Cited by 392Computational Drug Discovery MethodsMachine Learning in Materials ScienceHistory and advancements in chemistry

A Scoring Scheme for Discriminating between Drugs and Nondrugs

Sadowski, Jens, Kubinyi, Hugo·1998·Journal of Medicinal Chemistry

Abstract

A scoring scheme for the rapid and automatic classification of molecules into drugs and nondrugs was developed. The method is a valuable new tool that can aid in the selection and prioritization of compounds from large compound collections for purchase or biological testing and that can replace a considerable amount of laborious manual work by a more unbiased approach. It is based on the extraction of knowledge from large databases of drugs and nondrugs. The method was set up by using atom type descriptors for encoding the molecular structures and by training a feedforward neural network for classifying the molecules. It was parametrized and validated by using large databases of drugs and nondrugs (169 331 molecules from the Available Chemicals Directory, ACD, and 38 416 molecules from the World Drug Index, WDI). The method revealed features in the molecular descriptors that either qualify or disqualify a molecule for being a drug and classified 83% of the ACD and 77% of the WDI adequately.

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Crossref · 10.1021/jm9706776

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4 of 4 references verified0 citation errors · 0 not checkable

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  • The 'drug' quality is not an intrinsic property of chemicals since regulatory agencies and humans approve compounds for medicinal use.

    “The 'drug' quality is not an intrinsic property of chemicals since regulatory agencies and, implicitly, humans approve compounds for medicinal use (29).”
  • ML-based drug-likeness quantification is an integral part of the drug discovery process, with nearly 20 independent papers dedicated to drug-likeness discussed elsewhere.

    “Despite these caveats, ML-based drug-likeness quantification is an integral part of the drug discovery process, with nearly 20 independent papers dedicated to druglikeness discussed elsewhere (29).”

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Authors
Sadowski, J., & Kubinyi, H.
Affiliations
BASF (Germany) (DE)
Venue
Journal of Medicinal Chemistry
Published
1998-08-01
Volume
41
Issue
18
Pages
3325-3329
ISSN
  • 0022-2623 (ISSN-L)
  • 1520-4804
OpenAlex
W2010595835
Cited by
392
References
4
Citations by year
2026: 5 · 2025: 3 · 2024: 5 · 2023: 5 · 2022: 5 · 2021: 5 · 2020: 5 · 2019: 7 · 2018: 6 · 2017: 6 · 2016: 6 · 2015: 5 · 2014: 5 · 2013: 4 · 2012: 7
FWCI
40.88
Type
journal article
Language
en
Open access
closed
Locations
  • Journal of Medicinal Chemistry (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
  • Physical Sciences › Materials Science › Materials Chemistry › Machine Learning in Materials Science
  • Physical Sciences › Chemistry › Physical and Theoretical Chemistry › History and advancements in chemistry
Keywords
drug-likeness prediction, scoring system, molecular descriptors, feedforward neural networks, compound prioritization
MeSH terms
Pharmaceutical Preparations, Drug Design, Databases, Factual, Neural Networks, Computer

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