Arora Sakshi, Mittal Aayushi, Duari Subhadeep, Chauhan Sonam, Dixit Nilesh Kumar, Mohanty Sanjay Kumar, Sharma Arushi, Solanki Saveena, Sharma Anmol Kumar, Gautam Vishakha, Gahlot Pushpendra Singh, Satija Shiva, Nanshi Jeet, Kapoor Nikita, Cb Lavanya, Sengupta Debarka, Mehrotra Parul, Ghosh Tarini Shankar, Ahuja Gaurav
Department of Computational Biology, Indraprastha Institute of Information Technology-Delhi (IIIT-Delhi), New Delhi, India.
Kusuma School of Biological Sciences, Indian Institute of Technology, New Delhi, India.
Nat Aging. 2025 Jan;5(1):144-161. doi: 10.1038/s43587-024-00763-4. Epub 2024 Dec 3.
Aging involves metabolic changes that lead to reduced cellular fitness, yet the role of many metabolites in aging is unclear. Understanding the mechanisms of known geroprotective molecules reveals insights into metabolic networks regulating aging and aids in identifying additional geroprotectors. Here we present AgeXtend, an artificial intelligence (AI)-based multimodal geroprotector prediction platform that leverages bioactivity data of known geroprotectors. AgeXtend encompasses modules that predict geroprotective potential, assess toxicity and identify target proteins and potential mechanisms. We found that AgeXtend accurately identified the pro-longevity effects of known geroprotectors excluded from training data, such as metformin and taurine. Using AgeXtend, we screened ~1.1 billion compounds and identified numerous potential geroprotectors, which we validated using yeast and Caenorhabditis elegans lifespan assays, as well as exploring microbiome-derived metabolites. Finally, we evaluated endogenous metabolites predicted as senomodulators using senescence assays in human fibroblasts, highlighting AgeXtend's potential to reveal unidentified geroprotectors and provide insights into aging mechanisms.
衰老涉及导致细胞适应性降低的代谢变化，但许多代谢物在衰老中的作用尚不清楚。了解已知的老年保护分子的机制有助于深入了解调节衰老的代谢网络，并有助于识别其他老年保护剂。在这里，我们展示了AgeXtend，这是一个基于人工智能（AI）的多模式老年保护剂预测平台，它利用已知老年保护剂的生物活性数据。AgeXtend包含预测老年保护潜力、评估毒性以及识别靶蛋白和潜在机制的模块。我们发现，AgeXtend准确地识别了排除在训练数据之外的已知老年保护剂（如二甲双胍和牛磺酸）的延长寿命作用。使用AgeXtend，我们筛选了约11亿种化合物，并鉴定出许多潜在的老年保护剂，我们使用酵母和秀丽隐杆线虫寿命测定法对其进行了验证，并探索了微生物群衍生的代谢物。最后，我们使用人类成纤维细胞衰老测定法评估了预测为衰老调节剂的内源性代谢物，突出了AgeXtend在揭示未识别的老年保护剂和深入了解衰老机制方面的潜力。
