Artificial intelligence and machine learning are revolutionizing pharmaceutical research by enabling the rapid analysis of complex datasets and automating critical tasks throughout the drug-development process. In this review, we surveyed how artific...
To address the toxicity of current microtubule inhibitors, we employed the GeminiMol deep learning model to screen the Zinc20 database, identifying a novel 4,5-dihydropyrrolo[3,4-]pyrazol-6(2)-one scaffold () targeting the colchicine binding site. Su...
Journal of chemical information and modeling
Sep 19, 2025
Drug-target interaction (DTI) prediction plays a pivotal role in drug discovery. In recent years, deep learning-based models have been advanced rapidly, accelerating the identification of potential DTIs. However, how to effectively capture the cross-...
ChEMBL is a large-scale, open-access, FAIR database of bioactive molecules with drug-like properties. ChEMBL 35 contains 17,500 approved drugs, and drugs that are progressing through the clinical development pipeline. Drug curation has formed an inte...
European journal of medicinal chemistry
Sep 17, 2025
Developing optimized AI models for virtual screening requires coordinated selection of algorithms, molecular representations, and data splitting strategies, yet lacks integrated tools. We present PyaiVS, a Python package that integrates nine machine ...
Graph neural networks (GNNs), as topology/structure-aware models within deep learning, have emerged as powerful tools for AI-aided drug discovery (AIDD). By directly operating on molecular graphs, GNNs offer an intuitive and expressive framework for ...
Journal of chemical information and modeling
Sep 17, 2025
Free energy perturbation (FEP) methods are among the most accurate tools in structure-based drug design for predicting protein-ligand binding affinities. However, their adoption remains limited due to high computational demands and complex setup proc...
Journal of chemical information and modeling
Sep 17, 2025
The escalating issue of antibiotic resistance has created an urgent global demand within the biomedical field for the discovery of novel antimicrobial molecules as alternatives to traditional antibiotics. Previous studies have reported the identifica...
Journal of chemical information and modeling
Sep 16, 2025
Protein-ligand binding affinity assessment plays a pivotal role in virtual drug screening, yet conventional data-driven approaches rely heavily on limited protein-ligand crystal structures. Structure-free compound-protein interaction (CPI) methods ha...
Journal of chemical information and modeling
Sep 15, 2025
Tools available for analyzing next-generation sequencing (NGS) data produced from DNA-encoded library (DEL) screening campaigns are often constrained to customized methods developed internally by individual institutes, which usually generate data spe...
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