AIMC Topic: Protein Binding

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ERRα-Predictor: A Framework of Ensemble Models for Prediction of ERRα Binders, Antagonists, and Agonists Using Artificial Intelligence.

Journal of chemical information and modeling Jun 30, 2025
Estrogen-related receptor α (ERRα) is considered a promising target for the treatment of cancer and metabolic diseases. The development of comprehensive predictive models for ERRα binders, antagonists, and agonists is of significant importance. In th...
Ligands Receptors, Estrogen ERRalpha Estrogen-Related Receptor Machine Learning Protein Binding Neural Networks, Computer Artificial Intelligence Humans
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Machine learning application to predict binding affinity between peptide containing non-canonical amino acids and HLA-A0201.

PloS one Jun 27, 2025
Class Ι major histocompatibility complexes (MHC-Ι), encoded by the highly polymorphic HLA-A, HLA-B, and HLA-C genes in humans, are expressed on all nucleated cells. Both self and foreign proteins are processed to peptides of 8-10 amino acids, loaded ...
Amino Acids HLA-A2 Antigen Machine Learning Peptides Protein Binding Humans
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In-silico study of approved drugs as potential inhibitors against 3CLpro and other viral proteins of CoVID-19.

PloS one Jun 25, 2025
The global pandemic, due to the emergence of COVID-19, has created a public health crisis. It has a huge morbidity rate that was never comprehended in the recent decades. Despite numerous efforts, potent antiviral drugs are lacking. Repurposing of dr...
Coronavirus Nucleocapsid Proteins Humans Protein Binding Computer Simulation COVID-19 Drug Treatment SARS-CoV-2 Spike Glycoprotein, Coronavirus Drug Repositioning Machine Learning Coronavirus 3C Proteases Antiviral Agents COVID-19 Molecular Docking Simulation
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generation of peptide binders with desired properties by deep generative models reinforced through enrichment of focused sets for iterative fine-tuning.

Chemical communications (Cambridge, England) Jun 24, 2025
Recurrent neural networks underwent reinforcement procedures for generation of peptide binders with desired properties. Docking and scoring of peptides from these models allowed enrichment of focused sets with validated sequences for iterative fine-...
Neural Networks, Computer Peptides Protein Binding Molecular Docking Simulation
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Divergence in a eukaryotic transcription factor's co-TF dependence involves multiple intrinsically disordered regions.

Nature communications Jun 18, 2025
Combinatorial control by transcription factors (TFs) is central to eukaryotic gene regulation, yet its mechanism, evolution, and regulatory impact are not well understood. Here we use natural variation in the yeast phosphate starvation (PHO) response...
Saccharomyces cerevisiae DNA-Binding Proteins Protein Binding Saccharomyces cerevisiae Proteins Intrinsically Disordered Proteins Candida glabrata Transcription Factors Gene Expression Regulation, Fungal Phosphates
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Improved Prediction of Drug-Protein Interactions through Physics-Based Few-Shot Learning.

Journal of chemical information and modeling Jun 17, 2025
Accurate prediction of drug-protein interactions is crucial for drug discovery. Due to the bottleneck of traditional scoring functions, many machine learning scoring functions (MLSFs) have been proposed for structure-based drug screening. However, ex...
SARS-CoV-2 Drug Discovery Protein Binding Machine Learning COVID-19 Humans Proteins Pharmaceutical Preparations
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Comparing models and experimental structures of the GPR101 receptor: Artificial intelligence yields highly accurate models.

Journal of molecular graphics & modelling Jun 3, 2025
Experimental structures solved through cryo-electron microscopy have recently been published for GPR101, a G protein-coupled receptor (GPCR) implicated in the genetic condition X-linked acrogigantism (X-LAG). Here, we compared these experimental stru...
Humans Artificial Intelligence Protein Binding Amino Acid Sequence Protein Conformation Models, Molecular Receptors, G-Protein-Coupled Cryoelectron Microscopy Molecular Dynamics Simulation
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Disruption of Hsp70.14-BAG2 Protein-Protein interactions using deep Learning-Driven peptide design and molecular simulations.

Computers in biology and medicine Jun 3, 2025
Protein-protein interactions (PPIS) are critical in proteostasis, stress response, and disease progression. Targeting the interaction between Hsp70.14 and BAG2, a co-chaperone implicated in oncogenic survival, offers a promising therapeutic approach....
Mitochondrial Proteins Chaperonin 60 Protein Binding Molecular Dynamics Simulation Humans HSP70 Heat-Shock Proteins Molecular Docking Simulation Molecular Chaperones Deep Learning Antimicrobial Peptides
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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...
Calibration Binding Sites Uncertainty RNA-Binding Proteins RNA Neural Networks, Computer Temperature Protein Binding
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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 Protein Conformation Protein Binding Receptors, Neuropeptide Binding Sites Allosteric Regulation Humans
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