The PharmacoInformatics research group is devoted to the development and application of computational methodologies in the area of drug design and development.
Nowadays, computational methodologies are widely applied in many steps of the drug discovery and development; from the structural modeling of a pharmacological target to the prediction of the ligand binding affinity. However, in the vast majority of cases the limitations of current technology allow us only to obtain approximate representations of the complex biological phenomena that are the focus of interest in the development of new drugs.
The PharmacoInformatics group aims to improve the current state-of-the-art with a pragmatic approach. We want to develop useful tools that increase the efficiency of the pharmaceutical R&D process. At the same time, the need to produce robust models led us to go beyond reductionist approaches and to develop multi-scale methods, depicting richer and more realistic representations of the phenomena under study than those produced by classical computational methods.
Main Publications with IMIM
• López-Massaguer O, Sanz F, Pastor M. An automated tool for obtaining QSAR-ready series of compounds using semantic web technologies. Bioinformatics 2018; 34(1): 131-133. IF 5.481. D1.
• López-Massaguer O, Pinto-Gil K, Sanz F, Amberg A, Anger LT, Stolte M, Ravagli C, Marc P, Pastor M. Generating modelling data from repeat-dose toxicity reports. Toxicol Sci 2018; 162(1): 287-300. IF 4.181. Q1.
• Pastor M, Quintana J, Sanz F. Development of an Infrastructure for the Prediction of Biological Endpoints in Industrial Environments. Lessons Learned at the eTOX Project. Front Pharmacol 2018; 9: 1147. IF 3.831. Q1.
• Romero L, Cano J, Gomis-Tena J, Trenor B, Sanz F, Pastor M, Saiz J. In Silico QT and APD Prolongation Assay for Early Screening of Drug-Induced Proarrhythmic Risk. J Chem Inf Model 2018; 58(4): 867-878. IF 3.804. Q1.