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Binding Sites

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A KAN-based hybrid deep neural networks for accurate identification of transcription factor binding sites.

PloS one 40334196
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...
Algorithms Binding Sites Computational Biology Deep Learning Humans Neural Networks, Computer Promoter Regions, Genetic Protein Binding Transcription Factors
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DRLiPS: a novel method for prediction of druggable RNA-small molecule binding pockets using machine learning.

Nucleic acids research 40173014
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 Binding Sites Humans Ligands Machine Learning Molecular Docking Simulation Nucleic Acid Conformation RNA Software
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Deep-ProBind: binding protein prediction with transformer-based deep learning model.

BMC bioinformatics 40121399
Binding proteins play a crucial role in biological systems by selectively interacting with specific molecules, such as DNA, RNA, or peptides, to regulate various cellular processes. Their ability to recognize and bind target molecules with high speci...
Algorithms Binding Sites Computational Biology Databases, Protein Deep Learning Neural Networks, Computer Protein Binding Proteins Sequence Analysis, Protein
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RNAmigos2: accelerated structure-based RNA virtual screening with deep graph learning.

Nature communications 40118849
RNAs are a vast reservoir of untapped drug targets. Structure-based virtual screening (VS) identifies candidate molecules by leveraging binding site information, traditionally using molecular docking simulations. However, docking struggles to scale w...
Binding Sites Deep Learning Molecular Docking Simulation Nucleic Acid Conformation Riboswitch RNA
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TopEC: prediction of Enzyme Commission classes by 3D graph neural networks and localized 3D protein descriptor.

Nature communications 40108108
Tools available for inferring enzyme function from general sequence, fold, or evolutionary information are generally successful. However, they can lead to misclassification if a deviation in local structural features influences the function. Here, we...
Algorithms Binding Sites Computational Biology Enzymes Graph Neural Networks Neural Networks, Computer Protein Conformation Software
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TRAPT: a multi-stage fused deep learning framework for predicting transcriptional regulators based on large-scale epigenomic data.

Nature communications 40240358
It is challenging to identify regulatory transcriptional regulators (TRs), which control gene expression via regulatory elements and epigenomic signals, in context-specific studies on the onset and progression of diseases. The use of large-scale mult...
Binding Sites Chromatin Computational Biology Deep Learning Epigenomics Gene Expression Regulation Humans Regulatory Elements, Transcriptional Transcription Factors
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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 40183480
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. ...
Binding Sites Convolutional Neural Networks Humans NAD Neural Networks, Computer Sirtuins
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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 40335485
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...
Binding Sites Chromatin Immunoprecipitation Sequencing DNA, Bacterial Escherichia coli Escherichia coli Proteins Neural Networks, Computer Protein Binding Transcription Factors
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Integrating genetic variation with deep learning provides context for variants impacting transcription factor binding during embryogenesis.

Genome research 40234030
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...
Alleles Animals Binding Sites Deep Learning Drosophila Drosophila melanogaster Drosophila Proteins Embryonic Development Genetic Variation Protein Binding Transcription Factors
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iProtDNA-SMOTE: Enhancing protein-DNA binding sites prediction through imbalanced graph neural networks.

PloS one 40359455
Protein-DNA interactions play a crucial role in cellular biology, essential for maintaining life processes and regulating cellular functions. We propose a method called iProtDNA-SMOTE, which utilizes non-equilibrium graph neural networks along with p...
Algorithms Binding Sites Computational Biology Databases, Protein DNA DNA-Binding Proteins Graph Neural Networks Neural Networks, Computer Protein Binding Software
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