AIMC Topic: Drug Discovery
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Artificial intelligence (AI) and alternative variables (AV) in drug discovery: A promising alliance.
Drug discovery today
Apr 9, 2024
Prediction of drug-target binding affinity based on deep learning models.
Computers in biology and medicine
Apr 8, 2024
The prediction of drug-target binding affinity (DTA) plays an important role in drug discovery. Computerized virtual screening techniques have been used for DTA prediction, greatly reducing the time and economic costs of drug discovery. However, thes...
Boosting Clear Cell Renal Carcinoma-Specific Drug Discovery Using a Deep Learning Algorithm and Single-Cell Analysis.
International journal of molecular sciences
Apr 8, 2024
Clear cell renal carcinoma (ccRCC), the most common subtype of renal cell carcinoma, has the high heterogeneity of a highly complex tumor microenvironment. Existing clinical intervention strategies, such as target therapy and immunotherapy, have fail...
Advancing Ligand Docking through Deep Learning: Challenges and Prospects in Virtual Screening.
Accounts of chemical research
Apr 5, 2024
Molecular docking, also termed ligand docking (LD), is a pivotal element of structure-based virtual screening (SBVS) used to predict the binding conformations and affinities of protein-ligand complexes. Traditional LD methodologies rely on a search a...
A probabilistic knowledge graph for target identification.
PLoS computational biology
Apr 5, 2024
Early identification of safe and efficacious disease targets is crucial to alleviating the tremendous cost of drug discovery projects. However, existing experimental methods for identifying new targets are generally labor-intensive and failure-prone....
Editorial: Artificial intelligence in drug discovery and development.
Methods (San Diego, Calif.)
Apr 4, 2024
MolProphet: A One-Stop, General Purpose, and AI-Based Platform for the Early Stages of Drug Discovery.
Journal of chemical information and modeling
Apr 2, 2024
Artificial intelligence (AI) is an effective tool to accelerate drug discovery and cut costs in discovery processes. Many successful AI applications are reported in the early stages of small molecule drug discovery. However, most of those application...
MLASM: Machine learning based prediction of anticancer small molecules.
Molecular diversity
Mar 30, 2024
Cancer, being the second leading cause of death globally. So, the development of effective anticancer treatments is crucial in the field of medicine. Anticancer peptides (ACPs) have shown promising therapeutic potential in cancer treatment compared t...
Machine learning-aided search for ligands of P2Y and other P2Y receptors.
Purinergic signalling
Mar 25, 2024
The P2Y receptor, activated by uridine diphosphate (UDP), is a target for antagonists in inflammatory, neurodegenerative, and metabolic disorders, yet few potent and selective antagonists are known to date. This prompted us to use machine learning as...
Discovery of Covalent Lead Compounds Targeting 3CL Protease with a Lateral Interactions Spiking Neural Network.
Journal of chemical information and modeling
Mar 23, 2024
Covalent drugs exhibit advantages in that noncovalent drugs cannot match, and covalent docking is an important method for screening covalent lead compounds. However, it is difficult for covalent docking to screen covalent compounds on a large scale b...
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