The article:
Raucci R, Laine E, Carbone A. Local Interaction Signal Analysis Predicts Protein-Protein Binding Affinity, Structure, 2018 [ Link to the article ]
has been recommended in F1000Prime as being of special significance in its field by F1000 Faculty Member Alexandre Bonvin.
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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.
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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
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"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
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Alessandra Carbone and Elodie Laine are organizing the "UPMC Young Researchers' Meeting: Modeling Complex Biological Systems".
The talks on current work in computational biology at UPMC will be given by PhD students and Postdocs working at UPMC labs. It will be an opportunity to listen at ongoing research and learn what is done in close by departments.
The up to date program is available here
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F.Nadalin and A.Carbone published CIPS, a new computational method for scoring protein docking decoys based on a combination of residue-residue contact preferences and interface compositional bias. CIPS outperforms state-of-the-art methods on screening protein-protein docking models and improves the ranking on 28 CAPRI targets. The drastic reduction of candidate solutions produced by thousands of proteins docked against each other makes large-scale docking accessible to analysis.
To the Software
To the Article
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We highlight our new database Plasmobase to the community working in malaria with a new blog appeared in malariaworld.org.
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Plasmobase is a unique database designed for the comparative study of 11 Plasmodium genomes. Plasmobase proposes new domain architectures as well as new domain families that have never been reported before for these genomes. It allows for an easy comparison among architectures within Plasmodium species and with other species, described in UniProt. Joint work of J.Bernardes and A.Carbone.
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