AIMC Topic: Binding Sites

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Development of 3D-QSAR Model for Acetylcholinesterase Inhibitors Using a Combination of Fingerprint, Molecular Docking, and Structure-Based Pharmacophore Approaches.

Toxicological sciences : an official journal of the Society of Toxicology Jul 21, 2015
Acetylcholinesterase (AChE), a serine hydrolase vital for regulating the neurotransmitter acetylcholine in animals, has been used as a target for drugs and pesticides. With the increasing availability of AChE crystal structures, with or without ligan...
Humans Artificial Intelligence Animals Molecular Docking Simulation Imaging, Three-Dimensional Computational Biology Databases, Protein Expert Systems Catalytic Domain Molecular Conformation Quantitative Structure-Activity Relationship Binding Sites Peptide Mapping Nootropic Agents Nerve Tissue Proteins Insecticides Models, Molecular Ligands GPI-Linked Proteins Acetylcholinesterase Cholinesterase Inhibitors
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Machine-learning scoring functions for identifying native poses of ligands docked to known and novel proteins.

BMC bioinformatics Apr 17, 2015
BACKGROUND: Molecular docking is a widely-employed method in structure-based drug design. An essential component of molecular docking programs is a scoring function (SF) that can be used to identify the most stable binding pose of a ligand, when boun...
Ligands Drug Design Humans Binding Sites Drug Discovery Artificial Intelligence Protein Binding Software Proteins
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Accurate in silico identification of protein succinylation sites using an iterative semi-supervised learning technique.

Journal of theoretical biology Apr 2, 2015
As a widespread type of protein post-translational modifications (PTMs), succinylation plays an important role in regulating protein conformation, function and physicochemical properties. Compared with the labor-intensive and time-consuming experimen...
Artificial Intelligence Algorithms Lysine Support Vector Machine Binding Sites Protein Processing, Post-Translational Computer Simulation Succinates Proteins Reproducibility of Results Molecular Sequence Data Amino Acids Computational Biology Internet Supervised Machine Learning Amino Acid Sequence
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BgN-Score and BsN-Score: bagging and boosting based ensemble neural networks scoring functions for accurate binding affinity prediction of protein-ligand complexes.

BMC bioinformatics Feb 23, 2015
BACKGROUND: Accurately predicting the binding affinities of large sets of protein-ligand complexes is a key challenge in computational biomolecular science, with applications in drug discovery, chemical biology, and structural biology. Since a scorin...
Ligands Binding Sites Humans Computational Biology Neural Networks, Computer Models, Statistical Artificial Intelligence Proteins Algorithms Protein Binding
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A Bayesian Optimization-Based Hybrid Deep Prediction Method for Zinc-Binding Protein Interaction Sites.

Journal of chemical information and modeling Jul 14, 2025
The binding of zinc ions to proteins plays a crucial role in normal physiological functions and life activities of organisms. To enhance the prediction accuracy of zinc-binding protein interaction sites, the paper proposes a novel hybrid deep predict...
Bayes Theorem Binding Sites Zinc Protein Binding Computational Biology Carrier Proteins
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CACHE Challenge #2: Targeting the RNA Site of the SARS-CoV-2 Helicase Nsp13.

Journal of chemical information and modeling Jul 14, 2025
A critical assessment of computational hit-finding experiments (CACHE) challenge was conducted to predict ligands for the SARS-CoV-2 Nsp13 helicase RNA binding site, a highly conserved COVID-19 target. Twenty-three participating teams comprised of co...
Machine Learning COVID-19 SARS-CoV-2 Molecular Docking Simulation Humans RNA, Viral Ligands COVID-19 Drug Treatment Methyltransferases Drug Discovery Antiviral Agents Protein Binding Viral Nonstructural Proteins Binding Sites RNA Helicases
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RTK_RAG: Leveraging Retrieval Augmented Generation with Multi-Window Convolutional Neural Networks for Superior ATP Binding Site Prediction in Receptor Tyrosine Kinases.

Journal of chemical information and modeling Jul 14, 2025
Receptor tyrosine kinases (RTKs) are key regulators of cellular signaling and are frequently involved in cancer development. As their activation depends on ATP binding to the kinase domain, precisely identifying ATP binding sites is critical for mech...
Adenosine Triphosphate Binding Sites Receptor Protein-Tyrosine Kinases Humans Neural Networks, Computer Convolutional Neural Networks
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PrankWeb 4: a modular web server for protein-ligand binding site prediction and downstream analysis.

Nucleic acids research Jul 7, 2025
Knowledge of protein-ligand binding sites (LBSs) is crucial for advancing our understanding of biology and developing practical applications in fields such as medicine or biotechnology. PrankWeb is a web server that allows users to predict LBSs from ...
Protein Conformation Binding Sites Software Molecular Docking Simulation User-Computer Interface Protein Binding Proteins Internet Ligands Machine Learning
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InDeepNet: a web platform for predicting functional binding sites in proteins using InDeep.

Nucleic acids research Jul 7, 2025
Predicting functional binding sites in proteins is crucial for understanding protein-protein interactions (PPIs) and identifying drug targets. While various computational approaches exist, many fail to assess PPI ligandability, which often involves c...
Deep Learning Protein Binding Ligands Protein Conformation Binding Sites Protein Interaction Mapping Computational Biology Databases, Protein Proteins Models, Molecular Software Internet
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When Simulations Meet Machine Learning: Redefining Molecular Docking for Protein-Glycosaminoglycan Systems.

Journal of computational chemistry Jun 30, 2025
Glycosaminoglycans (GAGs) are linear, negatively charged carbohydrates that modulate enzymatic activity in the extracellular matrix. Their high flexibility and specificity in protein-GAG interactions pose challenges for both experimental and computat...
Ligands Binding Sites Machine Learning Molecular Docking Simulation Proteins Molecular Dynamics Simulation Glycosaminoglycans
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