Regression Modeling and Virtual Screening of Natural Products Exhibiting Antibacterial Activity. An Application of Electronic-structure Informatics Descriptors
Author:
Affiliation:
1. Graduate School of Science and Technology, Kumamoto University, 2-39-1 Kurokami, Chuo-ku, Kumamoto 860-8555, Japan
2. Faculty of Advanced Science and Technology, Kumamoto University, 2-39-1 Kurokami, Chuo-ku, Kumamoto 860-8555, Japan
Publisher
The Chemical Society of Japan
Subject
General Chemistry
Link
http://www.journal.csj.jp/doi/pdf/10.1246/cl.200966
Reference42 articles.
1. E. O. Pyzer-Knapp, T. Laino, ed. Machine Learning in Chemistry: Data-Driven Algorithms, Learning Systems, and Predictions, American Chemical Society, Washington, DC, 2020.
2. R. Todeschini, V. Consonni, Molecular Descriptors for Chemoinformatics, Wiley-VCH, Weinheim, 2009.
3. A. Mauri, alvaDesc: A Tool to Calculate and Analyze Molecular Descriptors and Fingerprints. In: K. Roy (eds) Ecotoxicological QSARs. Methods in Pharmacology and Toxicology. Humana, New York, NY, 2020.
4. T. Engel, J. Gasteiger, ed. Chemoinformatics: Basic Concepts and Methods, Wiley-VCH, Weinheim, 2018.
5. Combined use of computational chemistry and chemoinformatics methods for chemical discovery
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