Computationally driven Drug Discovery: tackling Kinetics and Residence time
CECAM-IT-SIMUL, Università Cattolica del Sacro Cuore in Rome, Italy
Following the previous editions held in L’Aquila in 2011, in Genova 2013, in Verona 2014, in Pomezia 2016 and in Milano 2017, the CDDD conference aims to gather together researchers making use of computational chemistry, chemoinformatics, QSAR and property prediction techniques, to carry on integrated drug discovery programs.
Expected outcomes of the convention are:
• to promote a deep scientific discussion in the multifaceted field of computational drug discovery;
• to promote the mutual acquaintance of research groups and to devise potential areas of collaboration;
• to promote the integration between industrial needs and academic expertise towards more effective drug discovery programs.
• to provide young researchers an exhaustive view of the most advanced in silico developments and applications.
This event has always gathered people coming from different environments. Although the major part is from Academy, representatives from Industry, as well as from Research Institutions (SISSA – Trieste, IFOM – Milano, IIT – Genova among the others), are usually present. We would like to underline that the event structure is mostly devoted to young researchers, which are given the opportunity to present their studies and results in a free and open discussion atmosphere.
The sessions will be focused on topical issues among which Kinetics and residence time in drug discovery, Cryptic and allosteric pocket identification and Big data and machine learning.
A particular focus will be given to "Ligand–target residence time”, an emerging key drug discovery parameter, able to reliably predict drug efficacy in vivo. Although wet experimental approaches are well established, reliable computational tools for predicting kinetics and residence time are still missing. Aim of this convention is to gather a sizeable number of scientist to examine and discuss different approaches, from brute-force molecular dynamics (MD) simulations, still computationally demanding, to new scaled-MD-based protocols, likely able to boost the use of in silico techniques in the field.
Stefano Alcaro ( University of Catanzaro ) - Organiser
Andrea Cavalli ( Italian Institute of Technology ) - Organiser
Rosella Ombrato ( Angelini Research Center (ACRAF), Roma ) - Organiser
Luca Sartori ( IFOM The FIRC Institute of Molecular Oncology ) - Organiser
Francesca Spyrakis ( University of Turin ) - Organiser
Giulio Vistoli ( University of Milan ) - Organiser