A deep learning-based theoretical protocol to identify potentially isoform-selective PI3Kα inhibitors.
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| Title: | A deep learning-based theoretical protocol to identify potentially isoform-selective PI3Kα inhibitors. |
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| Authors: | Shafiq M; H.E.J. Research Institute of Chemistry, International Center for Chemical and Biological Sciences, University of Karachi, Karachi, 75270, Pakistan., Sherwani ZA; Dr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences, University of Karachi, Karachi, 75270, Pakistan., Mushtaq M; Dr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences, University of Karachi, Karachi, 75270, Pakistan., Nur-E-Alam M; Department of Pharmacognosy, College of Pharmacy, King Saud University, P.O. Box. 2457, Riyadh, 11451, Kingdom of Saudi Arabia., Ahmad A; Department of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, CA, 92618, USA., Ul-Haq Z; Dr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences, University of Karachi, Karachi, 75270, Pakistan. zaheer.qasmi@iccs.edu. |
| Source: | Molecular diversity [Mol Divers] 2024 Aug; Vol. 28 (4), pp. 1907-1924. Date of Electronic Publication: 2024 Feb 02. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: ESCOM Science Publishers Country of Publication: Netherlands NLM ID: 9516534 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1573-501X (Electronic) Linking ISSN: 13811991 NLM ISO Abbreviation: Mol Divers Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1573-501X |
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| DOI: | 10.1007/s11030-023-10799-0 |
