Artificial intelligence to deep learning: machine intelligence approach for drug discovery
Drug designing and development is an important area of research for pharmaceutical
companies and chemical scientists. However, low efficacy, off-target delivery, time …
companies and chemical scientists. However, low efficacy, off-target delivery, time …
Concepts of artificial intelligence for computer-assisted drug discovery
X Yang, Y Wang, R Byrne, G Schneider… - Chemical …, 2019 - ACS Publications
Artificial intelligence (AI), and, in particular, deep learning as a subcategory of AI, provides
opportunities for the discovery and development of innovative drugs. Various machine …
opportunities for the discovery and development of innovative drugs. Various machine …
Artificial intelligence and machine learning‐aided drug discovery in central nervous system diseases: State‐of‐the‐arts and future directions
Neurological disorders significantly outnumber diseases in other therapeutic areas.
However, developing drugs for central nervous system (CNS) disorders remains the most …
However, developing drugs for central nervous system (CNS) disorders remains the most …
Alzheimer's disease: updated multi-targets therapeutics are in clinical and in progress
Z Sang, K Wang, J Dong, L Tang - European journal of medicinal chemistry, 2022 - Elsevier
Alzheimer's disease is a chronic and progressive brain neurodegenerative disease affecting
over 30 million people globally. Currently, no effective treatment is available due to multiple …
over 30 million people globally. Currently, no effective treatment is available due to multiple …
[HTML][HTML] Neuroprotective potential of ellagic acid: a critical review
Ellagic acid (EA) is a dietary polyphenol present in various fruits, vegetables, herbs, and
nuts. It exists either independently or as part of complex structures, such as ellagitannins …
nuts. It exists either independently or as part of complex structures, such as ellagitannins …
Machine learning-based virtual screening and its applications to Alzheimer's drug discovery: a review
KA Carpenter, X Huang - Current pharmaceutical design, 2018 - ingentaconnect.com
Background: Virtual Screening (VS) has emerged as an important tool in the drug
development process, as it conducts efficient in silico searches over millions of compounds …
development process, as it conducts efficient in silico searches over millions of compounds …
In silico polypharmacology of natural products
Natural products with polypharmacological profiles have demonstrated promise as novel
therapeutics for various complex diseases, including cancer. Currently, many gaps exist in …
therapeutics for various complex diseases, including cancer. Currently, many gaps exist in …
Baicalein as a potent neuroprotective agent: A review
In recent times, neurodegenerative diseases are the most challenging global health
problems. Neuronal cell death or damage is a key factor for many neurodegenerative …
problems. Neuronal cell death or damage is a key factor for many neurodegenerative …
Harnessing endophenotypes and network medicine for Alzheimer's drug repurposing
Following two decades of more than 400 clinical trials centered on the “one drug, one target,
one disease” paradigm, there is still no effective disease‐modifying therapy for Alzheimer's …
one disease” paradigm, there is still no effective disease‐modifying therapy for Alzheimer's …
Machine learning in Alzheimer's disease drug discovery and target identification
C Geng, ZB Wang, Y Tang - Ageing Research Reviews, 2024 - Elsevier
Alzheimer's disease (AD) stands as a formidable neurodegenerative ailment that poses a
substantial threat to the elderly population, with no known curative or disease-slowing drugs …
substantial threat to the elderly population, with no known curative or disease-slowing drugs …