yet complementary aspects of protein modeling: on the one hand, the relationship between the resolution of a model and its capacity of accurately reproducing the properties of interest; on the other hand, the possibility of employing a lower resolution description of a detailed model to extract simple, useful, and intelligible information from the latter.
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Affiliation(s)
- Marco Giulini
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
| | - Marta Rigoli
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
| | - Giovanni Mattiotti
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
| | - Roberto Menichetti
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
| | - Thomas Tarenzi
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
| | - Raffaele Fiorentini
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
| | - Raffaello Potestio
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
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4
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Jung T, Shin B, Tamo G, Kim H, Vijayvargia R, Leitner A, Marcaida MJ, Astorga-Wells J, Jung R, Aebersold R, Peraro MD, Hebert H, Seong IS, Song JJ. The Polyglutamine Expansion at the N-Terminal of Huntingtin Protein Modulates the Dynamic Configuration and Phosphorylation of the C-Terminal HEAT Domain. Structure 2020; 28:1035-1050.e8. [PMID: 32668197 PMCID: PMC11059206 DOI: 10.1016/j.str.2020.06.008] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Revised: 04/01/2020] [Accepted: 06/23/2020] [Indexed: 11/15/2022]
Abstract
The polyQ expansion in huntingtin protein (HTT) is the prime cause of Huntington's disease (HD). The recent cryoelectron microscopy (cryo-EM) structure of HTT-HAP40 complex provided the structural information on its HEAT-repeat domains. Here, we present analyses of the impact of polyQ length on the structure and function of HTT via an integrative structural and biochemical approach. The cryo-EM analysis of normal (Q23) and disease (Q78) type HTTs shows that the structures of apo HTTs significantly differ from the structure of HTT in a HAP40 complex and that the polyQ expansion induces global structural changes in the relative movements among the HTT domains. In addition, we show that the polyQ expansion alters the phosphorylation pattern across HTT and that Ser2116 phosphorylation in turn affects the global structure and function of HTT. These results provide a molecular basis for the effect of the polyQ segment on HTT structure and activity, which may be important for HTT pathology.
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Affiliation(s)
- Taeyang Jung
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), KI for the BioCentury, Daejeon 34141, Korea; School of Engineering Sciences in Chemistry, Biotechnology and Health, Department of Biomedical Engineering and Health Systems, KTH Royal Institute of Technology, 141 52 Huddinge, Sweden; Department of Biosciences and Nutrition, Karolinska Institutet, 141 83 Huddinge, Sweden
| | - Baehyun Shin
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Department of Neurology, Harvard Medical School, Boston, MA 02114, USA
| | - Giorgio Tamo
- Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
| | - Hyeongju Kim
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), KI for the BioCentury, Daejeon 34141, Korea
| | - Ravi Vijayvargia
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Department of Neurology, Harvard Medical School, Boston, MA 02114, USA
| | - Alexander Leitner
- Department of Biology, Institute of Molecular Systems Biology, ETH Zürich, 8093 Zürich, Switzerland
| | - Maria J Marcaida
- Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
| | - Juan Astorga-Wells
- Department of Medical Biochemistry & Biophysics, Karolinska Institutet, 171 65 Solna, Sweden; HDxperts AB, 183 48 Täby, Sweden
| | - Roy Jung
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Department of Neurology, Harvard Medical School, Boston, MA 02114, USA
| | - Ruedi Aebersold
- Department of Biology, Institute of Molecular Systems Biology, ETH Zürich, 8093 Zürich, Switzerland; Faculty of Science, University of Zürich, Zürich, Switzerland
| | - Matteo Dal Peraro
- Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland.
| | - Hans Hebert
- School of Engineering Sciences in Chemistry, Biotechnology and Health, Department of Biomedical Engineering and Health Systems, KTH Royal Institute of Technology, 141 52 Huddinge, Sweden; Department of Biosciences and Nutrition, Karolinska Institutet, 141 83 Huddinge, Sweden.
| | - Ihn Sik Seong
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Department of Neurology, Harvard Medical School, Boston, MA 02114, USA.
| | - Ji-Joon Song
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), KI for the BioCentury, Daejeon 34141, Korea.
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5
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Mioduszewski Ł, Różycki B, Cieplak M. Pseudo-Improper-Dihedral Model for Intrinsically Disordered Proteins. J Chem Theory Comput 2020; 16:4726-4733. [PMID: 32436706 PMCID: PMC7588027 DOI: 10.1021/acs.jctc.0c00338] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
We present a new coarse-grained Cα-based protein model with a nonradial multibody pseudo-improper-dihedral potential that is transferable, time-independent, and suitable for molecular dynamics. It captures the nature of backbone and side-chain interactions between amino acid residues by adapting a simple improper dihedral term for a one-bead-per-residue model. It is parameterized for intrinsically disordered proteins and applicable to simulations of such proteins and their assemblies on millisecond time scales.
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Affiliation(s)
- Łukasz Mioduszewski
- Institute of Physics, Polish Academy of Sciences, Al. Lotników 32/46, 02-668 Warsaw, Poland
| | - Bartosz Różycki
- Institute of Physics, Polish Academy of Sciences, Al. Lotników 32/46, 02-668 Warsaw, Poland
| | - Marek Cieplak
- Institute of Physics, Polish Academy of Sciences, Al. Lotników 32/46, 02-668 Warsaw, Poland
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6
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Bore SL, Kolli HB, Kawakatsu T, Milano G, Cascella M. Mesoscale Electrostatics Driving Particle Dynamics in Nonhomogeneous Dielectrics. J Chem Theory Comput 2019; 15:2033-2041. [DOI: 10.1021/acs.jctc.8b01201] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Sigbjørn Løland Bore
- Department of Chemistry and Hylleraas Centre for Quantum Molecular Sciences, University of Oslo, PO Box 1033 Blindern, 0315 Oslo, Norway
| | - Hima Bindu Kolli
- Department of Chemistry and Hylleraas Centre for Quantum Molecular Sciences, University of Oslo, PO Box 1033 Blindern, 0315 Oslo, Norway
| | - Toshihiro Kawakatsu
- Department of Physics, Tohoku University, Aoba, Aramaki, Aoba-ku, Sendai 980-8578, Miyagi, Japan
| | - Giuseppe Milano
- Department of Organic Materials Science, Yamagata University, 4-3-16 Jonan ,Yonezawa, Yamagata-ken 992-8510, Japan
| | - Michele Cascella
- Department of Chemistry and Hylleraas Centre for Quantum Molecular Sciences, University of Oslo, PO Box 1033 Blindern, 0315 Oslo, Norway
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7
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Kolli HB, de Nicola A, Bore SL, Schäfer K, Diezemann G, Gauss J, Kawakatsu T, Lu ZY, Zhu YL, Milano G, Cascella M. Hybrid Particle-Field Molecular Dynamics Simulations of Charged Amphiphiles in an Aqueous Environment. J Chem Theory Comput 2018; 14:4928-4937. [DOI: 10.1021/acs.jctc.8b00466] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Hima Bindu Kolli
- Department of Chemistry and Hylleraas Centre for Quantum Molecular Sciences, University of Oslo, P.O.
Box 1033, Blindern, 0315 Oslo, Norway
| | - Antonio de Nicola
- Department of Organic Materials Science, Yamagata University, 4-3-16 Jonan Yonezawa, Yamagata-ken 992-8510, Japan
| | - Sigbjørn Løland Bore
- Department of Chemistry and Hylleraas Centre for Quantum Molecular Sciences, University of Oslo, P.O.
Box 1033, Blindern, 0315 Oslo, Norway
| | - Ken Schäfer
- Institut für
Physikalische Chemie, Johannes Gutenberg-Universität Mainz, Duesbergweg 10-14, 55128 Mainz, Germany
| | - Gregor Diezemann
- Institut für
Physikalische Chemie, Johannes Gutenberg-Universität Mainz, Duesbergweg 10-14, 55128 Mainz, Germany
| | - Jürgen Gauss
- Institut für
Physikalische Chemie, Johannes Gutenberg-Universität Mainz, Duesbergweg 10-14, 55128 Mainz, Germany
| | - Toshihiro Kawakatsu
- Department of Physics, Tohoku University, Aoba, Aramaki, Aoba-ku, Sendai 980-8578, Japan
| | - Zhong-Yuan Lu
- State Key Laboratory of Supramolecular Structure and Materials, Institute of Theoretical Chemistry, Jilin University, Changchun 130023, China
| | - You-Liang Zhu
- State Key Laboratory of Polymer Physics and Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, China
| | - Giuseppe Milano
- Department of Organic Materials Science, Yamagata University, 4-3-16 Jonan Yonezawa, Yamagata-ken 992-8510, Japan
| | - Michele Cascella
- Department of Chemistry and Hylleraas Centre for Quantum Molecular Sciences, University of Oslo, P.O.
Box 1033, Blindern, 0315 Oslo, Norway
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8
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Elenewski JE, Velizhanin KA, Zwolak M. A spin-1 representation for dual-funnel energy landscapes. J Chem Phys 2018; 149:035101. [PMID: 30037251 PMCID: PMC7723752 DOI: 10.1063/1.5036677] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
The interconversion between the left- and right-handed helical folds of a polypeptide defines a dual-funneled free energy landscape. In this context, the funnel minima are connected through a continuum of unfolded conformations, evocative of the classical helix-coil transition. Physical intuition and recent conjectures suggest that this landscape can be mapped by assigning a left- or right-handed helical state to each residue. We explore this possibility using all-atom replica exchange molecular dynamics and an Ising-like model, demonstrating that the energy landscape architecture is at odds with a two-state picture. A three-state model-left, right, and unstructured-can account for most key intermediates during chiral interconversion. Competing folds and excited conformational states still impose limitations on the scope of this approach. However, the improvement is stark: Moving from a two-state to a three-state model decreases the fit error from 1.6 kBT to 0.3 kBT along the left-to-right interconversion pathway.
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Affiliation(s)
- Justin E. Elenewski
- Center for Nanoscale Science and Technology, National Institute of Standards and Technology, Gaithersburg, MD 20899, USA
- Maryland Nanocenter, University of Maryland, College Park, MD 20742, USA
| | | | - Michael Zwolak
- Center for Nanoscale Science and Technology, National Institute of Standards and Technology, Gaithersburg, MD 20899, USA
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9
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Sieradzan AK, Makowski M, Augustynowicz A, Liwo A. A general method for the derivation of the functional forms of the effective energy terms in coarse-grained energy functions of polymers. I. Backbone potentials of coarse-grained polypeptide chains. J Chem Phys 2018; 146:124106. [PMID: 28388107 DOI: 10.1063/1.4978680] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Abstract
A general and systematic method for the derivation of the functional expressions for the effective energy terms in coarse-grained force fields of polymer chains is proposed. The method is based on the expansion of the potential of mean force of the system studied in the cluster-cumulant series and expanding the all-atom energy in the Taylor series in the squares of interatomic distances about the squares of the distances between coarse-grained centers, to obtain approximate analytical expressions for the cluster cumulants. The primary degrees of freedom to average about are the angles for collective rotation of the atoms contained in the coarse-grained interaction sites about the respective virtual-bond axes. The approach has been applied to the revision of the virtual-bond-angle, virtual-bond-torsional, and backbone-local-and-electrostatic correlation potentials for the UNited RESidue (UNRES) model of polypeptide chains, demonstrating the strong dependence of the torsional and correlation potentials on virtual-bond angles, not considered in the current UNRES. The theoretical considerations are illustrated with the potentials calculated from the ab initiopotential-energysurface of terminally blocked alanine by numerical integration and with the statistical potentials derived from known protein structures. The revised torsional potentials correctly indicate that virtual-bond angles close to 90° result in the preference for the turn and helical structures, while large virtual-bond angles result in the preference for polyproline II and extended backbone geometry. The revised correlation potentials correctly reproduce the preference for the formation of β-sheet structures for large values of virtual-bond angles and for the formation of α-helical structures for virtual-bond angles close to 90°.
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Affiliation(s)
- Adam K Sieradzan
- Faculty of Chemistry, University of Gdańsk, ul. Wita-Stwosza 63, 80-308 Gdańsk, Poland
| | - Mariusz Makowski
- Faculty of Chemistry, University of Gdańsk, ul. Wita-Stwosza 63, 80-308 Gdańsk, Poland
| | - Antoni Augustynowicz
- Faculty of Mathematics, Physics, and Informatics, University of Gdańsk, ul. Wita Stwosza 57, 80-308 Gdańsk, Poland
| | - Adam Liwo
- Faculty of Chemistry, University of Gdańsk, ul. Wita-Stwosza 63, 80-308 Gdańsk, Poland
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10
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Bore SL, Milano G, Cascella M. Hybrid Particle-Field Model for Conformational Dynamics of Peptide Chains. J Chem Theory Comput 2018; 14:1120-1130. [DOI: 10.1021/acs.jctc.7b01160] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Affiliation(s)
- Sigbjørn Løland Bore
- Department
of Chemistry and Hylleraas Centre for Quantum Molecular Sciences, University of Oslo, P.O.
Box 1033 Blindern, 0315 Oslo, Norway
| | - Giuseppe Milano
- Department
of Organic Materials Science, University of Yamagata, 4-3-16 Jonan
Yonezawa, Yamagata-ken 992-8510, Japan
| | - Michele Cascella
- Department
of Chemistry and Hylleraas Centre for Quantum Molecular Sciences, University of Oslo, P.O.
Box 1033 Blindern, 0315 Oslo, Norway
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11
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Soares TA, Vanni S, Milano G, Cascella M. Toward Chemically Resolved Computer Simulations of Dynamics and Remodeling of Biological Membranes. J Phys Chem Lett 2017; 8:3586-3594. [PMID: 28707901 DOI: 10.1021/acs.jpclett.7b00493] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Cellular membranes are fundamental constituents of living organisms. Apart from defining the boundaries of the cells, they are involved in a wide range of biological functions, associated with both their structural and the dynamical properties. Biomembranes can undergo large-scale transformations when subject to specific environmental changes, including gel-liquid phase transitions, change of aggregation structure, formation of microtubules, or rupture into vesicles. All of these processes are dependent on a delicate interplay between intermolecular forces, molecular crowding, and entropy, and their understanding requires approaches that are able to capture and rationalize the details of all of the involved interactions. Molecular dynamics-based computational models at atom-level resolution are, in principle, the best way to perform such investigations. Unfortunately, the relevant spatial and time dimensionalities involved in membrane remodeling phenomena would require computational costs that are today unaffordable on a routinely basis. Such hurdles can be removed by coarse-graining the representations of the individual molecular components of the systems. This procedure anyway reduces the possibility of describing the chemical variations in the lipid mixtures composing biological membranes. New hybrid particle field multiscale approaches offer today a promising alternative to the more traditional particle-based simulations methods. By combining chemically distinguishable molecular representations with mesoscale-based computationally affordable potentials, they appear as one of the most promising ways to keep an accurate description of the chemical complexity of biological membranes and, at the same time, cover the required scales to describe remodeling events.
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Affiliation(s)
- Thereza A Soares
- Department of Fundamental Chemistry, Federal University of Pernambuco, Cidade Universitária , Recife PE 50740-560, Brazil
| | - Stefano Vanni
- Department of Biology, University of Fribourg , 1700 Fribourg, Switzerland
| | - Giuseppe Milano
- Dipartimento di Chimica e Biologia, Università di Salerno , Via Giovanni Paolo II, 132, I-84084 Fisciano, Italy
| | - Michele Cascella
- Department of Chemistry and Centre for Theoretical and Computational Chemistry (CTCC) , Sem Saelands vei 26, 0371 Oslo, Norway
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12
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Bhadra P, Pal D. Pipeline for inferring protein function from dynamics using coarse-grained molecular mechanics forcefield. Comput Biol Med 2017; 83:134-142. [PMID: 28279862 DOI: 10.1016/j.compbiomed.2017.02.009] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2016] [Revised: 02/18/2017] [Accepted: 02/22/2017] [Indexed: 11/28/2022]
Abstract
Dynamics is integral to the function of proteins, yet the use of molecular dynamics (MD) simulation as a technique remains under-explored for molecular function inference. This is more important in the context of genomics projects where novel proteins are determined with limited evolutionary information. Recently we developed a method to match the query protein's flexible segments to infer function using a novel approach combining analysis of residue fluctuation-graphs and auto-correlation vectors derived from coarse-grained (CG) MD trajectory. The method was validated on a diverse dataset with sequence identity between proteins as low as 3%, with high function-recall rates. Here we share its implementation as a publicly accessible web service, named DynFunc (Dynamics Match for Function) to query protein function from ≥1 µs long CG dynamics trajectory information of protein subunits. Users are provided with the custom-developed coarse-grained molecular mechanics (CGMM) forcefield to generate the MD trajectories for their protein of interest. On upload of trajectory information, the DynFunc web server identifies specific flexible regions of the protein linked to putative molecular function. Our unique application does not use evolutionary information to infer molecular function from MD information and can, therefore, work for all proteins, including moonlighting and the novel ones, whenever structural information is available. Our pipeline is expected to be of utility to all structural biologists working with novel proteins and interested in moonlighting functions.
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Affiliation(s)
- Pratiti Bhadra
- Institute Mathematics Initiative, Indian Institute of Science, Bengaluru 560012, India
| | - Debnath Pal
- Institute Mathematics Initiative, Indian Institute of Science, Bengaluru 560012, India; Computational and Data Sciences, Indian Institute of Science, Bengaluru 560012, India.
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13
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Tamò G, Maesani A, Träger S, Degiacomi MT, Floreano D, Dal Peraro M. Disentangling constraints using viability evolution principles in integrative modeling of macromolecular assemblies. Sci Rep 2017; 7:235. [PMID: 28331186 PMCID: PMC5427971 DOI: 10.1038/s41598-017-00266-w] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2016] [Accepted: 02/14/2017] [Indexed: 11/22/2022] Open
Abstract
Predicting the structure of large molecular assemblies remains a challenging task in structural biology when using integrative modeling approaches. One of the main issues stems from the treatment of heterogeneous experimental data used to predict the architecture of native complexes. We propose a new method, applied here for the first time to a set of symmetrical complexes, based on evolutionary computation that treats every available experimental input independently, bypassing the need to balance weight components assigned to aggregated fitness functions during optimization.
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Affiliation(s)
- Giorgio Tamò
- Laboratory for Biomolecular Modeling, Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, CH-1015, Switzerland.,Swiss Institute of Bioinformatics (SIB), Lausanne, CH-1015, Switzerland
| | - Andrea Maesani
- Laboratory of Intelligent Systems, Institute of Microengineering, École Polytechnique Fédérale de Lausanne, Lausanne, CH-1015, Switzerland
| | - Sylvain Träger
- Laboratory for Biomolecular Modeling, Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, CH-1015, Switzerland.,Swiss Institute of Bioinformatics (SIB), Lausanne, CH-1015, Switzerland
| | - Matteo T Degiacomi
- Chemistry Research Laboratory, Department of Chemistry, University of Oxford, Oxford, UK
| | - Dario Floreano
- Laboratory of Intelligent Systems, Institute of Microengineering, École Polytechnique Fédérale de Lausanne, Lausanne, CH-1015, Switzerland.
| | - Matteo Dal Peraro
- Laboratory for Biomolecular Modeling, Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, CH-1015, Switzerland. .,Swiss Institute of Bioinformatics (SIB), Lausanne, CH-1015, Switzerland.
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14
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Li M, Liu F, Zhang JZH. TMFF—A Two-Bead Multipole Force Field for Coarse-Grained Molecular Dynamics Simulation of Protein. J Chem Theory Comput 2016; 12:6147-6156. [DOI: 10.1021/acs.jctc.6b00769] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Min Li
- School
of Chemistry and Molecular Engineering and School of Physics and Materials
Science, East China Normal University, Shanghai 200062, China
| | - Fengjiao Liu
- School
of Chemistry and Molecular Engineering and School of Physics and Materials
Science, East China Normal University, Shanghai 200062, China
| | - John Z. H. Zhang
- School
of Chemistry and Molecular Engineering and School of Physics and Materials
Science, East China Normal University, Shanghai 200062, China
- NYU-ECNU
Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China
- Department
of Chemistry, New York University, New York, NY 10003, USA
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15
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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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16
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Haxton TK. High-Resolution Coarse-Grained Modeling Using Oriented Coarse-Grained Sites. J Chem Theory Comput 2015; 11:1244-54. [DOI: 10.1021/ct500881x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Affiliation(s)
- Thomas K. Haxton
- Molecular
Foundry, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
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17
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Haxton TK, Mannige RV, Zuckermann RN, Whitelam S. Modeling Sequence-Specific Polymers Using Anisotropic Coarse-Grained Sites Allows Quantitative Comparison with Experiment. J Chem Theory Comput 2014; 11:303-15. [DOI: 10.1021/ct5010559] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Affiliation(s)
- Thomas K. Haxton
- Molecular
Foundry, Lawrence Berkeley
National Laboratory, Berkeley, California 94720, United States
| | - Ranjan V. Mannige
- Molecular
Foundry, Lawrence Berkeley
National Laboratory, Berkeley, California 94720, United States
| | - Ronald N. Zuckermann
- Molecular
Foundry, Lawrence Berkeley
National Laboratory, Berkeley, California 94720, United States
| | - Stephen Whitelam
- Molecular
Foundry, Lawrence Berkeley
National Laboratory, Berkeley, California 94720, United States
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18
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Spampinato GLB, Maccari G, Tozzini V. Minimalist Model for the Dynamics of Helical Polypeptides: A Statistic-Based Parametrization. J Chem Theory Comput 2014; 10:3885-95. [PMID: 26588532 DOI: 10.1021/ct5004059] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Low-resolution models are often used to address macroscopic time and size scales in molecular dynamics simulations of biomolecular systems. Coarse graining is often coupled to knowledge-based parametrization to obtain empirical potentials able to reproduce the system thermodynamic behavior. Here, a minimalist coarse grained (GC) model for the helical structures of proteins is reported. A knowledge-based parametrization strategy is coupled to the explicit inclusion of hydrogen-bonding-related terms, resulting in an accurate reproduction of the structure and dynamics of each single helical type, as well as the internal conformational variables correlation. The proposed strategy of basing the force field terms on real physicochemical interactions is transferable to different secondary structures. Thus, this work, though conclusive for helices, is to be considered the first of a series devoted to the application of the knowledge-based, physicochemical model to extended secondary structures and unstructured proteins.
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Affiliation(s)
| | - Giuseppe Maccari
- Center for Nanotechnology and Innovation @NEST, Istituto Italiano di Tecnologia , Piazza San Silvestro 12-56127 Pisa, Italy
| | - Valentina Tozzini
- NEST, Istituto Nanoscienze-CNR and Scuola Normale Superiore , Piazza San Silvestro 12-56127 Pisa, Italy
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19
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Kar P, Gopal SM, Cheng YM, Panahi A, Feig M. Transferring the PRIMO Coarse-Grained Force Field to the Membrane Environment: Simulations of Membrane Proteins and Helix-Helix Association. J Chem Theory Comput 2014; 10:3459-3472. [PMID: 25136271 PMCID: PMC4132866 DOI: 10.1021/ct500443v] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2014] [Indexed: 12/03/2022]
Abstract
![]()
An
extension of the recently developed PRIMO coarse-grained force
field to membrane environments, PRIMO-M, is described. The membrane
environment is modeled with the heterogeneous dielectric generalized
Born (HDGB) methodology that simply replaces the standard generalized
Born model in PRIMO without further parametrization. The resulting
model was validated by comparing amino acid insertion free energy
profiles and application in molecular dynamics simulations of membrane
proteins and membrane-interacting peptides. Membrane proteins with
148–661 amino acids show stable root-mean-squared-deviations
(RMSD) between 2 and 4 Å for most systems. Transmembrane helical
peptides maintain helical shape and exhibit tilt angles in good agreement
with experimental or other simulation data. The association of two
glycophorin A (GpA) helices was simulated using replica exchange molecular
dynamics simulations yielding the correct dimer structure with a crossing
angle in agreement with previous studies. Finally, conformational
sampling of the influenza fusion peptide also generates structures
in agreement with previous studies. Overall, these findings suggest
that PRIMO-M can be used to study membrane bound peptides and proteins
and validates the transferable nature of the PRIMO coarse-grained
force field.
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Affiliation(s)
- Parimal Kar
- Department of Biochemistry and Molecular Biology and Department of Chemistry, Michigan State University , East Lansing, Michigan 48824, United States
| | - Srinivasa Murthy Gopal
- Department of Biochemistry and Molecular Biology and Department of Chemistry, Michigan State University , East Lansing, Michigan 48824, United States
| | - Yi-Ming Cheng
- Department of Biochemistry and Molecular Biology and Department of Chemistry, Michigan State University , East Lansing, Michigan 48824, United States
| | - Afra Panahi
- Departments of Chemistry and Biophysics, University of Michigan , Ann Arbor, Michigan 48109, United States
| | - Michael Feig
- Department of Biochemistry and Molecular Biology and Department of Chemistry, Michigan State University , East Lansing, Michigan 48824, United States ; Department of Biochemistry and Molecular Biology and Department of Chemistry, Michigan State University , East Lansing, Michigan 48824, United States
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20
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De novoinference of protein function from coarse-grained dynamics. Proteins 2014; 82:2443-54. [DOI: 10.1002/prot.24609] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2014] [Revised: 04/29/2014] [Accepted: 05/13/2014] [Indexed: 01/04/2023]
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21
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Ha-Duong T. Coarse-grained models of the proteins backbone conformational dynamics. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2014; 805:157-69. [PMID: 24446361 DOI: 10.1007/978-3-319-02970-2_7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Coarse-grained models are more and more frequently used in the studies of the proteins structural and dynamic properties, since the reduced number of degrees of freedom allows to enhance the conformational space exploration. This chapter attempts to provide an overview of the various coarse-grained models that were applied to study the functional conformational changes of the polypeptides main chain around their native state. It will more specifically discuss the methods used to represent the protein backbone flexibility and to account for the physico-chemical interactions that stabilize the secondary structure elements.
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Affiliation(s)
- Tap Ha-Duong
- BIOCIS - UMR CNRS 8076, Faculté de Pharmacie - Université Paris Sud, 5 rue Jean-Baptiste Clément, 92296, Châtenay-Malabry, France,
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22
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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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23
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Macromolecular symmetric assembly prediction using swarm intelligence dynamic modeling. Structure 2014; 21:1097-1106. [PMID: 23810695 DOI: 10.1016/j.str.2013.05.014] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2012] [Revised: 05/21/2013] [Accepted: 05/22/2013] [Indexed: 11/23/2022]
Abstract
Proteins often assemble in multimeric complexes to perform a specific biologic function. However, trapping these high-order conformations is difficult experimentally. Therefore, predicting how proteins assemble using in silico techniques can be of great help. The size of the associated conformational space and the fact that proteins are intrinsically flexible structures make this optimization problem extremely challenging. Nonetheless, known experimental spatial restraints can guide the search process, contributing to model biologically relevant states. We present here a swarm intelligence optimization protocol able to predict the arrangement of protein symmetric assemblies by exploiting a limited amount of experimental restraints and steric interactions. Importantly, within this scheme the native flexibility of each protein subunit is taken into account as extracted from molecular dynamics (MD) simulations. We show that this is a key ingredient for the prediction of biologically functional assemblies when, upon oligomerization, subunits explore activated states undergoing significant conformational changes.
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24
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Terakawa T, Takada S. RESPAC: Method to Determine Partial Charges in Coarse-Grained Protein Model and Its Application to DNA-Binding Proteins. J Chem Theory Comput 2014; 10:711-21. [DOI: 10.1021/ct4007162] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Tsuyoshi Terakawa
- Department of Biophysics,
Graduate School of Science, Kyoto University, Kitashirakawa Owake-cho, Sakyo, Kyoto, 606-8501, Japan
| | - Shoji Takada
- Department of Biophysics,
Graduate School of Science, Kyoto University, Kitashirakawa Owake-cho, Sakyo, Kyoto, 606-8501, Japan
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25
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Spiga E, Degiacomi MT, Dal Peraro M. New Strategies for Integrative Dynamic Modeling of Macromolecular Assembly. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2014; 96:77-111. [DOI: 10.1016/bs.apcsb.2014.06.008] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
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26
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27
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Hinsen K, Hu S, Kneller GR, Niemi AJ. A comparison of reduced coordinate sets for describing protein structure. J Chem Phys 2013; 139:124115. [DOI: 10.1063/1.4821598] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
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28
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Spiga E, Alemani D, Degiacomi MT, Cascella M, Peraro MD. Electrostatic-Consistent Coarse-Grained Potentials for Molecular Simulations of Proteins. J Chem Theory Comput 2013; 9:3515-26. [PMID: 26584108 DOI: 10.1021/ct400137q] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
We present a new generation of coarse-grained (CG) potentials that account for a simplified electrostatic description of soluble proteins. The treatment of permanent electrostatic dipoles of the backbone and polar side-chains allows to simulate proteins, preserving an excellent structural and dynamic agreement with respective reference structures and all-atom molecular dynamics simulations. Moreover, multiprotein complexes can be well described maintaining their molecular interfaces thanks to the ability of this scheme to better describe the actual electrostatics at a CG level of resolution. An efficient and robust heuristic algorithm based on particle swarm optimization is used for the derivation of CG parameters via a force-matching procedure. The ability of this protocol to deal with high dimensional search spaces suggests that the extension of this optimization procedure to larger data sets may lead to the generation of a fully transferable CG force field. At the present stage, these electrostatic-consistent CG potentials are easily and efficiently parametrized, show a good degree of transferability, and can be used to simulate soluble proteins or, more interestingly, large macromolecular assemblies for which long all-atom simulations may not be easily affordable.
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Affiliation(s)
- Enrico Spiga
- Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne-EPFL , Lausanne, CH-1015, Switzerland
| | - Davide Alemani
- Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne-EPFL , Lausanne, CH-1015, Switzerland
| | - Matteo T Degiacomi
- Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne-EPFL , Lausanne, CH-1015, Switzerland
| | - Michele Cascella
- Departement für Chemie und Biochemie, Universität Bern , Freiestrasse 3, Bern, CH-3012, Switzerland
| | - Matteo Dal Peraro
- Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne-EPFL , Lausanne, CH-1015, Switzerland
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29
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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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30
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31
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Abstract
Coarse-grained models for protein folding and aggregation are used to explore large dimension scales and timescales that are inaccessible to all-atom models in explicit aqueous solution. Combined with enhanced configuration search methods, these simplified models with various levels of granularity offer the possibility to determine equilibrium structures, compare folding kinetics and thermodynamics with experiments for single proteins and understand the dynamic assembly of amyloid proteins leading to neurodegenerative diseases. I shall describe recent progress in developing such models, and discuss their potentials and limitations in probing the folding and misfolding of proteins with computer simulations.
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32
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Abstract
The Martini force field is a coarse-grained force field suited for molecular dynamics simulations of biomolecular systems. The force field has been parameterized in a systematic way, based on the reproduction of partitioning free energies between polar and apolar phases of a large number of chemical compounds. In this chapter the methodology underlying the force field is presented together with details of its parameterization and limitations. Then currently available topologies are described with a short overview of the key elements of their parameterization. These include the new polarizable Martini water model. A set of three selected ongoing studies using the Martini force field is presented. Finally the latest lines of development are discussed.
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33
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Ghavami A, van der Giessen E, Onck PR. Coarse-Grained Potentials for Local Interactions in Unfolded Proteins. J Chem Theory Comput 2012; 9:432-40. [DOI: 10.1021/ct300684j] [Citation(s) in RCA: 50] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Affiliation(s)
- Ali Ghavami
- Micromechanics of Materials, Zernike
Institute for Advanced Materials, University of Groningen, 9747 AG Groningen, The Netherlands
| | - Erik van der Giessen
- Micromechanics of Materials, Zernike
Institute for Advanced Materials, University of Groningen, 9747 AG Groningen, The Netherlands
| | - Patrick R. Onck
- Micromechanics of Materials, Zernike
Institute for Advanced Materials, University of Groningen, 9747 AG Groningen, The Netherlands
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34
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Abstract
Coarse-grained (CG) force fields have become promising tools for studies of protein behavior, but the balance of speed and accuracy is still a challenge in the research of protein coarse graining methodology. In this work, 20 CG beads have been designed based on the structures of amino acid residues, with which an amino acid can be represented by one or two beads, and a CG solvent model with five water molecules was adopted to ensure the consistence with the protein CG beads. The internal interactions in protein were classified according to the types of the interacting CG beads, and adequate potential functions were chosen and systematically parameterized to fit the energy distributions. The proposed CG force field has been tested on eight proteins, and each protein was simulated for 1000 ns. Even without any extra structure knowledge of the simulated proteins, the Cα root mean square deviations (RMSDs) with respect to their experimental structures are close to those of relatively short time all atom molecular dynamics simulations. However, our coarse grained force field will require further refinement to improve agreement with and persistence of native-like structures. In addition, the root mean square fluctuations (RMSFs) relative to the average structures derived from the simulations show that the conformational fluctuations of the proteins can be sampled.
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Affiliation(s)
- Junfeng Gu
- State Key Laboratory of Structural Analysis for Industrial Equipment, Department of Engineering Mechanics, Dalian University of Technology, Dalian 116023, China; E-Mail:
| | - Fang Bai
- Faculty of Chemical, Environmental and Biological Science and Technology, Dalian University of Technology, Dalian 116023, China; E-Mail:
| | - Honglin Li
- School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China; E-Mail:
| | - Xicheng Wang
- State Key Laboratory of Structural Analysis for Industrial Equipment, Department of Engineering Mechanics, Dalian University of Technology, Dalian 116023, China; E-Mail:
- Author to whom correspondence should be addressed; E-Mail: ; Tel.: +86-411-84706223; Fax: +86-411-84708393
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35
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Chebaro Y, Pasquali S, Derreumaux P. The Coarse-Grained OPEP Force Field for Non-Amyloid and Amyloid Proteins. J Phys Chem B 2012; 116:8741-52. [DOI: 10.1021/jp301665f] [Citation(s) in RCA: 86] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Affiliation(s)
- Yassmine Chebaro
- Laboratoire de Biochimie Théorique,
CNRS UPR 9080, Université Paris Diderot, Sorbonne Paris Cité, Institut de Biologie Physico-Chimique,
13 rue Pierre et Marie Curie, 75005 Paris
| | - Samuela Pasquali
- Laboratoire de Biochimie Théorique,
CNRS UPR 9080, Université Paris Diderot, Sorbonne Paris Cité, Institut de Biologie Physico-Chimique,
13 rue Pierre et Marie Curie, 75005 Paris
| | - Philippe Derreumaux
- Laboratoire de Biochimie Théorique,
CNRS UPR 9080, Université Paris Diderot, Sorbonne Paris Cité, Institut de Biologie Physico-Chimique,
13 rue Pierre et Marie Curie, 75005 Paris
- Institut Universitaire de France, 103 Bvd Saint-Michel, Paris 75005, France
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36
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Enciso M, Rey A. Simple model for the simulation of peptide folding and aggregation with different sequences. J Chem Phys 2012; 136:215103. [DOI: 10.1063/1.4725883] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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37
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Ceres N, Lavery R. Coarse-grain Protein Models. INNOVATIONS IN BIOMOLECULAR MODELING AND SIMULATIONS 2012. [DOI: 10.1039/9781849735049-00219] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
Coarse-graining is a powerful approach for modeling biomolecules that, over the last few decades, has been extensively applied to proteins. Coarse-grain models offer access to large systems and to slow processes without becoming computationally unmanageable. In addition, they are very versatile, enabling both the protein representation and the energy function to be adapted to the biological problem in hand. This review concentrates on modeling soluble proteins and their assemblies. It presents an overview of the coarse-grain representations, of the associated interaction potentials, and of the optimization procedures used to define them. It then shows how coarse-grain models have been used to understand processes involving proteins, from their initial folding to their functional properties, their binary interactions, and the assembly of large complexes.
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Affiliation(s)
- N. Ceres
- Bases Moléculaires et Structurales des Systèmes Infectieux Université Lyon1/CNRS UMR 5086, IBCP, 7 Passage du Vercors, 69367, Lyon France
| | - R. Lavery
- Bases Moléculaires et Structurales des Systèmes Infectieux Université Lyon1/CNRS UMR 5086, IBCP, 7 Passage du Vercors, 69367, Lyon France
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38
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Bezkorovaynaya O, Lukyanov A, Kremer K, Peter C. Multiscale simulation of small peptides: Consistent conformational sampling in atomistic and coarse-grained models. J Comput Chem 2012; 33:937-49. [DOI: 10.1002/jcc.22915] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2011] [Accepted: 12/02/2011] [Indexed: 11/07/2022]
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39
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Orsi M, Essex JW. The ELBA force field for coarse-grain modeling of lipid membranes. PLoS One 2011; 6:e28637. [PMID: 22194874 PMCID: PMC3241685 DOI: 10.1371/journal.pone.0028637] [Citation(s) in RCA: 131] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2011] [Accepted: 11/11/2011] [Indexed: 02/05/2023] Open
Abstract
A new coarse-grain model for molecular dynamics simulation of lipid membranes is presented. Following a simple and conventional approach, lipid molecules are modeled by spherical sites, each representing a group of several atoms. In contrast to common coarse-grain methods, two original (interdependent) features are here adopted. First, the main electrostatics are modeled explicitly by charges and dipoles, which interact realistically through a relative dielectric constant of unity (ε(r) = 1). Second, water molecules are represented individually through a new parametrization of the simple Stockmayer potential for polar fluids; each water molecule is therefore described by a single spherical site embedded with a point dipole. The force field is shown to accurately reproduce the main physical properties of single-species phospholipid bilayers comprising dioleoylphosphatidylcholine (DOPC) and dioleoylphosphatidylethanolamine (DOPE) in the liquid crystal phase, as well as distearoylphosphatidylcholine (DSPC) in the liquid crystal and gel phases. Insights are presented into fundamental properties and phenomena that can be difficult or impossible to study with alternative computational or experimental methods. For example, we investigate the internal pressure distribution, dipole potential, lipid diffusion, and spontaneous self-assembly. Simulations lasting up to 1.5 microseconds were conducted for systems of different sizes (128, 512 and 1058 lipids); this also allowed us to identify size-dependent artifacts that are expected to affect membrane simulations in general. Future extensions and applications are discussed, particularly in relation to the methodology's inherent multiscale capabilities.
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Affiliation(s)
- Mario Orsi
- School of Chemistry, University of Southampton, Southampton, United Kingdom.
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40
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Wu Z, Cui Q, Yethiraj A. A New Coarse-Grained Force Field for Membrane–Peptide Simulations. J Chem Theory Comput 2011; 7:3793-802. [DOI: 10.1021/ct200593t] [Citation(s) in RCA: 71] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Affiliation(s)
- Zhe Wu
- Theoretical Chemistry Institute and Department of Chemistry, University of Wisconsin, Madison, 1101 University Avenue, Madison, Wisconsin 53706, United States
| | - Qiang Cui
- Theoretical Chemistry Institute and Department of Chemistry, University of Wisconsin, Madison, 1101 University Avenue, Madison, Wisconsin 53706, United States
| | - Arun Yethiraj
- Theoretical Chemistry Institute and Department of Chemistry, University of Wisconsin, Madison, 1101 University Avenue, Madison, Wisconsin 53706, United States
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41
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Engin O, Villa A, Peter C, Sayar M. A Challenge for Peptide Coarse Graining: Transferability of Fragment-Based Models. MACROMOL THEOR SIMUL 2011. [DOI: 10.1002/mats.201100005] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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42
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Barducci A, Bonomi M, Derreumaux P. Assessing the Quality of the OPEP Coarse-Grained Force Field. J Chem Theory Comput 2011; 7:1928-34. [DOI: 10.1021/ct100646f] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Affiliation(s)
- Alessandro Barducci
- Computational Science, Department of Chemistry and Applied Biosciences, ETH Zurich, c/o USI Campus, via Buffi 13, CH-6900 Lugano, Switzerland
| | - Massimiliano Bonomi
- Computational Science, Department of Chemistry and Applied Biosciences, ETH Zurich, c/o USI Campus, via Buffi 13, CH-6900 Lugano, Switzerland
| | - Philippe Derreumaux
- Laboratoire de Biochimie Théorique, UPR 9080 CNRS, Institut de Biologie Physico-Chimique and Université Paris Diderot, Paris 7, Institut Universitaire de France, 13 rue Pierre et Marie Curie, 75005 Paris, France
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43
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Abstract
The last decade has witnessed a renewed interest in the coarse-grained (CG) models for biopolymers, also stimulated by the needs of modern molecular biology, dealing with nano- to micro-sized bio-molecular systems and larger than microsecond timescale. This combination of size and timescale is, in fact, hard to access by atomic-based simulations. Coarse graining the system is a route to be followed to overcome these limits, but the ways of practically implementing it are many and different, making the landscape of CG models very vast and complex. In this paper, the CG models are reviewed and their features, applications and performances compared. This analysis, restricted to proteins, focuses on the minimalist models, namely those reducing at minimum the number of degrees of freedom without losing the possibility of explicitly describing the secondary structures. This class includes models using a single or a few interacting centers (beads) for each amino acid. From this analysis several issues emerge. The difficulty in building these models resides in the need for combining transferability/predictive power with the capability of accurately reproducing the structures. It is shown that these aspects could be optimized by accurately choosing the force field (FF) terms and functional forms, and combining different parameterization procedures. In addition, in spite of the variety of the minimalist models, regularities can be found in the parameters values and in FF terms. These are outlined and schematically presented with the aid of a generic phase diagram of the polypeptide in the parameter space and, hopefully, could serve as guidelines for the development of minimalist models incorporating the maximum possible level of predictive power and structural accuracy.
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