The Laboratory of Computational and Quantitative Biology (LCQB), headed by A. Carbone, is an interdisciplinary laboratory working at the interface between biology and quantitative sciences. It is built to promote a balanced interaction of theoretical and experimental approaches in biology and to foster the definition of new experimental questions, data analysis and modeling of biological phenomena. Our projects address questions on biological structures and processes through the gathering of experimental measures, the in silico generation of new biological data that remain inaccessible to experiments today (modeling of biological systems), the development of statistical methods for data analysis, and the conception of original algorithms aimed to predictions. The lab is supported by the CNRS and Sorbonne Université.

News

June 10, 2019

What can proteins tell us about how they interact and function together? At LCQB, we develop computational approaches to predict protein interactions, model protein social behaviour and infer the effect of mutations on protein interaction networks. We just posted this video explaining these ideas to the large public. 

Link to the french video

Link to the italian video

May 12, 2020

ANRS communicates today on our new webserver COVTree, designed to predict coevolving residues in overlapping genes and to detect mirrored coevolution.

Link to the article

May 11, 2020

Interested in phylogenetic reconstruction based on synteny rather than protein sequence? PhyChro is out in MBE. This is the last piece of a huge work, CHROnicle , done in collaboration by the Analytical Genomics and the Biology of Genomes teams.

Link to the article

 

May 11, 2020

A one-year postdoctoral position is open in the "Statistical Genomics and Biological Physics" team, to work on data-driven modeling of SARS-CoV-2 evolution. Interested candidates with a strong background in computational biology and/or statistical biological physics are invited to contact Martin Weigt for information.

May 10, 2020

Overlapping genes are commonplace in viruses and play an important role in their function and evolution. Coevolution in OVerlapped sequences by Tree analysis (COVTree) is a web server providing the online analysis of coevolving amino-acid pairs in overlapping genes, where residues might be located inside or outside the overlapping region.

Link to the article

May 4, 2020

We propose PhyloSofS, the first automated tool to reconstruct plausible evolutionary scenarios explaining a set of observed transcripts, and to generate 3D molecular models of the protein isoforms. We apply it to the JNK family (60 transcripts, 7 trees) to identify AS events of ancient origin and relate their functional outcome with changes in the protein dynamics. We also show that PhyloSofS can help identify new potential therapeutic targets.

Link to the paper

 

May 3, 2020

A.Carbone and F.Oteri work on the Spike protein of SARS2 in collaboration with the group of F.L.Cosset at CIRI in Lyon, expert in non-replicative retroviral pseudoparticles. Based on coevolution analysis of patient sequences and sequences from bats and other species, they aim at identifying key residues in the Spike protein involved in the entry mechanism of the virus in human cells. In the past, the two groups successfully combined their computational and experimental methods to unravel critical features of the original HCV fusion mechanism.

May 2, 2020

The team "Statistical Genomics and Biological Physics" has obtained financial support by the Faculty of Sciences and Engineering of Sorbonne Université, to develop sequence-data driven models of evolutionary landscapes and selective constraints acting in the Covid-19 causing virus SARS-CoV-2. The projects aims at finding signatures of selection in the rapidly increasing number of available 
genomes, and to interpret them in terms of protein structure, function and protein-protein interactions inside coronaviruses and with the host (e.g. the famous interaction of the viral spike protein with the human ACE2 receptor). 

December 2, 2019

The "Emergence program" promoted by the "Ville de Paris" is awarded to projects encouraging the creation and the development of new research teams in the Paris region.
Zhou Xu received one of these recognitions for 2019.
 

November 15, 2019

Nonribosomal peptide synthetases (NRPSs) are microbial megaenzymes that make a wide variety of small-molecule products, including many that are clinically used as antitumors, antibiotics, or immunosuppressants. Peptide synthesis proceeds with assembly-line logic, where each station on the NRPS assembly line is a multidomain unit called a module. While the function of single modules is well studied, much less is known how they work together. Researchers from the Schmeing lab at McGill University have resolved several dimodular NRPS structures, which show coordinated interactions between modules, and large conformational changes between catalytically relevant states. Martin Weigt from the “Statstical Genomics and Biological Physics” team has performed complementary coevolutionary analyses using the direct coupling analysis (DCA), which confirm the biological relevance and evolutionary conservation of the observed inter-modular interactions. DCA analysis has also allowed to suggest mutations in a module-swapped chimeric NRPS protein, which significantly increased the activity of the protein, a result of direct relevance toward the longstanding goal of NRPS bioengineering for production of new-to-nature bioactive small molecules.

Link to article in Science

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