Date: 28 January 2025
Time: 15:00 CET
Abstract
Knowledge of atomic-level structures of ligand-protein complexes is key for basic research and structure-based drug design. Computational methods have become a valid complement to experiments, but accuracy of predictions generally degrades with the extent of the structural changes associated to binding. Accurate description of ligand flexibility is equally crucial, particularly in a virtual screening (VS) whereby initial structures are often generated without accounting for structural adaptation in binding.
To address this issue on the proteins side, we recently introduced gEDES (generalized Ensemble Docking with Enhanced-sampling of pocket Shape), a computational method based on metadynamics to generate bound-like conformations of proteins by only exploiting their unbound structure. In this talk, I will first introduce the gEDES protocol; next, I will talk about SHAPER, an algorithm aiming to generate ligand structures snugly fitting into the binding pocket of a generic receptor, adapting to its geometry.
Preliminary results demonstrate that using this dynamic shape-matching algorithm improves the accuracy of VS campaigns compared to flexible docking calculations.
Presenter
Attilio Vargiu, University of Cagliari
After a Master’s degree in Physics at the same University in 2003, Attilio obtained his Ph.D. in Statistical and Biological Physics at the International School for Advanced Studies (ISAS/SISSA, Trieste, Italy) in 2008. Between 2008 and 2019 he traveled to Italy (University of Cagliari), Germany (Jacobs University, Bremen), The Netherlands (Utrecht University), and the U.S.A. (University of California, Berkeley). In 2019 he was appointed Assistant Professor of Applied Physics at the University of Cagliari, where he is now an Associate Professor.
His research is focused on simulating biological macromolecules, peptides, small molecules, membranes, and their assemblies using a plethora of advanced computational methods, from quantum-based to coarse-grained to machine-learning-based approaches. The main research lines focus on: bacterial resistance to antibiotics mediated by multi-drug transporters; self-assembly of chiral peptides for technological and biomedical applications; development of methods and protocols to accurately predict the structures of challenging protein-ligand complexes.
Attilio represents Italy on the BioExcel Ambassador Program Council
