Klebsiella pneumoniae (K. pneumoniae) has become a serious global health concern due to its rising virulence and antibiotic resistance. As one of the leading members of ESKAPE pathogens, it plays a major role in a wide range of infections that cause ...
Focal Adhesion Kinase (FAK) is a non-receptor tyrosine kinase that plays a crucial role in cell proliferation, migration, and signal transduction. FAK is overexpressed in metastatic and advanced-stage cancers, where it is considered a key kinase in c...
Molecules with potent anti-leishmanial activity play a crucial role in identifying treatments for leishmaniasis and aiding in the design of novel drugs to combat the disease, ultimately protecting individuals and populations. Various methods have bee...
Drug-target affinity prediction is a fundamental task in the field of drug discovery. Extracting and integrating structural information from proteins effectively is crucial to enhance the accuracy and generalization of prediction, which remains a sub...
Toxicity prediction is crucial in drug discovery, helping identify safe compounds and reduce development risks. However, the lack of known toxicity data for most compounds is a major challenge. Recently, data-driven models have gained attention as a ...
International journal of pharmaceutics
Jul 25, 2025
Integrating artificial intelligence (AI) into drug discovery has revolutionized pharmaceutical innovation, addressing the challenges of traditional methods that are costly, time-consuming, and suffer from high failure rates. By utilizing machine lear...
Drug-target interaction prediction serves as a crucial component in accelerating drug discovery. To overcome current limitations in deep learning approaches, specifically the inadequate representation of local features and insufficient modeling of dr...
Journal of chemical information and modeling
Jul 14, 2025
Recently, machine learning (ML) has gained popularity in the early stages of drug discovery. This trend is unsurprising given the increasing volume of relevant experimental data and the continuous improvement of ML algorithms. However, conventional m...
Journal of chemical information and modeling
Jul 14, 2025
Molecular property prediction with limited data in novel chemical domains remains challenging. We introduce an approach based on the hypothesis that prediction difficulty increases systematically with distance from well-characterized regions in an ap...
Journal of chemical information and modeling
Jul 14, 2025
The versatility of multimodal deep learning holds tremendous promise for advancing scientific research and practical applications. As this field continues to evolve, the collective power of cross-modal analysis promises to drive transformative innova...
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