AIMC Topic: Binding Sites

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DTBA-net: Drug-Target Binding Affinity prediction using feature selection in hybrid CNN model.

Journal of computer-aided molecular design Jun 16, 2025
In drug discovery, virtual screening and repositioning rely on accurate Drug-Target Binding Affinity (DTBA) prediction to develop effective therapies. However, DTBA prediction remains challenging due to limited annotated datasets, high-dimensional bi...
Binding Sites Protein Binding Proteins Algorithms Drug Discovery Humans Deep Learning Neural Networks, Computer
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CR-deal: Explainable Neural Network for circRNA-RBP Binding Site Recognition and Interpretation.

Interdisciplinary sciences, computational life sciences Jun 1, 2025
circRNAs are a type of single-stranded non-coding RNA molecules, and their unique feature is their closed circular structure. The interaction between circRNAs and RNA-binding proteins (RBPs) plays a key role in biological functions and is crucial for...
Humans Neural Networks, Computer Deep Learning RNA, Circular Computational Biology RNA-Binding Proteins Binding Sites
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CrypTothML: An Integrated Mixed-Solvent Molecular Dynamics Simulation and Machine Learning Approach for Cryptic Site Prediction.

International journal of molecular sciences May 14, 2025
Cryptic sites, which are transient binding sites that emerge through protein conformational changes upon ligand binding, are valuable targets for drug discovery, particularly for allosteric modulators. However, identifying these sites remains challen...
Solvents Binding Sites Drug Discovery Protein Binding Proteins Molecular Dynamics Simulation Ligands Machine Learning
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Small Molecules Targeting the Structural Dynamics of AR-V7 Partially Disordered Proteins Using Deep Ensemble Docking.

Journal of chemical theory and computation May 13, 2025
The extensive conformational dynamics of partially disordered proteins hinders the efficiency of traditional in-silico structure-based drug discovery approaches due to the challenge of screening large chemical spaces of compounds, albeit with an exce...
Humans Molecular Docking Simulation Molecular Dynamics Simulation Intrinsically Disordered Proteins Protein Conformation Receptors, Androgen Binding Sites Small Molecule Libraries
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Topology-driven negative sampling enhances generalizability in protein-protein interaction prediction.

Bioinformatics (Oxford, England) May 6, 2025
MOTIVATION: Unraveling the human interactome to uncover disease-specific patterns and discover drug targets hinges on accurate protein-protein interaction (PPI) predictions. However, challenges persist in machine learning (ML) models due to a scarcit...
Humans Machine Learning Protein Interaction Mapping Proteins Databases, Protein Binding Sites Protein Binding Computational Biology
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Gated-GPS: enhancing protein-protein interaction site prediction with scalable learning and imbalance-aware optimization.

Briefings in bioinformatics May 1, 2025
In protein-protein interaction site (PPIS) prediction, existing machine learning models struggle with small datasets, limiting their predictive accuracy for unseen proteins. Additionally, class imbalance in protein complexes, where binding residues c...
Binding Sites Protein Interaction Mapping Proteins Databases, Protein Humans Machine Learning Algorithms Protein Binding Computational Biology
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Scoring protein-ligand binding structures through learning atomic graphs with inter-molecular adjacency.

PLoS computational biology May 1, 2025
With a burgeoning number of artificial intelligence (AI) applications in various fields, biomolecular science has also given a big welcome to advanced AI techniques in recent years. In this broad field, scoring a protein-ligand binding structure to o...
Proteins Deep Learning Ligands Algorithms Models, Molecular Protein Binding Protein Conformation Drug Discovery Computational Biology Binding Sites
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NAD_MCNN: Combining Protein Language Models and Multiwindow Convolutional Neural Networks for Deacetylase NAD+ Binding Site Prediction.

Chemical biology & drug design Apr 1, 2025
Sirtuins, a class of NAD+ -dependent deacetylases, play a key role in aging, metabolism, and longevity. Their interaction with NAD+ at the catalytic site is crucial for function, but experimental methods to map NAD+ binding sites are time consuming. ...
Sirtuins Convolutional Neural Networks Humans Binding Sites Neural Networks, Computer NAD
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DRLiPS: a novel method for prediction of druggable RNA-small molecule binding pockets using machine learning.

Nucleic acids research Mar 20, 2025
Ribonucleic Acid (RNA) is the central conduit for information transfer in the cell. Identifying potential RNA targets in disease conditions is a challenging task, given the vast repertoire of functional non-coding RNAs in a human cell. A potential dr...
Algorithms Molecular Docking Simulation RNA Ligands Nucleic Acid Conformation Binding Sites Humans Machine Learning Software
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Probabilistic and machine-learning methods for predicting local rates of transcription elongation from nascent RNA sequencing data.

Nucleic acids research Feb 8, 2025
Rates of transcription elongation vary within and across eukaryotic gene bodies. Here, we introduce new methods for predicting elongation rates from nascent RNA sequencing data. First, we devise a probabilistic model that predicts nucleotide-specific...
CCCTC-Binding Factor Transcription Elongation, Genetic Machine Learning Binding Sites Sequence Analysis, RNA Humans RNA Splice Sites DNA Methylation Epigenomics Neural Networks, Computer Histone Code Models, Statistical Histones
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