Daniel Álvarez García Email & Phone Number

Barcelona, Catalonia, Es

I support pharma and biotechs in their drug design projects using computational and medicinal chemistry tools.

Bethesda, Maryland, Us

I led the computational chemistry support in several integrated drug discovery projects at Gain which involved different structure-based and ligand-based methodologies: from virtual screening to property prediction or hit to lead optimization. In parallel, I guided the development of the structure-based chemoinformatics discovery platform (SEE-Tx) by introducing new physics based methodologies and technologies (like AI) with the aim to increase the quality and throughput.

Paris, Ile-De-France, Fr

Design, development and management of 3decision: a scientific web application to handle structural knowledge for drug design. It includes 2D chemoinformatics and 3D protein-ligand structural data handling, analysis, and visualization tools in a modern website. We built a comprehensive structural database integrating different sources of information, linking ligands, pockets and protein data into a single information source, enabling complex and advanced structural queries. I participated in the development of off-target prediction algorithms, 3D interaction based searches and pocket determination algorithms. In collaboration with other partners and clients, I participated in the design and development of bespoke chemoinformatics software solutions (eg. crystallographic structures registration system).

Barcelona, Barcelona, Es

Barcelona, Barcelona, Es

My PhD thesis in Computer Aided Drug Discovery focused on developing, validating and extending a method called MDMix. It is based in the use of molecular dynamics with explicit aqueous-organic solvent mixtures to identify hot-spots ("high affinity binding spots") over macromolecular systems and try to use this information in a qualitative and quantitative manner. We investigated all the possible advantages of such information in the process of drug design: from quantitative free energy predictions to criptic pockets finding and virtual screening.Moreover I was involved in collaborative projects academic and industrial partners giving molecular modeling support: docking, structure and ligand based virtual screenings, virtual chemical libraries management, properties predictions and binding mode studies through molecular dynamics. Finally, a big component of my thesis involved programming and releasing open-source python tools to facilitate the application of the MDMix methodology.

Doctor Of Philosophy (Ph.D.), Molecular Modeling

Msc Bioinformatics For Health Sciences, Computational Chemistry, Computational Biology, Bioinformatics, Drug Design

Licentiate Degree, Pharmacy