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Your search keyword '"de Brevern, Alexandre"' showing total 16 results
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16 results on '"de Brevern, Alexandre"'

15. Structural variations within proteins can be as large as variations observed across their homologues

Author

Narayanaswamy Srinivasan, Bernard Offmann, Iyanar Vetrivel, Frédéric Cadet, Alexandre G. de Brevern, de Brevern, Alexandre G., Université de Paris - - Université de Paris2018 - ANR-18-IDEX-0001 - IDEX - VALID, Université Sorbonne Paris Cité - - USPC2011 - ANR-11-IDEX-0005 - IDEX - VALID, Unité de fonctionnalité et ingénierie de protéines (UFIP), Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Université de Nantes (UN)-Université de Nantes (UN)-Centre National de la Recherche Scientifique (CNRS), Biologie Intégrée du Globule Rouge (BIGR (UMR_S_1134 / U1134)), Institut National de la Transfusion Sanguine [Paris] (INTS)-Université de La Réunion (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pointe-à-Pitre/Abymes [Guadeloupe] -Université des Antilles (UA)-Université Paris Cité (UPCité), Institut National de la Transfusion Sanguine [Paris] (INTS), Laboratoire d'Excellence : Biogenèse et pathologies du globule rouge (Labex Gr-Ex), Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), Dynamique des Structures et Interactions des Macromolécules Biologiques - Pôle de La Réunion (DSIMB Réunion), Institut National de la Transfusion Sanguine [Paris] (INTS)-Université Paris Diderot - Paris 7 (UPD7)-Université de La Réunion (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université des Antilles (UA)-Institut National de la Transfusion Sanguine [Paris] (INTS)-Université Paris Diderot - Paris 7 (UPD7)-Université de La Réunion (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université des Antilles (UA), PEACCEL, Molecular Biophysics Unit, Indian Institute of Science, Région Réunion and the Fond Social Européen, Conseil Regional des Pays de la Loire in the framework of GRIOTE project, the Ministry of Research (France), University de Paris, University Paris Diderot, Sorbonne, Paris Cité (France), National Institute for Blood Transfusion (INTS, France), National Institute for Health and Medical Research (INSERM, France), Université de La Réunion, Faculty of Sciences and Technology, Indo-French Centre for the Promotion of Advanced Research / CEFIPRA for collaborative grant (number 5302-2), Department of Biotechnology, Government of India, J.C. Bose National Fellow, ANR-18-IDEX-0001,Université de Paris,Université de Paris(2018), ANR-11-IDEX-0005,USPC,Université Sorbonne Paris Cité(2011), Institut National de la Transfusion Sanguine [Paris] (INTS)-Université de La Réunion (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pointe-à-Pitre/Abymes [Guadeloupe] -Université des Antilles (UA)-Université de Paris (UP), and Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP)

Subjects
0301 basic medicine, Structural alphabet, [SDV]Life Sciences [q-bio], Datasets as Topic, Molecular Dynamics Simulation, Molecular dynamics, Biochemistry, Mice, 03 medical and health sciences, Protein structural variation, Protein structure, Protein Domains, [SDV.BBM] Life Sciences [q-bio]/Biochemistry, Molecular Biology, Animals, Humans, [SDV.BBM]Life Sciences [q-bio]/Biochemistry, Molecular Biology, Databases, Protein, [SDV.BIBS] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Bacteria, 030102 biochemistry & molecular biology, Chemistry, Proteins, General Medicine, Protein superfamily, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Nmr data, [SDV] Life Sciences [q-bio], 030104 developmental biology, Protein conformation, Structural Homology, Protein, Structural plasticity, Biophysics
Abstract

International audience; Understanding the structural plasticity of proteins is key to understanding the intricacies of their functions and mechanistic basis. In the current study, we analyzed the available multiple crystal structures of the same protein for the structural differences. For this purpose we used an abstraction of protein structures referred as Protein Blocks (PBs) that was previously established. We also characterized the nature of the structural variations for a few proteins using molecular dynamics simulations. In both the cases, the structural variations were summarized in the form of substitution matrices of PBs. We show that certain conformational states are preferably replaced by other specific conformational states. Interestingly, these structural variations are highly similar to those previously observed across structures of homologous proteins (r 2 =0.923) or across the ensemble of conformations from NMR data (r 2 =0.919). Thus our study quantitatively shows that overall trends of structural changes in a given protein are nearly identical to the trends of structural differences that occur in the topologically equivalent positions in homologous proteins. Specific case studies are used to illustrate the nature of these structural variations.

Published
2019

16. In silico prediction of protein flexibility with local structure approach

Author

Sylvain Leonard, Pierrick Craveur, Jean-Christophe Gelly, Narayanaswamy Srinivasan, Joseph Rebehmed, Catherine Etchebest, Tarun Jairaj Narwani, Alexandre G. de Brevern, Aurélie Bornot, Biologie Intégrée du Globule Rouge (BIGR (UMR_S_1134 / U1134)), Institut National de la Transfusion Sanguine [Paris] (INTS)-Université Paris Diderot - Paris 7 (UPD7)-Université de La Réunion (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université des Antilles (UA), Institut National de la Transfusion Sanguine [Paris] (INTS), Laboratoire d'Excellence : Biogenèse et pathologies du globule rouge (Labex Gr-Ex), Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP), Scripps Research Institute, Molecular Graphics Laboratory (MGL), Lebanese American University (LAU), Molecular Biophysics Unit, Indian Institute of Science, the Ministry of Research (France), University de Paris, University Paris Diderot, Sorbonne, Paris Cité (France), National Institute for Blood Transfusion (INTS, France), National Institute for Health and Medical Research (INSERM, France), Indo-French Centre for the Promotion of Advanced Research / CEFIPRA for collaborative grant (number 5302-2), French National Computing Centre CINES under grant no. c2013037147 by the GENCI (Grand Equipement National de Calcul Intensif), French National Computing Centre CINES under grant no. c2016077621 by the GENCI (Grand Equipement National de Calcul Intensif), French National Computing Centre CINES under grant no. A0010707621 by the GENCI (Grand Equipement National de Calcul Intensif), ANR-18-IDEX-0001,Université de Paris,Université de Paris(2018), ANR-11-IDEX-0005,USPC,Université Sorbonne Paris Cité(2011), de Brevern, Alexandre G., Université de Paris - - Université de Paris2018 - ANR-18-IDEX-0001 - IDEX - VALID, Université Sorbonne Paris Cité - - USPC2011 - ANR-11-IDEX-0005 - IDEX - VALID, Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), and The Scripps Research Institute [La Jolla, San Diego]

Subjects
0301 basic medicine, Bioinformatics, Protein Conformation, Datasets as Topic, Long Structural Prototypes, Molecular Dynamics Simulation, Biochemistry, Quantitative Biology - Quantitative Methods, 03 medical and health sciences, Matrix (mathematics), Structural bioinformatics, Protein structure, Protein Data Bank, evolutionary information, Support Vector Machines, Feature (machine learning), [SDV.BBM] Life Sciences [q-bio]/Biochemistry, Molecular Biology, [SDV.BBM]Life Sciences [q-bio]/Biochemistry, Molecular Biology, Representation (mathematics), Databases, Protein, Quantitative Methods (q-bio.QM), protein folds, Mathematics, Flexibility (engineering), [SDV.BIBS] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], 030102 biochemistry & molecular biology, Proteins, Biomolecules (q-bio.BM), General Medicine, computer.file_format, disorder, Structural Bioinformatics, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Support vector machine, 030104 developmental biology, Quantitative Biology - Biomolecules, FOS: Biological sciences, structural alphabet, Biological system, computer, amino acid, Software
Abstract

International audience; Flexibility is an intrinsic essential feature of protein structures, directly linked to their functions. To this day, most of the prediction methods use the crystallographic data (namely B-factors) as the only indicator of protein’s inner flexibility and predicts them as rigid or flexible.PredyFlexy stands differently from other approaches as it relies on the definition of protein flexibility (i) not only taken from crystallographic data, but also (ii) from Root Mean Square Fluctuation (RMSFs) observed in Molecular Dynamics simulations. It also uses a specific representation of protein structures, named Long Structural Prototypes (LSPs). From Position-Specific Scoring Matrix, the 120 LSPs are predicted with a good accuracy and directly used to predict (i) the protein flexibility in three categories (flexible, intermediate and rigid), (ii) the normalized B-factors, (iii) the normalized RMSFs, and (iv) a confidence index. Prediction accuracy among these three classes is equivalent to the best two class prediction methods, while the normalized B-factors and normalized RMSFs have a good correlation with experimental and in silico values. Thus, PredyFlexy is a unique approach, which is of major utility for the scientific community. It support parallelization features and can be run on a local cluster using multiple cores.The entire project is available under an open-source license at http://www.dsimb.inserm.fr/~debrevern/TOOLS/predyflexy_1.3/index.php.

Published
2018

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