Lessons learnt from machine learning in early stages of drug discovery

Abstract

With the promise of a big leap, the field of Drug Discovery (DD) seems to have been permeated by Machine Learning (ML); it is not unreasonable to think that for every single ‘classical’ computational method within DD, there exists an ML-based counterpart; namely, for docking, Molecular Dynamics (MD), protein modeling, etc. Furthermore, the amount of money being invested for ML in DD is growing steadily. Evidently, ML methods have come to stay, and, in our opinion, they will be a valuable aid in accelerating the drug discovery pipeline...