Covalent and non-covalent interactions self-supervised representation of molecules for chemotherapeutic drug design

Most of the drugs used to treat cancer have been originally identified from natural sources. While Nature did a great job selecting those compounds, some of them have shown limitations in the treatment of cancer and others have shown to be insufficient on some cancer types. Furthermore, it exists a gigantic number (nearly infinite) of small molecules human can synthetize. The goal of this project is to use existing machine learning technics and novel input representation approaches in order to efficiently search in this gigantic chemical space, newly potential molecules that could be used as new chemotherapeutic drugs.

Intern: 
Hadrien Mary
Faculty Supervisor: 
Gary Brouhard
Province: 
Quebec
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