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 with binding. Accurate description of ligand flexibility is equally crucial, particularly in virtual screening whereby initial structures are often generated without accounting for structural adaptation in binding. We will discuss the current advances in Computational Biology and machine learning and their synergism in drug resistance and development.
Facilitator
Dr. Helen Zgurskaya
Date & Time
February 20 // 10:00 a.m. - 12:00 p.m.
Location
SLSRC Astellas Conference Room, Third Floor
| Time | Program | Speaker |
|---|---|---|
| 10:30 am -10:40 am | Introductions | Dr. Helen Zgurskaya |
| 10:40 am - 11:30 am | Molecular machines: a computational view. | Professor Paolo Ruggerone |
| 11:30 am - 12:20 pm | Accounting for protein and ligand flexibility in molecular docking and virtual screening of challenging targets. | Associate Professor Attilio V. Vargiu |
| 12:20 pm - 12:30 pm | Discussion and Questions |
Dr. Paolo Ruggerone is Professor of Physics at the Department of Physics at the University of Cagliari, Italy. With a background in matter physics, he has gained experience with computational methods applied to biomedical and biological problems. He has studied the impact of mutations in globular proteins, the interaction of compounds with DNA, the dynamics of viral proteins and the mechanisms associated with the emergence of bacterial resistance to antibiotics. He has also developed automated pipelines to generate molecular descriptors for use in machine learning procedures. Furthermore, he has been involved in the construction of molecular databases for families of antimicrobial compounds and recently started a computational research on autism.
Dr. Attilio Vargiu is Associate Professor of Applied Physics at the University of Cagliari. After a M.Sc. in Physics at the same University in 2003, he completed a 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 conducted research in Italy (University of Cagliari), Germany (Jacobs University, Bremen), Netherlands (Utrecht University), and the U.S.A. (University of California, Berkeley). 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 approaches. The current research: 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.
