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Nucleic acid-binding proteins are involved in a great number of cellular processes. Understanding the mechanisms underlying these proteins first requires the identification of specific residues involved in nucleic acid binding. Prediction of NA-binding residues can provide practical assistance in the functional annotation of NA-binding proteins. Predictions can also be used to expedite mutagenesis experiments, guiding researchers to the correct binding residues in these proteins. Here, we present a method for the identification of amino acid residues involved in DNA- and RNA-binding using sequence-based attributes. The method used in this work combines the C4.5 algorithm with bootstrap aggregation and cost-sensitive learning. Our DNA-binding model achieved 79.1% accuracy, while the RNA-binding model reached an accuracy of 73.2%. The NAPS web server is freely available at http://proteomics.bioengr.uic.edu/NAPS.
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http://dx.doi.org/10.1093/nar/gkq361 | DOI Listing |
Brief Bioinform
August 2025
School of Information and Artificial Intelligence, Anhui Agricultural University, 130 Changjiang Road, Shushan District, Hefei, Anhui 230036, China.
Protein-nucleic acid binding sites play a crucial role in biological processes such as gene expression, signal transduction, replication, and transcription. In recent years, with the development of artificial intelligence, protein language models, graph neural networks, and transformer architectures have been adopted to develop both structure-based and sequence-based predictive models. Structure-based methods benefit from the spatial relationship between residues and have shown promising performance.
View Article and Find Full Text PDFBiochem Biophys Res Commun
September 2025
Beamline Development and Application Section, Bhabha Atomic Research Centre, Mumbai, 400085, India. Electronic address:
The UPF0235 UniProt family proteins are conserved across archaea, bacteria, and eukaryotes; however, they remain functionally uncharacterized. Here, we report the high resolution (1.3 Å) crystal structure of UPF0235 protein (PF1765, UniProt: Q8U052) from Pyrococcus furiosus.
View Article and Find Full Text PDFEur J Pharmacol
September 2025
Department of Dermatology, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China; Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, Anhui, China; Institute of Dermatology, Anhui Medical University, Hefei 230032, Anhui, China. Electronic
Vascular endothelial cells (ECs) damage is closely related to kidney injury. Our previous research revealed the involvement of interferon regulatory factor 1 (IRF1)-mediated PANoptosis of renal ECs in trichloroethylene (TCE)-induced immune kidney injury. However, how IRF1 regulates ECs PANoptosis remains unclear.
View Article and Find Full Text PDFBMC Plant Biol
September 2025
College of Grassland Agriculture, Northwest A&F University, Yangling, 712100, China.
Background: Dehydrin (DHN) proteins, belong to subfamily members of late embryogenesis abundant (LEA) proteins, are widely recognized as key determinants in plant abiotic stress tolerance.
Results: In this study, we identified eleven DHN genes in Zea mays and systematically analyzed their evolutionary relationships, structural features, cis-acting elements, expression patterns, protein interaction relation, and function validation in drought resistance. All ZmDHN proteins contained K-segment, and were classified into three subgroups, i.
Diagnostics (Basel)
August 2025
Department of Biology, Faculty of Art and Science, Gaziantep University, Gaziantep 27310, Turkey.
Colorectal cancer (CRC) is one of the most common malignancies worldwide. microRNAs (miRNAs) are small non-coding RNA molecules that regulate gene expression post-transcriptionally and have emerged as important regulators in cancer biology. This study aimed to investigate the roles of miR-379-5p and miR-519a-3p in CRC using Quantitative Real-Time PCR (RT-qPCR) and comprehensive bioinformatic analyses.
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