1
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Stieffenhofer M, Scherer C, May F, Bereau T, Andrienko D. Benchmarking coarse-grained models of organic semiconductors via deep backmapping. Front Chem 2022; 10:982757. [PMID: 36157043 PMCID: PMC9500322 DOI: 10.3389/fchem.2022.982757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 07/22/2022] [Indexed: 11/13/2022] Open
Abstract
The potential of mean force is an effective coarse-grained potential, which is often approximated by pairwise potentials. While the approximated potential reproduces certain distributions of the reference all-atom model with remarkable accuracy, important cross-correlations are typically not captured. In general, the quality of coarse-grained models is evaluated at the coarse-grained resolution, hindering the detection of important discrepancies between the all-atom and coarse-grained ensembles. In this work, the quality of different coarse-grained models is assessed at the atomistic resolution deploying reverse-mapping strategies. In particular, coarse-grained structures for Tris-Meta-Biphenyl-Triazine are reverse-mapped from two different sources: 1) All-atom configurations projected onto the coarse-grained resolution and 2) snapshots obtained by molecular dynamics simulations based on the coarse-grained force fields. To assess the quality of the coarse-grained models, reverse-mapped structures of both sources are compared revealing significant discrepancies between the all-atom and the coarse-grained ensembles. Specifically, the reintroduced details enable force computations based on the all-atom force field that yield a clear ranking for the quality of the different coarse-grained models.
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Affiliation(s)
| | | | | | - Tristan Bereau
- Van ‘t Hoff Institute for Molecular Sciences and Informatics Institute, University of Amsterdam, Amsterdam, Netherlands
| | - Denis Andrienko
- Max Planck Institute for Polymer Research, Mainz, Germany
- *Correspondence: Denis Andrienko,
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2
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Statistical potentials from the Gaussian scaling behaviour of chain fragments buried within protein globules. PLoS One 2022; 17:e0254969. [PMID: 35085247 PMCID: PMC8794220 DOI: 10.1371/journal.pone.0254969] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Accepted: 10/28/2021] [Indexed: 11/19/2022] Open
Abstract
Knowledge-based approaches use the statistics collected from protein data-bank structures to estimate effective interaction potentials between amino acid pairs. Empirical relations are typically employed that are based on the crucial choice of a reference state associated to the null interaction case. Despite their significant effectiveness, the physical interpretation of knowledge-based potentials has been repeatedly questioned, with no consensus on the choice of the reference state. Here we use the fact that the Flory theorem, originally derived for chains in a dense polymer melt, holds also for chain fragments within the core of globular proteins, if the average over buried fragments collected from different non-redundant native structures is considered. After verifying that the ensuing Gaussian statistics, a hallmark of effectively non-interacting polymer chains, holds for a wide range of fragment lengths, although with significant deviations at short spatial scales, we use it to define a ‘bona fide’ reference state. Notably, despite the latter does depend on fragment length, deviations from it do not. This allows to estimate an effective interaction potential which is not biased by the presence of correlations due to the connectivity of the protein chain. We show how different sequence-independent effective statistical potentials can be derived using this approach by coarse-graining the protein representation at varying levels. The possibility of defining sequence-dependent potentials is explored.
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3
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Li B, Fooksa M, Heinze S, Meiler J. Finding the needle in the haystack: towards solving the protein-folding problem computationally. Crit Rev Biochem Mol Biol 2018; 53:1-28. [PMID: 28976219 PMCID: PMC6790072 DOI: 10.1080/10409238.2017.1380596] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2017] [Revised: 08/22/2017] [Accepted: 09/13/2017] [Indexed: 12/22/2022]
Abstract
Prediction of protein tertiary structures from amino acid sequence and understanding the mechanisms of how proteins fold, collectively known as "the protein folding problem," has been a grand challenge in molecular biology for over half a century. Theories have been developed that provide us with an unprecedented understanding of protein folding mechanisms. However, computational simulation of protein folding is still difficult, and prediction of protein tertiary structure from amino acid sequence is an unsolved problem. Progress toward a satisfying solution has been slow due to challenges in sampling the vast conformational space and deriving sufficiently accurate energy functions. Nevertheless, several techniques and algorithms have been adopted to overcome these challenges, and the last two decades have seen exciting advances in enhanced sampling algorithms, computational power and tertiary structure prediction methodologies. This review aims at summarizing these computational techniques, specifically conformational sampling algorithms and energy approximations that have been frequently used to study protein-folding mechanisms or to de novo predict protein tertiary structures. We hope that this review can serve as an overview on how the protein-folding problem can be studied computationally and, in cases where experimental approaches are prohibitive, help the researcher choose the most relevant computational approach for the problem at hand. We conclude with a summary of current challenges faced and an outlook on potential future directions.
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Affiliation(s)
- Bian Li
- Department of Chemistry, Vanderbilt University, Nashville, TN, USA
- Center for Structural Biology, Vanderbilt University, Nashville, TN, USA
| | - Michaela Fooksa
- Center for Structural Biology, Vanderbilt University, Nashville, TN, USA
- Chemical and Physical Biology Graduate Program, Vanderbilt University, Nashville, TN, USA
| | - Sten Heinze
- Department of Chemistry, Vanderbilt University, Nashville, TN, USA
- Center for Structural Biology, Vanderbilt University, Nashville, TN, USA
| | - Jens Meiler
- Department of Chemistry, Vanderbilt University, Nashville, TN, USA
- Center for Structural Biology, Vanderbilt University, Nashville, TN, USA
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4
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Das S, Bhadra P, Ramakumar S, Pal D. Molecular Dynamics Information Improves cis-Peptide-Based Function Annotation of Proteins. J Proteome Res 2017. [PMID: 28633522 DOI: 10.1021/acs.jproteome.7b00217] [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] [Indexed: 11/28/2022]
Abstract
cis-Peptide bonds, whose occurrence in proteins is rare but evolutionarily conserved, are implicated to play an important role in protein function. This has led to their previous use in a homology-independent, fragment-match-based protein function annotation method. However, proteins are not static molecules; dynamics is integral to their activity. This is nicely epitomized by the geometric isomerization of cis-peptide to trans form for molecular activity. Hence we have incorporated both static (cis-peptide) and dynamics information to improve the prediction of protein molecular function. Our results show that cis-peptide information alone cannot detect functional matches in cases where cis-trans isomerization exists but 3D coordinates have been obtained for only the trans isomer or when the cis-peptide bond is incorrectly assigned as trans. On the contrary, use of dynamics information alone includes false-positive matches for cases where fragments with similar secondary structure show similar dynamics, but the proteins do not share a common function. Combining the two methods reduces errors while detecting the true matches, thereby enhancing the utility of our method in function annotation. A combined approach, therefore, opens up new avenues of improving existing automated function annotation methodologies.
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Affiliation(s)
- Sreetama Das
- Department of Physics and ‡Department of Computational and Data Sciences, Indian Institute of Science , Bangalore 560012, India
| | - Pratiti Bhadra
- Department of Physics and ‡Department of Computational and Data Sciences, Indian Institute of Science , Bangalore 560012, India
| | - Suryanarayanarao Ramakumar
- Department of Physics and ‡Department of Computational and Data Sciences, Indian Institute of Science , Bangalore 560012, India
| | - Debnath Pal
- Department of Physics and ‡Department of Computational and Data Sciences, Indian Institute of Science , Bangalore 560012, India
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5
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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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6
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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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7
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Alemani D, Collu F, Cascella M, Dal Peraro M. A Nonradial Coarse-Grained Potential for Proteins Produces Naturally Stable Secondary Structure Elements. J Chem Theory Comput 2015; 6:315-24. [PMID: 26614340 DOI: 10.1021/ct900457z] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
We introduce a nonradial potential term for coarse-grained (CG) molecular simulations of proteins. This term mimics the backbone dipole-dipole interactions and accounts for the needed directionality to form stable folded secondary structure elements. We show that α-helical and β-sheet peptide chains are correctly described in dynamics without the need of introducing any a priori bias potentials or ad hoc parametrizations, which limit broader applicability of CG simulations for proteins. Moreover, our model is able to catch the formation of supersecondary structural motifs, like transitions from long single α-helices to helix-coil-helix or β-hairpin assemblies. This novel scheme requires the structural information of Cα beads only; it does not introduce any additional degrees of freedom to the system and has a general formulation, which allows it to be used in synergy with various CG protocols, leading to an improved description of the structural and dynamic properties of protein assemblies and networks.
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Affiliation(s)
- Davide Alemani
- Laboratory for Biomolecular Modeling, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland and Departement für Chemie und Biochemie, Universität Bern, Freiestrasse 3, CH-3012 Bern, Switzerland
| | - Francesca Collu
- Laboratory for Biomolecular Modeling, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland and Departement für Chemie und Biochemie, Universität Bern, Freiestrasse 3, CH-3012 Bern, Switzerland
| | - Michele Cascella
- Laboratory for Biomolecular Modeling, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland and Departement für Chemie und Biochemie, Universität Bern, Freiestrasse 3, CH-3012 Bern, Switzerland
| | - Matteo Dal Peraro
- Laboratory for Biomolecular Modeling, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland and Departement für Chemie und Biochemie, Universität Bern, Freiestrasse 3, CH-3012 Bern, Switzerland
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8
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Frembgen-Kesner T, Andrews CT, Li S, Ngo NA, Shubert SA, Jain A, Olayiwola OJ, Weishaar MR, Elcock AH. Parametrization of Backbone Flexibility in a Coarse-Grained Force Field for Proteins (COFFDROP) Derived from All-Atom Explicit-Solvent Molecular Dynamics Simulations of All Possible Two-Residue Peptides. J Chem Theory Comput 2015; 11:2341-54. [PMID: 26574429 DOI: 10.1021/acs.jctc.5b00038] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Recently, we reported the parametrization of a set of coarse-grained (CG) nonbonded potential functions, derived from all-atom explicit-solvent molecular dynamics (MD) simulations of amino acid pairs and designed for use in (implicit-solvent) Brownian dynamics (BD) simulations of proteins; this force field was named COFFDROP (COarse-grained Force Field for Dynamic Representations Of Proteins). Here, we describe the extension of COFFDROP to include bonded backbone terms derived from fitting to results of explicit-solvent MD simulations of all possible two-residue peptides containing the 20 standard amino acids, with histidine modeled in both its protonated and neutral forms. The iterative Boltzmann inversion (IBI) method was used to optimize new CG potential functions for backbone-related terms by attempting to reproduce angle, dihedral, and distance probability distributions generated by the MD simulations. In a simple test of the transferability of the extended force field, the angle, dihedral, and distance probability distributions obtained from BD simulations of 56 three-residue peptides were compared to results from corresponding explicit-solvent MD simulations. In a more challenging test of the COFFDROP force field, it was used to simulate eight intrinsically disordered proteins and was shown to quite accurately reproduce the experimental hydrodynamic radii (Rhydro), provided that the favorable nonbonded interactions of the force field were uniformly scaled downward in magnitude. Overall, the results indicate that the COFFDROP force field is likely to find use in modeling the conformational behavior of intrinsically disordered proteins and multidomain proteins connected by flexible linkers.
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Affiliation(s)
| | - Casey T Andrews
- Department of Biochemistry, University of Iowa , Iowa City, Iowa 52242, United States
| | - Shuxiang Li
- Department of Biochemistry, University of Iowa , Iowa City, Iowa 52242, United States
| | - Nguyet Anh Ngo
- Department of Biochemistry, University of Iowa , Iowa City, Iowa 52242, United States
| | - Scott A Shubert
- Department of Biochemistry, University of Iowa , Iowa City, Iowa 52242, United States
| | - Aakash Jain
- Department of Biochemistry, University of Iowa , Iowa City, Iowa 52242, United States
| | - Oluwatoni J Olayiwola
- Department of Biochemistry, University of Iowa , Iowa City, Iowa 52242, United States
| | - Mitch R Weishaar
- Department of Biochemistry, University of Iowa , Iowa City, Iowa 52242, United States
| | - Adrian H Elcock
- Department of Biochemistry, University of Iowa , Iowa City, Iowa 52242, United States
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9
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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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10
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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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11
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Thompson JJ, Tabatabaei Ghomi H, Lill MA. Application of information theory to a three-body coarse-grained representation of proteins in the PDB: insights into the structural and evolutionary roles of residues in protein structure. Proteins 2014; 82:3450-65. [PMID: 25269778 DOI: 10.1002/prot.24698] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2014] [Revised: 09/09/2014] [Accepted: 09/19/2014] [Indexed: 01/03/2023]
Abstract
Knowledge-based methods for analyzing protein structures, such as statistical potentials, primarily consider the distances between pairs of bodies (atoms or groups of atoms). Considerations of several bodies simultaneously are generally used to characterize bonded structural elements or those in close contact with each other, but historically do not consider atoms that are not in direct contact with each other. In this report, we introduce an information-theoretic method for detecting and quantifying distance-dependent through-space multibody relationships between the sidechains of three residues. The technique introduced is capable of producing convergent and consistent results when applied to a sufficiently large database of randomly chosen, experimentally solved protein structures. The results of our study can be shown to reproduce established physico-chemical properties of residues as well as more recently discovered properties and interactions. These results offer insight into the numerous roles that residues play in protein structure, as well as relationships between residue function, protein structure, and evolution. The techniques and insights presented in this work should be useful in the future development of novel knowledge-based tools for the evaluation of protein structure.
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Affiliation(s)
- Jared J Thompson
- Department of Medicinal Chemistry and Molecular Pharmacology, College of Pharmacy, Purdue University, West Lafayette, Indiana
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12
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Willmann KL, Klaver S, Doğu F, Santos-Valente E, Garncarz W, Bilic I, Mace E, Salzer E, Domínguez Conde C, Sic H, Májek P, Banerjee PP, Vladimer GI, Haskoloğlu Ş, Gökalp Bolkent M, Küpesiz A, Condino-Neto A, Colinge J, Superti-Furga G, Pickl WF, van Zelm MC, Eibel H, Orange JS, Ikincioğulları A, Boztuğ K. Biallelic loss-of-function mutation in NIK causes a primary immunodeficiency with multifaceted aberrant lymphoid immunity. Nat Commun 2014; 5:5360. [PMID: 25406581 PMCID: PMC4263125 DOI: 10.1038/ncomms6360] [Citation(s) in RCA: 96] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2014] [Accepted: 09/23/2014] [Indexed: 12/18/2022] Open
Abstract
Primary immunodeficiency disorders enable identification of genes with crucial roles in the human immune system. Here we study patients suffering from recurrent bacterial, viral and Cryptosporidium infections, and identify a biallelic mutation in the MAP3K14 gene encoding NIK (NF-κB-inducing kinase). Loss of kinase activity of mutant NIK, predicted by in silico analysis and confirmed by functional assays, leads to defective activation of both canonical and non-canonical NF-κB signalling. Patients with mutated NIK exhibit B-cell lymphopenia, decreased frequencies of class-switched memory B cells and hypogammaglobulinemia due to impaired B-cell survival, and impaired ICOSL expression. Although overall T-cell numbers are normal, both follicular helper and memory T cells are perturbed. Natural killer (NK) cells are decreased and exhibit defective activation, leading to impaired formation of NK-cell immunological synapses. Collectively, our data illustrate the non-redundant role for NIK in human immune responses, demonstrating that loss-of-function mutations in NIK can cause multiple aberrations of lymphoid immunity.
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Affiliation(s)
- Katharina L. Willmann
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna 1090, Austria
| | - Stefanie Klaver
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna 1090, Austria
- Department of Immunology, Institute of Biomedical Sciences, University of São Paulo, São Paulo 05508-900, Brazil
| | - Figen Doğu
- Department of Pediatric Immunology and Allergy, Ankara University Medical School, Ankara 06100, Turkey
| | - Elisangela Santos-Valente
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna 1090, Austria
| | - Wojciech Garncarz
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna 1090, Austria
| | - Ivan Bilic
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna 1090, Austria
| | - Emily Mace
- Center for Human Immunobiology, Baylor College of Medicine and Texas Children’s Hospital, Houston, Texas 77030, USA
| | - Elisabeth Salzer
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna 1090, Austria
| | - Cecilia Domínguez Conde
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna 1090, Austria
| | - Heiko Sic
- Centre of Chronic Immunodeficiency, University Medical Centre Freiburg, Freiburg 79180, Germany
| | - Peter Májek
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna 1090, Austria
| | - Pinaki P. Banerjee
- Center for Human Immunobiology, Baylor College of Medicine and Texas Children’s Hospital, Houston, Texas 77030, USA
| | - Gregory I. Vladimer
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna 1090, Austria
| | - Şule Haskoloğlu
- Department of Pediatric Immunology and Allergy, Ankara University Medical School, Ankara 06100, Turkey
| | - Musa Gökalp Bolkent
- Department of Pediatric Immunology and Allergy, Ankara University Medical School, Ankara 06100, Turkey
| | - Alphan Küpesiz
- Department of Pediatric Hematology, Akdeniz University Medical School, Antalya 07985, Turkey
| | - Antonio Condino-Neto
- Department of Immunology, Institute of Biomedical Sciences, University of São Paulo, São Paulo 05508-900, Brazil
| | - Jacques Colinge
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna 1090, Austria
| | - Giulio Superti-Furga
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna 1090, Austria
| | - Winfried F. Pickl
- Christian Doppler Laboratory for Immunomodulation and Institute of Immunology, Center for Pathophysiology, Infectiology and Immunology, Medical University of Vienna, Vienna 1090, Austria
| | - Menno C. van Zelm
- Department of Immunology, Erasmus MC, University Medical Center, Rotterdam 3015GE, The Netherlands
| | - Hermann Eibel
- Centre of Chronic Immunodeficiency, University Medical Centre Freiburg, Freiburg 79180, Germany
| | - Jordan S. Orange
- Center for Human Immunobiology, Baylor College of Medicine and Texas Children’s Hospital, Houston, Texas 77030, USA
| | - Aydan Ikincioğulları
- Department of Pediatric Immunology and Allergy, Ankara University Medical School, Ankara 06100, Turkey
| | - Kaan Boztuğ
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna 1090, Austria
- Department of Paediatrics and Adolescent Medicine, Medical University of Vienna, Vienna 1090, Austria
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13
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Andrews CT, Elcock AH. COFFDROP: A Coarse-Grained Nonbonded Force Field for Proteins Derived from All-Atom Explicit-Solvent Molecular Dynamics Simulations of Amino Acids. J Chem Theory Comput 2014; 10:5178-5194. [PMID: 25400526 PMCID: PMC4230375 DOI: 10.1021/ct5006328] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2014] [Indexed: 02/06/2023]
Abstract
![]()
We describe the derivation of a set
of bonded and nonbonded coarse-grained
(CG) potential functions for use in implicit-solvent Brownian dynamics
(BD) simulations of proteins derived from all-atom explicit-solvent
molecular dynamics (MD) simulations of amino acids. Bonded potential
functions were derived from 1 μs MD simulations of each of the
20 canonical amino acids, with histidine modeled in both its protonated
and neutral forms; nonbonded potential functions were derived from
1 μs MD simulations of every possible pairing of the amino acids
(231 different systems). The angle and dihedral probability distributions
and radial distribution functions sampled during MD were used to optimize
a set of CG potential functions through use of the iterative Boltzmann
inversion (IBI) method. The optimized set of potential functions—which
we term COFFDROP (COarse-grained Force Field for Dynamic Representation
Of Proteins)—quantitatively reproduced all of the “target”
MD distributions. In a first test of the force field, it was used
to predict the clustering behavior of concentrated amino acid solutions;
the predictions were directly compared with the results of corresponding
all-atom explicit-solvent MD simulations and found to be in excellent
agreement. In a second test, BD simulations of the small protein villin
headpiece were carried out at concentrations that have recently been
studied in all-atom explicit-solvent MD simulations by Petrov and
Zagrovic (PLoS Comput. Biol.2014, 5, e1003638). The anomalously strong intermolecular interactions
seen in the MD study were reproduced in the COFFDROP simulations;
a simple scaling of COFFDROP’s nonbonded parameters, however,
produced results in better accordance with experiment. Overall, our
results suggest that potential functions derived from simulations
of pairwise amino acid interactions might be of quite broad applicability,
with COFFDROP likely to be especially useful for modeling unfolded
or intrinsically disordered proteins.
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Affiliation(s)
- Casey T Andrews
- Department of Biochemistry, University of Iowa , Iowa City, Iowa 52242, United States
| | - Adrian H Elcock
- Department of Biochemistry, University of Iowa , Iowa City, Iowa 52242, United States
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14
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Kar P, Feig M. Recent advances in transferable coarse-grained modeling of proteins. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2014; 96:143-80. [PMID: 25443957 PMCID: PMC5366245 DOI: 10.1016/bs.apcsb.2014.06.005] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Computer simulations are indispensable tools for studying the structure and dynamics of biological macromolecules. Biochemical processes occur on different scales of length and time. Atomistic simulations cannot cover the relevant spatiotemporal scales at which the cellular processes occur. To address this challenge, coarse-grained (CG) modeling of the biological systems is employed. Over the last few years, many CG models for proteins continue to be developed. However, many of them are not transferable with respect to different systems and different environments. In this review, we discuss those CG protein models that are transferable and that retain chemical specificity. We restrict ourselves to CG models of soluble proteins only. We also briefly review recent progress made in the multiscale hybrid all-atom/CG simulations of proteins.
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Affiliation(s)
- Parimal Kar
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan, USA
| | - Michael Feig
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan, USA; Department of Chemistry, Michigan State University, East Lansing, Michigan, USA.
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15
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On simplified global nonlinear function for fitness landscape: a case study of inverse protein folding. PLoS One 2014; 9:e104403. [PMID: 25110986 PMCID: PMC4128808 DOI: 10.1371/journal.pone.0104403] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2013] [Accepted: 07/14/2014] [Indexed: 11/19/2022] Open
Abstract
The construction of fitness landscape has broad implication in understanding molecular evolution, cellular epigenetic state, and protein structures. We studied the problem of constructing fitness landscape of inverse protein folding or protein design, with the aim to generate amino acid sequences that would fold into an a priori determined structural fold which would enable engineering novel or enhanced biochemistry. For this task, an effective fitness function should allow identification of correct sequences that would fold into the desired structure. In this study, we showed that nonlinear fitness function for protein design can be constructed using a rectangular kernel with a basis set of proteins and decoys chosen a priori. The full landscape for a large number of protein folds can be captured using only 480 native proteins and 3,200 non-protein decoys via a finite Newton method. A blind test of a simplified version of fitness function for sequence design was carried out to discriminate simultaneously 428 native sequences not homologous to any training proteins from 11 million challenging protein-like decoys. This simplified function correctly classified 408 native sequences (20 misclassifications, 95% correct rate), which outperforms several other statistical linear scoring function and optimized linear function. Our results further suggested that for the task of global sequence design of 428 selected proteins, the search space of protein shape and sequence can be effectively parametrized with just about 3,680 carefully chosen basis set of proteins and decoys, and we showed in addition that the overall landscape is not overly sensitive to the specific choice of this set. Our results can be generalized to construct other types of fitness landscape.
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16
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Rudzinski JF, Noid WG. Investigation of coarse-grained mappings via an iterative generalized Yvon-Born-Green method. J Phys Chem B 2014; 118:8295-312. [PMID: 24684663 DOI: 10.1021/jp501694z] [Citation(s) in RCA: 45] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Low resolution coarse-grained (CG) models enable highly efficient simulations of complex systems. The interactions in CG models are often iteratively refined over multiple simulations until they reproduce the one-dimensional (1-D) distribution functions, e.g., radial distribution functions (rdfs), of an all-atom (AA) model. In contrast, the multiscale coarse-graining (MS-CG) method employs a generalized Yvon-Born-Green (g-YBG) relation to determine CG potentials directly (i.e., without iteration) from the correlations observed for the AA model. However, MS-CG models do not necessarily reproduce the 1-D distribution functions of the AA model. Consequently, recent studies have incorporated the g-YBG equation into iterative methods for more accurately reproducing AA rdfs. In this work, we consider a theoretical framework for an iterative g-YBG method. We numerically demonstrate that the method robustly determines accurate models for both hexane and also a more complex molecule, 3-hexylthiophene. By examining the MS-CG and iterative g-YBG models for several distinct CG representations of both molecules, we investigate the approximations of the MS-CG method and their sensitivity to the CG mapping. More generally, we explicitly demonstrate that CG models often reproduce 1-D distribution functions of AA models at the expense of distorting the cross-correlations between the corresponding degrees of freedom. In particular, CG models that accurately reproduce intramolecular 1-D distribution functions may still provide a poor description of the molecular conformations sampled by the AA model. We demonstrate a simple and predictive analysis for determining CG mappings that promote an accurate description of these molecular conformations.
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Affiliation(s)
- Joseph F Rudzinski
- Department of Chemistry, The Pennsylvania State University , University Park, Pennsylvania 16802, United States
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17
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Sterpone F, Melchionna S, Tuffery P, Pasquali S, Mousseau N, Cragnolini T, Chebaro Y, St-Pierre JF, Kalimeri M, Barducci A, Laurin Y, Tek A, Baaden M, Nguyen PH, Derreumaux P. The OPEP protein model: from single molecules, amyloid formation, crowding and hydrodynamics to DNA/RNA systems. Chem Soc Rev 2014; 43:4871-93. [PMID: 24759934 PMCID: PMC4426487 DOI: 10.1039/c4cs00048j] [Citation(s) in RCA: 123] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
The OPEP coarse-grained protein model has been applied to a wide range of applications since its first release 15 years ago. The model, which combines energetic and structural accuracy and chemical specificity, allows the study of single protein properties, DNA-RNA complexes, amyloid fibril formation and protein suspensions in a crowded environment. Here we first review the current state of the model and the most exciting applications using advanced conformational sampling methods. We then present the current limitations and a perspective on the ongoing developments.
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Affiliation(s)
- Fabio Sterpone
- Laboratoire de Biochimie Théorique, UPR 9080 CNRS, Université Paris Diderot, Sorbonne Paris Cité, IBPC, 13 rue Pierre et Marie Curie, 75005, Paris, France.
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18
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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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19
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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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20
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Salzer E, Kansu A, Sic H, Májek P, Ikincioğullari A, Dogu FE, Prengemann NK, Santos-Valente E, Pickl WF, Bilic I, Ban SA, Kuloğlu Z, Demir AM, Ensari A, Colinge J, Rizzi M, Eibel H, Boztug K. Early-onset inflammatory bowel disease and common variable immunodeficiency-like disease caused by IL-21 deficiency. J Allergy Clin Immunol 2014; 133:1651-9.e12. [PMID: 24746753 DOI: 10.1016/j.jaci.2014.02.034] [Citation(s) in RCA: 75] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2013] [Revised: 01/16/2014] [Accepted: 02/05/2014] [Indexed: 02/06/2023]
Abstract
BACKGROUND Alterations of immune homeostasis in the gut can result in development of inflammatory bowel disease (IBD). Recently, Mendelian forms of IBD have been discovered, as exemplified by deficiency of IL-10 or its receptor subunits. In addition, other types of primary immunodeficiency disorders might be associated with intestinal inflammation as one of their leading clinical presentations. OBJECTIVE We investigated a large consanguineous family with 3 children who presented with early-onset IBD within the first year of life, leading to death in infancy in 2 of them. METHODS Homozygosity mapping combined with exome sequencing was performed to identify the molecular cause of the disorder. Functional experiments were performed to assess the effect of IL-21 on the immune system. RESULTS A homozygous mutation in IL21 was discovered that showed perfect segregation with the disease. Deficiency of IL-21 resulted in reduced numbers of circulating CD19(+) B cells, including IgM(+) naive and class-switched IgG memory B cells, with a concomitant increase in transitional B-cell numbers. In vitro assays demonstrated that mutant IL-21(Leu49Pro) did not induce signal transducer and activator of transcription 3 phosphorylation and immunoglobulin class-switch recombination. CONCLUSION Our study uncovers IL-21 deficiency as a novel cause of early-onset IBD in human subjects accompanied by defects in B-cell development similar to those found in patients with common variable immunodeficiency. IBD might mask an underlying primary immunodeficiency, as illustrated here with IL-21 deficiency.
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Affiliation(s)
- Elisabeth Salzer
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Aydan Kansu
- Department of Pediatric Gastroenterology, Ankara University, Ankara, Turkey
| | - Heiko Sic
- Center for Chronic Immunodeficiency, University Medical Center, Freiburg, Germany
| | - Peter Májek
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | | | - Figen E Dogu
- Department of Pediatric Immunology, Ankara University, Ankara, Turkey
| | - Nina Kathrin Prengemann
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | | | - Winfried F Pickl
- Christian Doppler Laboratory for Immunomodulation and Institute of Immunology, Center for Pathophysiology, Infectiology and Immunology, Medical University of Vienna, Vienna, Austria
| | - Ivan Bilic
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Sol A Ban
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Zarife Kuloğlu
- Department of Pediatric Gastroenterology, Ankara University, Ankara, Turkey
| | - Arzu Meltem Demir
- Department of Pediatric Gastroenterology, Ankara University, Ankara, Turkey
| | - Arzu Ensari
- Department of Pathology, Ankara University, Ankara, Turkey
| | - Jacques Colinge
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Marta Rizzi
- Center for Chronic Immunodeficiency, University Medical Center, Freiburg, Germany
| | - Hermann Eibel
- Center for Chronic Immunodeficiency, University Medical Center, Freiburg, Germany
| | - Kaan Boztug
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria; Department of Pediatrics and Adolescent Medicine, Medical University of Vienna, Vienna, Austria.
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21
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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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22
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Lopes A, Sacquin-Mora S, Dimitrova V, Laine E, Ponty Y, Carbone A. Protein-protein interactions in a crowded environment: an analysis via cross-docking simulations and evolutionary information. PLoS Comput Biol 2013; 9:e1003369. [PMID: 24339765 PMCID: PMC3854762 DOI: 10.1371/journal.pcbi.1003369] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2013] [Accepted: 10/15/2013] [Indexed: 12/27/2022] Open
Abstract
Large-scale analyses of protein-protein interactions based on coarse-grain molecular docking simulations and binding site predictions resulting from evolutionary sequence analysis, are possible and realizable on hundreds of proteins with variate structures and interfaces. We demonstrated this on the 168 proteins of the Mintseris Benchmark 2.0. On the one hand, we evaluated the quality of the interaction signal and the contribution of docking information compared to evolutionary information showing that the combination of the two improves partner identification. On the other hand, since protein interactions usually occur in crowded environments with several competing partners, we realized a thorough analysis of the interactions of proteins with true partners but also with non-partners to evaluate whether proteins in the environment, competing with the true partner, affect its identification. We found three populations of proteins: strongly competing, never competing, and interacting with different levels of strength. Populations and levels of strength are numerically characterized and provide a signature for the behavior of a protein in the crowded environment. We showed that partner identification, to some extent, does not depend on the competing partners present in the environment, that certain biochemical classes of proteins are intrinsically easier to analyze than others, and that small proteins are not more promiscuous than large ones. Our approach brings to light that the knowledge of the binding site can be used to reduce the high computational cost of docking simulations with no consequence in the quality of the results, demonstrating the possibility to apply coarse-grain docking to datasets made of thousands of proteins. Comparison with all available large-scale analyses aimed to partner predictions is realized. We release the complete decoys set issued by coarse-grain docking simulations of both true and false interacting partners, and their evolutionary sequence analysis leading to binding site predictions. Download site: http://www.lgm.upmc.fr/CCDMintseris/ Protein-protein interactions (PPI) are at the heart of the molecular processes governing life and constitute an increasingly important target for drug design. Given their importance, it is vital to determine which protein interactions have functional relevance and to characterize the protein competition inherent to crowded environments, as the cytoplasm or the cellular organelles. We show that combining coarse-grain molecular cross-docking simulations and binding site predictions based on evolutionary sequence analysis is a viable route to identify true interacting partners for hundreds of proteins with a variate set of protein structures and interfaces. Also, we realize a large-scale analysis of protein binding promiscuity and provide a numerical characterization of partner competition and level of interaction strength for about 28000 false-partner interactions. Finally, we demonstrate that binding site prediction is useful to discriminate native partners, but also to scale up the approach to thousands of protein interactions. This study is based on the large computational effort made by thousands of internautes helping World Community Grid over a period of 7 months. The complete dataset issued by the computation and the analysis is released to the scientific community.
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Affiliation(s)
- Anne Lopes
- Université Pierre et Marie Curie, UMR 7238, Equipe de Génomique Analytique, Paris, France
- CNRS, UMR 7238, Laboratoire de Génomique des Microorganismes, Paris, France
| | - Sophie Sacquin-Mora
- Laboratoire de Biochimie Théorique, CNRS UPR 9080, Institut de Biologie Physico-Chimique, Paris, France
| | - Viktoriya Dimitrova
- Université Pierre et Marie Curie, UMR 7238, Equipe de Génomique Analytique, Paris, France
- CNRS, UMR 7238, Laboratoire de Génomique des Microorganismes, Paris, France
| | - Elodie Laine
- Université Pierre et Marie Curie, UMR 7238, Equipe de Génomique Analytique, Paris, France
- CNRS, UMR 7238, Laboratoire de Génomique des Microorganismes, Paris, France
| | - Yann Ponty
- Université Pierre et Marie Curie, UMR 7238, Equipe de Génomique Analytique, Paris, France
- LIX, CNRS UMR 7161 - INRIA AMIB, École polytechnique, Palaiseau, France
| | - Alessandra Carbone
- Université Pierre et Marie Curie, UMR 7238, Equipe de Génomique Analytique, Paris, France
- CNRS, UMR 7238, Laboratoire de Génomique des Microorganismes, Paris, France
- * E-mail:
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23
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Sterpone F, Nguyen PH, Kalimeri M, Derreumaux P. Importance of the ion-pair interactions in the OPEP coarse-grained force field: parametrization and validation. J Chem Theory Comput 2013; 9:4574-4584. [PMID: 25419192 DOI: 10.1021/ct4003493] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
We have derived new effective interactions that improve the description of ion-pairs in the OPEP coarse-grained force field without introducing explicit electrostatic terms. The iterative Boltzmann inversion method was used to extract these potentials from all atom simulations by targeting the radial distribution function of the distance between the center of mass of the side-chains. The new potentials have been tested on several systems that differ in structural properties, thermodynamic stabilities and number of ion-pairs. Our modeling, by refining the packing of the charged amino-acids, impacts the stability of secondary structure motifs and the population of intermediate states during temperature folding/unfolding; it also improves the aggregation propensity of peptides. The new version of the OPEP force field has the potentiality to describe more realistically a large spectrum of situations where salt-bridges are key interactions.
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Affiliation(s)
- Fabio Sterpone
- Laboratoire de Biochimie Théorique, IBPC, CNRS, UPR9080, Univ. Paris Diderot, Sorbonne Paris Cité, 13 rue Pierre et Marie Curie, 75005, Paris, France
| | - Phuong H Nguyen
- Laboratoire de Biochimie Théorique, IBPC, CNRS, UPR9080, Univ. Paris Diderot, Sorbonne Paris Cité, 13 rue Pierre et Marie Curie, 75005, Paris, France
| | - Maria Kalimeri
- Laboratoire de Biochimie Théorique, IBPC, CNRS, UPR9080, Univ. Paris Diderot, Sorbonne Paris Cité, 13 rue Pierre et Marie Curie, 75005, Paris, France
| | - Philippe Derreumaux
- Laboratoire de Biochimie Théorique, IBPC, CNRS, UPR9080, Univ. Paris Diderot, Sorbonne Paris Cité, 13 rue Pierre et Marie Curie, 75005, Paris, France ; Institut Universitaire de France, Bvd St Michel, 75005, Paris, France
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24
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Kar P, Gopal SM, Cheng YM, Predeus A, Feig M. PRIMO: A Transferable Coarse-grained Force Field for Proteins. J Chem Theory Comput 2013; 9:3769-3788. [PMID: 23997693 PMCID: PMC3755638 DOI: 10.1021/ct400230y] [Citation(s) in RCA: 76] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
We describe here the PRIMO (PRotein Intermediate Model) force field, a physics-based fully transferable additive coarse-grained potential energy function that is compatible with an all-atom force field for multi-scale simulations. The energy function consists of standard molecular dynamics energy terms plus a hydrogen-bonding potential term and is mainly parameterized based on the CHARMM22/CMAP force field in a bottom-up fashion. The solvent is treated implicitly via the generalized Born model. The bonded interactions are either harmonic or distance-based spline interpolated potentials. These potentials are defined on the basis of all-atom molecular dynamics (MD) simulations of dipeptides with the CHARMM22/CMAP force field. The non-bonded parameters are tuned by matching conformational free energies of diverse set of conformations with that of CHARMM all-atom results. PRIMO is designed to provide a correct description of conformational distribution of the backbone (ϕ/ψ) and side chains (χ1) for all amino acids with a CMAP correction term. The CMAP potential in PRIMO is optimized based on the new CHARMM C36 CMAP. The resulting optimized force field has been applied in MD simulations of several proteins of 36-155 amino acids and shown that the root-mean-squared-deviation of the average structure from the corresponding crystallographic structure varies between 1.80 and 4.03 Å. PRIMO is shown to fold several small peptides to their native-like structures from extended conformations. These results suggest the applicability of the PRIMO force field in the study of protein structures in aqueous solution, structure predictions as well as ab initio folding of small peptides.
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Affiliation(s)
- Parimal Kar
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824, USA
| | - Srinivasa Murthy Gopal
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824, USA
| | - Yi-Ming Cheng
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824, USA
| | - Alexander Predeus
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824, USA
| | - Michael Feig
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824, USA
- Department of Chemistry, Michigan State University, East Lansing, MI 48824, USA
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25
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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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26
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Pasi M, Lavery R, Ceres N. PaLaCe: A Coarse-Grain Protein Model for Studying Mechanical Properties. J Chem Theory Comput 2012; 9:785-93. [DOI: 10.1021/ct3007925] [Citation(s) in RCA: 44] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Affiliation(s)
- Marco Pasi
- Bases Moléculaires
et Structurales des Systèmes
Infectieux, Univ. Lyon I/CNRS UMR 5086, IBCP, 7 Passage du Vercors,
69367 Lyon, France
| | - Richard Lavery
- Bases Moléculaires
et Structurales des Systèmes
Infectieux, Univ. Lyon I/CNRS UMR 5086, IBCP, 7 Passage du Vercors,
69367 Lyon, France
| | - Nicoletta Ceres
- Bases Moléculaires
et Structurales des Systèmes
Infectieux, Univ. Lyon I/CNRS UMR 5086, IBCP, 7 Passage du Vercors,
69367 Lyon, France
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27
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Han W, Schulten K. Further optimization of a hybrid united-atom and coarse-grained force field for folding simulations: Improved backbone hydration and interactions between charged side chains. J Chem Theory Comput 2012; 8:4413-4424. [PMID: 23204949 PMCID: PMC3507460 DOI: 10.1021/ct300696c] [Citation(s) in RCA: 101] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
PACE, a hybrid force field which couples united-atom protein models with coarse-grained (CG) solvent, has been further optimized, aiming to improve itse ciency for folding simulations. Backbone hydration parameters have been re-optimized based on hydration free energies of polyalanyl peptides through atomistic simulations. Also, atomistic partial charges from all-atom force fields were combined with PACE in order to provide a more realistic description of interactions between charged groups. Using replica exchange molecular dynamics (REMD), ab initio folding using the new PACE has been achieved for seven small proteins (16 - 23 residues) with different structural motifs. Experimental data about folded states, such as their stability at room temperature, melting point and NMR NOE constraints, were also well reproduced. Moreover, a systematic comparison of folding kinetics at room temperature has been made with experiments, through standard MD simulations, showing that the new PACE may speed up the actual folding kinetics 5-10 times. Together with the computational speedup benefited from coarse-graining, the force field provides opportunities to study folding mechanisms. In particular, we used the new PACE to fold a 73-residue protein, 3D, in multiple 10 - 30 μs simulations, to its native states (C(α) RMSD ~ 0.34 nm). Our results suggest the potential applicability of the new PACE for the study of folding and dynamics of proteins.
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Affiliation(s)
- Wei Han
- Beckman Institute, University of Illinois at Urbana-Champaign, USA
- Center for Biophysics and Computational Biology, University of Illinois at Urbana-Champaign, USA
| | - Klaus Schulten
- Beckman Institute, University of Illinois at Urbana-Champaign, USA
- Center for Biophysics and Computational Biology, University of Illinois at Urbana-Champaign, USA
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28
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Pape S, Hoffgaard F, Dür M, Hamacher K. Distance dependency and minimum amino acid alphabets for decoy scoring potentials. J Comput Chem 2012; 34:10-20. [DOI: 10.1002/jcc.23099] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2012] [Revised: 07/12/2012] [Accepted: 07/26/2012] [Indexed: 11/09/2022]
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29
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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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30
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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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31
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Abstract
Refinement of protein structures from a correct topology to atomically detailed resolution has proven remarkably difficult. Jian et al. (in this issue of Structure) illustrate a significant advance in this task by carefully incorporating into the refinement process many body interactions extracted from fragment statistics.
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32
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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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33
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Liang S, Zhou Y, Grishin N, Standley DM. Protein side chain modeling with orientation-dependent atomic force fields derived by series expansions. J Comput Chem 2011; 32:1680-6. [PMID: 21374632 PMCID: PMC3072444 DOI: 10.1002/jcc.21747] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2010] [Revised: 12/10/2010] [Accepted: 12/11/2010] [Indexed: 11/09/2022]
Abstract
We describe the development of new force fields for protein side chain modeling called optimized side chain atomic energy (OSCAR). The distance-dependent energy functions (OSCAR-d) and side-chain dihedral angle potential energy functions were represented as power and Fourier series, respectively. The resulting 802 adjustable parameters were optimized by discriminating the native side chain conformations from non-native conformations, using a training set of 12,000 side chains for each residue type. In the course of optimization, for every residue, its side chain was replaced by varying rotamers, whereas conformations for all other residues were kept as they appeared in the crystal structure. Then, the OSCAR-d were multiplied by an orientation-dependent function to yield OSCAR-o. A total of 1087 parameters of the orientation-dependent energy functions (OSCAR-o) were optimized by maximizing the energy gap between the native conformation and subrotamers calculated as low energy by OSCAR-d. When OSCAR-o with optimized parameters were used to model side chain conformations simultaneously for 218 recently released protein structures, the prediction accuracies were 88.8% for χ(1) , 79.7% for χ(1 + 2) , 1.24 Å overall root mean square deviation (RMSD), and 0.62 Å RMSD for core residues, respectively, compared with the next-best performing side-chain modeling program which achieved 86.6% for χ(1) , 75.7% for χ(1 + 2) , 1.40 Å overall RMSD, and 0.86 Å RMSD for core residues, respectively. The continuous energy functions obtained in this study are suitable for gradient-based optimization techniques for protein structure refinement. A program with built-in OSCAR for protein side chain prediction is available for download at http://sysimm.ifrec.osaka-u.ac.jp/OSCAR/.
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Affiliation(s)
- Shide Liang
- Systems Immunology Lab, Immunology Frontier Research Center, Osaka University, Suita, Osaka 565-0871, Japan.
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Hamelryck T, Borg M, Paluszewski M, Paulsen J, Frellsen J, Andreetta C, Boomsma W, Bottaro S, Ferkinghoff-Borg J. Potentials of mean force for protein structure prediction vindicated, formalized and generalized. PLoS One 2010; 5:e13714. [PMID: 21103041 PMCID: PMC2978081 DOI: 10.1371/journal.pone.0013714] [Citation(s) in RCA: 54] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2010] [Accepted: 10/04/2010] [Indexed: 11/26/2022] Open
Abstract
Understanding protein structure is of crucial importance in science, medicine and biotechnology. For about two decades, knowledge-based potentials based on pairwise distances – so-called “potentials of mean force” (PMFs) – have been center stage in the prediction and design of protein structure and the simulation of protein folding. However, the validity, scope and limitations of these potentials are still vigorously debated and disputed, and the optimal choice of the reference state – a necessary component of these potentials – is an unsolved problem. PMFs are loosely justified by analogy to the reversible work theorem in statistical physics, or by a statistical argument based on a likelihood function. Both justifications are insightful but leave many questions unanswered. Here, we show for the first time that PMFs can be seen as approximations to quantities that do have a rigorous probabilistic justification: they naturally arise when probability distributions over different features of proteins need to be combined. We call these quantities “reference ratio distributions” deriving from the application of the “reference ratio method.” This new view is not only of theoretical relevance but leads to many insights that are of direct practical use: the reference state is uniquely defined and does not require external physical insights; the approach can be generalized beyond pairwise distances to arbitrary features of protein structure; and it becomes clear for which purposes the use of these quantities is justified. We illustrate these insights with two applications, involving the radius of gyration and hydrogen bonding. In the latter case, we also show how the reference ratio method can be iteratively applied to sculpt an energy funnel. Our results considerably increase the understanding and scope of energy functions derived from known biomolecular structures.
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Affiliation(s)
- Thomas Hamelryck
- Bioinformatics Center, Department of Biology, University of Copenhagen, Copenhagen, Denmark
- * E-mail: (TH); (JFB)
| | - Mikael Borg
- Bioinformatics Center, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Martin Paluszewski
- Bioinformatics Center, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Jonas Paulsen
- Bioinformatics Center, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Jes Frellsen
- Bioinformatics Center, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Christian Andreetta
- Bioinformatics Center, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Wouter Boomsma
- Biomedical Engineering, Technical University of Denmark (DTU) Elektro, Technical University of Denmark, Lyngby, Denmark
- Department of Chemistry, University of Cambridge, Cambridge, United Kingdom
| | - Sandro Bottaro
- Biomedical Engineering, Technical University of Denmark (DTU) Elektro, Technical University of Denmark, Lyngby, Denmark
| | - Jesper Ferkinghoff-Borg
- Biomedical Engineering, Technical University of Denmark (DTU) Elektro, Technical University of Denmark, Lyngby, Denmark
- * E-mail: (TH); (JFB)
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Abstract
Knowledge-based approaches frequently employ empirical relations to determine effective potentials for coarse-grained protein models directly from protein databank structures. Although these approaches have enjoyed considerable success and widespread popularity in computational protein science, their fundamental basis has been widely questioned. It is well established that conventional knowledge-based approaches do not correctly treat many-body correlations between amino acids. Moreover, the physical significance of potentials determined by using structural statistics from different proteins has remained obscure. In the present work, we address both of these concerns by introducing and demonstrating a theory for calculating transferable potentials directly from a databank of protein structures. This approach assumes that the databank structures correspond to representative configurations sampled from equilibrium solution ensembles for different proteins. Given this assumption, this physics-based theory exactly treats many-body structural correlations and directly determines the transferable potentials that provide a variationally optimized approximation to the free energy landscape for each protein. We illustrate this approach by first constructing a databank of protein structures using a model potential and then quantitatively recovering this potential from the structure databank. The proposed framework will clarify the assumptions and physical significance of knowledge-based potentials, allow for their systematic improvement, and provide new insight into many-body correlations and cooperativity in folded proteins.
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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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Multiscale coarse-graining of the protein energy landscape. PLoS Comput Biol 2010; 6:e1000827. [PMID: 20585614 PMCID: PMC2891700 DOI: 10.1371/journal.pcbi.1000827] [Citation(s) in RCA: 103] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2010] [Accepted: 05/21/2010] [Indexed: 12/05/2022] Open
Abstract
A variety of coarse-grained (CG) models exists for simulation of proteins. An outstanding problem is the construction of a CG model with physically accurate conformational energetics rivaling all-atom force fields. In the present work, atomistic simulations of peptide folding and aggregation equilibria are force-matched using multiscale coarse-graining to develop and test a CG interaction potential of general utility for the simulation of proteins of arbitrary sequence. The reduced representation relies on multiple interaction sites to maintain the anisotropic packing and polarity of individual sidechains. CG energy landscapes computed from replica exchange simulations of the folding of Trpzip, Trp-cage and adenylate kinase resemble those of other reduced representations; non-native structures are observed with energies similar to those of the native state. The artifactual stabilization of misfolded states implies that non-native interactions play a deciding role in deviations from ideal funnel-like cooperative folding. The role of surface tension, backbone hydrogen bonding and the smooth pairwise CG landscape is discussed. Ab initio folding aside, the improved treatment of sidechain rotamers results in stability of the native state in constant temperature simulations of Trpzip, Trp-cage, and the open to closed conformational transition of adenylate kinase, illustrating the potential value of the CG force field for simulating protein complexes and transitions between well-defined structural states. Biological function originates from the dynamical motions of proteins in response to cellular stimuli. Protein dynamics arise from physical interactions that are well-predicted by detailed atomistic simulations. In order to examine large protein complexes on long timescales of biological importance, however, coarse-grained simulation approaches are needed to complement experiment. Previous coarse-grained models have proved successful for investigations involving a given protein's native structure, including protein folding and structure prediction. We construct a model capable of simulating proteins regardless of their sequence or structure. The present coarse-grained model was, however, developed rigorously from the underlying atomistic forces as opposed to knowledge-based or ad hoc parameterizations. Examination of the model predictions on various accessible timescales reveals successes and limitations of the model. While functionally relevant conformational transitions can be studied, the coarse-grained representation has some difficulty with the ab initio folding of the peptide chain into its proper structure. Our observations highlight the complex molecular nature of a protein's underlying energy landscape, offering rigorous insight into the information missing in reduced representations of the peptide chain. With these caveats in mind, the physical interaction–based, coarse-grained model will find application in simulations of a wide variety of proteins and continue to guide future coarse-graining efforts.
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Cao B, Elber R. Computational exploration of the network of sequence flow between protein structures. Proteins 2010; 78:985-1003. [PMID: 19899165 DOI: 10.1002/prot.22622] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
We investigate small sequence adjustments (of one or a few amino acids) that induce large conformational transitions between distinct and stable folds of proteins. Such transitions are intriguing from evolutionary and protein-design perspectives. They make it possible to search for ancient protein structures or to design protein switches that flip between folds and functions. A network of sequence flow between protein folds is computed for representative structures of the Protein Data Bank. The computed network is dense, on an average each structure is connected to tens of other folds. Proteins that attract sequences from a higher than expected number of neighboring folds are more likely to be enzymes and alpha/beta fold. The large number of connections between folds may reflect the need of enzymes to adjust their structures for alternative substrates. The network of the Cro family is discussed, and we speculate that capacity is an important factor (but not the only one) that determines protein evolution. The experimentally observed flip from all alpha to alpha + beta fold is examined by the network tools. A kinetic model for the transition of sequences between the folds (with only protein stability in mind) is proposed. Proteins 2010. (c) 2009 Wiley-Liss, Inc.
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Affiliation(s)
- Baoqiang Cao
- Institute for Computational Engineering and Sciences, University of Texas at Austin, Austin, Texas 78712, USA
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Ha-Duong T. Protein Backbone Dynamics Simulations Using Coarse-Grained Bonded Potentials and Simplified Hydrogen Bonds. J Chem Theory Comput 2010; 6:761-73. [DOI: 10.1021/ct900408s] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Affiliation(s)
- Tap Ha-Duong
- Laboratoire Analyse et Modélisation pour la Biologie et l’Environnement Université d’Evry-Val-d’Essonne Rue du Pere André Jarlan, 91025 Evry Cedex, France
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Vallat BK, Pillardy J, Májek P, Meller J, Blom T, Cao B, Elber R. Building and assessing atomic models of proteins from structural templates: learning and benchmarks. Proteins 2009; 76:930-45. [PMID: 19326457 PMCID: PMC2719020 DOI: 10.1002/prot.22401] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
One approach to predict a protein fold from a sequence (a target) is based on structures of related proteins that are used as templates. We present an algorithm that examines a set of candidates for templates, builds from each of the templates an atomically detailed model, and ranks the models. The algorithm performs a hierarchical selection of the best model using a diverse set of signals. After a quick and suboptimal screening of template candidates from the protein data bank, the current method fine-tunes the selection to a few models. More detailed signals test the compatibility of the sequence and the proposed structures, and are merged to give a global fitness measure using linear programming. This algorithm is a component of the prediction server LOOPP (http://www.loopp.org). Large-scale training and tests sets were designed and are presented. Recent results of the LOOPP server in CASP8 are discussed.
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Affiliation(s)
- Brinda Kizhakke Vallat
- Department of Chemistry and Biochemistry, Institute of Computational Engineering and Sciences, University of Texas at Austin, 1 University Station, ICES C0200, Austin TX 78712
| | - Jaroslaw Pillardy
- Computational Biology Service Unit, Core Laboratories Center and Center for Advanced Computing, Cornell University, Ithaca, New York 14853
| | - Peter Májek
- Department of Computer Science, Cornell University, Ithaca, New York, 14853
| | - Jaroslaw Meller
- Division of Biomedical Informatics, Children’s Hospital Research Foundation, 3333 Burnet Avenue, Cincinnati, Ohio 45229
- Departments of Environmental Health and Biomedical Engineering, University of Cincinnati, College of Medicine, 231 Albert Sabin way, Ohio 45267
| | - Thomas Blom
- Department of Chemistry and Biochemistry, Institute of Computational Engineering and Sciences, University of Texas at Austin, 1 University Station, ICES C0200, Austin TX 78712
| | - BaoQiang Cao
- Department of Chemistry and Biochemistry, Institute of Computational Engineering and Sciences, University of Texas at Austin, 1 University Station, ICES C0200, Austin TX 78712
| | - Ron Elber
- Department of Chemistry and Biochemistry, Institute of Computational Engineering and Sciences, University of Texas at Austin, 1 University Station, ICES C0200, Austin TX 78712
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