Introduction to the BioChemical Library (BCL): An Application-Based Open-Source Toolkit for Integrated Cheminformatics and Machine Learning in Computer-Aided Drug Discovery.

Autor:	Brown BP; Chemical and Physical Biology Program, Medical Scientist Training Program, Center for Structural Biology, Vanderbilt University, Nashville, TN, United States., Vu O; Department of Chemistry, Center for Structural Biology, Vanderbilt University, Nashville, TN, United States., Geanes AR; Department of Chemistry, Center for Structural Biology, Vanderbilt University, Nashville, TN, United States., Kothiwale S; Department of Chemistry, Center for Structural Biology, Vanderbilt University, Nashville, TN, United States., Butkiewicz M; Department of Chemistry, Center for Structural Biology, Vanderbilt University, Nashville, TN, United States., Lowe EW Jr; Department of Chemistry, Center for Structural Biology, Vanderbilt University, Nashville, TN, United States., Mueller R; Department of Chemistry, Center for Structural Biology, Vanderbilt University, Nashville, TN, United States., Pape R; Department of Chemistry, Center for Structural Biology, Vanderbilt University, Nashville, TN, United States., Mendenhall J; Department of Chemistry, Center for Structural Biology, Vanderbilt University, Nashville, TN, United States., Meiler J; Department of Chemistry, Departments of Pharmacology and Biomedical Informatics, Center for Structural Biology, Vanderbilt University, Nashville, TN, United States.; Institute for Drug Discovery, Leipzig University Medical School, Leipzig, Germany.
Jazyk:	angličtina
Zdroj:	Frontiers in pharmacology [Front Pharmacol] 2022 Feb 21; Vol. 13, pp. 833099. Date of Electronic Publication: 2022 Feb 21 (Print Publication: 2022).
DOI:	10.3389/fphar.2022.833099
Abstrakt:	The BioChemical Library (BCL) cheminformatics toolkit is an application-based academic open-source software package designed to integrate traditional small molecule cheminformatics tools with machine learning-based quantitative structure-activity/property relationship (QSAR/QSPR) modeling. In this pedagogical article we provide a detailed introduction to core BCL cheminformatics functionality, showing how traditional tasks (e.g., computing chemical properties, estimating druglikeness) can be readily combined with machine learning. In addition, we have included multiple examples covering areas of advanced use, such as reaction-based library design. We anticipate that this manuscript will be a valuable resource for researchers in computer-aided drug discovery looking to integrate modular cheminformatics and machine learning tools into their pipelines. Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. (Copyright © 2022 Brown, Vu, Geanes, Kothiwale, Butkiewicz, Lowe, Mueller, Pape, Mendenhall and Meiler.)
Databáze:	MEDLINE
Externí odkaz:	Zobrazit plný text záznamu