Research group

The group of Computational Biology and Bioinformatics at the Centro de Biologia Molecular Severo Ochoa in Madrid aims at developing an integrated biophysical model of proteins that integrates protein dynamics predicted through the torsional elastic network model, folding stability and molecular evolution in structure and sequence space. We also investigate genome replication under the light of chromatin structure. Our research in theoretical ecology addresses the structural stability of ecosystems against environmental fluctuations, focusing on mutualistic interactions and bacterial communities The group of Computational Biology and Bioinformatics descends from the Bioinformatics Unit of the CBM, founded by Ángel Ramírez Ortiz and previously also integrated by the group of Antonio Morreale. The group is now directed by Ugo Bastolla, a physicist who has always been interested in biology, convinced that a multidisciplinary approach is necessary for understanding the complexity of living beings and that modern biology requires quantitative methods and a mathematical formalization resting on statistical physics on one side and evolution on the other side. In this framework, proteins are particularly interesting as a bridge between the two disciplines. The group has three main research lines. The first line pursues a comprehensive approach to proteins that integrates protein dynamics, the thermodynamic stability of the folded state, and molecular evolution. For studying protein dynamics, we developed an elastic network model in torsion angle space (TNM) that characterizes and predicts, among others, functional conformational changes, structural changes due to mutations and the dynamical couplings between protein residues that play a role in ligand binding and allostery. We are interested in the relationship between protein evolution and folding stability, which we predict through our model based on contact interactions and the statistical physics of the misfolded state. In this framework, we addressed how evolution acts on the structure and the stability of proteins and how structural requirements constrain evolution. We developed structure and stability constrained substitution models of protein evolution (SSCPE) based on predicted fitness changes, adopting a fitness model based on folding stability and structure conservation. The SSCPE models improve the realism of site-specific patterns of amino acid frequencies and evolutionary rates and infer more accurate maximum-likelihood phylogenetic trees than empirical substitution models that do not take into account the protein structure. We are now pursuing several bioinformatics applications of the SSCPE models. Relatedly, we developed a hybrid measure of protein sequence and structure similarity and we used it for achieving more accurate multiple protein alignments, structure-based phylogenetic trees and predicted protein functions. Finally, we study how disordered proteins that lack a stable three-dimensional structure contribute to the complexity of eukaryotic cells. Our second research line concerns the bioinformatics analysis of genomic scale experiments on epigenetic regulation, replication and transcription in complex cells. In collaboration with the group of Crisanto Gutierrez, we characterized nine chromatin states of the model plant Arabidopsis thaliana and their relationship with genome replication and transcription, and in collaboration that also involves Maria Gomez, we studied the relationship between eukaryotic genomes replication, sequence motifs (GGN triplets) and the properties [...]