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SUMMARY:Computational Approaches to Drug Discovery in the Era of Precision
  Medicine
DTSTART:20231109T111500
DTEND:20231109T133000
DTSTAMP:20260527T151236Z
UID:fd4845af9125ccdd8b180109ff37b94c319c846cf8a3f408ed441865
CATEGORIES:Inaugural lectures - Honorary Lecture
DESCRIPTION:Prof. Dr. Andrea Cavalli\nAbstract\n\nComputational drug disco
 very 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 over
 come this challenge\, physics-based computational approaches (e.g.\, enhan
 ced sampling methods) have been developed to accelerate the exploration of
  the conformational space of molecules. These methods also enable research
 ers to compute the free energy differences between different states of a m
 olecule 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 dr
 ug molecules. This talk overviews various enhanced sampling methods in com
 putational drug discovery\, their advantages\, and limitations. The discus
 sion then focuses on using these methods for free energy and kinetics esti
 mations\, reporting on the significant limitations toward accurate estimat
 es for large datasets of compounds.\nThe second part of the discussion dea
 ls 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 ef
 fectiveness of computational drug discovery and\, along with genomics anal
 ysis\, the development of new therapeutics to treat cancer via precision m
 edicine strategies.\n\nReferences\n \n\n	Decherchi S\, Cavalli A. Chem Re
 v. 2020\, 120\, 12788-12833.\n	Bernetti M\, Masetti M\, Rocchia W\, Cavall
 i A. Annu Rev Phys Chem. 2019\, 70\, 143-171.\n\n\nOnline event: https://e
 pfl.zoom.us/j/64852867309\n 
LOCATION:CE 1 5 https://plan.epfl.ch/?room==CE%201%205
STATUS:CONFIRMED
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