Machine learning methods for small data challenges in molecular science
B Dou, Z Zhu, E Merkurjev, L Ke, L Chen… - Chemical …, 2023 - ACS Publications
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, developing drugs for central nervous system (CNS) disorders remains the most …
However, developing 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 …
Alkaloid from Geissospermum sericeum Benth. & Hook.f. ex Miers (Apocynaceae) Induce Apoptosis by Caspase Pathway in Human Gastric Cancer Cells
ML Carmo Bastos, JV Silva-Silva, J Neves Cruz… - Pharmaceuticals, 2023 - mdpi.com
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 …
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 …
Machine learning in Alzheimer's disease drug discovery and target identification
C Geng, ZB Wang, Y Tang - Ageing Research Reviews, 2023 - 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 …
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 …
Mutually beneficial confluence of structure-based modeling of protein dynamics and machine learning methods
Proteins sample an ensemble of conformers under physiological conditions, having access
to a spectrum of modes of motions, also called intrinsic dynamics. These motions ensure the …
to a spectrum of modes of motions, also called intrinsic dynamics. These motions ensure the …