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Electrostatic Interaction Force–Based Features Using PointNet Framework in Predicting RSK2 Inhibitor Bioactivity.

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Title: Electrostatic Interaction Force–Based Features Using PointNet Framework in Predicting RSK2 Inhibitor Bioactivity.
Authors: Zhao, Tian1,2 (AUTHOR), Gu, Rong-Ling3 (AUTHOR), Du, Shijie1 (AUTHOR), Xu, Lu1,2 (AUTHOR) lxchemo@163.com, Basu Roy, Sohini (AUTHOR) sbasuroy@wiley.com
Source: Journal of Chemistry. 3/30/2026, Vol. 2026, p1-16. 16p.
Database: Academic Search Ultimate
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  Data: Electrostatic Interaction Force–Based Features Using PointNet Framework in Predicting RSK2 Inhibitor Bioactivity.
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Chemistry%22">Journal of Chemistry</searchLink>. 3/30/2026, Vol. 2026, p1-16. 16p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=192658928
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      – Type: doi
        Value: 10.1155/joch/4899563
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      – Code: eng
        Text: English
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        PageCount: 16
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      – TitleFull: Electrostatic Interaction Force–Based Features Using PointNet Framework in Predicting RSK2 Inhibitor Bioactivity.
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            NameFull: Zhao, Tian
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              Text: 3/30/2026
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              Y: 2026
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