1
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Tarrat N, Schön JC, Cortés J. Dependence of lactose adsorption on the exposed crystal facets of metals: a comparative study of gold, silver and copper. Phys Chem Chem Phys 2024; 26:21134-21146. [PMID: 39069955 DOI: 10.1039/d4cp01559b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/30/2024]
Abstract
In this theoretical work, we investigated the adsorption of a lactose molecule on metal-based surfaces, with a focus on the influence of the nature of the metal and of the type of exposed crystal facet on the adsorbed structures and energetics. More precisely, we considered three flat crystallographic facets of three face-centered cubic metals (gold, silver, and copper). For the global exploration of the energy landscape, we employed a multi-stage procedure where high-throughput searches, using a stochastic method that performs global optimization by iterating local searches, are followed by a refinement of the most probable adsorption conformations of the molecule at the ab initio level. We predicted the optimal conformation of lactose on each of the nine metal-surface combinations, classified the many low-energy minima into possible adsorption modes, and analyzed the structural, electronic and energetic aspects of the lactose molecule on the surface, as well as their dependence on the type of metal and exposed crystal facet. We observed structural similarities between the various minimum-energy conformations of lactose in vacuum and on the surface, a rough correlation between adsorption and interaction energies of the molecule, and a small charge transfer between molecule and surface whose direction is metal-dependent. During adsorption, an electronic reorganization occurs at the metal-molecule interface only, without affecting the vacuum-pointing atoms of the lactose molecule. For all types of surfaces, lactose exhibits the weakest adsorption on silver substrates, while for each coinage metal the adsorption is strongest on the (110) crystal facet. This study demonstrates that the control of exposed facets can allow to modulate the interaction between metals and small saccharides.
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Affiliation(s)
- Nathalie Tarrat
- CEMES, Université de Toulouse, CNRS, 29 rue Jeanne Marvig, 31055 Toulouse, France.
| | - J Christian Schön
- Max Planck Institute for Solid State Research, Heisenbergstr. 1, 70569 Stuttgart, Germany
| | - Juan Cortés
- LAAS-CNRS, Université de Toulouse, CNRS, 31400 Toulouse, France
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2
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Milia V, Tarrat N, Zanon C, Cortés J, Rapacioli M. Exploring Molecular Energy Landscapes by Coupling the DFTB Potential with a Tree-Based Stochastic Algorithm: Investigation of the Conformational Diversity of Phthalates. J Chem Inf Model 2024; 64:3290-3301. [PMID: 38497727 DOI: 10.1021/acs.jcim.3c01981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Exploring the global energy landscape of relatively large molecules at the quantum level is a challenging problem. In this work, we report the coupling of a nonredundant conformational space exploration method, namely, the robotics-inspired iterative global exploration and local optimization (IGLOO) algorithm, with the quantum-chemical density functional tight binding (DFTB) potential. The application of this fast and efficient computational approach to three close-sized molecules of the phthalate family (DBP, BBP, and DEHP) showed that they present different conformational landscapes. These differences have been rationalized by making use of descriptors based on distances and dihedral angles. Coulomb interactions, steric hindrance, and dispersive interactions have been found to drive the geometric properties. A strong correlation has been evidenced between the two dihedral angles describing the side-chain orientation of the phthalate molecules. Our approach identifies low-energy minima without prior knowledge of the potential energy surface, paving the way for future investigations into transition paths and states.
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Affiliation(s)
- Valentin Milia
- LAAS-CNRS, Université de Toulouse, CNRS, 31031 Toulouse, France
- Laboratoire de Chimie et Physique Quantiques LCPQ/FERMI, UMR 5626, Université de Toulouse (UPS) and CNRS, 118 Route de Narbonne, F-31062 Toulouse, France
| | - Nathalie Tarrat
- CEMES, Université de Toulouse, CNRS, 29 Rue Jeanne Marvig, F-31055 Toulouse, France
| | | | - Juan Cortés
- LAAS-CNRS, Université de Toulouse, CNRS, 31031 Toulouse, France
| | - Mathias Rapacioli
- Laboratoire de Chimie et Physique Quantiques LCPQ/FERMI, UMR 5626, Université de Toulouse (UPS) and CNRS, 118 Route de Narbonne, F-31062 Toulouse, France
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3
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Alencar WLM, da Silva Arouche T, Neto AFG, de Castro Ramalho T, de Carvalho Júnior RN, de Jesus Chaves Neto AM. Interactions of Co, Cu, and non-metal phthalocyanines with external structures of SARS-CoV-2 using docking and molecular dynamics. Sci Rep 2022; 12:3316. [PMID: 35228662 PMCID: PMC8885651 DOI: 10.1038/s41598-022-07396-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 02/10/2022] [Indexed: 02/06/2023] Open
Abstract
The new coronavirus, SARS-CoV-2, caused the COVID-19 pandemic, characterized by its high rate of contamination, propagation capacity, and lethality rate. In this work, we approach the use of phthalocyanines as an inhibitor of SARS-CoV-2, as they present several interactive properties of the phthalocyanines (Pc) of Cobalt (CoPc), Copper (CuPc) and without a metal group (NoPc) can interact with SARS-CoV-2, showing potential be used as filtering by adsorption on paints on walls, masks, clothes, and air conditioning filters. Molecular modeling techniques through Molecular Docking and Molecular Dynamics were used, where the target was the external structures of the virus, but specifically the envelope protein, main protease, and Spike glycoprotein proteases. Using the g_MM-GBSA module and with it, the molecular docking studies show that the ligands have interaction characteristics capable of adsorbing the structures. Molecular dynamics provided information on the root-mean-square deviation of the atomic positions provided values between 1 and 2.5. The generalized Born implicit solvation model, Gibbs free energy, and solvent accessible surface area approach were used. Among the results obtained through molecular dynamics, it was noticed that interactions occur since Pc could bind to residues of the active site of macromolecules, demonstrating good interactions; in particular with CoPc. Molecular couplings and free energy showed that S-gly active site residues interacted strongly with phthalocyanines with values of - 182.443 kJ/mol (CoPc), 158.954 kJ/mol (CuPc), and - 129.963 kJ/mol (NoPc). The interactions of Pc's with SARS-CoV-2 may predict some promising candidates for antagonists to the virus, which if confirmed through experimental approaches, may contribute to resolving the global crisis of the COVID-19 pandemic.
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Affiliation(s)
- Wilson Luna Machado Alencar
- Laboratory of Preparation and Computation of Nanomaterials (LPCN), Federal University of Pará, C. P. 479, Belem, PA, 66075-110, Brazil
- Pos-Graduation Program in Engineering of Natural Resources of the Amazon, ITEC, Federal University of Pará, C. P. 2626, Belém, PA, 66050-540, Brazil
- Federal Institute of Pará (IFPA), C. P. BR 316, Km 61, Castanhal, PA, 68740-970, Brazil
| | - Tiago da Silva Arouche
- Laboratory of Preparation and Computation of Nanomaterials (LPCN), Federal University of Pará, C. P. 479, Belem, PA, 66075-110, Brazil
| | | | | | - Raul Nunes de Carvalho Júnior
- Pos-Graduation Program in Engineering of Natural Resources of the Amazon, ITEC, Federal University of Pará, C. P. 2626, Belém, PA, 66050-540, Brazil
- Pos-Graduation Program in Chemical Engineering, ITEC, Federal University of Pará, C. P. 479, Belém, PA, 66075-900, Brazil
| | - Antonio Maia de Jesus Chaves Neto
- Laboratory of Preparation and Computation of Nanomaterials (LPCN), Federal University of Pará, C. P. 479, Belem, PA, 66075-110, Brazil.
- Pos-Graduation Program in Engineering of Natural Resources of the Amazon, ITEC, Federal University of Pará, C. P. 2626, Belém, PA, 66050-540, Brazil.
- Pos-Graduation Program in Chemical Engineering, ITEC, Federal University of Pará, C. P. 479, Belém, PA, 66075-900, Brazil.
- National Professional Master's in Physics Teaching, Federal University of Pará, C. P. 479, Belém, PA, 66075-110, Brazil.
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4
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ART-RRT: As-Rigid-As-Possible search for protein conformational transition paths. J Comput Aided Mol Des 2019; 33:705-727. [PMID: 31435895 DOI: 10.1007/s10822-019-00216-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2019] [Accepted: 08/06/2019] [Indexed: 10/26/2022]
Abstract
The possible functions of a protein are strongly related to its structural rearrangements in the presence of other molecules or environmental changes. Hence, the evaluation of transition paths of proteins, which encodes conformational changes between stable states, is important since it may reveal the underlying mechanisms of the biochemical processes related to these motions. During the last few decades, different geometry-based methods have been proposed to predict such transition paths. However, in the cases where the solution requires complex motions, these methods, which typically constrain only locally the molecular structures, could produce physically irrelevant solutions involving self-intersection. Recently, we have proposed ART-RRT, an efficient method for finding ligand-unbinding pathways. It relies on the exploration of energy valleys in low-dimensional spaces, taking advantage of some mechanisms inspired from computer graphics to ensure the consistency of molecular structures. This article extends ART-RRT to the problem of finding probable conformational transition between two stable states for proteins. It relies on a bidirectional exploration rooted on the two end states and introduces an original strategy to attempt connections between the explored regions. The resulting method is able to produce at low computational cost biologically realistic paths free from self-intersection. These paths can serve as valuable input to other advanced methods for the study of proteins. A better understanding of conformational changes of proteins is important since it may reveal the underlying mechanisms of the biochemical processes related to such motions. Recently, the ART-RRT method has been introduced for finding ligand-unbinding pathways. This article presents an adaptation of the method for finding probable conformational transition between two stable states of a protein. The method is not only computationally cost-effective but also able to produce biologically realistic paths which are free from self-intersection.
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5
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Ishii Y, Yamamoto N, Matubayasi N, Zhang BW, Cui D, Levy RM. Spatially-Decomposed Free Energy of Solvation Based on the Endpoint Density-Functional Method. J Chem Theory Comput 2019; 15:2896-2912. [PMID: 30990682 DOI: 10.1021/acs.jctc.8b01309] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
A spatially resolved version of the density-functional method for solvation thermodynamics is presented by extending the free-energy functional previously established in the one-dimensional, energy representation and formulating a new expression in a mixed four-dimensional representation (three dimensions for position and one dimension for energy). The space was further divided into a set of discrete regions with respect to the relative position of a solvent molecule from the solute, and the spatially decomposed energetics of solvation were analyzed for small molecules with a methyl, amine, or hydroxyl group and alanine dipeptide in solvent water. It was observed that the density of the solvation free energy is weakly dependent on the solute site in the excluded-volume region and is distinctively favorable in the first shells of the solute atoms that can readily form hydrogen bonds with water. The solvent-reorganization term reduces faster with the separation from the solute than the direct interaction between the solute and solvent, and the latter governs the energetics in the second shell and outer regions. The sum of the contributions to the free energy from the excluded volume and first shell was found to deviate significantly from the total sum over all the regions, implying that the solvation free energy is not spatially localized near the solute in a quantitative sense. Still, a local description was shown to be valid as confirmed by the correlation of the total value of free energy with the corresponding value obtained by integrating the free-energy density to the second shell. The theoretical framework developed in the present work to spatially decompose the solvation free energy can thus be useful to identify stabilizing or destabilizing regions of solvent proximate to a solute and to analyze the role that the displacement of interfacial water plays in the thermodynamics of molecular association.
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Affiliation(s)
- Yoshiki Ishii
- Division of Chemical Engineering, Graduate School of Engineering Science , Osaka University , Toyonaka , Osaka 560-8531 , Japan
| | - Naoki Yamamoto
- Division of Chemical Engineering, Graduate School of Engineering Science , Osaka University , Toyonaka , Osaka 560-8531 , Japan
| | - Nobuyuki Matubayasi
- Division of Chemical Engineering, Graduate School of Engineering Science , Osaka University , Toyonaka , Osaka 560-8531 , Japan.,Elements Strategy Initiative for Catalysts and Batteries , Kyoto University , Katsura , Kyoto 615-8520 , Japan
| | - Bin W Zhang
- Center for Biophysics and Computational Biology, Department of Chemistry, and Institute for Computational Molecular Science , Temple University , Philadelphia , Pennsylvania 19122 , United States
| | - Di Cui
- Center for Biophysics and Computational Biology, Department of Chemistry, and Institute for Computational Molecular Science , Temple University , Philadelphia , Pennsylvania 19122 , United States
| | - Ronald M Levy
- Center for Biophysics and Computational Biology, Department of Chemistry, and Institute for Computational Molecular Science , Temple University , Philadelphia , Pennsylvania 19122 , United States
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6
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Maximova T, Plaku E, Shehu A. Structure-Guided Protein Transition Modeling with a Probabilistic Roadmap Algorithm. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2018; 15:1783-1796. [PMID: 27411226 DOI: 10.1109/tcbb.2016.2586044] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Proteins are macromolecules in perpetual motion, switching between structural states to modulate their function. A detailed characterization of the precise yet complex relationship between protein structure, dynamics, and function requires elucidating transitions between functionally-relevant states. Doing so challenges both wet and dry laboratories, as protein dynamics involves disparate temporal scales. In this paper, we present a novel, sampling-based algorithm to compute transition paths. The algorithm exploits two main ideas. First, it leverages known structures to initialize its search and define a reduced conformation space for rapid sampling. This is key to address the insufficient sampling issue suffered by sampling-based algorithms. Second, the algorithm embeds samples in a nearest-neighbor graph where transition paths can be efficiently computed via queries. The algorithm adapts the probabilistic roadmap framework that is popular in robot motion planning. In addition to efficiently computing lowest-cost paths between any given structures, the algorithm allows investigating hypotheses regarding the order of experimentally-known structures in a transition event. This novel contribution is likely to open up new venues of research. Detailed analysis is presented on multiple-basin proteins of relevance to human disease. Multiscaling and the AMBER ff14SB force field are used to obtain energetically-credible paths at atomistic detail.
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7
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Nguyen MK, Jaillet L, Redon S. ART-RRT: As-Rigid-As-Possible exploration of ligand unbinding pathways. J Comput Chem 2018; 39:665-678. [DOI: 10.1002/jcc.25132] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2017] [Revised: 10/30/2017] [Accepted: 11/20/2017] [Indexed: 01/09/2023]
Affiliation(s)
- Minh Khoa Nguyen
- Univ. Grenoble Alpes, Inria, CNRS, Grenoble INP (Institute of Engineering Univ. Grenoble Alpes), LJK; 38000 Grenoble France
| | - Léonard Jaillet
- Univ. Grenoble Alpes, Inria, CNRS, Grenoble INP (Institute of Engineering Univ. Grenoble Alpes), LJK; 38000 Grenoble France
| | - Stéphane Redon
- Univ. Grenoble Alpes, Inria, CNRS, Grenoble INP (Institute of Engineering Univ. Grenoble Alpes), LJK; 38000 Grenoble France
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8
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Abella JR, Moll M, Kavraki LE. Maintaining and Enhancing Diversity of Sampled Protein Conformations in Robotics-Inspired Methods. J Comput Biol 2018; 25:3-20. [PMID: 29035572 PMCID: PMC5756939 DOI: 10.1089/cmb.2017.0164] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
The ability to efficiently sample structurally diverse protein conformations allows one to gain a high-level view of a protein's energy landscape. Algorithms from robot motion planning have been used for conformational sampling, and several of these algorithms promote diversity by keeping track of "coverage" in conformational space based on the local sampling density. However, large proteins present special challenges. In particular, larger systems require running many concurrent instances of these algorithms, but these algorithms can quickly become memory intensive because they typically keep previously sampled conformations in memory to maintain coverage estimates. In addition, robotics-inspired algorithms depend on defining useful perturbation strategies for exploring the conformational space, which is a difficult task for large proteins because such systems are typically more constrained and exhibit complex motions. In this article, we introduce two methodologies for maintaining and enhancing diversity in robotics-inspired conformational sampling. The first method addresses algorithms based on coverage estimates and leverages the use of a low-dimensional projection to define a global coverage grid that maintains coverage across concurrent runs of sampling. The second method is an automatic definition of a perturbation strategy through readily available flexibility information derived from B-factors, secondary structure, and rigidity analysis. Our results show a significant increase in the diversity of the conformations sampled for proteins consisting of up to 500 residues when applied to a specific robotics-inspired algorithm for conformational sampling. The methodologies presented in this article may be vital components for the scalability of robotics-inspired approaches.
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Affiliation(s)
- Jayvee R Abella
- 1 Department of Computer Science, Rice University , Houston, Texas
| | - Mark Moll
- 1 Department of Computer Science, Rice University , Houston, Texas
| | - Lydia E Kavraki
- 1 Department of Computer Science, Rice University , Houston, Texas
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9
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Maximova T, Zhang Z, Carr DB, Plaku E, Shehu A. Sample-Based Models of Protein Energy Landscapes and Slow Structural Rearrangements. J Comput Biol 2018; 25:33-50. [DOI: 10.1089/cmb.2017.0158] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Affiliation(s)
- Tatiana Maximova
- Department of Computer Science, George Mason University, Fairfax, Virginia
| | - Zijing Zhang
- Department of Statistics, George Mason University, Fairfax, Virginia
| | - Daniel B. Carr
- Department of Statistics, George Mason University, Fairfax, Virginia
| | - Erion Plaku
- Department of Electrical Engineering and Computer Science, The Catholic University of America, Washington, D.C
| | - Amarda Shehu
- Department of Computer Science, George Mason University, Fairfax, Virginia
- Department of Bioengineering, George Mason University, Fairfax, Virginia
- School of Systems Biology, George Mason University, Manassas, Virginia
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10
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Nguyen MK, Jaillet L, Redon S. As-Rigid-As-Possible molecular interpolation paths. J Comput Aided Mol Des 2017; 31:403-417. [DOI: 10.1007/s10822-017-0012-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2016] [Accepted: 02/17/2017] [Indexed: 01/10/2023]
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11
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Maximova T, Moffatt R, Ma B, Nussinov R, Shehu A. Principles and Overview of Sampling Methods for Modeling Macromolecular Structure and Dynamics. PLoS Comput Biol 2016; 12:e1004619. [PMID: 27124275 PMCID: PMC4849799 DOI: 10.1371/journal.pcbi.1004619] [Citation(s) in RCA: 132] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Investigation of macromolecular structure and dynamics is fundamental to understanding how macromolecules carry out their functions in the cell. Significant advances have been made toward this end in silico, with a growing number of computational methods proposed yearly to study and simulate various aspects of macromolecular structure and dynamics. This review aims to provide an overview of recent advances, focusing primarily on methods proposed for exploring the structure space of macromolecules in isolation and in assemblies for the purpose of characterizing equilibrium structure and dynamics. In addition to surveying recent applications that showcase current capabilities of computational methods, this review highlights state-of-the-art algorithmic techniques proposed to overcome challenges posed in silico by the disparate spatial and time scales accessed by dynamic macromolecules. This review is not meant to be exhaustive, as such an endeavor is impossible, but rather aims to balance breadth and depth of strategies for modeling macromolecular structure and dynamics for a broad audience of novices and experts.
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Affiliation(s)
- Tatiana Maximova
- Department of Computer Science, George Mason University, Fairfax, Virginia, United States of America
| | - Ryan Moffatt
- Department of Computer Science, George Mason University, Fairfax, Virginia, United States of America
| | - Buyong Ma
- Basic Science Program, Leidos Biomedical Research, Inc. Cancer and Inflammation Program, National Cancer Institute, Frederick, Maryland, United States of America
| | - Ruth Nussinov
- Basic Science Program, Leidos Biomedical Research, Inc. Cancer and Inflammation Program, National Cancer Institute, Frederick, Maryland, United States of America
- Sackler Institute of Molecular Medicine, Department of Human Genetics and Molecular Medicine, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Amarda Shehu
- Department of Computer Science, George Mason University, Fairfax, Virginia, United States of America
- Department of Biongineering, George Mason University, Fairfax, Virginia, United States of America
- School of Systems Biology, George Mason University, Manassas, Virginia, United States of America
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12
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Schön JC, Oligschleger C, Cortes J. Prediction and clarification of structures of (bio)molecules on surfaces. ACTA ACUST UNITED AC 2016. [DOI: 10.1515/znb-2015-0222] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Abstract
The design of future materials for biotechnological applications via deposition of molecules on surfaces will require not only exquisite control of the deposition procedure, but of equal importance will be our ability to predict the shapes and stability of individual molecules on various surfaces. Furthermore, one will need to be able to predict the structure patterns generated during the self-organization of whole layers of (bio)molecules on the surface. In this review, we present an overview over the current state of the art regarding the prediction and clarification of structures of biomolecules on surfaces using theoretical and computational methods.
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Affiliation(s)
- J. Christian Schön
- Max-Planck-Institute for Solid State Research , Heisenbergstr. 1, D-70569 Stuttgart, Germany
| | - Christina Oligschleger
- University of Applied Sciences Bonn-Rhein-Sieg , Von-Liebigstr. 20, D-53359 Rheinbach, Germany
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13
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Molloy K, Shehu A. A General, Adaptive, Roadmap-Based Algorithm for Protein Motion Computation. IEEE Trans Nanobioscience 2016; 15:158-65. [PMID: 26863668 DOI: 10.1109/tnb.2016.2519246] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Precious information on protein function can be extracted from a detailed characterization of protein equilibrium dynamics. This remains elusive in wet and dry laboratories, as function-modulating transitions of a protein between functionally-relevant, thermodynamically-stable and meta-stable structural states often span disparate time scales. In this paper we propose a novel, robotics-inspired algorithm that circumvents time-scale challenges by drawing analogies between protein motion and robot motion. The algorithm adapts the popular roadmap-based framework in robot motion computation to handle the more complex protein conformation space and its underlying rugged energy surface. Given known structures representing stable and meta-stable states of a protein, the algorithm yields a time- and energy-prioritized list of transition paths between the structures, with each path represented as a series of conformations. The algorithm balances computational resources between a global search aimed at obtaining a global view of the network of protein conformations and their connectivity and a detailed local search focused on realizing such connections with physically-realistic models. Promising results are presented on a variety of proteins that demonstrate the general utility of the algorithm and its capability to improve the state of the art without employing system-specific insight.
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15
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Roth CA, Dreyfus T, Robert CH, Cazals F. Hybridizing rapidly exploring random trees and basin hopping yields an improved exploration of energy landscapes. J Comput Chem 2015; 37:739-52. [DOI: 10.1002/jcc.24256] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2015] [Revised: 10/05/2015] [Accepted: 10/15/2015] [Indexed: 12/25/2022]
Affiliation(s)
- Christine-Andrea Roth
- Laboratoire De Biochimie Théorique, CNRS, UPR 9080, Univ Paris Diderot, Sorbonne Paris Cité; 13 Rue Pierre Et Marie Curie Paris 75005 France
| | - Tom Dreyfus
- Laboratoire De Biochimie Théorique, CNRS, UPR 9080, Univ Paris Diderot, Sorbonne Paris Cité; 13 Rue Pierre Et Marie Curie Paris 75005 France
| | - Charles H. Robert
- Laboratoire De Biochimie Théorique, CNRS, UPR 9080, Univ Paris Diderot, Sorbonne Paris Cité; 13 Rue Pierre Et Marie Curie Paris 75005 France
| | - Frédéric Cazals
- Laboratoire De Biochimie Théorique, CNRS, UPR 9080, Univ Paris Diderot, Sorbonne Paris Cité; 13 Rue Pierre Et Marie Curie Paris 75005 France
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16
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Devaurs D, Molloy K, Vaisset M, Shehu A, Simeon T, Cortes J. Characterizing Energy Landscapes of Peptides Using a Combination of Stochastic Algorithms. IEEE Trans Nanobioscience 2015; 14:545-52. [DOI: 10.1109/tnb.2015.2424597] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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17
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Cazals F, Dreyfus T, Mazauric D, Roth CA, Robert CH. Conformational ensembles and sampled energy landscapes: Analysis and comparison. J Comput Chem 2015; 36:1213-31. [DOI: 10.1002/jcc.23913] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2014] [Revised: 02/25/2015] [Accepted: 03/02/2015] [Indexed: 12/11/2022]
Affiliation(s)
- Frédéric Cazals
- Inria 2004 route des Lucioles, BP 93; F-06902 Sophia-Antipolis; FRANCE
| | - Tom Dreyfus
- Inria 2004 route des Lucioles, BP 93; F-06902 Sophia-Antipolis; FRANCE
| | - Dorian Mazauric
- Inria 2004 route des Lucioles, BP 93; F-06902 Sophia-Antipolis; FRANCE
| | | | - Charles H. Robert
- CNRS Laboratory of Theoretical Biochemistry (LBT) Institut de Biologie Physico-Chimique 13; rue Pierre et Marie Curie 75005 Paris
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18
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Efficient Sampling-Based Approaches to Optimal Path Planning in Complex Cost Spaces. SPRINGER TRACTS IN ADVANCED ROBOTICS 2015. [DOI: 10.1007/978-3-319-16595-0_9] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
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19
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Molloy K, Shehu A. Elucidating the ensemble of functionally-relevant transitions in protein systems with a robotics-inspired method. BMC STRUCTURAL BIOLOGY 2013; 13 Suppl 1:S8. [PMID: 24565158 PMCID: PMC3952944 DOI: 10.1186/1472-6807-13-s1-s8] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Background Many proteins tune their biological function by transitioning between different functional states, effectively acting as dynamic molecular machines. Detailed structural characterization of transition trajectories is central to understanding the relationship between protein dynamics and function. Computational approaches that build on the Molecular Dynamics framework are in principle able to model transition trajectories at great detail but also at considerable computational cost. Methods that delay consideration of dynamics and focus instead on elucidating energetically-credible conformational paths connecting two functionally-relevant structures provide a complementary approach. Effective sampling-based path planning methods originating in robotics have been recently proposed to produce conformational paths. These methods largely model short peptides or address large proteins by simplifying conformational space. Methods We propose a robotics-inspired method that connects two given structures of a protein by sampling conformational paths. The method focuses on small- to medium-size proteins, efficiently modeling structural deformations through the use of the molecular fragment replacement technique. In particular, the method grows a tree in conformational space rooted at the start structure, steering the tree to a goal region defined around the goal structure. We investigate various bias schemes over a progress coordinate for balance between coverage of conformational space and progress towards the goal. A geometric projection layer promotes path diversity. A reactive temperature scheme allows sampling of rare paths that cross energy barriers. Results and conclusions Experiments are conducted on small- to medium-size proteins of length up to 214 amino acids and with multiple known functionally-relevant states, some of which are more than 13Å apart of each-other. Analysis reveals that the method effectively obtains conformational paths connecting structural states that are significantly different. A detailed analysis on the depth and breadth of the tree suggests that a soft global bias over the progress coordinate enhances sampling and results in higher path diversity. The explicit geometric projection layer that biases the exploration away from over-sampled regions further increases coverage, often improving proximity to the goal by forcing the exploration to find new paths. The reactive temperature scheme is shown effective in increasing path diversity, particularly in difficult structural transitions with known high-energy barriers.
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Al-Bluwi I, Vaisset M, Siméon T, Cortés J. Modeling protein conformational transitions by a combination of coarse-grained normal mode analysis and robotics-inspired methods. BMC STRUCTURAL BIOLOGY 2013; 13 Suppl 1:S2. [PMID: 24564964 PMCID: PMC3953241 DOI: 10.1186/1472-6807-13-s1-s2] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
BACKGROUND Obtaining atomic-scale information about large-amplitude conformational transitions in proteins is a challenging problem for both experimental and computational methods. Such information is, however, important for understanding the mechanisms of interaction of many proteins. METHODS This paper presents a computationally efficient approach, combining methods originating from robotics and computational biophysics, to model protein conformational transitions. The ability of normal mode analysis to predict directions of collective, large-amplitude motions is applied to bias the conformational exploration performed by a motion planning algorithm. To reduce the dimension of the problem, normal modes are computed for a coarse-grained elastic network model built on short fragments of three residues. Nevertheless, the validity of intermediate conformations is checked using the all-atom model, which is accurately reconstructed from the coarse-grained one using closed-form inverse kinematics. RESULTS Tests on a set of ten proteins demonstrate the ability of the method to model conformational transitions of proteins within a few hours of computing time on a single processor. These results also show that the computing time scales linearly with the protein size, independently of the protein topology. Further experiments on adenylate kinase show that main features of the transition between the open and closed conformations of this protein are well captured in the computed path. CONCLUSIONS The proposed method enables the simulation of large-amplitude conformational transitions in proteins using very few computational resources. The resulting paths are a first approximation that can directly provide important information on the molecular mechanisms involved in the conformational transition. This approximation can be subsequently refined and analyzed using state-of-the-art energy models and molecular modeling methods.
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Affiliation(s)
- Ibrahim Al-Bluwi
- CNRS, LAAS, 7 avenue du colonel Roche, F-31400 Toulouse, France
- Univ de Toulouse, LAAS, F-31400 Toulouse, France
| | - Marc Vaisset
- CNRS, LAAS, 7 avenue du colonel Roche, F-31400 Toulouse, France
- Univ de Toulouse, LAAS, F-31400 Toulouse, France
| | - Thierry Siméon
- CNRS, LAAS, 7 avenue du colonel Roche, F-31400 Toulouse, France
- Univ de Toulouse, LAAS, F-31400 Toulouse, France
| | - Juan Cortés
- CNRS, LAAS, 7 avenue du colonel Roche, F-31400 Toulouse, France
- Univ de Toulouse, LAAS, F-31400 Toulouse, France
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Campañá C, Miller RE. Transiting the molecular potential energy surface along low energy pathways: The TRREAT algorithm. J Comput Chem 2013; 34:2502-13. [DOI: 10.1002/jcc.23408] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2013] [Revised: 06/20/2013] [Accepted: 07/21/2013] [Indexed: 11/09/2022]
Affiliation(s)
- Carlos Campañá
- Department of Mechanical and Aerospace Engineering; Carleton University; Ottawa K1S 5B6 Canada
| | - Ronald E. Miller
- Department of Mechanical and Aerospace Engineering; Carleton University; Ottawa K1S 5B6 Canada
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Devaurs D, Bouard L, Vaisset M, Zanon C, Al-Bluwi I, Iehl R, Siméon T, Cortés J. MoMA-LigPath: a web server to simulate protein-ligand unbinding. Nucleic Acids Res 2013; 41:W297-302. [PMID: 23671332 PMCID: PMC3692135 DOI: 10.1093/nar/gkt380] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Protein–ligand interactions taking place far away from the active site, during ligand binding or release, may determine molecular specificity and activity. However, obtaining information about these interactions with experimental or computational methods remains difficult. The computational tool presented in this article, MoMA-LigPath, is based on a mechanistic representation of the molecular system, considering partial flexibility, and on the application of a robotics-inspired algorithm to explore the conformational space. Such a purely geometric approach, together with the efficiency of the exploration algorithm, enables the simulation of ligand unbinding within short computing time. Ligand unbinding pathways generated by MoMA-LigPath are a first approximation that can provide useful information about protein–ligand interactions. When needed, this approximation can be subsequently refined and analyzed using state-of-the-art energy models and molecular modeling methods. MoMA-LigPath is available at http://moma.laas.fr. The web server is free and open to all users, with no login requirement.
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Affiliation(s)
- Didier Devaurs
- CNRS, LAAS, 7 av du colonel Roche, F-31400 Toulouse, France
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Porta JM, Jaillet L. Exploring the energy landscapes of flexible molecular loops using higher-dimensional continuation. J Comput Chem 2012; 34:234-44. [PMID: 23015474 DOI: 10.1002/jcc.23128] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2012] [Revised: 08/06/2012] [Accepted: 08/30/2012] [Indexed: 12/27/2022]
Abstract
The conformational space of a flexible molecular loop includes the set of conformations fulfilling the geometric loop-closure constraints and its energy landscape can be seen as a scalar field defined on this implicit set. Higher-dimensional continuation tools, recently developed in dynamical systems and also applied to robotics, provide efficient algorithms to trace out implicitly defined sets. This article describes these tools and applies them to obtain full descriptions of the energy landscapes of short molecular loops that, otherwise, can only be partially explored, mainly via sampling. Moreover, to deal with larger loops, this article exploits the higher-dimensional continuation tools to find local minima and minimum energy transition paths between them, without deviating from the loop-closure constraints. The proposed techniques are applied to previously studied molecules revealing the intricate structure of their energy landscapes.
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Affiliation(s)
- Josep M Porta
- Institut de Robótica i Informática Industrial, UPC-CSIC, Llorens Artigas 4-6, 08028 Barcelona, Spain.
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