Machine learning methods for small data challenges in molecular science
Small data are often used in scientific and engineering research due to the presence of
various constraints, such as time, cost, ethics, privacy, security, and technical limitations in …
various constraints, such as time, cost, ethics, privacy, security, and technical limitations in …
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 …
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, develo** drugs for central nervous system (CNS) disorders remains the most …
However, develo** drugs for central nervous system (CNS) disorders remains the most …
Application advances of deep learning methods for de novo drug design and molecular dynamics simulation
De novo drug design is a stationary way to build novel ligands in the confined pocket of
receptor by assembling the atoms or fragments, while molecular dynamics (MD) simulation …
receptor by assembling the atoms or fragments, while molecular dynamics (MD) simulation …
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 …
Alkaloid from Geissospermum sericeum Benth. & Hook.f. ex Miers (Apocynaceae) Induce Apoptosis by Caspase Pathway in Human Gastric Cancer Cells
Gastric cancer is among the major causes of death from neoplasia leading causes of death
worldwide, with high incidence rates and problems related to its treatment. Here, we outline …
worldwide, with high incidence rates and problems related to its treatment. Here, we outline …
Caspase-8 in inflammatory diseases: a potential therapeutic target
W Zhang, C Zhu, Y Liao, M Zhou, W Xu… - Cellular & Molecular …, 2024 - Springer
Abstract Caspase-8, a renowned cysteine-aspartic protease within its enzyme family, initially
garnered attention for its regulatory role in extrinsic apoptosis. With advancing research, a …
garnered attention for its regulatory role in extrinsic apoptosis. With advancing research, a …
Can molecular dynamics simulations improve predictions of protein-ligand binding affinity with machine learning?
Binding affinity prediction largely determines the discovery efficiency of lead compounds in
drug discovery. Recently, machine learning (ML)-based approaches have attracted much …
drug discovery. Recently, machine learning (ML)-based approaches have attracted much …
Machine learning and deep learning in data-driven decision making of drug discovery and challenges in high-quality data acquisition in the pharmaceutical industry
SA Kumar, TD Ananda Kumar… - Future Medicinal …, 2022 - Taylor & Francis
Predicting novel small molecule bioactivities for the target deconvolution, hit-to-lead
optimization in drug discovery research, requires molecular representation. Previous reports …
optimization in drug discovery research, requires molecular representation. Previous reports …
Pandemic drugs at pandemic speed: infrastructure for accelerating COVID-19 drug discovery with hybrid machine learning-and physics-based simulations on high …
The race to meet the challenges of the global pandemic has served as a reminder that the
existing drug discovery process is expensive, inefficient and slow. There is a major …
existing drug discovery process is expensive, inefficient and slow. There is a major …