Prof. Andrea Cavalli

Seminar Series
Get To Know Your Neighbors
Prof. Andrea Cavalli, Director, CECAM
Computational Approaches to Drug Discovery in the Era of Precision Medicine
Monday, Oct. 02, 2023 3:15 – 4:15pm (CET)
Hybrid or on-site INF 328

This talk is reserved for the EPFL community. Please log in to Zoom with your EPFL credentials. 

Computational drug discovery has become an increasingly important tool in the search for new drugs to treat a wide range of diseases. One of the critical challenges in this field is simulating the complex behavior of molecules at the atomic level, which can be computationally very expensive and time-consuming. To overcome this challenge, physics-based computational approaches (e.g., enhanced sampling methods) have been developed to accelerate the exploration of the conformational space of molecules. These methods also enable researchers to compute the free energy differences between different states of a molecule and estimate thermodynamic and kinetics properties such as binding free energies, residence time, etc. By using enhanced sampling methods, researchers can more efficiently search for potential drug candidates, screen databases of compounds, and optimize the properties of existing drug molecules. This talk overviews various enhanced sampling methods in computational drug discovery, their advantages, and limitations. The discussion then focuses on using these methods for free energy and kinetics estimations, reporting on the significant limitations toward accurate estimates for large datasets of compounds.

The second part of the discussion deals with recent applications in anticancer drug discovery, focusing on the computational approaches used to identify synthetic lethality targets and design drugs that can exploit this paradigm. Particular attention will be given to genomics analysis, computational methods, and drug repurposing/discovery for personalized and precision treatments. We also discuss the challenges and limitations, including the need for comprehensive data on genetic alterations in cancer cells and the optimization of drug delivery for next-generation therapeutics. In conclusion, the talk illustrates how enhanced sampling methods can significantly improve the efficiency and effectiveness of computational drug discovery and, along with genomics analysis, the development of new therapeutics to treat cancer via precision medicine strategies.

On January 2003, Professor Andrea Cavalli was appointed Director of CECAM (Centre Européen de Calcul Atomique et Moléculaire) at the EPFL. Until 2022, he was the Director of Computational Sciences and the Vice-Scientific Director of the Italian Institute of Technology. His research combines computational physics/chemistry with drug discovery, focusing mainly on cancer. He has developed and applied algorithms and protocols to accelerate and enhance the discovery of novel lead and drug candidates. In particular, he has been a pioneer in using molecular dynamics (MD) simulations and related approaches to (multitarget) drug discovery, developing algorithms for dynamic docking, allosteric modulation, residence time prediction, free energy estimation, etc. He has recently led a project to build genomics and computational infrastructures for precision medicine. In collaboration with clinics and hospitals, he has developed programs in oncogenomics aimed at discovering actionable drug genes through next-generation sequencing, bioinformatics, and machine learning. New targets from omics analyses feed novel drug discovery programs focusing on synthetic lethality. He is one of the founders of BiKi Technologies, a high-tech company focused on MD and enhanced sampling for drug design and discovery.