The impact of machine learning on future tuberculosis drug discovery

David A Winkler

doi:10.1080/17460441.2022.2108785

The impact of machine learning on future tuberculosis drug discovery

Expert Opin Drug Discov. 2022 Sep;17(9):925-927. doi: 10.1080/17460441.2022.2108785. Epub 2022 Aug 2.

Author

David A Winkler^{1

2

3}

Affiliations

¹ Department of Biochemistry and Chemistry, La Trobe Institute for Molecular Science, La Trobe University, Melbourne, Australia.
² Medicinal Chemistry, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Australia.
³ School of Pharmacy, University of Nottingham, Nottingham, UK.

PMID: 35912878
DOI: 10.1080/17460441.2022.2108785

No abstract available

Keywords: 3D-QSAR; Bayesian; COMSIA; CoMFA; Mycobacterium tuberculosis; drug discovery; machine learning; molecular docking; random forest; support vector machines; virtual screening.

Publication types

Editorial

MeSH terms

Drug Discovery
Humans
Machine Learning
Molecular Docking Simulation
Quantitative Structure-Activity Relationship*
Tuberculosis* / drug therapy