首页|University of Belgrade Reports Findings in Machine Learning (Integration of 3D-Q SAR, molecular docking, and machine learning techniques for rational design of nicotinamide-based SIRT2 inhibitors)
University of Belgrade Reports Findings in Machine Learning (Integration of 3D-Q SAR, molecular docking, and machine learning techniques for rational design of nicotinamide-based SIRT2 inhibitors)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is the subject of a report. According to news reporting out of Belgrade, Serbia, by N ewsRx editors, research stated, “Selective inhibitors of sirtuin-2 (SIRT2) are i ncreasingly recognized as potential therapeutics for cancer and neurodegenerativ e diseases. Derivatives of 5-((3-amidobenzyl)oxy)nicotinamides have been identif ied as some of the most potent and selective SIRT2 inhibitors reported to date ( Ai et al., 2016; Ai et al., 2023, Baroni et al., 2007).”
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