Wezen, Xavier Chee and Kai, Lee Fong and Fatima, Ayesha (2025) In silico methods in discovering novel inhibitors of sirtuins. In: Ranganathan, Shoba and Cannataro, Mario and Khan, Asif M., (eds.) Encyclopedia of Bioinformatics and Computational Biology. Elsevier, Amsterdam, pp. 657-667. ISBN 9780323955034 (Print) 9780323955027 (Online)
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Official URL: https://dx.doi.org/10.1016/B978-0-323-95502-7.00270-0
Abstract
Sirtuins are signaling proteins that belong to class III histone deacetylases and require NAD for activity. In mammals, seven sirtuins (SIRT1-SIRT7) exist, each with distinct cellular localizations and functions. Sirtuins play crucial roles in DNA repair, neurogenesis, aging, metabolism, and inflammation, and they are involved in cancer progression, either as tumor suppressors or promoters. Structurally, sirtuins have a conserved catalytic core and vary in their N- and C-terminal domains. SIRT activators and inhibitors are being explored for therapeutic purposes, including virtual screening methods for drug discovery. Machine learning and structure-based approaches have identified several potential sirtuin modulators, particularly for SIRT1, SIRT2 and SIRT3 highlighting their promise in treating various diseases.
| Item Type: | Book Section / Chapter |
|---|---|
| Uncontrolled Keywords: | Drug discovery; Machine learning approaches; Novel anti-cancer drugs; Sirtuin modulators |
| Divisions: | Faculty of Engineering and Natural Sciences |
| Depositing User: | Ayesha Fatima |
| Date Deposited: | 09 Apr 2026 11:18 |
| Last Modified: | 09 Apr 2026 11:18 |
| URI: | https://research.sabanciuniv.edu/id/eprint/53759 |

