Design of Biological Systems
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1981 Biology Sciences, Universidad Complutense de Madrid (Spain)
1982 Master of Sciences, Universidad Complutense de Madrid (Spain).
1985 Ph.D. in Biochemistry, Universidad Complutense de Madrid (Spain).
1987 Postdoctoral, Center of Mollecuar Biology (CSIC-UAM), Universidad Autónoma de Madrid (Spain).
1991 Postdoctoral, Cambridge University (Great Britain).
2001-2005 Head of Dpt., Dpt. Structural & Computational Biology, EMBL (Germany).
2005-present ICREA Research Professor and Group Leader at the Center for Genomic Regulation, Barcelona (Spain)
2005-June 2011 Coordinator of the Systems Biology Program at the Center for Genomic Regulation, Barcelona (Spain)
2006-present Director of the EMBL/CRG Systems Biology Research Unit at the Centre for Genomic Regulation, Barcelona (Spain)
July 2011-present Director of the Centre for Genomic Regulation, Barcelona (Spain)
In our group we are aiming at a quantitative understanding of biological systems to an extent that one is able to predict systemic features and with the hope to rational design and modify their behaviour. This applies to any system comprising biological components that is more than the mere sum of its components, or, in other words, the addition of the individual components results in systemic properties that could not be predicted by considering the components individually. By achieving this objective we are aiming at new global understanding and treatment of human diseases in which the target will not be a single molecule but a network. For this purpose in our group we develop on one hand new software and theoretical approximations to understand complex systems and on the other we do experiments to validate our predictions.
You can find more information about our group and our research projects on our website
A database for the prediction of protein-protein interactions of modular domains
Most of the structures and function of globular domains from the proteome are yet unknown. In order to get some information about the biological role of these domains, the development of a methodology for the modelling, prediction and localization of putative partners is of crucial importance since it can be of general applicability for any domain involved in protein-protein interactions.
ADAN is a database of putative ligands for the most well-known modular protein-protein interaction domains like SH3, PDZ, etc. Many of these domains have a large number of homologues of which only a small fraction has been crystallized and only limited number of ligands is known. Based on the known structures, the ADAN project creates full atomic models of unknown protein-ligand structures using the FoldX algorithm and predicts new putative binders. A querying function allows the user to input a polypeptide sequence and retrieve the putative binding segments for a particular domain.
ADAN results from the collaboration between the group of Luis Serrano, currently at the CRG in Barcelona and Gregorio Fernández, researcher from the Cellular and Molecular Biology Institute of the Miguel Hernández University in Elche, Alicante.
An algorithm for the prediction of the helical content of peptides
Agadir is a prediction algorithm based on the helix/coil transition theory. Agadir predicts the helical behaviour of monomeric peptides. It only considers short range interactions. Conditions such as pH, temperature and ionic strength are used in the calculation. Modifications of the termini are also allowed. Agadir is not a program to predict secondary structure of proteins.
A structural classification of protein fragments
BriX is a structural classification of protein fragments. The library comprises fragments ranging from 4 to 14 amino acids that are clustered against 6 different distance thresholds. This has lead to an alphabet of around 2000 frequently observed letters or structural classes per chain length. These classes are accessible through a search and a browse interface.
BriX is being developed by Joost Schymkowitz and Frederic Rousseau and their team at the SWITCH Laboratory of VIB in Brussels, Belgium, in collaboration with Luis Serrano and his team at the CRG in Barcelona, Spain.
For more information about this software, please click here.
An automatic protein design algorithm that can be used to rationally modify protein stability, change protein specificity and affinity and predict metal binding sites. It can also be used to design protein-DNA interactions
FoldX is a computer algorithm developed to provide a fast and quantitative estimation of the importance of the interactions contributing to the stability of proteins and protein complexes. The predictive power of the algorithm has been tested on a very large set of point mutants spanning most of the structural environments found in proteins, as well as on protein complexes and protein-DNA complexes of medical and biotechnological relevance. FoldX uses a full atomic description of the structure of the proteins. The different energy terms taken into account in FoldX have been weighted using empirical data obtained from protein engineering experiments.
FoldX is being developed by the group of Luis Serrano at the CRG in Barcelona, Spain, in collaboration with Joost Schymkowitz and Frederic Rousseau and their team at the SWITCH Laboratory of VIB in Brussels, Belgium.
SmartCell is a program developed to provide an idea of the evolution of a network in a whole, single cell.
SmartCell is a program developed to provide an idea of the evolution of a network in a whole, single cell. Based on stochastic algorithms, SmartCell needs multiple runs to have mean results. To help the user, SmartCell is distributed with a graphic user interface that allows for the creation of a model with a user friendly interface, as well as for the analysis and treatment of the results after the runs.
SmartCell is being developed by Luis Serrano and his team at the CRG in Barcelona.
A database for the molecular phenotyping of human SNPs and disease mutations
Single nucleotide polymorphisms (SNPs) are, together with copy number variation, the primary source of variation in the human genome. SNPs are associated with altered response to drug treatment, susceptibility to disease, and other phenotypic variation. Furthermore, during genetic screens for disease-associated mutations in groups of patients and control individuals, the distinction between disease causing mutations and polymorphisms is often unclear. Annotation of the functional and structural implications of single nucleotide changes thus provides valuable information to interpret and guide experiments.
SNPeffect is a database of non-synonymous SNPs and their predicted effect on the functional and physicochemical properties of the affected proteins. More precisely, SNPeffect analyses the effect of coding, non-synonymous SNPs on 3 categories of functional and physico-chemical properties of the affected proteins, namely protein structure and dynamics [stability, aggregation, dynamics, etc.], integrity of functional sites and cellular processing.
SNPeffect was originally developed by Joost Schymkowitz and Frederic Rousseau and their team at the SWITCH Laboratory of VIB in Brussels, Belgium, in collaboration with Luis Serrano and his team at the European Molecular Biology Laboratory in Heidelberg, Germany.
An algorithm for the prediction of aggregating regions in unfolded polypeptide chains
TANGO is a statistical mechanics computer algorithm developed for the prediction of aggregation nucleating regions in proteins, as well as of the effect of mutations and environmental conditions on the aggregation propensity of these regions.
TANGO is based on the physico-chemical principles of b-sheet formation extended by the assumption that the core regions of an aggregate are fully buried. TANGO was benchmarked against 175 peptides of over 20 proteins and was able to predict the sequences experimentally observed to contribute to the aggregation of these proteins. TANGO also correctly predicts the aggregation propensities of several disease-related mutations in the Alzheimer´s b-peptide, human lysozyme and transthyrethin, and discriminates between b-sheet tendency and aggregation.
The success of TANGO confirms the model of intermolecular b-sheet formation as a wide-spread underlying mechanism of protein aggregation and opens the possibility of screening large databases for potential disease-related aggregation motifs, as well as optimizing recombinant protein yields by rationally out-designing protein aggregation.
TANGO was originally developed by Luis Serrano and his team at the European Molecular Biology Laboratory in Heidelberg, Germany.
An algorithm for the prediction of amylogenic regions in protein sequences
We have developed the WALTZ algorithm for the identification of amyloid forming hexapeptides in amino acid sequences. WALTZ combines terms from amino acid sequence scoring in the learning set, physical property analysis and homology modelling. The method shows ~84% sensitivity at ~92% specificity on the AmylHex dataset, and correctly identifies mutations in human proteins known to be associated with amyloid deposition. The combination of the aggregation predicting algorithm TANGO with WALTZ, provides a complete cover of aggregation and amyloid tendency in protein sequences.
WALTZ is being developed by Joost Schymkowitz and Frederic Rousseau and their team at the SWITCH Laboratory of VIB in Brussels, Belgium, in collaboration with Luis Serrano and his team at the CRG in Barcelona, Spain.