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Challapa-Mamani MR, Tomás-Alvarado E, Espinoza-Baigorria A, León-Figueroa DA, Sah R, Rodriguez-Morales AJ, Barboza JJ. Molecular Docking and Molecular Dynamics Simulations in Related to Leishmania donovani: An Update and Literature Review. Trop Med Infect Dis 2023; 8:457. [PMID: 37888585 PMCID: PMC10610989 DOI: 10.3390/tropicalmed8100457] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 09/19/2023] [Accepted: 09/20/2023] [Indexed: 10/28/2023] Open
Abstract
Leishmaniasis, a disease caused by Leishmania parasites and transmitted via sandflies, presents in two main forms: cutaneous and visceral, the latter being more severe. With 0.7 to 1 million new cases each year, primarily in Brazil, diagnosing remains challenging due to diverse disease manifestations. Traditionally, the identification of Leishmania species is inferred from clinical and epidemiological data. Advances in disease management depend on technological progress and the improvement of parasite identification programs. Current treatments, despite the high incidence, show limited efficacy due to factors like cost, toxicity, and lengthy regimens causing poor adherence and resistance development. Diagnostic techniques have improved but a significant gap remains between scientific progress and application in endemic areas. Complete genomic sequence knowledge of Leishmania allows for the identification of therapeutic targets. With the aid of computational tools, testing, searching, and detecting affinity in molecular docking are optimized, and strategies that assess advantages among different options are developed. The review focuses on the use of molecular docking and molecular dynamics (MD) simulation for drug development. It also discusses the limitations and advancements of current treatments, emphasizing the importance of new techniques in improving disease management.
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Affiliation(s)
- Mabel R. Challapa-Mamani
- Escuela de Medicina, Universidad Cesar Vallejo, Trujillo 13007, Peru;
- Sociedad Científica de Estudiantes de Medicina de la Universidad César Vallejo, Trujillo 13007, Peru
| | - Eduardo Tomás-Alvarado
- Hospital General Regional 17, Instituto Mexicano del Seguro Social, Cancún 75533, Mexico;
| | | | | | - Ranjit Sah
- Department of Clinical Microbiology, Institute of Medicine, Tribhuvan University Teaching Hospital, Kathmandu 44600, Nepal;
- Department of Microbiology, Dr. D. Y. Patil Medical College, Hospital and Research Centre, Dr. D. Y. Patil Vidyapeeth, Pune 411018, Maharashtra, India
| | - Alfonso J. Rodriguez-Morales
- Faculty of Health Sciences, Universidad Científica del Sur, Lima 150152, Peru;
- Gilbert and Rose-Marie Chagoury School of Medicine, Lebanese American University, Beirut 350000, Lebanon
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2
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Sabei A, Caldas Baia TG, Saffar R, Martin J, Frezza E. Internal Normal Mode Analysis Applied to RNA Flexibility and Conformational Changes. J Chem Inf Model 2023; 63:2554-2572. [PMID: 36972178 DOI: 10.1021/acs.jcim.2c01509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/29/2023]
Abstract
We investigated the capability of internal normal modes to reproduce RNA flexibility and predict observed RNA conformational changes and, notably, those induced by the formation of RNA-protein and RNA-ligand complexes. Here, we extended our iNMA approach developed for proteins to study RNA molecules using a simplified representation of the RNA structure and its potential energy. Three data sets were also created to investigate different aspects. Despite all the approximations, our study shows that iNMA is a suitable method to take into account RNA flexibility and describe its conformational changes opening the route to its applicability in any integrative approach where these properties are crucial.
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3
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van Keulen SC, Martin J, Colizzi F, Frezza E, Trpevski D, Diaz NC, Vidossich P, Rothlisberger U, Hellgren Kotaleski J, Wade RC, Carloni P. Multiscale molecular simulations to investigate adenylyl cyclase‐based signaling in the brain. WIRES COMPUTATIONAL MOLECULAR SCIENCE 2022. [DOI: 10.1002/wcms.1623] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Affiliation(s)
- Siri C. van Keulen
- Computational Structural Biology Group, Bijvoet Center for Biomolecular Research, Science for Life, Faculty of Science – Chemistry Utrecht University Utrecht The Netherlands
| | - Juliette Martin
- CNRS, UMR 5086 Molecular Microbiology and Structural Biochemistry University of Lyon Lyon France
| | - Francesco Colizzi
- Molecular Ocean Laboratory, Department of Marine Biology and Oceanography Institute of Marine Sciences, ICM‐CSIC Barcelona Spain
| | - Elisa Frezza
- Université Paris Cité, CiTCoM, CNRS Paris France
| | - Daniel Trpevski
- Science for Life Laboratory, School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm
| | - Nuria Cirauqui Diaz
- CNRS, UMR 5086 Molecular Microbiology and Structural Biochemistry University of Lyon Lyon France
| | - Pietro Vidossich
- Molecular Modeling and Drug Discovery Lab Istituto Italiano di Tecnologia Genoa Italy
| | - Ursula Rothlisberger
- Laboratory of Computational Chemistry and Biochemistry Ecole Polytechnique Fédérale de Lausanne (EPFL) Lausanne
| | - Jeanette Hellgren Kotaleski
- Science for Life Laboratory, School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm
- Department of Neuroscience Karolinska Institute Stockholm
| | - Rebecca C. Wade
- Molecular and Cellular Modeling Group Heidelberg Institute for Theoretical Studies (HITS) Heidelberg Germany
- Center for Molecular Biology (ZMBH), DKFZ‐ZMBH Alliance, and Interdisciplinary Center for Scientific Computing (IWR) Heidelberg University Heidelberg Germany
| | - Paolo Carloni
- Institute for Neuroscience and Medicine (INM‐9) and Institute for Advanced Simulations (IAS‐5) “Computational biomedicine” Forschungszentrum Jülich Jülich Germany
- INM‐11 JARA‐Institute: Molecular Neuroscience and Neuroimaging Forschungszentrum Jülich Jülich Germany
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4
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Karaca E, Prévost C, Sacquin-Mora S. Modeling the Dynamics of Protein–Protein Interfaces, How and Why? Molecules 2022; 27:molecules27061841. [PMID: 35335203 PMCID: PMC8950966 DOI: 10.3390/molecules27061841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2022] [Revised: 03/06/2022] [Accepted: 03/08/2022] [Indexed: 12/07/2022] Open
Abstract
Protein–protein assemblies act as a key component in numerous cellular processes. Their accurate modeling at the atomic level remains a challenge for structural biology. To address this challenge, several docking and a handful of deep learning methodologies focus on modeling protein–protein interfaces. Although the outcome of these methods has been assessed using static reference structures, more and more data point to the fact that the interaction stability and specificity is encoded in the dynamics of these interfaces. Therefore, this dynamics information must be taken into account when modeling and assessing protein interactions at the atomistic scale. Expanding on this, our review initially focuses on the recent computational strategies aiming at investigating protein–protein interfaces in a dynamic fashion using enhanced sampling, multi-scale modeling, and experimental data integration. Then, we discuss how interface dynamics report on the function of protein assemblies in globular complexes, in fuzzy complexes containing intrinsically disordered proteins, as well as in active complexes, where chemical reactions take place across the protein–protein interface.
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Affiliation(s)
- Ezgi Karaca
- Izmir Biomedicine and Genome Center, Izmir 35340, Turkey;
- Izmir International Biomedicine and Genome Institute, Dokuz Eylul University, Izmir 35340, Turkey
| | - Chantal Prévost
- CNRS, Laboratoire de Biochimie Théorique, UPR9080, Université de Paris, 13 rue Pierre et Marie Curie, 75005 Paris, France;
- Institut de Biologie Physico-Chimique, Fondation Edmond de Rothschild, PSL Research University, 75006 Paris, France
| | - Sophie Sacquin-Mora
- CNRS, Laboratoire de Biochimie Théorique, UPR9080, Université de Paris, 13 rue Pierre et Marie Curie, 75005 Paris, France;
- Institut de Biologie Physico-Chimique, Fondation Edmond de Rothschild, PSL Research University, 75006 Paris, France
- Correspondence:
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5
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Sanejouand YH. Normal-mode driven exploration of protein domain motions. J Comput Chem 2021; 42:2250-2257. [PMID: 34599620 DOI: 10.1002/jcc.26755] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 07/02/2021] [Accepted: 09/05/2021] [Indexed: 12/27/2022]
Abstract
Domain motions involved in the function of proteins can often be well described as a combination of motions along a handfull of low-frequency modes, that is, with the values of a few normal coordinates. This means that, when the functional motion of a protein is unknown, it should prove possible to predict it, since it amounts to guess a few values. However, without the help of additional experimental data, using normal coordinates for generating accurate conformers far away from the initial one is not so straightforward. To do so, a new approach is proposed: instead of building conformers directly with the values of a subset of normal coordinates, they are built in two steps, the conformer built with normal coordinates being just used for defining a set of distance constraints, the final conformer being built so as to match them. Note that this approach amounts to transform the problem of generating accurate protein conformers using normal coordinates into a better known one: the distance-geometry problem, which is herein solved with the help of the ROSETTA software. In the present study, this approach allowed to rebuild accurately six large amplitude conformational changes, using at most six low-frequency normal coordinates. As a consequence of the low-dimensionality of the corresponding subspace, random exploration also proved enough for generating low-energy conformers close to the known end-point of the conformational change of the LAO binding protein, lysozyme T4 and adenylate kinase.
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Lee BH, Park SW, Jo S, Kim MK. Protein conformational transitions explored by a morphing approach based on normal mode analysis in internal coordinates. PLoS One 2021; 16:e0258818. [PMID: 34735476 PMCID: PMC8568156 DOI: 10.1371/journal.pone.0258818] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Accepted: 10/05/2021] [Indexed: 11/19/2022] Open
Abstract
Large-scale conformational changes are essential for proteins to function properly. Given that these transition events rarely occur, however, it is challenging to comprehend their underlying mechanisms through experimental and theoretical approaches. In this study, we propose a new computational methodology called internal coordinate normal mode-guided elastic network interpolation (ICONGENI) to predict conformational transition pathways in proteins. Its basic approach is to sample intermediate conformations by interpolating the interatomic distance between two end-point conformations with the degrees of freedom constrained by the low-frequency dynamics afforded by normal mode analysis in internal coordinates. For validation of ICONGENI, it is applied to proteins that undergo open-closed transitions, and the simulation results (i.e., simulated transition pathways) are compared with those of another technique, to demonstrate that ICONGENI can explore highly reliable pathways in terms of thermal and chemical stability. Furthermore, we generate an ensemble of transition pathways through ICONGENI and investigate the possibility of using this method to reveal the transition mechanisms even when there are unknown metastable states on rough energy landscapes.
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Affiliation(s)
- Byung Ho Lee
- School of Mechanical Engineering, Sungkyunkwan University, Suwon, South Korea
| | - Soon Woo Park
- School of Mechanical Engineering, Sungkyunkwan University, Suwon, South Korea
| | - Soojin Jo
- Department of Physics and Institute of Basic Science, Sungkyunkwan University, Suwon, South Korea
| | - Moon Ki Kim
- School of Mechanical Engineering, Sungkyunkwan University, Suwon, South Korea
- Sungkyunkwan Advanced Institute of Nanotechnology (SAINT), Sungkyunkwan University, Suwon, South Korea
- * E-mail:
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7
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Jourdi G, Abdoul J, Siguret V, Decleves X, Frezza E, Pailleret C, Gouin-Thibault I, Gandrille S, Neveux N, Samama CM, Pasquali S, Gaussem P. Induced forms of α 2-macroglobulin neutralize heparin and direct oral anticoagulant effects. Int J Biol Macromol 2021; 184:209-217. [PMID: 34126147 DOI: 10.1016/j.ijbiomac.2021.06.058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Revised: 06/07/2021] [Accepted: 06/08/2021] [Indexed: 10/21/2022]
Abstract
Alpha2-macroglobulin (α2M) is a physiological macromolecule that facilitates the clearance of many proteinases, cytokines and growth factors in human. Here, we explored the effect of induced forms of α2M on anticoagulant drugs. Gla-domainless factor Xa (GDFXa) and methylamine (MA)-induced α2M were prepared and characterized by electrophoresis, immunonephelometry, chromogenic, clot waveform and rotational thromboelastometry assays. Samples from healthy volunteers and anticoagulated patients were included. In vivo neutralization of anticoagulants was evaluated in C57Bl/6JRj mouse bleeding-model. Anticoagulant binding sites on induced α2M were depicted by computer-aided energy minimization modeling. GDFXa-induced α2M neutralized dabigatran and heparins in plasma and whole blood. In mice, a single IV dose of GDFXa-induced α2M following anticoagulant administration significantly reduced blood loss and bleeding time. Being far easier to prepare, we investigated the efficacy of MA-induced α2M. It neutralized rivaroxaban, apixaban, dabigatran and heparins in spiked samples in a concentration-dependent manner and in samples from treated patients. Molecular docking analysis evidenced the ability of MA-induced α2M to bind non-covalently these compounds via some deeply buried binding sites. Induced forms of α2M have the potential to neutralize direct oral anticoagulants and heparins, and might be developed as a universal antidote in case of major bleeding or urgent surgery.
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Affiliation(s)
- Georges Jourdi
- Université de Paris, Innovative Therapies in Haemostasis, INSERM UMR_S1140, F-75006, Paris, France; AP-HP. Centre-Université de Paris, Hôpital Cochin, F-75014, Paris, France; Research Centre, Montreal Heart Institute, University of Montreal, Faculty of Pharmacy, Montreal, Canada.
| | - Johan Abdoul
- Université de Paris, Innovative Therapies in Haemostasis, INSERM UMR_S1140, F-75006, Paris, France
| | - Virginie Siguret
- Université de Paris, Innovative Therapies in Haemostasis, INSERM UMR_S1140, F-75006, Paris, France; AP-HP. Nord-Université de Paris, Hôpital Lariboisière, F-75010 Paris, France
| | - Xavier Decleves
- AP-HP. Centre-Université de Paris, Hôpital Cochin, F-75014, Paris, France; Université de Paris, Variabilité de réponse aux psychotropes, INSERM UMR_S1144, F-75006 Paris, France
| | - Elisa Frezza
- Laboratoire CiTCoM, Université de Paris, CNRS, F-75006 Paris, France
| | - Claire Pailleret
- Université de Paris, Innovative Therapies in Haemostasis, INSERM UMR_S1140, F-75006, Paris, France; Clinique du Mont Louis, F-75011 Paris, France
| | - Isabelle Gouin-Thibault
- Laboratoire d'hématologie, CHU Pontchaillou, Université de Rennes 1, CIC-Inserm1414, F-35000 Rennes, France
| | - Sophie Gandrille
- Université de Paris, Innovative Therapies in Haemostasis, INSERM UMR_S1140, F-75006, Paris, France; AP-HP. Centre-Université de Paris, Hôpital Européen Georges Pompidou, F-75015 Paris, France
| | - Nathalie Neveux
- AP-HP. Centre-Université de Paris, Hôpital Cochin, F-75014, Paris, France
| | - Charles Marc Samama
- Université de Paris, Innovative Therapies in Haemostasis, INSERM UMR_S1140, F-75006, Paris, France; AP-HP. Centre-Université de Paris, Hôpital Cochin, F-75014, Paris, France
| | - Samuela Pasquali
- Laboratoire CiTCoM, Université de Paris, CNRS, F-75006 Paris, France
| | - Pascale Gaussem
- Université de Paris, Innovative Therapies in Haemostasis, INSERM UMR_S1140, F-75006, Paris, France; AP-HP. Centre-Université de Paris, Hôpital Européen Georges Pompidou, F-75015 Paris, France.
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8
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Garcia Michel LR, Keirns CD, Ahlbrecht BC, Barr DA. Calculating Transfer Entropy from Variance-Covariance Matrices Provides Insight into Allosteric Communication in ERK2. J Chem Theory Comput 2021; 17:3168-3177. [PMID: 33929855 DOI: 10.1021/acs.jctc.1c00004] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
We develop an approach by which reliable estimates of the transfer entropy can be obtained from the variance-covariance matrix of atomic fluctuations, which converges quickly and retains sensitivity to the full chemical profile of the biomolecular system. We validate our method on ERK2, a well-studied kinase involved in the MAPK signaling cascade for which considerable computational, experimental, and mutation data are available. We present the results of transfer entropy analysis on data obtained from molecular dynamics simulations of wild-type active and inactive ERK2, along with mutants Q103A, I84A, L73P, and G83A. We show that our method is systematically consistent within the context of other approaches for calculating transfer entropy, and we provide a method for interpreting networks of interconnected residues in the protein from a perspective of allosteric coupling. We introduce new insights about possible allosteric activity of the extreme N-terminal region of the kinase, and we describe evidence that suggests that activation may occur by different paths or routes in different mutants. Our results highlight systematic advantages and disadvantages of each method for calculating transfer entropy and show the important role of transfer entropy analysis for understanding allosteric behavior in biomolecular systems.
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Affiliation(s)
- Luisa R Garcia Michel
- Department of Chemistry, University of Mary, Bismarck, North Dakota 58504, United States
| | - Clara D Keirns
- Department of Chemistry, University of Mary, Bismarck, North Dakota 58504, United States
| | - Benjamin C Ahlbrecht
- Department of Chemistry, University of Mary, Bismarck, North Dakota 58504, United States
| | - Daniel A Barr
- Department of Chemistry, University of Mary, Bismarck, North Dakota 58504, United States
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9
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Laine E, Grudinin S. HOPMA: Boosting Protein Functional Dynamics with Colored Contact Maps. J Phys Chem B 2021; 125:2577-2588. [PMID: 33687221 DOI: 10.1021/acs.jpcb.0c11633] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
In light of the recent very rapid progress in protein structure prediction, accessing the multitude of functional protein states is becoming more central than ever before. Indeed, proteins are flexible macromolecules, and they often perform their function by switching between different conformations. However, high-resolution experimental techniques such as X-ray crystallography and cryogenic electron microscopy can catch relatively few protein functional states. Many others are only accessible under physiological conditions in solution. Therefore, there is a pressing need to fill this gap with computational approaches. We present HOPMA, a novel method to predict protein functional states and transitions by using a modified elastic network model. The method exploits patterns in a protein contact map, taking its 3D structure as input, and excludes some disconnected patches from the elastic network. Combined with nonlinear normal mode analysis, this strategy boosts the protein conformational space exploration, especially when the input structure is highly constrained, as we demonstrate on a set of more than 400 transitions. Our results let us envision the discovery of new functional conformations, which were unreachable previously, starting from the experimentally known protein structures. The method is computationally efficient and available at https://github.com/elolaine/HOPMA and https://team.inria.fr/nano-d/software/nolb-normal-modes.
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Affiliation(s)
- Elodie Laine
- CNRS, IBPS, Laboratoire de Biologie Computationnelle et Quantitative (LCQB), Sorbonne Université, 75005 Paris, France
| | - Sergei Grudinin
- CNRS, Inria, Grenoble INP, LJK, Univ. Grenoble Alpes, 38000 Grenoble, France
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Harmalkar A, Gray JJ. Advances to tackle backbone flexibility in protein docking. Curr Opin Struct Biol 2020; 67:178-186. [PMID: 33360497 DOI: 10.1016/j.sbi.2020.11.011] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Revised: 11/18/2020] [Accepted: 11/25/2020] [Indexed: 12/11/2022]
Abstract
Computational docking methods can provide structural models of protein-protein complexes, but protein backbone flexibility upon association often thwarts accurate predictions. In recent blind challenges, medium or high accuracy models were submitted in less than 20% of the 'difficult' targets (with significant backbone change or uncertainty). Here, we describe recent developments in protein-protein docking and highlight advances that tackle backbone flexibility. In molecular dynamics and Monte Carlo approaches, enhanced sampling techniques have reduced time-scale limitations. Internal coordinate formulations can now capture realistic motions of monomers and complexes using harmonic dynamics. And machine learning approaches adaptively guide docking trajectories or generate novel binding site predictions from deep neural networks trained on protein interfaces. These tools poise the field to break through the longstanding challenge of correctly predicting complex structures with significant conformational change.
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Affiliation(s)
- Ameya Harmalkar
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Jeffrey J Gray
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, USA; Program in Molecular Biophysics, Institute for Nanobiotechnology, and Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA.
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11
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Cirauqui Diaz N, Frezza E, Martin J. Using normal mode analysis on protein structural models. How far can we go on our predictions? Proteins 2020; 89:531-543. [PMID: 33349977 DOI: 10.1002/prot.26037] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Accepted: 12/12/2020] [Indexed: 01/01/2023]
Abstract
Normal mode analysis (NMA) is a fast and inexpensive approach that is largely used to gain insight into functional protein motions, and more recently to create conformations for further computational studies. However, when the protein structure is unknown, the use of computational models is necessary. Here, we analyze the capacity of NMA in internal coordinate space to predict protein motion, its intrinsic flexibility, and atomic displacements, using protein models instead of native structures, and the possibility to use it for model refinement. Our results show that NMA is quite insensitive to modeling errors, but that calculations are strictly reliable only for very accurate models. Our study also suggests that internal NMA is a more suitable tool for the improvement of structural models, and for integrating them with experimental data or in other computational techniques, such as protein docking or more refined molecular dynamics simulations.
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Affiliation(s)
- Nuria Cirauqui Diaz
- CNRS, UMR 5086 Molecular Microbiology and Structural Biochemistry, Université de Lyon, Lyon, France
| | - Elisa Frezza
- CiTCoM, CNRS, Université de Paris, Paris, France
| | - Juliette Martin
- CNRS, UMR 5086 Molecular Microbiology and Structural Biochemistry, Université de Lyon, Lyon, France
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12
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Zou W, Tao Y, Kraka E. Systematic description of molecular deformations with Cremer-Pople puckering and deformation coordinates utilizing analytic derivatives: Applied to cycloheptane, cyclooctane, and cyclo[18]carbon. J Chem Phys 2020; 152:154107. [PMID: 32321269 DOI: 10.1063/1.5144278] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
The conformational properties of ring compounds such as cycloalkanes determine to a large extent their stability and reactivity. Therefore, the investigation of conformational processes such as ring inversion and/or ring pseudorotation has attracted a lot of attention over the past decades. An in-depth conformational analysis of ring compounds requires mapping the relevant parts of the conformational energy surface at stationary and also at non-stationary points. However, the latter is not feasible by a description of the ring with Cartesian or internal coordinates. We provide in this work, a solution to this problem by introducing a new coordinate system based on the Cremer-Pople puckering and deformation coordinates. Furthermore, analytic first- and second-order derivatives of puckering and deformation coordinates, i.e., B-matrices and D-tensors, were developed simplifying geometry optimization and frequency calculations. The new coordinate system is applied to map the potential energy surfaces and reaction paths of cycloheptane (C7H14), cyclooctane (C8H16), and cyclo[18]carbon (C18) at the quantum chemical level and to determine for the first time all stationary points of these ring compounds in a systematic way.
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Affiliation(s)
- Wenli Zou
- Computational and Theoretical Chemistry Group (CATCO), Department of Chemistry, Southern Methodist University, 3215 Daniel Ave., Dallas, Texas 75275-0314, USA
| | - Yunwen Tao
- Computational and Theoretical Chemistry Group (CATCO), Department of Chemistry, Southern Methodist University, 3215 Daniel Ave., Dallas, Texas 75275-0314, USA
| | - Elfi Kraka
- Computational and Theoretical Chemistry Group (CATCO), Department of Chemistry, Southern Methodist University, 3215 Daniel Ave., Dallas, Texas 75275-0314, USA
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Bastolla U, Dehouck Y. Can Conformational Changes of Proteins Be Represented in Torsion Angle Space? A Study with Rescaled Ridge Regression. J Chem Inf Model 2019; 59:4929-4941. [PMID: 31600071 DOI: 10.1021/acs.jcim.9b00627] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Torsion angles are the natural degrees of freedom of protein structures. The ability to determine torsional variations corresponding to observed changes in Cartesian coordinates is highly valuable, notably to investigate the mechanisms of functional conformational changes or to develop computational models of protein dynamics. This issue is far from trivial in practice since the impact of modifying one torsion angle strongly depends on all other angles, and the compounding effects of small variations in bond lengths and valence angles can completely disrupt a protein fold. We demonstrate that naive strategies, such as directly comparing torsion angles between structures without correcting for variations in bond lengths and valence angles or fitting torsional variations without a proper regularization scheme, fail at producing an adequate representation of conformational changes in internal coordinates. In contrast, rescaled ridge regression, a method recently introduced to regularize multidimensional regressions with correlated explanatory variables, is shown to consistently identify a minimal set of torsion angles variations that closely reproduce changes in Cartesian coordinates. This torsional representation of conformational changes is shown to be robust to the choice of experimental structures. It also provides a better agreement with theoretical models of protein dynamics than the Cartesian representation, regarding notably the predominance of low-frequency normal modes in functional motions and the presence, in predicted equilibrium dynamics, of hints of natural selection for specific functional motions. The software is available at https://github.com/ugobas/tnm .
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Affiliation(s)
- Ugo Bastolla
- Centro de Biologia Molecular "Severo Ochoa", CSIC-UAM Cantoblanco , 28049 Madrid , Spain
| | - Yves Dehouck
- Centro de Biologia Molecular "Severo Ochoa", CSIC-UAM Cantoblanco , 28049 Madrid , Spain
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