A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
Yadi Zhou, Yuan Hou, Jiayu Shen, et al.
This paper presents a network-based drug repurposing methodology using systems pharmacology and network medicine to identify 16 potential anti-HCoV drugs and three drug combinations targeting 2019-nCoV/SARS-CoV-2.
Jinlong Ru, Peng Li, Jinan Wang, et al.
TCMSP is a systems pharmacology database integrating pharmacochemistry, ADME properties, drug targets, diseases, and interaction networks for 499 Chinese herbs to accelerate drug discovery.
Cristian Nogales, Zeinab M. Mamdouh, Markus List, et al.
Network pharmacology replaces the one disease-one target-one drug dogma with causal multitarget signaling modules for precise, curative intervention.
Solveig Badillo, Balázs Bánfai, Fabian Birzele, et al.
This paper introduces foundational machine learning concepts to the pharmacometrics and clinical pharmacology community, bridging basic principles with applications in molecular biology and drug development.
Luca Pinzi, Giulio Rastelli
This review describes the evolution of molecular docking in drug discovery from its original use in understanding molecular recognition to modern applications in polypharmacology, drug repurposing, and integration with artificial intelligence.