Objective Due to its fundamental regulatory role, molecular recognition has been extensively studied by both experiments andsimulations. During the last 30 years impressive technical advances allowed significant progress in understanding molecularrecognition mechanisms. However, the matter is far from settled and contradictory reports are still appearing in the literature.Lately, I have been studying these processes using a combination of computational and experimental approaches indifferent systems. Here I propose to study several representative model systems in great details, taking advantages of new force fields, DFT functionals and enhanced sampling algorithms recently emerged. These systems are small enough to allow the use of state-of-the-art simulation techniques; still they are sufficiently complex not only to mimic the behaviour of far larger systems but also to use apparently different mechanisms. Indeed, their molecular recognition needs complex conformational changes, the re-arrangementof water molecules in the binding cavity, and an active role of the ligand in the binding/release mechanisms. The overarchingobjective of my proposal is to learn the state-of-the-art enhanced sampling techniques developed at UCL and combine themwith QM/MM approaches to: i) understand how bio-molecular recognition works in both isoforms, ii) fully characterize thethermodynamics and kinetic processes that govern them and iii) validate the computational approaches against high-qualityexperimental data. If successful, the in-depth understanding of the molecular binding mechanism will shed light on anintriguing and important biological system and provide a much needed benchmark to the computational community. Thischallenging but feasible project will have a far reaching impact on a number of H2020 priority areas, including drug discoveryand bio-molecular engineering. Fields of science medical and health sciencesbasic medicinepharmacology and pharmacydrug discoverynatural sciencesphysical sciencesthermodynamics Programme(s) H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions Main Programme H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility Topic(s) MSCA-IF-2017 - Individual Fellowships Call for proposal H2020-MSCA-IF-2017 See other projects for this call Funding Scheme MSCA-IF-EF-ST - Standard EF Coordinator UNIVERSITY COLLEGE LONDON Net EU contribution € 195 454,80 Address Gower street WC1E 6BT London United Kingdom See on map Region London Inner London — West Camden and City of London Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Other funding € 0,00
