AIMC Topic: Binding Sites

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MMPD-DTA: Integrating Multi-Modal Deep Learning with Pocket-Drug Graphs for Drug-Target Binding Affinity Prediction.

Journal of chemical information and modeling Jan 20, 2025
Predicting drug-target binding affinity (DTA) is a crucial task in drug discovery research. Recent studies have demonstrated that pocket features and interactions between targets and drugs significantly improve the understanding of DTA. However, chal...
Humans Drug Discovery Deep Learning Pharmaceutical Preparations Binding Sites Protein Binding Proteins
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Identifying Protein-Nucleotide Binding Residues via Grouped Multi-task Learning and Pre-trained Protein Language Models.

Journal of chemical information and modeling Jan 9, 2025
The accurate identification of protein-nucleotide binding residues is crucial for protein function annotation and drug discovery. Numerous computational methods have been proposed to predict these binding residues, achieving remarkable performance. H...
Protein Binding Proteins Nucleotides Binding Sites Databases, Protein Deep Learning
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ProPr54 web server: predicting σ promoters and regulon with a hybrid convolutional and recurrent deep neural network.

NAR genomics and bioinformatics Jan 7, 2025
σ serves as an unconventional sigma factor with a distinct mechanism of transcription initiation, which depends on the involvement of a transcription activator. This unique sigma factor σ is indispensable for orchestrating the transcription of genes ...
Bacterial Proteins Internet Promoter Regions, Genetic Sigma Factor Binding Sites Neural Networks, Computer Regulon Genome, Bacterial Software RNA Polymerase Sigma 54
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Deep Learning Approaches for the Prediction of Protein Functional Sites.

Molecules (Basel, Switzerland) Jan 7, 2025
Knowing which residues of a protein are important for its function is of paramount importance for understanding the molecular basis of this function and devising ways of modifying it for medical or biotechnological applications. Due to the difficulty...
Computational Biology Proteins Databases, Protein Humans Deep Learning Binding Sites Sequence Analysis, Protein
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PharmRL: pharmacophore elucidation with deep geometric reinforcement learning.

BMC biology Dec 31, 2024
BACKGROUND: Molecular interactions between proteins and their ligands are important for drug design. A pharmacophore consists of favorable molecular interactions in a protein binding site and can be utilized for virtual screening. Pharmacophores are ...
Binding Sites Pharmacophore Humans Deep Learning Proteins Algorithms Ligands Drug Design
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DeepMiRBP: a hybrid model for predicting microRNA-protein interactions based on transfer learning and cosine similarity.

BMC bioinformatics Dec 18, 2024
BACKGROUND: Interactions between microRNAs and RNA-binding proteins are crucial for microRNA-mediated gene regulation and sorting. Despite their significance, the molecular mechanisms governing these interactions remain underexplored, apart from sequ...
Deep Learning Computational Biology Neural Networks, Computer Binding Sites RNA-Binding Proteins MicroRNAs
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Residue-Level Multiview Deep Learning for ATP Binding Site Prediction and Applications in Kinase Inhibitors.

Journal of chemical information and modeling Dec 17, 2024
Accurate identification of adenosine triphosphate (ATP) binding sites is crucial for understanding cellular functions and advancing drug discovery, particularly in targeting kinases for cancer treatment. Existing methods face significant challenges d...
Binding Sites Drug Discovery Deep Learning Ligands Protein Kinase Inhibitors Humans Adenosine Triphosphate Molecular Docking Simulation
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Docking-Informed Machine Learning for Kinome-wide Affinity Prediction.

Journal of chemical information and modeling Dec 10, 2024
Kinase inhibitors are an important class of anticancer drugs, with 80 inhibitors clinically approved and >100 in active clinical testing. Most bind competitively in the ATP-binding site, leading to challenges with selectivity for a specific kinase, r...
Protein Binding Protein Kinases Protein Kinase Inhibitors Binding Sites Protein Conformation Machine Learning Molecular Docking Simulation Humans
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MMD-DTA: A Multi-Modal Deep Learning Framework for Drug-Target Binding Affinity and Binding Region Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
The prediction of drug-target affinity (DTA) plays a crucial role in drug development and the identification of potential drug targets. In recent years, computer-assisted DTA prediction has emerged as a significant approach in this field. In this stu...
Protein Binding Drug Discovery Pharmaceutical Preparations Humans Computational Biology Proteins Neural Networks, Computer Deep Learning Binding Sites
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Intra-Inter Graph Representation Learning for Protein-Protein Binding Sites Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Graph neural networks have drawn increasing attention and achieved remarkable progress recently due to their potential applications for a large amount of irregular data. It is a natural way to represent protein as a graph. In this work, we focus on p...
Algorithms Protein Binding Computational Biology Neural Networks, Computer Ligands Proteins Binding Sites Machine Learning Databases, Protein
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