Local Interaction Signal Analysis (LISA) is an empirical function designed to estimate protein-protein binding affinities. It explores the geometry of contact distributions at protein-protein interfaces and enables to identify hot-sites of favorable contacts playing a major contribution in binding affinity. LISA applies to a large variety of complexes resulting in a very stable behavior. It outperforms all existing comparable predictor methods predicting binding affinity.The Analytical Genomics team.Link to the article. 

Several members of LCQB co-authored « Meet-U: educating through research immersion », which appeared in PLOS Computational Biology on 03/15/2018. Meet-U is a new educational initiative that aims to train students for collaborative work in computational biology and to bridge the gap between education and research. Meet-U mimics the setup of collaborative research projects and takes advantage of the most popular tools for collaborative work and of cloud computing. Students are grouped in teams of 4–5 people and have to realize a project from A to Z that answers a challenging question in biology. In this paper, we report on our experience with Meet-U in two French universities with master’s students in bioinformatics and modeling, and with protein–protein docking as the subject of the course. To the Article

"A protein coevolution method uncovers critical features of the Hepatitis C Virus fusion mechanism" appeared in PLoS Pathogens, from A.Carbone team. This work sheds light on important structural features of the HCV fusion mechanism and contributes to advance our functional understanding of this process. This study also provides an important proof of concept that coevolution can be employed to explore viral protein mediated-processes, and can guide the development of innovative translational strategies against challenging human-tropic viruses.To the Article