Life Sciences

The fundamental goal of our group is the theoretical study of biochemical systems, from general methodological development, to the analysis of specific problems of special biological relevance. For instance, we are using molecular dynamics and statistical mechanics to study anomalous forms of nucleic acids. Particular attention is paid to the study of conformational transitions in DNA, drug-DNA interactions, and the analysis of triple helices and other structures of potential impact in antigene or antisense therapies. We are also interested in the understanding of the basis of protein interactions, including those of pharmacological importance, and have also made several studies on very basic aspects of enzymatic reactivity, protein folding and docking. In this context, we have created the MODEL (Molecular Dynamics Extended Library) library of molecular dynamics trajectories for all the representative proteins. The project, the largest of this type in the world, provide us with a complete picture of protein dynamics and help us in drug-design projects.

Our goal is to take advantage of computing resources to contribute to the general understanding of the biology of genomes. We are focused in the design, development, and use of bioinformatic protocols and tools in the context of comparative genomics and analyses of gene and protein collections. These approaches are designed to answer questions related to the modifications of genes and regulatory regions during evolution and their impact in the physiology of the organisms, as well as to understand the evolution of biological systems.

The key aim of the INB is to generate and apply bioinformatics solutions to special requirements emerging from the development and execution of national research projects with a genomic or proteomics focus. Within INB the mission Computational Node 2 is to provide computational resources, including hardware specifically intended to the INB, biological databases, and generic analysis applications to the bioinformatics community.

Our research focuses on theoretical and computational approaches to protein interactions. We aim to develop and optimize computational algorithms for characterizing and understanding protein-protein association, which remains one of the most important challenges in Structural Biology. The ultimate goal is to understand the subtle determinants of the specificity of protein-protein binding, which in turn will help us to make more accurate predictions of complexes of biological and therapeutical interest. All this knowledge will also help to predict the interaction of small molecules with protein-protein interfaces, with the goal of designing compounds capable of inhibiting protein interactions of therapeutical interest.

Our main goal is the study of complex biochemical processes both at an electronic, by means of quantum mechanics, and atomic, by means of classical mechanics, theoretical detail. First, we place particular on the application of such methods, with emphasis on protein-ligand interactions. The second area involves the development of new methodological components, centered in obtaining long time protein dynamics by means of a kinetic Monte Carlo scheme.