AIMC Topic: Protein Binding

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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...
Sequence Alignment RNA-Binding Proteins Databases, Protein RNA Binding Sites Models, Molecular Protein Binding Machine Learning Computational Biology
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Bioactivity Deep Learning for Complex Structure-Free Compound-Protein Interaction Prediction.

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...
Deep Learning Protein Binding Proteins Drug Discovery Drug Evaluation, Preclinical Ligands
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Sampling and Ranking of Protein Conformations Using Machine Learning Techniques Do Not Improve the Quality of Rigid Protein-Protein Docking.

Journal of chemical information and modeling Sep 16, 2025
Rigid docking remains the most popular method of predicting protein-protein interactions in cases when experimental 3D structures of the complexes are not available. The docking often relies on known unbound (Apo) protein structures, which may differ...
Molecular Docking Simulation Protein Binding Proteins Machine Learning Protein Conformation
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Precision in Predicting Protein-Nucleic Acid Complexes: Establishing a Benchmark Data Set and Comparative Metrics.

Journal of chemical information and modeling Sep 11, 2025
Protein-nucleic acid interactions are fundamental to biological processes and biotechnology, yet their computational prediction lags behind protein structure or protein-protein interaction modeling. This study introduces ProNASet, a benchmark data se...
Nucleic Acids Molecular Docking Simulation Deep Learning Proteins Benchmarking Protein Binding
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HPDAF: A practical tool for predicting drug-target binding affinity using multimodal features.

European journal of medicinal chemistry Sep 8, 2025
Accurate prediction of drug-target binding affinity is crucial for efficient drug discovery and design, enabling researchers to better understand molecular interactions and accelerate the identification of promising drug candidates. Despite recent ad...
Drug Design Drug Discovery Deep Learning Humans Molecular Structure Pharmaceutical Preparations Binding Sites Protein Binding Proteins
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Multiview Deep Learning Framework for Precise Prediction of Transcription Factor Binding Sites.

Journal of chemical information and modeling Sep 7, 2025
Transcription factors (TFs) are essential proteins that regulate gene expression by specifically binding to transcription factor binding sites (TFBSs) within DNA sequences. Their ability to precisely control the transcription process is crucial for u...
DNA Binding Sites Computational Biology Transcription Factors Deep Learning Protein Binding
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A Machine Learning Model for the Proteome-Wide Prediction of Lipid-Interacting Proteins.

Journal of chemical information and modeling Sep 4, 2025
Lipids are essential metabolites that play critical roles in multiple cellular pathways. Like many primary metabolites, mutations that disrupt lipid synthesis can be lethal. Proteins involved in lipid synthesis, trafficking, and modification, are tar...
Machine Learning Algorithms Humans Models, Molecular Hydrophobic and Hydrophilic Interactions Binding Sites Proteome Lipids Proteins Protein Binding Computational Biology
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PepBAN: A Deep Learning Framework with Bilinear Attention and Adversarial Learning for Peptide-Protein Interaction Prediction.

Journal of chemical information and modeling Aug 25, 2025
Accurate prediction of the peptide-protein interaction (PepPI) is crucial for developing peptide-based therapeutics and vaccines. However, this computational task has traditionally faced significant challenges, such as the scarcity of structure data ...
Protein Binding Proteins Peptides Deep Learning
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Harnessing artificial intelligence to identify Bufalin as a molecular glue degrader of estrogen receptor alpha.

Nature communications Aug 22, 2025
Target identification in natural products plays a critical role in the development of innovative drugs. Bufalin, a compound derived from traditional medicines, has shown promising anti-cancer activity; however, its precise molecular mechanism of acti...
Antineoplastic Agents Bufanolides Molecular Dynamics Simulation Cell Line, Tumor Tamoxifen Xenograft Model Antitumor Assays Protein Binding Humans Drug Resistance, Neoplasm Female Estrogen Receptor alpha Animals Mice Artificial Intelligence Molecular Docking Simulation Breast Neoplasms MCF-7 Cells
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BiVAE-CPI: An Interpretable Generative Model Using a Bilateral Variational Autoencoder for Compound-Protein Interaction Prediction.

Journal of chemical information and modeling Aug 21, 2025
Predicting compound-protein interaction (CPI) plays a critical role in drug discovery and development, but traditional screening experiments consume much time and resources. Therefore, deep learning methods for CPI prediction are popular now. However...
Autoencoder Protein Binding Drug Discovery Proteins Deep Learning
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