AIMC Topic: Binding Sites

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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...
Proteins Hydrophobic and Hydrophilic Interactions Surface Properties Binding Sites Molecular Docking Simulation ROC Curve Protein Binding Neural Networks, Computer
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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...
Models, Molecular RNA Nucleic Acid Conformation Deep Learning Computational Biology Binding Sites Small Molecule Libraries Drug Discovery
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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 Molecular Docking Simulation RNA, Ribosomal, 16S Animals Klebsiella Laccase Binding Sites Cloning, Molecular Mutagenesis, Site-Directed 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 Humans Metalloproteins Models, Molecular Binding Sites
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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 ...
Drug Discovery Calcium Calcium Channel Blockers Binding Sites Humans Ion Channels Neural Networks, Computer
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The prediction of RNA-small-molecule ligand binding affinity based on geometric deep learning.

Computational biology and chemistry Jan 29, 2025
Small molecule-targeted RNA is an emerging technology that plays a pivotal role in drug discovery and inhibitor design, with widespread applications in disease treatment. Consequently, predicting RNA-small-molecule ligand interactions is crucial. Wit...
Ligands Deep Learning Binding Sites RNA Small Molecule Libraries
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MutualDTA: An Interpretable Drug-Target Affinity Prediction Model Leveraging Pretrained Models and Mutual Attention.

Journal of chemical information and modeling Jan 29, 2025
Efficient and accurate drug-target affinity (DTA) prediction can significantly accelerate the drug development process. Recently, deep learning models have been widely applied to DTA prediction and have achieved notable success. However, existing met...
Pharmaceutical Preparations Humans Deep Learning Drug Discovery Binding Sites Protein Binding Proteins
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MAI-TargetFisher: A proteome-wide drug target prediction method synergetically enhanced by artificial intelligence and physical modeling.

Acta pharmacologica Sinica Jan 27, 2025
Computational target identification plays a pivotal role in the drug development process. With the significant advancements of deep learning methods for protein structure prediction, the structural coverage of human proteome has increased substantial...
Humans Databases, Protein Drug Discovery Artificial Intelligence Binding Sites Proteome Algorithms Proteins
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DisDock: A Deep Learning Method for Metal Ion-Protein Redocking.

Proteins Jan 22, 2025
The structures of metalloproteins are essential for comprehending their functions and interactions. The breakthrough of AlphaFold has made it possible to predict protein structures with experimental accuracy. However, the type of metal ion that a met...
Metalloproteins Software Computational Biology Databases, Protein Ions Algorithms Deep Learning Ligands Molecular Docking Simulation Metals Protein Conformation Protein Binding Binding Sites
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MVGNN-PPIS: A novel multi-view graph neural network for protein-protein interaction sites prediction based on Alphafold3-predicted structures and transfer learning.

International journal of biological macromolecules Jan 21, 2025
Protein-protein interactions (PPI) are crucial for understanding numerous biological processes and pathogenic mechanisms. Identifying interaction sites is essential for biomedical research and targeted drug development. Compared to experimental metho...
Protein Conformation Binding Sites Protein Interaction Mapping Computational Biology Graph Neural Networks Algorithms Proteins Neural Networks, Computer Protein Binding Models, Molecular
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