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Protein Binding

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Feature selection enhances peptide binding predictions for TCR-specific interactions.

Frontiers in immunology 39916960
INTRODUCTION: T-cell receptors (TCRs) play a critical role in the immune response by recognizing specific ligand peptides presented by major histocompatibility complex (MHC) molecules. Accurate prediction of peptide binding to TCRs is essential for a...
Animals Machine Learning Mice Peptide Library Peptides Protein Binding Receptors, Antigen, T-Cell
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Attention-aware differential learning for predicting peptide-MHC class I binding and T cell receptor recognition.

Briefings in bioinformatics 39883517
The identification of neoantigens is crucial for advancing vaccines, diagnostics, and immunotherapies. Despite this importance, a fundamental question remains: how to model the presentation of neoantigens by major histocompatibility complex class I m...
Algorithms Computational Biology Histocompatibility Antigens Class I Humans Machine Learning Peptides Protein Binding Receptors, Antigen, T-Cell
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TPepRet: a deep learning model for characterizing T-cell receptors-antigen binding patterns.

Bioinformatics (Oxford, England) 39880376
MOTIVATION: T-cell receptors (TCRs) elicit and mediate the adaptive immune response by recognizing antigenic peptides, a process pivotal for cancer immunotherapy, vaccine design, and autoimmune disease management. Understanding the intricate binding ...
Computational Biology COVID-19 Deep Learning Humans Peptides Protein Binding Receptors, Antigen, T-Cell SARS-CoV-2
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ZeRPI: A graph neural network model for zero-shot prediction of RNA-protein interactions.

Methods (San Diego, Calif.) 39892680
RNA-protein interactions are crucial for biological functions across multiple levels. RNA binding proteins (RBPs) intricately engage in diverse biological processes through specific RNA molecule interactions. Previous studies have revealed the indisp...
Algorithms Computational Biology Graph Neural Networks Humans Machine Learning Neural Networks, Computer Protein Binding RNA RNA-Binding Proteins
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MutualDTA: An Interpretable Drug-Target Affinity Prediction Model Leveraging Pretrained Models and Mutual Attention.

Journal of chemical information and modeling 39878060
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...
Binding Sites Deep Learning Drug Discovery Humans Pharmaceutical Preparations Protein Binding Proteins
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Machine learning models for predicting interaction affinity energy between human serum proteins and hemodialysis membrane materials.

Scientific reports 39875505
Membrane incompatibility poses significant health risks, including severe complications and potential fatality. Surface modification of membranes has emerged as a pivotal technology in the membrane industry, aiming to improve the hemocompatibility an...
Adsorption Algorithms Blood Proteins Humans Machine Learning Membranes, Artificial Molecular Docking Simulation Protein Binding Renal Dialysis
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Transformer Decoder Learns from a Pretrained Protein Language Model to Generate Ligands with High Affinity.

Journal of chemical information and modeling 39871540
The drug discovery process can be significantly accelerated by using deep learning methods to suggest molecules with druglike features and, more importantly, that are good candidates to bind specific proteins of interest. We present a novel deep lear...
Deep Learning Drug Discovery Ligands Models, Molecular Protein Binding Proteins
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Deep Learning of CYP450 Binding of Small Molecules by Quantum Information.

Journal of chemical information and modeling 39869197
Drug-drug interaction can lead to diminished therapeutic effects or increased toxicity, posing significant risks, especially in polypharmacy, and cytochrome P450 plays an indispensable role in this interaction. Cytochrome P450, responsible for the me...
Cytochrome P-450 CYP1A2 Cytochrome P-450 Enzyme System Deep Learning Drug Interactions Humans Protein Binding Quantum Theory Small Molecule Libraries
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Protein ligand structure prediction: From empirical to deep learning approaches.

Current opinion in structural biology 39914050
Protein-ligand structure prediction methods, aiming to predict the three-dimensional complex structure and binding energy of a compound and target protein, are essential in many structure-based drug discovery pipelines, including virtual screening an...
Computational Biology Deep Learning Drug Discovery Ligands Models, Molecular Protein Binding Protein Conformation Proteins
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CL-GNN: Contrastive Learning and Graph Neural Network for Protein-Ligand Binding Affinity Prediction.

Journal of chemical information and modeling 39913849
In the realm of drug discovery and design, the accurate prediction of protein-ligand binding affinity is of paramount importance as it underpins the functional interactions within biological systems. This study introduces a novel self-supervised lear...
Drug Discovery Graph Neural Networks Ligands Machine Learning Neural Networks, Computer Protein Binding Proteins
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