Franca Fraternali

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Franca Fraternali, Group Leader / Head of the ISMB and Professor of Integrative Computational Biology, UCL

Tel (direct):

Email: f [dot] fraternali@ucl.ac.uk

Biography

  • Chair in Integrative Computationl Biology, Department of Structure and Molecular Biology University College London
  • Head Institute of Structural and Molecular Biology
  • Head, Randall Centre of Cell and Molecular Biophysics, King’s College London
  • Professor of Bioinformatics and Computational Biology, Randall Centre, King’s College London
  • Staff Scientist, National Institute for Medical Research of London
  • Research Associate, EMBL Heidelberg
  • Post Doctoral Research Fellow, University of Strasbourg
  • EMBO Fellowship, ETHZ, Zurich
  • PhD in Physical Chemistry, University of Naples & ETHZ, Zurich

Career highlights Professor Franca Fraternali is a computational biologist and biophysicist. She began her career with a PhD in Physical Chemistry at the University of Naples before taking up an EMBO fellowship at ETH Zurich and positions with the University of Strasbourg and EMBL Heidelberg. She has been a permanent staff scientist in the Mathematical Biology Division of the National Institute for Medical Research of London before joining King’s in 2005 to build her own group. In 2016 she got a satellite position at the Francis Crick Institute in London. From 2018 till 2022 she was the Head of the Randall Centre for Structural and Molecular Biophysics. In November 2022 she moved to UCL with a Chair in Integrative Computational Biology to direct the Institute of Structure and Molecular Biology.

Research Interests : Structural Bioinformatics of Proteins and Nucleic acids; Protein Structure Prediction; Molecular Dynamics of folded and misfolded proteins; Systems Biology and Immunology; Statistical Analysis of Protein Interaction Networks.

Fraternalilab The group research aims are in the identification of the molecular determinants in the functioning or mis-functioning of protein structures and protein-protein interactions. The wider objective is to understand, at a molecular level, the nature of the interactions occurring in the cell. We use bioinformatics methods to analyse available data on protein structures and protein interactions, and molecular simulations and/or computational biology methods to characterize and determine their stability. The group develops computational methods and large-scale data analysis tools and applies these in fields such as Structural Biology of Proteins and Nucleic acids; Systems Biology and Immunology; Protein Structure Prediction; Molecular Dynamics of folded and misfolded proteins; Statistical Analysis of Protein Interaction Networks. A number of projects in the group integrate protein structural information with Protein-Protein Interaction Networks (PPIN)s to perform large scale studies to uncover observed cellular mechanism and the role of protein complexes in these. One of the major interests in these analyses is to investigate how disease-related mutations may disrupt protein functions and lead to a pathogenic phenotype. These effects can be mediated by alterations of the protein stability induced by the mutation and specific associated molecular signatures. Once these signatures have been identified, one can propose ‘rescue’ mutants to restore the protein function; one can design proteins with enhanced binding; one can design inhibitors to disrupt the binding.

We use and develop methods in molecular simulations aimed at characterizing the role of dynamics in molecular processes; we focus particularly on allosteric signalling in proteins regulated by multiple effectors. We have developed user-friendly software to extract molecular determinants of allosteric communication by the use of molecular dynamics. We compare the data with experimental studies on the induced conformational changes and binding kinetics FF has also a strong and long-standing interest in the role of water at the surface of proteins and in the modelling of solvent in simulations.