Neural Network Sharpens Early Drug Discovery With 95.9% Accuracy in Predicting Painkilling Compounds
Researchers in Algeria have built an optimized neural network that predicts the analgesic activity of drug-like molecules with 95.9 percent ...
Researchers in Algeria have built an optimized neural network that predicts the analgesic activity of drug-like molecules with 95.9 percent ...
A new review argues that AI-driven antiviral discovery must be benchmarked against respiratory RNA virus polymerases under virologically realistic conditions ...
Computational screening of four halogenated quinoline derivatives identifies QNL1 and QNL3 as promising oral drug candidates against tuberculosis, E. coli, ...
A computational screen of 2,847 plant compounds against ten Alzheimer's-related proteins identified 36 multitarget phytochemicals with stable binding and literature-backed ...
Researchers combined virtual screening, mutational analysis, molecular dynamics simulations, and antimicrobial testing to identify two promising small-molecule inhibitors of the ...
Virtual screening of a Central African natural-product library has identified homoisoflavanone and related compounds as stable computational inhibitors of the ...
Computational screening of the Pan-African Natural Products Library identified two compounds, 152CSB2 and Thix6g, as promising selective COX-2 inhibitors with ...
Japanese researchers used an amino acid mapping descriptor derived from the natural antibiotic waldiomycin to screen nearly 12 million compounds ...
A virtual library of 30 isoniazid-based Schiff base derivatives was computationally screened, and the top-ranked compound SLB-5 was synthesized and ...
A comprehensive review in Results in Chemistry details how molecular docking, virtual screening, and ADMET prediction are accelerating the discovery ...
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© 2026 Scienmag - Science Magazine