Thursday, 21. October 2021 | 15:15 - 16:00

Forum

Program Entry

«Machine Learning Drug Design (MLDD)»

Title: «Applications of Machine Learning Drug Design (MLDD)» Referenten: Elisa Liberatore and Julien Hazemann, Idorsia, elisa.liberatore@idorsia.com, julien.hazemann@idorsia.com

Machine Learning Drug Design (MLDD) is a data-driven, iterative, and highly collaborative way of designing new drug candidates. MLDD can integrate several ML models for multi-parameter optimisation and more traditional CADD approaches such as 3D docking or pharmacophore screening to identify the most promising among the generated virtual compounds. It is also an extremely modular approach, in which every step, from structure generation to filtering, can be adapted to the specific project needs. 
In this talk we will introduce Idorsia’s MLDD platform, focusing on its most challenging aspects, and we will present an application of MLDD to the quest for new SARS-CoV-2 Mpro inhibitors, a project in collaboration with TU-Dortmund. 

Authors

Elisa Liberatore, Julien Hazemann, Idorsia

 

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