AIMC Topic: Binding Sites

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CoBdock-2: enhancing blind docking performance through hybrid feature selection combining ensemble and multimodel feature selection approaches.

Journal of computer-aided molecular design Jul 13, 2025
Identifying orthosteric binding sites and predicting small molecule affinities remains a key challenge in virtual screening. While blind docking explores the entire protein surface, its precision is hindered by the vast search space. Cavity detection...
Machine Learning Software Algorithms Ligands Protein Conformation Binding Sites Molecular Docking Simulation Protein Binding Proteins
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AI based natural inhibitor targeting RPS20 for colorectal cancer treatment using integrated computational approaches.

Scientific reports Jul 10, 2025
The increasing global incidence of cancer emphasizes the vital role of machine learning algorithms and artificial intelligence (AI) in identifying novel anticancer targets and developing new drugs. Computational approaches can significantly quicken r...
Machine Learning Binding Sites Ribosomal Proteins Colorectal Neoplasms Humans Molecular Docking Simulation Artificial Intelligence Antineoplastic Agents Molecular Dynamics Simulation Indoles
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Machine learning-based QSAR and structure-based virtual screening guided discovery of novel mIDH1 inhibitors from natural products.

Journal of computer-aided molecular design Jul 8, 2025
Mutations in isocitrate dehydrogenase 1 (IDH1) have been widely observed in various tumors, such as gliomas and acute myeloid leukemia, and therefore has become one of the current research focal points. Therefore, it is crucial to find inhibitors tha...
Humans Machine Learning Biological Products Ligands Enzyme Inhibitors Molecular Docking Simulation Drug Discovery Protein Binding Binding Sites Quantitative Structure-Activity Relationship Isocitrate Dehydrogenase
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Evaluation of Small-Molecule Binding Site Prediction Methods on Membrane-Embedded Protein Interfaces.

Journal of chemical information and modeling Jul 2, 2025
Increasing structural and biophysical evidence suggests that many drug molecules bind to the protein-membrane interface region in membrane protein structures. An important starting point for drug discovery is the determination of a ligand's binding s...
Small Molecule Libraries Ligands Binding Sites Protein Binding Membrane Proteins Models, Molecular
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Uncertainty Quantification and Temperature Scaling Calibration for Protein-RNA Binding Site Prediction.

Journal of chemical information and modeling Jun 2, 2025
The black-box nature of deep learning has increasingly drawn attention to the reliability and uncertainty of predictive models. Currently, several uncertainty quantification (UQ) methods have been proposed and successfully applied in the fields of mo...
Binding Sites Uncertainty RNA-Binding Proteins RNA Calibration Temperature Protein Binding Neural Networks, Computer
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Molecular insights into the unique activation and allosteric modulation mechanisms of the human mas-related G-protein-coupled receptor X1.

International journal of biological macromolecules May 30, 2025
MRGPRX1 plays dual roles in mediating nociception and pruritus, making it a promising target for alleviating itch and inhibiting pain. However, the mechanisms underlying MRGPRX1 activation and allosteric modulation remain poorly understood, posing si...
Receptors, G-Protein-Coupled Molecular Dynamics Simulation Humans Protein Conformation Protein Binding Receptors, Neuropeptide Binding Sites Allosteric Regulation
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CrypToth: Cryptic Pocket Detection through Mixed-Solvent Molecular Dynamics Simulations-Based Topological Data Analysis.

Journal of chemical information and modeling May 22, 2025
Some functional proteins undergo conformational changes to expose hidden binding sites when a binding molecule approaches their surface. Such binding sites are called cryptic sites and are important targets for drug discovery. However, it is still di...
Proteins Molecular Dynamics Simulation Ligands Solvents Protein Conformation Binding Sites
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Predictive biophysical neural network modeling of a compendium of in vivo transcription factor DNA binding profiles for Escherichia coli.

Nature communications May 7, 2025
The DNA binding of most Escherichia coli Transcription Factors (TFs) has not been comprehensively mapped, and few have models that can quantitatively predict binding affinity. We report the global mapping of in vivo DNA binding for 139 E. coli TFs us...
Transcription Factors Escherichia coli Escherichia coli Proteins Protein Binding DNA, Bacterial Binding Sites Chromatin Immunoprecipitation Sequencing Neural Networks, Computer
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A KAN-based hybrid deep neural networks for accurate identification of transcription factor binding sites.

PloS one May 7, 2025
BACKGROUND: Predicting protein-DNA binding sites in vivo is a challenging but urgent task in many fields such as drug design and development. Most promoters contain many transcription factor (TF) binding sites, yet only a few have been identified thr...
Computational Biology Transcription Factors Promoter Regions, Genetic Binding Sites Algorithms Humans Deep Learning Neural Networks, Computer Protein Binding
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Integrating genetic variation with deep learning provides context for variants impacting transcription factor binding during embryogenesis.

Genome research May 2, 2025
Understanding how genetic variation impacts transcription factor (TF) binding remains a major challenge, limiting our ability to model disease-associated variants. Here, we used a highly controlled system of F crosses with extensive genetic diversity...
Deep Learning Protein Binding Transcription Factors Binding Sites Animals Drosophila Alleles Genetic Variation Embryonic Development Drosophila Proteins Drosophila melanogaster
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