AIMC Topic: Drug Discovery
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Artificial Intelligence in Clinical Oncology: From Data to Digital Pathology and Treatment.
American Society of Clinical Oncology educational book. American Society of Clinical Oncology. Annual Meeting
May 1, 2023
Recently, a wide spectrum of artificial intelligence (AI)-based applications in the broader categories of digital pathology, biomarker development, and treatment have been explored. In the domain of digital pathology, these have included novel analyt...
Drug repurposing for viral cancers: A paradigm of machine learning, deep learning, and virtual screening-based approaches.
Journal of medical virology
Apr 1, 2023
Cancer management is major concern of health organizations and viral cancers account for approximately 15.4% of all known human cancers. Due to large number of patients, efficient treatments for viral cancers are needed. De novo drug discovery is tim...
Modern semiempirical electronic structure methods and machine learning potentials for drug discovery: Conformers, tautomers, and protonation states.
The Journal of chemical physics
Mar 28, 2023
Modern semiempirical electronic structure methods have considerable promise in drug discovery as universal "force fields" that can reliably model biological and drug-like molecules, including alternative tautomers and protonation states. Herein, we c...
Targeting trypanosomes: how chemogenomics and artificial intelligence can guide drug discovery.
Biochemical Society transactions
Feb 27, 2023
Trypanosomatids are protozoan parasites that cause human and animal neglected diseases. Despite global efforts, effective treatments are still much needed. Phenotypic screens have provided several chemical leads for drug discovery, but the mechanism ...
DrugAI: a multi-view deep learning model for predicting drug-target activating/inhibiting mechanisms.
Briefings in bioinformatics
Jan 19, 2023
Understanding the mechanisms of candidate drugs play an important role in drug discovery. The activating/inhibiting mechanisms between drugs and targets are major types of mechanisms of drugs. Owing to the complexity of drug-target (DT) mechanisms an...
Editorial: Machine Learning in Bio-cheminformatics.
Journal of chemical information and modeling
Jan 9, 2023
canSAR: update to the cancer translational research and drug discovery knowledgebase.
Nucleic acids research
Jan 6, 2023
canSAR (https://cansar.ai) is the largest public cancer drug discovery and translational research knowledgebase. Now hosted in its new home at MD Anderson Cancer Center, canSAR integrates billions of experimental measurements from across molecular pr...
DrugMAP: molecular atlas and pharma-information of all drugs.
Nucleic acids research
Jan 6, 2023
The efficacy and safety of drugs are widely known to be determined by their interactions with multiple molecules of pharmacological importance, and it is therefore essential to systematically depict the molecular atlas and pharma-information of studi...
Drug-Protein Interactions Prediction Models Using Feature Selection and Classification Techniques.
Current drug metabolism
Jan 1, 2023
BACKGROUND: Drug-Protein Interaction (DPI) identification is crucial in drug discovery. The high dimensionality of drug and protein features poses challenges for accurate interaction prediction, necessitating the use of computational techniques. Dock...
Revolutionizing Drug Discovery: The Role of AI and Machine Learning.
Current pharmaceutical design
Jan 1, 2023
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