Generative kinase inhibitor modeling viewed from a medicinal chemistry perspective.

Future Medicinal ChemistryVol. 15, No. 4 CommentaryGenerative kinase inhibitor modeling viewed from a medicinal chemistry perspectiveJürgen BajorathJürgen Bajorath *Author for correspondence: Tel.: +49 228 7369 100; E-mail Address: bajorath@bit.uni-bonn.dehttps://orcid.org/0000-0002-0557-5714Department of Life Science Informatics & Data Science, B-IT, LIMES Program Unit Chemical Biology & Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Friedrich-Hirzebruch-Allee 5/6, D-53115, Bonn, GermanySearch for more papers by this authorPublished Online:9 Mar 2023https://doi.org/10.4155/fmc-2023-0029AboutSectionsView ArticleView Full TextPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinkedInRedditEmail View articleKeywords: compound designgenerative modelingkinase inhibitorsmedicinal chemistry relevancepublication standardsReferences1. Yoshimori A, Chen H, Bajorath J. Chemical language models for applications in medicinal chemistry. Future Med. Chem. (Ahead of Print. DOI: 10.4155/fmc-2022-0315).Google Scholar2. Segler MHS, Kogej T, Tyrchan C, Waller MP. Generating focused molecule libraries for drug discovery with recurrent neural networks. ACS Cent. Sci. 4(1), 120–131 (2018).Crossref, Medline, CAS, Google Scholar3. Gomez-Bombarelli R, Wei JN, Duvenaud D et al. Automatic chemical design using a data-driven continuous representation of molecules. ACS Cent. Sci. 4(2), 268–276 (2018).Crossref, Medline, CAS, Google Scholar4. Skinnider MA, Stacey RG, Wishart DS, Foster LJ. Chemical language models enable navigation in sparsely populated chemical space. Nat. Mach. Intell. 3(9), 759–770 (2021).Crossref, Google Scholar5. Flam-Shepherd D, Zhu K, Aspuru-Guzik A. Language models can learn complex molecular distributions. Nat. Commun. 13(1), e3293 (2022).Crossref, Medline, CAS, Google Scholar6. Sanchez-Lengeling B, Aspuru-Guzik A. Inverse molecular design using machine learning: generative models for matter engineering. Science 361(6400), 360–365 (2018).Crossref, Medline, CAS, Google Scholar7. Walters WP, Murcko M. Assessing the impact of generative AI on medicinal chemistry. Nat. Biotechnol. 38(2), 143–145 (2020).Crossref, Medline, CAS, Google Scholar8. Stokes JM, Yang K, Swanson K et al. A deep learning approach to antibiotic discovery. Cell 180(4), 688–702 (2020).Crossref, Medline, CAS, Google Scholar9. Laufer S, Bajorath J, Gehringer M, Gray N, Frye S, Lindsley CW. Publication criteria and requirements for studies on protein kinase inhibitors–what is expected? (“it is pretty easy to make a bad kinase inhibitor”). J. Med. Chem. 65(10), 6973–6974 (2022).Crossref, Medline, CAS, Google Scholar10. de Almeida AF, Moreira R, Rodrigues T. Synthetic organic chemistry driven by artificial intelligence. Nat. Rev. Chem. 3(10), 589–604 (2019).Crossref, Google Scholar11. Schwaller P, Laino T, Gaudin T et al. Molecular transformer: a model for uncertainty-calibrated chemical reaction prediction. ACS Cent. Sci. 5(9), 1572–1583 (2019).Crossref, Medline, CAS, Google Scholar12. Struble TJ, Alvarez JC, Brown SP et al. Current and future roles of artificial intelligence in medicinal chemistry synthesis. J. Med. Chem. 63(16), 8667–8682 (2020).Crossref, Medline, CAS, Google ScholarFiguresReferencesRelatedDetails Vol. 15, No. 4 STAY CONNECTED Metrics Downloaded 31 times History Received 31 January 2023 Accepted 9 February 2023 Published online 9 March 2023 Published in print February 2023 Information© 2023 Newlands PressKeywordscompound designgenerative modelingkinase inhibitorsmedicinal chemistry relevancepublication standardsFinancial & competing interests disclosureThe author has no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending or royalties.No writing assistance was utilized in the production of this manuscript.PDF download