Machine learning models to identify lead compound and substitution optimization to have derived energetics and conformational stability through docking and MD simulations for sphingosine kinase 1.
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| Title: | Machine learning models to identify lead compound and substitution optimization to have derived energetics and conformational stability through docking and MD simulations for sphingosine kinase 1. |
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| Authors: | Dhanabalan AK; Department of Biotechnology, School of Bioengineering, SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu, 603203, India., Devadasan V; Department of Biotechnology, School of Bioengineering, SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu, 603203, India. Shirai2011@gmail.com., Haribabu J; Facultad de Medicina, Universidad de Atacama, Los Carreras 1579, 1532502, Copiapó, Chile.; Chennai Institute of Technology (CIT), Chennai, Tamil Nadu, 600069, India., Krishnasamy G; Centre of Advanced Study in Crystallography and Biophysics, University of Madras, Guindy Campus, Chennai, Tamil Nadu, 600025, India. gunaunom@gmail.com. |
| Source: | Molecular diversity [Mol Divers] 2025 Aug; Vol. 29 (4), pp. 2945-2977. Date of Electronic Publication: 2024 Oct 17. |
| 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/s11030-024-10997-4 |
