1
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Abbass J, Parisi C. Machine learning-based prediction of proteins' architecture using sequences of amino acids and structural alphabets. J Biomol Struct Dyn 2024:1-16. [PMID: 38505995 DOI: 10.1080/07391102.2024.2328736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 03/05/2024] [Indexed: 03/21/2024]
Abstract
In addition to the growth of protein structures generated through wet laboratory experiments and deposited in the PDB repository, AlphaFold predictions have significantly contributed to the creation of a much larger database of protein structures. Annotating such a vast number of structures has become an increasingly challenging task. CATH is widely recognized as one the most common platforms for addressing this challenge, as it classifies proteins based on their structural and evolutionary relationships, offering the scientific community an invaluable resource for uncovering various properties, including functional annotations. While CATH annotation involves - to some extent - human intervention, keeping up with the classification of the rapidly expanding repositories of protein structures has become exceedingly difficult. Therefore, there is a pressing need for a fully automated approach. On the other hand, the abundance of protein sequences stemming from next generation sequencing technologies, lacking structural annotations, presents an additional challenge to the scientific community. Consequently, 'pre-annotating' protein sequences with structural features, ensuring a high level of precision, could prove highly advantageous. In this paper, after a thorough investigation, we introduce a novel machine-learning model capable of classifying any protein domain, whether it has a known structure or not, into one of the 40 main CATH Architectures. We achieve an F1 Score of 0.92 using only the amino acid sequence and a score of 0.94 using both the sequence of amino acids and the sequence of structural alphabets.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Jad Abbass
- School of Computer Science and Mathematics, Kingston University, London, UK
| | - Charles Parisi
- School of Computer Science and Mathematics, Kingston University, London, UK
- Telecom Physique Strasbourg, Strasbourg University, Strasbourg, France
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2
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Structural and Dynamic Differences between Calreticulin Mutants Associated with Essential Thrombocythemia. Biomolecules 2023; 13:biom13030509. [PMID: 36979444 PMCID: PMC10046389 DOI: 10.3390/biom13030509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Revised: 02/28/2023] [Accepted: 03/03/2023] [Indexed: 03/12/2023] Open
Abstract
Essential thrombocythemia (ET) is a blood cancer. ET is characterized by an overproduction of platelets that can lead to thrombosis formation. Platelet overproduction occurs in megakaryocytes through a signaling pathway that could involve JAK2, MPL, or CALR proteins. CALR mutations are associated with 25–30% of ET patients; CALR variants must be dimerized to induce ET. We classified these variants into five classes named A to E; classes A and B are the most frequent classes in patients with ET. The dynamic properties of these five classes using structural models of CALR’s C-domain were analyzed using molecular dynamics simulations. Classes A, B, and C are associated with frameshifts in the C-domain. Their dimers can be stable only if a disulfide bond is formed; otherwise, the two monomers repulse each other. Classes D and E cannot be stable as dimers due to the absence of disulfide bonds. Class E and wild-type CALR have similar dynamic properties. These results suggest that the disulfide bond newly formed in classes A, B, and C may be essential for the pathogenicity of these variants. They also underline that class E cannot be directly related to ET but corresponds to human polymorphisms.
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3
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Analysis of Integrin α IIb Subunit Dynamics Reveals Long-Range Effects of Missense Mutations on Calf Domains. Int J Mol Sci 2022; 23:ijms23020858. [PMID: 35055046 PMCID: PMC8776176 DOI: 10.3390/ijms23020858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 12/23/2021] [Accepted: 12/30/2021] [Indexed: 11/17/2022] Open
Abstract
Integrin αIIbβ3, a glycoprotein complex expressed at the platelet surface, is involved in platelet aggregation and contributes to primary haemostasis. Several integrin αIIbβ3 polymorphisms prevent the aggregation that causes haemorrhagic syndromes, such as Glanzmann thrombasthenia (GT). Access to 3D structure allows understanding the structural effects of polymorphisms related to GT. In a previous analysis using Molecular Dynamics (MD) simulations of αIIbCalf-1 domain structure, it was observed that GT associated with single amino acid variation affects distant loops, but not the mutated position. In this study, experiments are extended to Calf-1, Thigh, and Calf-2 domains. Two loops in Calf-2 are unstructured and therefore are modelled expertly using biophysical restraints. Surprisingly, MD revealed the presence of rigid zones in these loops. Detailed analysis with structural alphabet, the Proteins Blocks (PBs), allowed observing local changes in highly flexible regions. The variant P741R located at C-terminal of Calf-1 revealed that the Calf-2 presence did not affect the results obtained with isolated Calf-1 domain. Simulations for Calf-1 + Calf-2, and Thigh + Calf-1 variant systems are designed to comprehend the impact of five single amino acid variations in these domains. Distant conformational changes are observed, thus highlighting the potential role of allostery in the structural basis of GT.
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4
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Melarkode Vattekatte A, Shinada NK, Narwani TJ, Noël F, Bertrand O, Meyniel JP, Malpertuy A, Gelly JC, Cadet F, de Brevern AG. Discrete analysis of camelid variable domains: sequences, structures, and in-silico structure prediction. PeerJ 2020; 8:e8408. [PMID: 32185102 PMCID: PMC7061911 DOI: 10.7717/peerj.8408] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2019] [Accepted: 12/16/2019] [Indexed: 12/28/2022] Open
Abstract
Antigen binding by antibodies requires precise orientation of the complementarity- determining region (CDR) loops in the variable domain to establish the correct contact surface. Members of the family Camelidae have a modified form of immunoglobulin gamma (IgG) with only heavy chains, called Heavy Chain only Antibodies (HCAb). Antigen binding in HCAbs is mediated by only three CDR loops from the single variable domain (VHH) at the N-terminus of each heavy chain. This feature of the VHH, along with their other important features, e.g., easy expression, small size, thermo-stability and hydrophilicity, made them promising candidates for therapeutics and diagnostics. Thus, to design better VHH domains, it is important to thoroughly understand their sequence and structure characteristics and relationship. In this study, sequence characteristics of VHH domains have been analysed in depth, along with their structural features using innovative approaches, namely a structural alphabet. An elaborate summary of various studies proposing structural models of VHH domains showed diversity in the algorithms used. Finally, a case study to elucidate the differences in structural models from single and multiple templates is presented. In this case study, along with the above-mentioned aspects of VHH, an exciting view of various factors in structure prediction of VHH, like template framework selection, is also discussed.
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Affiliation(s)
- Akhila Melarkode Vattekatte
- Biologie Intégrée du Globule Rouge UMR_S1134, Inserm, Univ. Paris, Univ. de la Réunion, Univ. des Antilles, Paris, France.,Laboratoire d'Excellence GR-Ex, Paris, France.,Faculté des Sciences et Technologies, Saint Denis, La Réunion, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France
| | - Nicolas Ken Shinada
- Biologie Intégrée du Globule Rouge UMR_S1134, Inserm, Univ. Paris, Univ. de la Réunion, Univ. des Antilles, Paris, France.,Laboratoire d'Excellence GR-Ex, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France.,Discngine SAS, Paris, France
| | - Tarun J Narwani
- Biologie Intégrée du Globule Rouge UMR_S1134, Inserm, Univ. Paris, Univ. de la Réunion, Univ. des Antilles, Paris, France.,Laboratoire d'Excellence GR-Ex, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France
| | - Floriane Noël
- Biologie Intégrée du Globule Rouge UMR_S1134, Inserm, Univ. Paris, Univ. de la Réunion, Univ. des Antilles, Paris, France.,Laboratoire d'Excellence GR-Ex, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France.,PSL Research University, INSERM, UMR 932, Institut Curie, Paris, France.,Université Paris Sud, Université Paris-Saclay, Orsay, France
| | - Olivier Bertrand
- Biologie Intégrée du Globule Rouge UMR_S1134, Inserm, Univ. Paris, Univ. de la Réunion, Univ. des Antilles, Paris, France.,Laboratoire d'Excellence GR-Ex, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France
| | | | | | - Jean-Christophe Gelly
- Biologie Intégrée du Globule Rouge UMR_S1134, Inserm, Univ. Paris, Univ. de la Réunion, Univ. des Antilles, Paris, France.,Laboratoire d'Excellence GR-Ex, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France.,IBL, Paris, France
| | - Frédéric Cadet
- Biologie Intégrée du Globule Rouge UMR_S1134, Inserm, Univ. Paris, Univ. de la Réunion, Univ. des Antilles, Paris, France.,Laboratoire d'Excellence GR-Ex, Paris, France.,Faculté des Sciences et Technologies, Saint Denis, La Réunion, France.,Peaccel, Protein Engineering Accelerator, Paris, France
| | - Alexandre G de Brevern
- Biologie Intégrée du Globule Rouge UMR_S1134, Inserm, Univ. Paris, Univ. de la Réunion, Univ. des Antilles, Paris, France.,Laboratoire d'Excellence GR-Ex, Paris, France.,Faculté des Sciences et Technologies, Saint Denis, La Réunion, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France.,IBL, Paris, France
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5
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Craveur P, Narwani TJ, Rebehmed J, de Brevern AG. Investigation of the impact of PTMs on the protein backbone conformation. Amino Acids 2019; 51:1065-1079. [DOI: 10.1007/s00726-019-02747-w] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2018] [Accepted: 05/18/2019] [Indexed: 12/17/2022]
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6
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Barnoud J, Santuz H, Craveur P, Joseph AP, Jallu V, de Brevern AG, Poulain P. PBxplore: a tool to analyze local protein structure and deformability with Protein Blocks. PeerJ 2017; 5:e4013. [PMID: 29177113 PMCID: PMC5700758 DOI: 10.7717/peerj.4013] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2017] [Accepted: 10/19/2017] [Indexed: 11/20/2022] Open
Abstract
This paper describes the development and application of a suite of tools, called PBxplore, to analyze the dynamics and deformability of protein structures using Protein Blocks (PBs). Proteins are highly dynamic macromolecules, and a classical way to analyze their inherent flexibility is to perform molecular dynamics simulations. The advantage of using small structural prototypes such as PBs is to give a good approximation of the local structure of the protein backbone. More importantly, by reducing the conformational complexity of protein structures, PBs allow analysis of local protein deformability which cannot be done with other methods and had been used efficiently in different applications. PBxplore is able to process large amounts of data such as those produced by molecular dynamics simulations. It produces frequencies, entropy and information logo outputs as text and graphics. PBxplore is available at https://github.com/pierrepo/PBxplore and is released under the open-source MIT license.
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Affiliation(s)
- Jonathan Barnoud
- INSERM, U 1134, DSIMB, Paris, France.,Univ. Paris Diderot, Sorbonne Paris Cité, Univ de la Réunion, Univ des Antilles, UMR-S 1134, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France.,Laboratoire d'Excellence GR-Ex, Paris, France.,Current affiliation: Groningen Biomolecular Sciences and Biotechnology Institute and Zernike Institute for Advanced Materials, University of Groningen, Groningen, The Netherlands
| | - Hubert Santuz
- INSERM, U 1134, DSIMB, Paris, France.,Univ. Paris Diderot, Sorbonne Paris Cité, Univ de la Réunion, Univ des Antilles, UMR-S 1134, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France.,Laboratoire d'Excellence GR-Ex, Paris, France.,Current affiliation: Laboratoire de Biochimie Théorique, CNRS UPR 9080, Institut de Biologie Physico-Chimique, Paris, France
| | - Pierrick Craveur
- INSERM, U 1134, DSIMB, Paris, France.,Univ. Paris Diderot, Sorbonne Paris Cité, Univ de la Réunion, Univ des Antilles, UMR-S 1134, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France.,Laboratoire d'Excellence GR-Ex, Paris, France.,Current affiliation: Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, United States of America
| | - Agnel Praveen Joseph
- INSERM, U 1134, DSIMB, Paris, France.,Univ. Paris Diderot, Sorbonne Paris Cité, Univ de la Réunion, Univ des Antilles, UMR-S 1134, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France.,Laboratoire d'Excellence GR-Ex, Paris, France.,Current affiliation: Birkbeck College, University of London, London, UK
| | | | - Alexandre G de Brevern
- INSERM, U 1134, DSIMB, Paris, France.,Univ. Paris Diderot, Sorbonne Paris Cité, Univ de la Réunion, Univ des Antilles, UMR-S 1134, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France.,Laboratoire d'Excellence GR-Ex, Paris, France
| | - Pierre Poulain
- INSERM, U 1134, DSIMB, Paris, France.,Univ. Paris Diderot, Sorbonne Paris Cité, Univ de la Réunion, Univ des Antilles, UMR-S 1134, Paris, France.,Institut National de la Transfusion Sanguine (INTS), Paris, France.,Laboratoire d'Excellence GR-Ex, Paris, France.,Current affiliation: Mitochondria, Metals and Oxidative Stress Group, Institut Jacques Monod, UMR 7592, Univ. Paris Diderot, CNRS, Sorbonne Paris Cité, Paris, France
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7
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In silico analysis of Glanzmann variants of Calf-1 domain of α IIbβ 3 integrin revealed dynamic allosteric effect. Sci Rep 2017; 7:8001. [PMID: 28808266 PMCID: PMC5556033 DOI: 10.1038/s41598-017-08408-w] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2017] [Accepted: 07/12/2017] [Indexed: 11/08/2022] Open
Abstract
Integrin αIIbβ3 mediates platelet aggregation and thrombus formation. In a rare hereditary bleeding disorder, Glanzmann thrombasthenia (GT), αIIbβ3 expression / function are impaired. The impact of deleterious missense mutations on the complex structure remains unclear. Long independent molecular dynamics (MD) simulations were performed for 7 GT variants and reference structure of the Calf-1 domain of αIIb. Simulations were analysed using a structural alphabet to describe local protein conformations. Common and flexible regions as well as deformable zones were observed in all the structures. The most flexible region of Calf-1 (with highest B-factor) is rather a rigid region encompassed into two deformable zones. Each mutated structure barely showed any modifications at the mutation sites while distant conformational changes were observed. These unexpected results question the relationship between molecular dynamics and allostery; and the role of these long-range effects in the impaired αIIbβ3 expression. This method is aimed at studying all αIIbβ3 sub-domains and impact of missense mutations at local and global structural level.
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8
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Ritchie DW. Calculating and scoring high quality multiple flexible protein structure alignments. Bioinformatics 2016; 32:2650-8. [PMID: 27187202 DOI: 10.1093/bioinformatics/btw300] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2015] [Accepted: 05/07/2016] [Indexed: 11/14/2022] Open
Abstract
MOTIVATION Calculating multiple protein structure alignments (MSAs) is important for understanding functional and evolutionary relationships between protein families, and for modeling protein structures by homology. While incorporating backbone flexibility promises to circumvent many of the limitations of rigid MSA algorithms, very few flexible MSA algorithms exist today. This article describes several novel improvements to the Kpax algorithm which allow high quality flexible MSAs to be calculated. This article also introduces a new Gaussian-based MSA quality measure called 'M-score', which circumvents the pitfalls of RMSD-based quality measures. RESULTS As well as calculating flexible MSAs, the new version of Kpax can also score MSAs from other aligners and from previously aligned reference datasets. Results are presented for a large-scale evaluation of the Homstrad, SABmark and SISY benchmark sets using Kpax and Matt as examples of state-of-the-art flexible aligners and 3DCOMB as an example of a state-of-the-art rigid aligner. These results demonstrate the utility of the M-score as a measure of MSA quality and show that high quality MSAs may be achieved when structural flexibility is properly taken into account. AVAILABILITY AND IMPLEMENTATION Kpax 5.0 may be downloaded for academic use at http://kpax.loria.fr/ CONTACT dave.ritchie@inria.fr SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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9
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Craveur P, Joseph AP, Esque J, Narwani TJ, Noël F, Shinada N, Goguet M, Leonard S, Poulain P, Bertrand O, Faure G, Rebehmed J, Ghozlane A, Swapna LS, Bhaskara RM, Barnoud J, Téletchéa S, Jallu V, Cerny J, Schneider B, Etchebest C, Srinivasan N, Gelly JC, de Brevern AG. Protein flexibility in the light of structural alphabets. Front Mol Biosci 2015; 2:20. [PMID: 26075209 PMCID: PMC4445325 DOI: 10.3389/fmolb.2015.00020] [Citation(s) in RCA: 65] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2015] [Accepted: 04/30/2015] [Indexed: 01/01/2023] Open
Abstract
Protein structures are valuable tools to understand protein function. Nonetheless, proteins are often considered as rigid macromolecules while their structures exhibit specific flexibility, which is essential to complete their functions. Analyses of protein structures and dynamics are often performed with a simplified three-state description, i.e., the classical secondary structures. More precise and complete description of protein backbone conformation can be obtained using libraries of small protein fragments that are able to approximate every part of protein structures. These libraries, called structural alphabets (SAs), have been widely used in structure analysis field, from definition of ligand binding sites to superimposition of protein structures. SAs are also well suited to analyze the dynamics of protein structures. Here, we review innovative approaches that investigate protein flexibility based on SAs description. Coupled to various sources of experimental data (e.g., B-factor) and computational methodology (e.g., Molecular Dynamic simulation), SAs turn out to be powerful tools to analyze protein dynamics, e.g., to examine allosteric mechanisms in large set of structures in complexes, to identify order/disorder transition. SAs were also shown to be quite efficient to predict protein flexibility from amino-acid sequence. Finally, in this review, we exemplify the interest of SAs for studying flexibility with different cases of proteins implicated in pathologies and diseases.
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Affiliation(s)
- Pierrick Craveur
- Institut National de la Santé et de la Recherche Médicale U 1134 Paris, France ; UMR_S 1134, DSIMB, Université Paris Diderot, Sorbonne Paris Cite Paris, France ; Institut National de la Transfusion Sanguine, DSIMB Paris, France ; UMR_S 1134, DSIMB, Laboratory of Excellence GR-Ex Paris, France
| | - Agnel P Joseph
- Rutherford Appleton Laboratory, Science and Technology Facilities Council Didcot, UK
| | - Jeremy Esque
- Institut National de la Santé et de la Recherche Médicale U964,7 UMR Centre National de la Recherche Scientifique 7104, IGBMC, Université de Strasbourg Illkirch, France
| | - Tarun J Narwani
- Institut National de la Santé et de la Recherche Médicale U 1134 Paris, France ; UMR_S 1134, DSIMB, Université Paris Diderot, Sorbonne Paris Cite Paris, France ; Institut National de la Transfusion Sanguine, DSIMB Paris, France ; UMR_S 1134, DSIMB, Laboratory of Excellence GR-Ex Paris, France
| | - Floriane Noël
- Institut National de la Santé et de la Recherche Médicale U 1134 Paris, France ; UMR_S 1134, DSIMB, Université Paris Diderot, Sorbonne Paris Cite Paris, France ; Institut National de la Transfusion Sanguine, DSIMB Paris, France ; UMR_S 1134, DSIMB, Laboratory of Excellence GR-Ex Paris, France
| | - Nicolas Shinada
- Institut National de la Santé et de la Recherche Médicale U 1134 Paris, France ; UMR_S 1134, DSIMB, Université Paris Diderot, Sorbonne Paris Cite Paris, France ; Institut National de la Transfusion Sanguine, DSIMB Paris, France ; UMR_S 1134, DSIMB, Laboratory of Excellence GR-Ex Paris, France
| | - Matthieu Goguet
- Institut National de la Santé et de la Recherche Médicale U 1134 Paris, France ; UMR_S 1134, DSIMB, Université Paris Diderot, Sorbonne Paris Cite Paris, France ; Institut National de la Transfusion Sanguine, DSIMB Paris, France ; UMR_S 1134, DSIMB, Laboratory of Excellence GR-Ex Paris, France
| | - Sylvain Leonard
- Institut National de la Santé et de la Recherche Médicale U 1134 Paris, France ; UMR_S 1134, DSIMB, Université Paris Diderot, Sorbonne Paris Cite Paris, France ; Institut National de la Transfusion Sanguine, DSIMB Paris, France ; UMR_S 1134, DSIMB, Laboratory of Excellence GR-Ex Paris, France
| | - Pierre Poulain
- Institut National de la Santé et de la Recherche Médicale U 1134 Paris, France ; UMR_S 1134, DSIMB, Université Paris Diderot, Sorbonne Paris Cite Paris, France ; Institut National de la Transfusion Sanguine, DSIMB Paris, France ; UMR_S 1134, DSIMB, Laboratory of Excellence GR-Ex Paris, France ; Ets Poulain Pointe-Noire, Congo
| | - Olivier Bertrand
- Institut National de la Santé et de la Recherche Médicale U 1134 Paris, France ; Institut National de la Transfusion Sanguine, DSIMB Paris, France ; UMR_S 1134, DSIMB, Laboratory of Excellence GR-Ex Paris, France
| | - Guilhem Faure
- National Library of Medicine, National Center for Biotechnology Information, National Institutes of Health Bethesda, MD, USA
| | - Joseph Rebehmed
- Centre National de la Recherche Scientifique UMR7590, Sorbonne Universités, Université Pierre et Marie Curie - MNHN - IRD - IUC Paris, France
| | | | - Lakshmipuram S Swapna
- Molecular Biophysics Unit, Indian Institute of Science, Bangalore Bangalore, India ; Hospital for Sick Children, and Departments of Biochemistry and Molecular Genetics, University of Toronto Toronto, ON, Canada
| | - Ramachandra M Bhaskara
- Molecular Biophysics Unit, Indian Institute of Science, Bangalore Bangalore, India ; Department of Theoretical Biophysics, Max Planck Institute of Biophysics Frankfurt, Germany
| | - Jonathan Barnoud
- Institut National de la Santé et de la Recherche Médicale U 1134 Paris, France ; UMR_S 1134, DSIMB, Université Paris Diderot, Sorbonne Paris Cite Paris, France ; Institut National de la Transfusion Sanguine, DSIMB Paris, France ; UMR_S 1134, DSIMB, Laboratory of Excellence GR-Ex Paris, France ; Laboratoire de Physique, École Normale Supérieure de Lyon, Université de Lyon, Centre National de la Recherche Scientifique UMR 5672 Lyon, France
| | - Stéphane Téletchéa
- Institut National de la Santé et de la Recherche Médicale U 1134 Paris, France ; UMR_S 1134, DSIMB, Université Paris Diderot, Sorbonne Paris Cite Paris, France ; Institut National de la Transfusion Sanguine, DSIMB Paris, France ; UMR_S 1134, DSIMB, Laboratory of Excellence GR-Ex Paris, France ; Faculté des Sciences et Techniques, Université de Nantes, Unité Fonctionnalité et Ingénierie des Protéines, Centre National de la Recherche Scientifique UMR 6286, Université Nantes Nantes, France
| | - Vincent Jallu
- Platelet Unit, Institut National de la Transfusion Sanguine Paris, France
| | - Jiri Cerny
- Institute of Biotechnology, The Czech Academy of Sciences Prague, Czech Republic
| | - Bohdan Schneider
- Institute of Biotechnology, The Czech Academy of Sciences Prague, Czech Republic
| | - Catherine Etchebest
- Institut National de la Santé et de la Recherche Médicale U 1134 Paris, France ; UMR_S 1134, DSIMB, Université Paris Diderot, Sorbonne Paris Cite Paris, France ; Institut National de la Transfusion Sanguine, DSIMB Paris, France ; UMR_S 1134, DSIMB, Laboratory of Excellence GR-Ex Paris, France
| | | | - Jean-Christophe Gelly
- Institut National de la Santé et de la Recherche Médicale U 1134 Paris, France ; UMR_S 1134, DSIMB, Université Paris Diderot, Sorbonne Paris Cite Paris, France ; Institut National de la Transfusion Sanguine, DSIMB Paris, France ; UMR_S 1134, DSIMB, Laboratory of Excellence GR-Ex Paris, France
| | - Alexandre G de Brevern
- Institut National de la Santé et de la Recherche Médicale U 1134 Paris, France ; UMR_S 1134, DSIMB, Université Paris Diderot, Sorbonne Paris Cite Paris, France ; Institut National de la Transfusion Sanguine, DSIMB Paris, France ; UMR_S 1134, DSIMB, Laboratory of Excellence GR-Ex Paris, France
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Craveur P, Rebehmed J, de Brevern AG. PTM-SD: a database of structurally resolved and annotated posttranslational modifications in proteins. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2014; 2014:bau041. [PMID: 24857970 PMCID: PMC4038255 DOI: 10.1093/database/bau041] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Posttranslational modifications (PTMs) define covalent and chemical modifications of protein residues. They play important roles in modulating various biological functions. Current PTM databases contain important sequence annotations but do not provide informative 3D structural resource about these modifications. Posttranslational modification structural database (PTM-SD) provides access to structurally solved modified residues, which are experimentally annotated as PTMs. It combines different PTM information and annotation gathered from other databases, e.g. Protein DataBank for the protein structures and dbPTM and PTMCuration for fine sequence annotation. PTM-SD gives an accurate detection of PTMs in structural data. PTM-SD can be browsed by PDB id, UniProt accession number, organism and classic PTM annotation. Advanced queries can also be performed, i.e. detailed PTM annotations, amino acid type, secondary structure, SCOP class classification, PDB chain length and number of PTMs by chain. Statistics and analyses can be computed on a selected dataset of PTMs. Each PTM entry is detailed in a dedicated page with information on the protein sequence, local conformation with secondary structure and Protein Blocks. PTM-SD gives valuable information on observed PTMs in protein 3D structure, which is of great interest for studying sequence-structure- function relationships at the light of PTMs, and could provide insights for comparative modeling and PTM predictions protocols. Database URL: PTM-SD can be accessed at http://www.dsimb.inserm.fr/dsimb_tools/PTM-SD/.
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Affiliation(s)
- Pierrick Craveur
- INSERM, U 1134, DSIMB, F-75739 Paris, France, Univ Paris Diderot, Sorbonne Paris Cité, UMR-S 1134, F-75739 Paris, France, Institut National de la Transfusion Sanguine (INTS), F-75739 Paris, France and Laboratoire d'Excellence GR-Ex, F-75739 Paris, FranceINSERM, U 1134, DSIMB, F-75739 Paris, France, Univ Paris Diderot, Sorbonne Paris Cité, UMR-S 1134, F-75739 Paris, France, Institut National de la Transfusion Sanguine (INTS), F-75739 Paris, France and Laboratoire d'Excellence GR-Ex, F-75739 Paris, FranceINSERM, U 1134, DSIMB, F-75739 Paris, France, Univ Paris Diderot, Sorbonne Paris Cité, UMR-S 1134, F-75739 Paris, France, Institut National de la Transfusion Sanguine (INTS), F-75739 Paris, France and Laboratoire d'Excellence GR-Ex, F-75739 Paris, FranceINSERM, U 1134, DSIMB, F-75739 Paris, France, Univ Paris Diderot, Sorbonne Paris Cité, UMR-S 1134, F-75739 Paris, France, Institut National de la Transfusion Sanguine (INTS), F-75739 Paris, France and Laboratoire d'Excellence GR-Ex, F-75739 Paris, France
| | - Joseph Rebehmed
- INSERM, U 1134, DSIMB, F-75739 Paris, France, Univ Paris Diderot, Sorbonne Paris Cité, UMR-S 1134, F-75739 Paris, France, Institut National de la Transfusion Sanguine (INTS), F-75739 Paris, France and Laboratoire d'Excellence GR-Ex, F-75739 Paris, FranceINSERM, U 1134, DSIMB, F-75739 Paris, France, Univ Paris Diderot, Sorbonne Paris Cité, UMR-S 1134, F-75739 Paris, France, Institut National de la Transfusion Sanguine (INTS), F-75739 Paris, France and Laboratoire d'Excellence GR-Ex, F-75739 Paris, FranceINSERM, U 1134, DSIMB, F-75739 Paris, France, Univ Paris Diderot, Sorbonne Paris Cité, UMR-S 1134, F-75739 Paris, France, Institut National de la Transfusion Sanguine (INTS), F-75739 Paris, France and Laboratoire d'Excellence GR-Ex, F-75739 Paris, FranceINSERM, U 1134, DSIMB, F-75739 Paris, France, Univ Paris Diderot, Sorbonne Paris Cité, UMR-S 1134, F-75739 Paris, France, Institut National de la Transfusion Sanguine (INTS), F-75739 Paris, France and Laboratoire d'Excellence GR-Ex, F-75739 Paris, France
| | - Alexandre G de Brevern
- INSERM, U 1134, DSIMB, F-75739 Paris, France, Univ Paris Diderot, Sorbonne Paris Cité, UMR-S 1134, F-75739 Paris, France, Institut National de la Transfusion Sanguine (INTS), F-75739 Paris, France and Laboratoire d'Excellence GR-Ex, F-75739 Paris, FranceINSERM, U 1134, DSIMB, F-75739 Paris, France, Univ Paris Diderot, Sorbonne Paris Cité, UMR-S 1134, F-75739 Paris, France, Institut National de la Transfusion Sanguine (INTS), F-75739 Paris, France and Laboratoire d'Excellence GR-Ex, F-75739 Paris, FranceINSERM, U 1134, DSIMB, F-75739 Paris, France, Univ Paris Diderot, Sorbonne Paris Cité, UMR-S 1134, F-75739 Paris, France, Institut National de la Transfusion Sanguine (INTS), F-75739 Paris, France and Laboratoire d'Excellence GR-Ex, F-75739 Paris, FranceINSERM, U 1134, DSIMB, F-75739 Paris, France, Univ Paris Diderot, Sorbonne Paris Cité, UMR-S 1134, F-75739 Paris, France, Institut National de la Transfusion Sanguine (INTS), F-75739 Paris, France and Laboratoire d'Excellence GR-Ex, F-75739 Paris, France
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Jallu V, Poulain P, Fuchs PFJ, Kaplan C, de Brevern AG. Modeling and molecular dynamics of HPA-1a and -1b polymorphisms: effects on the structure of the β3 subunit of the αIIbβ3 integrin. PLoS One 2012; 7:e47304. [PMID: 23155369 PMCID: PMC3498292 DOI: 10.1371/journal.pone.0047304] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2012] [Accepted: 09/11/2012] [Indexed: 11/18/2022] Open
Abstract
Background The HPA-1 alloimmune system carried by the platelet integrin αIIbβ3 is the primary cause of alloimmune thrombocytopenia in Caucasians and the HPA-1b allele might be a risk factor for thrombosis. HPA-1a and -1b alleles are defined by a leucine and a proline, respectively, at position 33 in the β3 subunit. Although the structure of αIIbβ3 is available, little is known about structural effects of the L33P substitution and its consequences on immune response and integrin functions. Methodology/Principal Findings A complete 3D model of the L33-β3 extracellular domain was built and a P33 model was obtained by in silico mutagenesis. We then performed molecular dynamics simulations. Analyses focused on the PSI, I-EGF-1, and I-EGF-2 domains and confirmed higher exposure of residue 33 in the L33 β3 form. These analyses also showed major structural flexibility of all three domains in both forms, but increased flexibility in the P33 β3 form. The L33P substitution does not alter the local structure (residues 33 to 35) of the PSI domain, but modifies the structural equilibrium of the three domains. Conclusions These results provide a better understanding of HPA-1 epitopes complexity and alloimmunization prevalence of HPA-1a. P33 gain of structure flexibility in the β3 knee may explain the increased adhesion capacity of HPA-1b platelets and the associated thrombotic risk. Our study provides important new insights into the relationship between HPA-1 variants and β3 structure that suggest possible effects on the alloimmune response and platelet function.
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Affiliation(s)
- Vincent Jallu
- Laboratoire d'Immunologie Plaquettaire, INTS, Paris, France
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