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Improving the Odds in Discriminating “Drug-like” from “Non Drug-like” Compounds

https://doi.org/10.1021/ci0003810
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Can We Learn To Distinguish between “Drug-like” and “Nondrug-like” Molecules?
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A Scoring Scheme for Discriminating between Drugs and Nondrugs
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Parallel Distributed Processing

What points at this work

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Additional file 1 of Virtual screening of Indonesian herbal compounds as COVID-19 supportive therapy: machine learning and pharmacophore modeling approaches
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Additional file 2 of Virtual screening of Indonesian herbal compounds as COVID-19 supportive therapy: machine learning and pharmacophore modeling approaches
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Additional file 3 of Virtual screening of Indonesian herbal compounds as COVID-19 supportive therapy: machine learning and pharmacophore modeling approaches
inferred← citeshttps://doi.org/10.6084/m9.figshare.20430722openalex-snapshot
Additional file 4 of Virtual screening of Indonesian herbal compounds as COVID-19 supportive therapy: machine learning and pharmacophore modeling approaches
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Additional file 5 of Virtual screening of Indonesian herbal compounds as COVID-19 supportive therapy: machine learning and pharmacophore modeling approaches
inferred← citeshttps://doi.org/10.6084/m9.figshare.20430728openalex-snapshot
Additional file 6 of Virtual screening of Indonesian herbal compounds as COVID-19 supportive therapy: machine learning and pharmacophore modeling approaches
inferred← citeshttps://doi.org/10.6084/m9.figshare.20430731openalex-snapshot
Additional file 7 of Virtual screening of Indonesian herbal compounds as COVID-19 supportive therapy: machine learning and pharmacophore modeling approaches
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