AIMC Topic: Binding Sites

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RBPsuite 2.0: an updated RNA-protein binding site prediction suite with high coverage on species and proteins based on deep learning.

BMC biology Mar 11, 2025
BACKGROUND: RNA-binding proteins (RBPs) play crucial roles in many biological processes, and computationally identifying RNA-RBP interactions provides insights into the biological mechanism of diseases associated with RBPs.
Binding Sites RNA, Circular RNA-Binding Proteins RNA Humans Software Deep Learning Computational Biology
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Development of DeepPQK and DeepQK sequence-based deep learning models to predict protein-ligand affinity and application in the directed evolution of ferulic esterase DLfae4.

International journal of biological macromolecules Mar 5, 2025
Affinity plays an essential role in the rate and stability of enzyme-catalyzed reactions, thus directly impacting the catalytic activity. In general, the predictive method for protein-ligand binding affinity mainly relies on high-resolution protein c...
Binding Sites Directed Molecular Evolution Deep Learning Protein Binding Models, Molecular Amino Acid Sequence Ligands Carboxylic Ester Hydrolases Neural Networks, Computer
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Skittles: GNN-Assisted Pseudo-Ligands Generation and Its Application for Binding Sites Classification and Affinity Prediction.

Proteins Feb 28, 2025
Nowadays, multiple solutions are known for identifying ligand-protein binding sites. Another important task is labeling each point of a binding site with the appropriate atom type, a process known as pseudo-ligand generation. The number of solutions ...
Proteins Ligands Algorithms Neural Networks, Computer Databases, Protein Binding Sites Machine Learning Protein Binding Models, Molecular Computational Biology
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Transfer learning reveals sequence determinants of the quantitative response to transcription factor dosage.

Cell genomics Feb 27, 2025
Deep learning models have advanced our ability to predict cell-type-specific chromatin patterns from transcription factor (TF) binding motifs, but their application to perturbed contexts remains limited. We applied transfer learning to predict how co...
Transcription Factors Deep Learning Humans Nucleosomes Binding Sites Protein Binding Animals SOX9 Transcription Factor Chromatin Mice
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Recent advances in AI-driven protein-ligand interaction predictions.

Current opinion in structural biology Feb 24, 2025
Structure-based drug discovery is a fundamental approach in modern drug development, leveraging computational models to predict protein-ligand interactions. AI-driven methodologies are significantly improving key aspects of the field, including ligan...
Humans Artificial Intelligence Molecular Docking Simulation Proteins Ligands Binding Sites Drug Discovery Deep Learning Protein Binding
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Compact Assessment of Molecular Surface Complementarities Enhances Neural Network-Aided Prediction of Key Binding Residues.

Journal of chemical information and modeling Feb 21, 2025
Predicting interactions between proteins is fundamental for understanding the mechanisms underlying cellular processes, since protein-protein complexes are crucial in physiological conditions but also in many diseases, for example by seeding aggregat...
Protein Binding Proteins Hydrophobic and Hydrophilic Interactions Molecular Docking Simulation ROC Curve Surface Properties Neural Networks, Computer Binding Sites
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Identifying RNA-small Molecule Binding Sites Using Geometric Deep Learning with Language Models.

Journal of molecular biology Feb 15, 2025
RNAs are emerging as promising therapeutic targets, yet identifying small molecules that bind to them remains a significant challenge in drug discovery. This underscores the crucial role of computational modeling in predicting RNA-small molecule bind...
Binding Sites Deep Learning RNA Small Molecule Libraries Computational Biology Drug Discovery Nucleic Acid Conformation Models, Molecular
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Cloning, Characterization, and Computer-Aided Evolution of a Thermostable Laccase of the DUF152 Family From Klebsiella michiganensis.

Proteins Feb 14, 2025
Bacterial laccases exhibit relatively high optimal reaction temperatures and possess a broad substrate spectrum, thereby expanding the range of potential applications for laccase enzymes. This study aims to investigate the molecular evolution of bact...
Bacterial Proteins Copper Amino Acid Sequence Klebsiella Molecular Docking Simulation Animals Binding Sites RNA, Ribosomal, 16S Mutagenesis, Site-Directed Laccase Cloning, Molecular Enzyme Stability
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Recent advances and future challenges in predictive modeling of metalloproteins by artificial intelligence.

Molecules and cells Feb 10, 2025
Metal coordination is essential for structural/catalytic functions of metalloproteins that mediate a wide range of biological processes in living organisms. Advances in bioinformatics have significantly enhanced our understanding of metal-binding sit...
Artificial Intelligence Metals Computational Biology Models, Molecular Binding Sites Metalloproteins Humans
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CaBind_MCNN: Identifying Potential Calcium Channel Blocker Targets by Predicting Calcium-Binding Sites in Ion Channels and Ion Transporters Using Protein Language Models and Multiscale Feature Extraction.

Journal of chemical information and modeling Feb 6, 2025
Calcium ions (Ca) are crucial for various physiological processes, including neurotransmission and cardiac function. Dysregulation of Ca homeostasis can lead to serious health conditions such as cardiac arrhythmias and hypertension. Ion channels and ...
Binding Sites Drug Discovery Humans Ion Channels Calcium Neural Networks, Computer Calcium Channel Blockers
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