Discovery of a novel drug is an optimizing challenge against an array of chemical and biological attributes to reach the desired efficacy and safety profile. The immense complexity of the human body combined with the astronomically large druggable chemical space hinders the selection of molecules with such a balanced profile. Therefore, the medicinal chemistry toolbox embraces all computational techniques with predictive power to focus the chemical space to the most promising candidates for synthesis and testing. The diversity includes data analysis tools, physics-based simulations, biological target structure driven or ligand structure based approaches [1-3]. While the size of the compound collections vary from a couple of close analogues up to billions of virtual compounds to process[4]. This presentation will highlight general concepts and techniques applied in computer aided drug design, focusing on data and ligand based computational chemistry approaches and showcase solutions developed by ChemAxon.

[1] Gisbert Schneider, David E Clark, Angew Chem Int Ed Engl. 2019, 5;58(32):10792-10803.
[2] John G Cumming, Andrew M Davis, Sorel Muresan, Markus Haeberlein, Hongming Chen, Nat Rev Drug Discov, 2013, 12(12):948-62.
[3] Yu-Chen Lo, Stefano E Rensi, Wen Torng, Russ B Altman, Drug Discov Today 2018, 23(8):1538-1546
[4] Torsten Hoffmanm, Marcus Gastreich, Drug Discov Today, 2019, 24(5):1148-1156.