Guallar Tasies, Víctor
ICREA Research Professor at Barcelona Supercomputing Center - Centro Nacional de Supercomputación (BSC-CNS).
Life & Medical Sciences
Short biography
Professor Guallar performed his undergraduate at the Autonomous University of Barcelona (Spain), with a major in Chemistry, followed by a joined PhD in physical chemistry at UC Berkeley and Autonomous University of Barcelona, with Professors Josep M. Lluch, Miquel Moreno and William H Miller (November 1999 thesis defense). Afterwards, he moved for a postdoctoral research position (2000-2003) to Columbia University in New York City, under the supervision of Prof. Richard Friesner. In 2003 he got a teanured position as an assistant Professor at the Biochemistry and Molecular Biophysics department at the School of Medicine in Washington University in St. Louis. In 2006 he was appointed ICREA Research Professor in the Life Science Department at the Barcelona Supercomputing Center (BSC), were he has been developing his research group. In 2016 he co-founded Nostrum Biodiscovery, the first spin-off from the BSC.
Research interests
In the EAPM lab at BSC we are devoted to the development and application of computational algorithms in molecular modeling. Using techniques such as Monte Carlo simulations, bioinformatics, machine learning and mixed quantum mechanics/molecular mechanics methods, we face different biophysical and biochemical challenges, including characterization and engineering of enzymes for industrial and biomedical applications, software development for more efficient early stages of drug design, and neoantigen presentation prediction.
Along 2019, particular interest has focused on: i) developing the first PluriZyme with two activities, providing complex cascade reactions in a single enzyme, ii) enhancing our software PELE with a fragment builder and a Markov State Model modules, and iii) the development of NOAH (Neoantigen Optimization AlgoritHm), the first bioinformatics procedure for neoantigen selection that correlates with an immunogenic response.