19.6.2024. 15:15h, Faculty of Mathematics (online and live in room BIM)

Application of Structural Bioinformatics to Analyze a Biomedical Question: The Case of Essential Thrombocythemia

Dr. Alexandre de Brevern

DSIMB Bioinformatics team, INSERM UMR_S 1134, BIGR unit Université Paris Cité & Université de la Réunion, Necker Hospital, Paris, France

A meeting of the Bioinformatics seminar will be held on Thursday, June 19th, starting at 15:15, in room BIM and in online classroom. Teachers and students of doctoral and master studies in computer science, mathematics, biology and other related disciplines are invited to join us.

LINK: https://zoom.us/j/2183428158?pwd=ouAZtpLrbPnOBsKjQiarS9Rh59fyqF.1

Please note that for this meeting we will switch to the Zoom platform instead of the usual Webex.

Abstract

Essential thrombocythemia (ET) is a blood cancer belonging to the Myeloproliferative Neoplasms (MPNs) family. ET is characterized by an increase in the production of blood platelets. The high level of platelets associated with ET lead to complications such as thrombosis, clots (agglutination of platelets), which could partially or totally obstruct a blood vessel, or even haemorrhages. This disease is uncommon, with 2.3 cases per 100,000 people each year. Several mutations are associated with ET. In 2005, a first mutation was found implying Janus Kinase 2 (JAK2) and V617F mutation, one year later; it was another protein that binds this one, namely MPL with W515L mutation. In 2013. It was calreticulin (CALR) protein that was underlined. These 3 proteins encompass 90% of ET patients. Since few years, we so decided to better characterize them, and sometimes underlying strange properties.

The first case was CALR protein ends with a highly disorder or flexible domain. A novel carboxyl-terminal sequence is generated by a frameshift mutation in CALR implied in ET (named CALR-ET), losing the ER retention peptide. CALR-ET therefore tends to go out of the ER. CALR-ETs mediate intermolecular interactions to form homodimer, bind MPL and activates it, leading to ET phenotype. We have provided a new classification of CALR-ET variants underlying different dynamical properties, but also showing potential sequencing annotation. For JAK2, two domains were analysed. The first one is the JH2 domain with the pathological mutation V617F; it is in fact quite rigid. We underlined interest of a new drug. The second one is JH1 that binds an essential FDA-approved drug, Ruxolitinib. We highlighted why this drug represses the function when it is slightly phosphorylated, but not when it is entirely phosphorylated. Finally, we show very recent results on MPL.

Lecturer

Trained as a Cell Biologist, Alexandre G. de Brevern is a Structural Bioinformatician from Université Paris Cité. Senior Researcher at the French National Institute for Health and Medical Research (INSERM), he is the head of DSIMB, the Bioinformatics team of BIGR unit (12 permanent researchers located in Paris and Saint-Denis de la Reunion). He has two main axes of researches: (i) developing innovate methodologies useful for the scientific community and (ii) specific application to proteins implicated in diseases and pathologies, mainly linked to haematology and transfusion.

Concerning the first axis, he provided 20 tools, webservers and databases. He is a recognized specialist of protein local conformations e.g. extension of definition of -turn classes. He is the designer of the most important structural alphabet able to approximate protein structures, the Protein Blocks. PBs have been used to analyse protein structures, protein dynamics, disordered proteins, binding sites, protein superimposition and prediction.

For prediction purposes, he uses biostatistics and learning approaches ranging from Bayesian approach, to Artificial Neural Networks, Support Vector Machines and Deep Learning.

Concerning the second axis, he used structural modelling and molecular dynamics to analyse Red Blood Cell and platelet proteins. He is specialized in transmembrane proteins and protein implicated in blood group transfusion.

He also extended his work to drug design with collaborations with companies and NGS. He had authored more than 180 publications and one book, is editor in 8 peer-reviewed journals. He is implicated in numerous scientific societies, being awarded by French Molecular Modelling group award (GGMM) and Prix Maurice Nicloux award (SFBBM). He is involved in many institutes evaluation in France, Czech Republic, Finland and Poland and has International collaborations e.g. India, Taiwan, Lebanon and Serbia.

Seminar

The organizer of the seminar is BIRBI. The heads of the seminar are Prof. dr Nataša Pržulj and dr Jovana Kovačević.

17.6.2024. 13:15h, Faculty of Mathematics (online and live in room BIM)

A Critical View of the Contribution of AlphaFold in Light of the Nobel Prize in Chemistry

Dr. Alexandre de Brevern

DSIMB Bioinformatics team, INSERM UMR_S 1134, BIGR unit Université Paris Cité & Université de la Réunion, Necker Hospital, Paris, France

A meeting of the Bioinformatics seminar will be held on Tuesday, June 17th, starting at 13:15, in room BIM and in online classroom. Teachers and students of doctoral and master studies in computer science, mathematics, biology and other related disciplines are invited to join us.

LINK: https://zoom.us/j/2183428158?pwd=ouAZtpLrbPnOBsKjQiarS9Rh59fyqF.1

Please note that for this meeting we will switch to the Zoom platform instead of the usual Webex.

Abstract

The three-dimensional (3D) structure of proteins supports the majority of essential biological functions and also associated pathologies. Access to this information not only enables us to understand biological function at an atomistic level, but is also essential for the design of new drugs. However, obtaining these 3D structures experimentally is complex, time-consuming and expensive, and in many cases impossible. For over 35 years, computational approaches have been used to propose 3D structural models from sequence. Techniques have evolved from simple comparative modelling approaches (copy/paste) to increasingly complex approaches. In 2018, the deep learning method AlphaFold (from the company DeepMind) was proposed in the CASP competition which allows assessing the quality of such approaches, with very fair results, but comparable to the best approaches. DeepMind engineers modified the architecture of the project, and in 2020 AlphaFold2 achieved remarkable results. The media hype was impressive, leading to memorable headlines such as: 'an AI algorithm that solved the 50-year challenge of predicting protein structure'. Declared method of the year by Science, Nature, Life... AlphaFold will be awarded the Nobel Prize in Chemistry in 2024. The aim of this talk is to put the scientific question of the proposal for 3D structural models, real applications and potential limitations of the approach back into perspective with concrete cases, and to open the discussion on AlphaFold as an evolution or revolution in structural bioinformatics and, above all, beyond.

Lecturer

Trained as a Cell Biologist, Alexandre G. de Brevern is a Structural Bioinformatician from Université Paris Cité. Senior Researcher at the French National Institute for Health and Medical Research (INSERM), he is the head of DSIMB, the Bioinformatics team of BIGR unit (12 permanent researchers located in Paris and Saint-Denis de la Reunion). He has two main axes of researches: (i) developing innovate methodologies useful for the scientific community and (ii) specific application to proteins implicated in diseases and pathologies, mainly linked to haematology and transfusion.

Concerning the first axis, he provided 20 tools, webservers and databases. He is a recognized specialist of protein local conformations e.g. extension of definition of -turn classes. He is the designer of the most important structural alphabet able to approximate protein structures, the Protein Blocks. PBs have been used to analyse protein structures, protein dynamics, disordered proteins, binding sites, protein superimposition and prediction.

For prediction purposes, he uses biostatistics and learning approaches ranging from Bayesian approach, to Artificial Neural Networks, Support Vector Machines and Deep Learning.

Concerning the second axis, he used structural modelling and molecular dynamics to analyse Red Blood Cell and platelet proteins. He is specialized in transmembrane proteins and protein implicated in blood group transfusion.

He also extended his work to drug design with collaborations with companies and NGS. He had authored more than 180 publications and one book, is editor in 8 peer-reviewed journals. He is implicated in numerous scientific societies, being awarded by French Molecular Modelling group award (GGMM) and Prix Maurice Nicloux award (SFBBM). He is involved in many institutes evaluation in France, Czech Republic, Finland and Poland and has International collaborations e.g. India, Taiwan, Lebanon and Serbia.

Seminar

The organizer of the seminar is BIRBI. The heads of the seminar are Prof. dr Nataša Pržulj and dr Jovana Kovačević.

11.12.2024. 18:15h, Faculty of Mathematics (online)

A bioinformatics strategy for the discovery of host-based biomarkers from human cell-free DNA in blood plasma

Dr. Alessandra Vittorini Orgeas

Hungarian Centre of Excellence for Molecular Medicine, Szeged, Hungary

    Video: Recorded lecture (MP4, 62min, 154MB)

A meeting of the Bioinformatics seminar will be held on Wednesday, December 11th, starting at 18:15, in online classroom. Teachers and students of doctoral and master studies in computer science, mathematics, biology and other related disciplines are invited to join us.

Please note that for this meeting we will switch to the Zoom platform instead of the usual Webex.

Abstract

Human cell-free DNA molecules in the bloodstream originate from various tissues and can be easily isolated and analysed. Although the biogenesis of these molecules is still not well understood, their abundance, size, genetic and epigenetic alterations are associated with many benign and malignant diseases. A large number of samples can be collected easily and quickly through a routine blood draw. In addition, high-throughput sequencing technologies (NGS) have made it possible to generate substantial amounts of complex genomic data. This has led to a great interest in cell-free DNA in clinical settings, due to its potential role as a biomarker. However, this potential can only be exploited if supported by a computational platform that simplifies the execution of the analysis and makes it efficient, reproducible and portable across different platforms. To address the complexity of this analysis, we have implemented a computational pipeline for the discovery of host-based genetic biomarkers of infectious diseases and beyond that addresses some of the well-known challenges associated with traditional pipelines as well as less well-known challenges associated with the output data of NGS methods. In this talk, I will summarize the challenges faced in the development of this pipeline and offer a solution based on the results of our previous studies and the particular characteristics of our dataset. Finally, I will describe the workflow of the pipeline and explain the function of each module into which it is decomposed. Finally, I will describe the workflow of the pipeline and explain the function of each module into which it is decomposed. The pipeline is currently in the testing phase, but we believe that it could serve as a model for future projects of this kind.

Lecturer

Alessandra Vittorini Orgeas is an interdisciplinary scientist with a strong academic and research background in biophysics, mathematical physics, and bioinformatics. She holds two PhDs: one in Mathematical Physics from the University of Melbourne (2019) and another in Materials for Health, Environment, and Energy from the University of Rome Tor Vergata (2013). Alessandra also earned a Master’s Degree in Biophysics and a Bachelor’s in Physics, both with top honors, from the University of Rome La Sapienza.

Alessandra has gained valuable academic research experience at internationally recognized institutions, including Leibniz Universität Hannover (Germany) and the Institut national de la recherche scientifique (INRS) in Canada. Her work has been published in leading scientific journals such as Nature Materials and Journal of Physics A.

After a period of work in IT consulting, Alessandra returned to research and is currently a Postdoctoral Researcher at HCEMM Nonprofit kft. in Hungary. As part of the Circulating Nucleic Acids Biomarkers Core Group, she investigates novel methods for using nucleic acids as biomarkers to diagnose infectious diseases and other malignancies.

Seminar

The organizer of the seminar is BIRBI. The heads of the seminar are Prof. dr Nataša Pržulj and dr Jovana Kovačević.