Dr. Ferran Feixas is currently a Ramón y Cajal researcher at the Institute of Computational Chemistry and Catalysis (IQCC) of the University of Girona. Dr. Feixas obtained his doctorate in Chemistry in 2011 at the University of Girona (Spain) under the direction of Prof. Miquel Solà, Prof. Jordi Poater and Dr. Eduard Matito During the doctoral thesis (FPU scholarship), he worked on the application and development of computational chemistry tools for the analysis of chemical bonding and aromaticity. In this period, he carried out research stays in France (Prof. B. Silvi) and Germany (Prof. L. González). Upon graduation, he joined the University of California, San Diego (UCSD, USA) for a two-year postdoctoral position with a Beatriu de Pinós (BP) fellowship with the group of Prof. J. Andrew McCammon. At UCSD, he gained experience in computational biochemistry, drug discovery, and biomolecular simulations. In particular, he worked on the incorporation of molecular dynamics simulations into computer-aided drug discovery protocols and on the development and application of improved sampling techniques based on accelerated molecular dynamics (aMD) simulations to study protein folding. In 2015, he joined the Institute of Computational Chemistry and Catalysis (UdG) with a Marie Curie IF Individual Grant to study the molecular basis of (bio)molecular recognition and self-assembly with molecular dynamics simulations. In 2018, he joined the CompBioLab research group as Senior Researcher and co-PI together with Prof. Sílvia Osuna (IUdG) working on the application of improved sampling techniques to explore the role of conformational dynamics in enzyme catalysis and the improvement of computational protocols for enzyme design. In 2019, Dr. Feixas was awarded as principal investigator with a JIN de Retos de la Societat project (RTI2018-101032-J-I00,), in 2021 a Ramón y Cajal grant (RYC2020-029552-I) and in 2022 a TED project (TED2021 -130173B-C42). The goal of the research group is to develop strategies that combine different simulation techniques that take into account the dynamics of (bio)molecules to reconstruct step-by-step (bio)chemical and (bio)molecular recognition processes and then take advantage of this information to improve the discovery and rational design of new drugs, supramolecular complexes and/or (bio)catalysts.