Virtual Drug Screening in the Chemical Space Accessible by Chemical Synthesis

• Applicants: Professor Dr. Jens Meiler; Professor Dr. Peter Florian Stadler
• Subject Area: Theoretical Chemistry: Electronic Structure, Dynamics, Simulation
• Term: since 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 497135079

Modern approaches to drug development start with the identification of a target and virtual screening of “drug-like” organic molecules. This entails two intertwined challenges: first the “ligand” must be functional and second it must be synthetically accessible. Often, previously studied substance classes are to be avoided due competing patents. Here we propose a computational approach to virtual drug screening that combines modern techniques of machine learning for functional evaluation of molecules, rule-based modelling to chemical reactions to maintain synthetic plausibility, and an Evolutionary Algorithm-inspired optimization approach. Cross-over and mutation operations are phrased in the rule-based framework, aiming at restricting the search to chemically realistic molecules. We propose, based on recent observations on the importance of representation, that the graph grammars built to reflect the chemist’s intuition of structural formulae and elementary reactions constitute a natural representative framework for both the traversal of chemical space and for learning functionally important features. We aim at the development of a comprehensive framework and accompanying software for virtual drug screening that will be tested against a suite of screening that are already available to the applicants. A part of the proposal we will also devise benchmarking procedures for this kind of virtual screening approaches including experimental validation with collaboration partners at University of Leipzig.

• DFG Programme: Priority Programmes
• Subproject of: SPP 2363: Utilization and Development of Machine Learning for Molecular Applications – Molecular Machine Learning
• International Connection: Denmark
• Cooperation Partner: Professor Dr. Jakob Lykke Andersen