adress : DSIMB Bioinformatics team, Universite Paris Cite & Universite de la Reunion, INSERM, BIGR 1134, EFS, InIdex GREx, Hopital Necker 149 rue de Sevres 757015 Paris, France

I have been a bioinformatics researcher at the French National Institute for Health and Medical Research (INSERM) since 2002. I am currently a Senior Researcher and Head of the DSIMB Bioinformatics Team, whose name stands for Dynamics of Structures and Interactions of Macromolecules in Biology. DSIMB is part of the BIGR research unit, Integrated Biology of the Red Blood Cell and Erythropoiesis, INSERM UMR_S 1134. This joint research unit brings together INSERM, Universite Paris Cite and the French Blood Establishment, EFS, in association with the Universite de La Reunion . The Paris branch of the team is located at Necker-Enfants Malades University Hospital of AP-HP, while another branch is based at the Universite de La Reunion in Saint-Denis, Reunion Island.
This research team (known as EBGM) was established and led by Professor Serge Hazout until 2005, and subsequently by Professor Catherine Etchebest from 2005 to 2019.

DSIMB researches

   DSIMB develops and applies computational approaches for studying the structures, dynamics and molecular interactions of biological macromolecules. Our research encompasses structural bioinformatics, molecular modelling, molecular dynamics simulations, protein-protein and protein-ligand docking, statistical learning, machine learning and deep learning.

   The distinctive feature of our research strategy is the close integration of methodological development with biomedical applications. We pursue two complementary objectives: (i) to design new computational methods, structural descriptors, prediction tools, web servers and databases for the scientific community, and (ii) to apply both established and newly developed approaches to proteins involved in human diseases.

   Our methodological research focuses particularly on protein local conformations, structural alphabets, protein flexibility, conformational dynamics, intrinsically disordered regions, transmembrane proteins and the structural interpretation of genetic variants. A major contribution of the team is the development and application of Protein Blocks, a structural alphabet that provides a detailed description of local protein backbone conformations and their transitions.

   Our biomedical applications primarily concern haematology, transfusion medicine and blood-cell biology. We investigate proteins associated with blood groups, red blood cells, platelets, coagulation, membrane organisation and cellular signalling. We seek to understand how mutations, post-translational modifications and molecular interactions affect protein structure, dynamics and function, and how these alterations contribute to inherited or acquired diseases.

   Through this combined methodological and biomedical strategy, we aim to bridge fundamental structural bioinformatics and translational research. Our work ranges from the development of general computational concepts and publicly accessible resources to the molecular investigation of disease-associated proteins and clinically relevant genetic variants.

My research

My research activities are primarily situated at the interface between structural bioinformatics, computational biology and molecular biophysics. I aim to understand how protein sequences determine local and global three-dimensional structures, conformational dynamics, molecular interactions and biological functions. A central objective of my work is to develop computational approaches capable of describing protein structures at a finer level of resolution than conventional secondary-structure classifications, while remaining sufficiently robust for large-scale analyses of structural databases, molecular simulations and predicted protein models.

Protein structures and developpment

A major component of my research concerns local protein conformations and structural alphabets. I have contributed extensively to the characterization of recurrent structural motifs, including β-turns, polyproline II helices, β-bulges and other non-canonical or transitional conformations. This work led to the development and broad application of Protein Blocks, a structural alphabet composed of representative local backbone conformations. Protein Blocks provide a compact and informative description of protein structures and make it possible to analyse structural similarities, conformational variability, flexibility and sequence-structure relationships with greater precision than classical helix, strand and coil assignments. I have applied this framework to experimental structures, molecular dynamics trajectories, intrinsically disordered regions, binding sites and large collections of predicted protein structures.

A second major research axis focuses on protein flexibility and dynamics. I investigate these properties through the combined use of structural database analyses, molecular modelling, molecular dynamics simulations and statistical descriptors of local conformational changes. I pay particular attention to the distinction between rigid, flexible and highly dynamic regions, as well as to the identification of conformational transitions associated with molecular recognition, allosteric regulation, ligand binding or pathological mutations. My analyses address both global structural rearrangements and subtle local modifications that may not be adequately detected by conventional metrics such as RMSD or RMSF alone.

I also study intrinsically disordered proteins and regions, low-complexity sequences, repeats and chameleon sequences capable of adopting different conformations depending on their structural environment. In these systems, I seek to determine how sequence composition, local context, evolutionary conservation and molecular interactions influence structural plasticity. One of my objectives is to improve the interpretation of regions that remain difficult to characterize experimentally and that are often poorly represented by a single static structural model.

Another important area of my research concerns transmembrane proteins, protein-protein interfaces and protein-ligand interactions. I use computational modelling and simulation to analyse the organisation of membrane-spanning regions, intracellular domains, extracellular modules and multimeric assemblies. These approaches allow me to identify interaction sites, conformationally sensitive regions and structural determinants involved in signalling, regulation and complex formation. I also investigate the structural and dynamic consequences of post-translational modifications, including phosphorylation and glycosylation.

My methodological developments increasingly integrate machine learning, deep learning and protein language models. I use these approaches to predict local conformations, structural flexibility, intrinsic disorder, variant pathogenicity and other protein properties from sequence or structural information. Particular emphasis is placed on interpretable models and on the combination of data-driven approaches with physically meaningful structural descriptors. My aim is to improve predictive performance while preserving a direct connection with molecular mechanisms.

My biomedical applications

The biomedical applications of my research are especially developed in haematology, transfusion medicine and blood-cell biology. I study blood-group proteins, erythrocyte and platelet proteins, coagulation-related factors, membrane receptors, integrins and signalling proteins involved in myeloproliferative neoplasms and other inherited or acquired disorders. Through these studies, I seek to determine how mutations, genetic variants and post-translational modifications alter protein stability, conformational dynamics, molecular interactions or signalling properties.

A related objective is the structural and functional interpretation of genetic variants. By combining evolutionary information, structural modelling, molecular dynamics, machine learning and protein language models, I aim to distinguish variants that are likely to be functionally neutral from those that may disrupt protein folding, stability, interactions or regulation. This work contributes to the development of computational approaches for variant prioritisation and supports broader efforts in precision medicine and molecular diagnostics.

My research programme also includes applications in drug design and ligand-protein recognition. I use structural modelling, docking, scoring functions and molecular dynamics simulations to investigate binding sites, ligand-induced conformational changes and the influence of protein flexibility on molecular recognition. These approaches are intended not only to identify potential binding modes, but also to understand the dynamic and energetic mechanisms that determine the efficacy and selectivity of molecular interactions.

A significant part of my activity is devoted to the development and dissemination of computational resources. I have contributed to numerous software tools, web servers, databases and publicly accessible datasets supporting the analysis, comparison and prediction of protein structures and dynamics. These resources are designed to facilitate reproducible research and to make advanced structural bioinformatics methodologies accessible to the wider scientific community.

Overall, my research combines methodological innovation with biomedical application. I seek to provide a multiscale understanding of proteins, ranging from local backbone conformations to complete macromolecular assemblies, and from static structures to dynamic conformational ensembles. By integrating structural bioinformatics, molecular modelling, statistical learning and artificial intelligence, my work contributes to a more detailed understanding of protein function, dysfunction and molecular variability.

Five main publications (methods):

• de Brevern A.G., Etchebest C. and Hazout S. (2000), Bayesian probabilistic approach for predicting backbone structures in terms of protein blocks, Proteins, 41, 271-287 [article].
• Barnoud J., Santuz H., Craveur P., Joseph A.P., Jallu V., Poulain P. and de Brevern A.G. (2017), PBxplore: A tool to analyze local protein structure and deformability with Protein Blocks, PeerJ, 5, e4013 [article].
• Narwani T.J., Craveur P., Shinada N.K., Floch A., Santuz H., Melarkode Vattekatte A., Srinivasan N., Rebehmed J., Gelly J.-C., Etchebest C. and de Brevern A.G. (2020), Discrete analyses of protein dynamics, Journal of Biomolecular Structure and Dynamics, 38, 2988-3002 [article].
• de Brevern A.G. (2023), An agnostic analysis of the human AlphaFold2 proteome using local protein conformations, Biochimie, 207, 11-19 [article].
• Radjasandirane R., Cretin G., Diharce J., de Brevern A.G. and Gelly J.-C. (2026), PATHOS: Predicting variant pathogenicity by combining protein language models and biological features, Artificial Intelligence in the Life Sciences, 9, 100165 [article].

Five main publications (applications):

• Arnaud L., Saison C., Hélias V., Lucien N., Steschenko D., Giarratana M.-C., Préhu C., Foliguet B., Montout L., de Brevern A.G., Francina A., Ripoche P., Fenneteau O., Da Costa L., Peyrard T., Coghlan G., Illum N., Birgens H., Tamary H., Iolascon A., Delaunay J., Tchernia G. and Cartron J.-P. (2010), A dominant mutation in the gene encoding the erythroid transcription factor KLF1 causes a congenital dyserythropoietic anemia, The American Journal of Human Genetics, 87, 721-727 [article].
• Anies S., Jallu V., Diharce J., Narwani T.J. and de Brevern A.G. (2022), Analysis of Integrin αIIb Subunit Dynamics Reveals Long-Range Effects of Missense Mutations on Calf Domains, International Journal of Molecular Sciences, 23, 858 [article].
• Kranjc A., Narwani T.J., Abby S.S. and de Brevern A.G. (2023), Structural Space of the Duffy Antigen/Receptor for Chemokines' Intrinsically Disordered Ectodomain 1 Explored by Temperature Replica-Exchange Molecular Dynamics Simulations, International Journal of Molecular Sciences, 24, 13280 [article].
• Floch A., Galochkina T., Pirenne F., Tournamille C. and de Brevern A.G. (2024), Molecular dynamics of the human RhD and RhAG blood group proteins, Frontiers in Chemistry, 12, 1360392 [article].
• Vu H.N., Radjasandirane R., Diharce J. and de Brevern A.G. (2025), Impact of Ruxolitinib Interactions on JAK2 JH1 Domain Dynamics, International Journal of Molecular Sciences, 26, 3727 [article].

Five main reviews:

• Joseph A.P., Agarwal G., Mahajan S., Gelly J.-C., Swapna L.S., Offmann B., Cadet F., Bornot A., Tyagi M., Valadié H., Schneider B., Etchebest C., Srinivasan N. and de Brevern A.G. (2010), A short survey on Protein Blocks, Biophysical Reviews, 2, 137-145 [article].
• Craveur P., Joseph A.P., Esque J., Narwani T.J., Noël F., Shinada N., Goguet M., Leonard S., Poulain P., Bertrand O., Faure G., Rebehmed J., Ghozlane A., Swapna L.S., Bhaskara R.M., Srinivasan N., Gelly J.-C. and de Brevern A.G. (2015), Protein flexibility in the light of structural alphabets, Frontiers in Molecular Biosciences, 2, 20 [article].
• de Brevern A.G. (2022), A Perspective on the Rise and Fall of Protein β-Turns, International Journal of Molecular Sciences, 23, 12314 [article].
• Tourlet S., Radjasandirane R., Diharce J. and de Brevern A.G. (2023), AlphaFold2 Update and Perspectives, BioMedInformatics, 3, 378-390 [article].
• Offmann B. and de Brevern A.G. (2025), A 25-Year Journey with Protein Blocks: Unveiling the Versatility of a Structural Alphabet, Biochimie, 239, 58-71 [article].

Alexandre G. de Brevern
Last Modification : July 2026