Drug-target interactions (DTIs) play a critical role in drug discovery and repurposing. Deep learning-based methods for predicting drug-target interactions are more efficient than wet-lab experiments. The extraction of original and substructural feat...
International journal of molecular sciences
May 29, 2025
Protein embeddings are the new main source of information about proteins, producing state-of-the-art solutions to many problems, including protein interaction prediction, a fundamental issue in proteomics. Understanding the embeddings and what causes...
Despite the recent breakthrough of AlphaFold (AF) in the field of protein sequence-to-structure prediction, modeling protein interfaces and predicting protein complex structures remains challenging, especially when there is a significant conformation...
Journal of chemical information and modeling
May 26, 2025
Computational protein design (CPD) refers to the use of computational methods to design proteins. Traditional methods relying on energy functions and heuristic algorithms for sequence design are inefficient and do not meet the demands of the big data...
Journal of chemical information and modeling
May 22, 2025
Some functional proteins undergo conformational changes to expose hidden binding sites when a binding molecule approaches their surface. Such binding sites are called cryptic sites and are important targets for drug discovery. However, it is still di...
Journal of chemical information and modeling
May 22, 2025
Docking-based virtual screening tools customized to mine ultralarge chemical spaces are consistently reported to yield both higher hit rates and more potent ligands than that achieved by conventional docking of smaller million-sized compound librarie...
Proteins are biomolecules characterized by uncommon chemical and physicochemical complexities coupled with extreme responsiveness to even minor chemical modifications or environmental variations. Since the shape that proteins assume is fundamental fo...
BACKGROUND: Association and cooperation among structural domains play an important role in protein function and drug design. Despite remarkable advancements in highly accurate single-domain protein structure prediction through the collaborative effor...
Proceedings of the National Academy of Sciences of the United States of America
May 2, 2025
Understanding the effects of missense mutations or single amino acid variants (SAVs) on protein function is crucial for elucidating the molecular basis of diseases/disorders and designing rational therapies. We introduce here , a machine learning too...
IEEE transactions on neural networks and learning systems
May 2, 2025
Protein function prediction is crucial for understanding species evolution, including viral mutations. Gene ontology (GO) is a standardized representation framework for describing protein functions with annotated terms. Each ontology is a specific fu...
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