Deep Learning in Virtual Screening: Recent Applications and Developments.

ABSTRACT: Drug discovery is a cost and time-intensive process that is often assisted by computational methods, such as virtual screening, to speed up and guide the design of new compounds. For many years, machine learning methods have been successfully applied in the context of computer-aided drug discovery. Recently, thanks to the rise of novel technologies as well as the increasing amount of available chemical and bioactivity data, deep learning has gained a tremendous impact in rational active compound discovery. Herein, recent applications and developments of machine learning, with a focus on deep learning, in virtual screening for active compound design are reviewed. This includes introducing different compound and protein encodings, deep learning techniques as well as frequently used bioactivi

SUBMITTER: Kimber TB 

PROVIDER: S-EPMC8123040 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature