Predictive Modelling of Natural Medicinal Compounds for Alzheimer disease Using Machine Learning and Cheminformatics
Alzheimer disease (AD) is a neurodegenerative disease that lacks specific treatment options. Natural drugs have displayed neuroprotective effects; however, their high-throughput discovery is challenging because of the expense of experimental testing.The study proposed a machine learning approach to identify the anti-dementia activity of natural compounds based on molecular descriptors obtained from cheminformatics. The study used a set of active and inactive compounds obtained from public databases like ChEMBL and PubChem. Various molecular descriptors, including molecular weight, lipophilicity (LogP), topological polar surface area (TPSA), and hydrogen bonding descriptors, were calculate...
| Authors | Hafiza Syeda Yusra Tirmizi, Syed Ibad Hasnain, Muhammad Faris et al. |
|---|---|
| Primary category | q-bio.OT |
| Published | 20 April 2026 |
| Last updated at source | 25 April 2026 |
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