AIMC Topic: Binding Sites

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Comparative analysis of RNA 3D structure prediction methods: towards enhanced modeling of RNA-ligand interactions.

Nucleic acids research Jul 22, 2024
Accurate RNA structure models are crucial for designing small molecule ligands that modulate their functions. This study assesses six standalone RNA 3D structure prediction methods-DeepFoldRNA, RhoFold, BRiQ, FARFAR2, SimRNA and Vfold2, excluding web...
Machine Learning Software Models, Molecular Binding Sites RNA Folding RNA Ligands Nucleic Acid Conformation
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The developmental and evolutionary characteristics of transcription factor binding site clustered regions based on an explainable machine learning model.

Nucleic acids research Jul 22, 2024
Gene expression is temporally and spatially regulated by the interaction of transcription factors (TFs) and cis-regulatory elements (CREs). The uneven distribution of TF binding sites across the genome poses challenges in understanding how this distr...
Humans Transcription Factors Evolution, Molecular Oryzias Embryonic Development Cattle Machine Learning Promoter Regions, Genetic Mice Animals Binding Sites Chickens Gene Expression Regulation, Developmental Chromatin
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AIUPred: combining energy estimation with deep learning for the enhanced prediction of protein disorder.

Nucleic acids research Jul 5, 2024
Intrinsically disordered proteins and protein regions (IDPs/IDRs) carry out important biological functions without relying on a single well-defined conformation. As these proteins are a challenge to study experimentally, computational methods play im...
Software Deep Learning Protein Conformation Computational Biology Binding Sites Thermodynamics Internet Intrinsically Disordered Proteins
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Geometric epitope and paratope prediction.

Bioinformatics (Oxford, England) Jul 1, 2024
MOTIVATION: Identifying the binding sites of antibodies is essential for developing vaccines and synthetic antibodies. In this article, we investigate the optimal representation for predicting the binding sites in the two molecules and emphasize the ...
Protein Conformation Binding Sites Software Deep Learning Computational Biology Antibodies Epitopes
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DEAttentionDTA: protein-ligand binding affinity prediction based on dynamic embedding and self-attention.

Bioinformatics (Oxford, England) Jun 3, 2024
MOTIVATION: Predicting protein-ligand binding affinity is crucial in new drug discovery and development. However, most existing models rely on acquiring 3D structures of elusive proteins. Combining amino acid sequences with ligand sequences and bette...
Amino Acid Sequence Ligands Binding Sites Proteins Databases, Protein Neural Networks, Computer Software Protein Binding Computational Biology
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PTFSpot: deep co-learning on transcription factors and their binding regions attains impeccable universality in plants.

Briefings in bioinformatics May 23, 2024
Unlike animals, variability in transcription factors (TFs) and their binding regions (TFBRs) across the plants species is a major problem that most of the existing TFBR finding software fail to tackle, rendering them hardly of any use. This limitatio...
Transcription Factors Plants Binding Sites Genome, Plant Arabidopsis Software Deep Learning Computational Biology
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EGPDI: identifying protein-DNA binding sites based on multi-view graph embedding fusion.

Briefings in bioinformatics May 23, 2024
Mechanisms of protein-DNA interactions are involved in a wide range of biological activities and processes. Accurately identifying binding sites between proteins and DNA is crucial for analyzing genetic material, exploring protein functions, and desi...
DNA-Binding Proteins Binding Sites Protein Binding Computational Biology Neural Networks, Computer DNA Algorithms
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BERT-TFBS: a novel BERT-based model for predicting transcription factor binding sites by transfer learning.

Briefings in bioinformatics Mar 27, 2024
Transcription factors (TFs) are proteins essential for regulating genetic transcriptions by binding to transcription factor binding sites (TFBSs) in DNA sequences. Accurate predictions of TFBSs can contribute to the design and construction of metabol...
Algorithms Deep Learning Protein Binding Humans Neural Networks, Computer Computational Biology Transcription Factors Binding Sites
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EquiPNAS: improved protein-nucleic acid binding site prediction using protein-language-model-informed equivariant deep graph neural networks.

Nucleic acids research Mar 21, 2024
Protein language models (pLMs) trained on a large corpus of protein sequences have shown unprecedented scalability and broad generalizability in a wide range of predictive modeling tasks, but their power has not yet been harnessed for predicting prot...
Neural Networks, Computer Nucleic Acids Proteins Amino Acid Sequence Binding Sites
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Protein-protein and protein-nucleic acid binding site prediction via interpretable hierarchical geometric deep learning.

GigaScience Jan 2, 2024
Identification of protein-protein and protein-nucleic acid binding sites provides insights into biological processes related to protein functions and technical guidance for disease diagnosis and drug design. However, accurate predictions by computati...
Protein Binding COVID-19 Humans Spike Glycoprotein, Coronavirus SARS-CoV-2 Neural Networks, Computer Deep Learning Computational Biology Nucleic Acids Binding Sites
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