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...
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 ...
Journal of chemical information and modeling
Sep 15, 2025
This study introduces MolAI, a robust deep learning model designed for data-driven molecular descriptor generation. Utilizing a vast training data set of 221 million unique compounds, MolAI employs an autoencoder neural machine translation model to g...
Marine bioactive peptides (MBPs) are short-chain amino acid polymers derived from marine sources that possess specific physiological activities. Owing to their unique origins and structural diversity, MBPs have attracted considerable research interes...
Bacterial polysaccharides have attracted considerable interest due to their rapid production, customizable properties, and suitability for large-scale manufacturing. Unlike plant or algal polysaccharides, they can be efficiently synthesized through f...
PGE2 plays important roles in immune cell function and in potentiating tissue regeneration. 15-PGDH is the key enzyme involved in inactivation of PGE2 and its inhibition therefore provides valuable therapeutic opportunity. We have solved the first co...
European journal of medicinal chemistry
Jul 25, 2025
The orthopoxvirus genus, particularly the monkeypox virus (MPXV), continues to pose a significant global public health threat. Therefore, the development of novel anti-orthopoxvirus agents remains an urgent priority. Machine learning has proven to be...
Journal of chemical theory and computation
Jul 14, 2025
In this study, we propose a Kernel-PCA model designed to capture structure-function relationships in a protein. This model also enables the ranking of reaction coordinates according to their impact on protein properties. By leveraging machine learnin...
Lactate dehydrogenase A (LDHA) is a promising target for cancer therapy due to its crucial role in aerobic glycolysis. Despite extensive efforts, the structural diversity of LDHA inhibitors remains limited. Here, we utilized machine learning techniqu...
Comprehensively acquiring biological tissue information is pivotal for advancing our understanding of biological systems, elucidating disease mechanisms, and developing innovative clinical strategies. Biological tissues, as nature's archetypal biomat...
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