AIMC Topic: Binding Sites

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A novel prediction method for protein-DNA binding sites based on protein language model fusion features with SE-connection pyramidal network and ensemble learning.

BMC genomics Oct 30, 2025
Protein-DNA interactions are crucial in life processes such as gene expression and regulation. Therefore, the accurate prediction of DNA-binding sites on proteins is highly important for the advancement of scientific understanding in the field of bio...
DNA-Binding Proteins Binding Sites Ensemble Learning Protein Binding Computational Biology DNA Machine Learning Algorithms
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Kideraspa: designing variants of staphylococcal protein a based on a diffusion model with kidera factors.

Journal of computer-aided molecular design Oct 24, 2025
The interaction between staphylococcal protein A (SpA) and human immunoglobulin G (IgG) is pivotal in treating diseases such as cancer, inflammation, infections, and autoimmune disorders. However, acquiring natural SpA variants is labor-intensive, tr...
Staphylococcal Protein A Mutation Binding Sites Protein Engineering Deep Learning Protein Binding Humans Models, Molecular Immunoglobulin G
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Predicting the Impact of Drug Resistance Mutations on Inhibitor Potency with Molecular Dynamics and Machine Learning.

The journal of physical chemistry. B Oct 15, 2025
Many enzymes are vital drug targets in diseases such as cancer and pathogenic infections; however, mutations can drastically disrupt inhibitor binding to confer resistance. Resistance mutations primarily occur at the inhibitor binding site, but accom...
Humans Machine Learning Mutation Molecular Dynamics Simulation Darunavir Drug Resistance, Viral HIV Protease HIV Protease Inhibitors Binding Sites
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More Sophisticated Is Not Always Better: A Comparison of Similarity Measures for Unsupervised Learning of Pathways in Biomolecular Simulations.

The journal of physical chemistry. B Oct 8, 2025
Finding process pathways in molecular simulations such as the unbinding paths of small molecule ligands from their binding sites at protein targets in a set of trajectories via unsupervised learning approaches requires the definition of a suitable si...
Biotin Ligands Streptavidin Binding Sites Cluster Analysis Unsupervised Machine Learning Molecular Dynamics Simulation
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AI-driven protein pocket detection through integrating deep Q-networks for structural analysis.

Journal of computer-aided molecular design Oct 6, 2025
Protein pockets, or small cavities on the protein surface, are critical sites for enzymatic catalysis, molecular recognition, and drug binding. Accurately identifying these pockets is crucial for understanding protein function and designing therapeut...
Protein Binding Proteins Databases, Protein Molecular Dynamics Simulation Algorithms Protein Conformation Humans Binding Sites Molecular Docking Simulation Deep Learning
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GENEOnet: a breakthrough in protein binding pocket detection using group equivariant non-expansive operators.

Scientific reports Oct 3, 2025
Structure-based virtual screening approaches like molecular docking rely on accurately identifying and precisely calculating binding pockets to efficiently search for potential ligands. In this paper, we introduce GENEOnet, a machine learning model d...
Machine Learning Software Algorithms Molecular Docking Simulation Protein Binding Proteins Humans Ligands Binding Sites
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Structure based drug design and machine learning approaches for identifying natural inhibitors against the human αβIII tubulin isotype.

Scientific reports Sep 24, 2025
Microtubules (MTs) play a crucial role in mitosis and are composed of α-/β-tubulin heterodimeric subunits. In eukaryotes, eight α-tubulin and ten β-tubulin isotypes have been reported, each displaying tissue-specific expression patterns. Among them, ...
Molecular Docking Simulation Drug Design Protein Binding Humans Machine Learning Binding Sites Tubulin Modulators Biological Products Molecular Dynamics Simulation Tubulin
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Discovery of Novel 4,5-Dihydropyrrolo[3,4-]pyrazol-6()-one-Based Tubulin Inhibitors Targeting Colchicine Binding Site with Potent Anti-Ovarian Cancer Activity.

Journal of medicinal chemistry Sep 20, 2025
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...
Tubulin Binding Sites Colchicine Structure-Activity Relationship Xenograft Model Antitumor Assays Pyrazoles Tubulin Modulators Mice Drug Discovery Humans Cell Proliferation Antineoplastic Agents Female Mice, Nude Animals Cell Line, Tumor Apoptosis Ovarian Neoplasms Drug Screening Assays, Antitumor
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A deep learning approach based on molecular graph features and residual blocks to predict interaction sites between CircRNA and RBP.

Biochemical and biophysical research communications Sep 16, 2025
CircRNAs are ubiquitously expressed across diverse tissues and cells, playing a pivotal role not only in protein-mediated biological processes but also in disease prevention and therapeutics. RNA-RBP interactions are critical for deciphering gene reg...
RNA-Binding Proteins Binding Sites RNA, Circular Humans Deep Learning Computational Biology
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Partner-RBR: Predicting Multitype RNA-Binding Residues Based on Mutual Learning.

Journal of chemical information and modeling Sep 16, 2025
RNA molecules play diverse and critical roles in various biological processes, including gene expression, post-transcriptional regulation, and disease pathogenesis. Understanding the interaction between proteins and RNA necessitates the precise ident...
RNA Binding Sites Sequence Alignment RNA-Binding Proteins Databases, Protein Models, Molecular Machine Learning Protein Binding Computational Biology
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