Protein motifs, which are specific regions and conserved regions, are found by comparing multiple protein sequences. These conserved regions in general play an important role in protein functions and protein folds, for example, for their binding properties or enzymatic activities. The aim here is to find the existence correlations of protein motifs. The knowledge of protein motif/domain sharing should be important in shedding new light on the biologic functions of proteins and offering a basis in analyzing the evolution in the human genome or other genomes. The protein sequences used here are obtained from the PIR-NREF database and the protein motifs are retrieved from the PROSITE database. We apply data mining approach to discover the occurrence correlations of motif in protein sequences. The correlation of motifs mined can be used in evolution analyses and protein structure prediction. We discuss the latter, i.e., protein structure prediction in this study. The correlations mined are stored and maintained in a database system. The database is now available at http://bioinfo.csie.ncu.edu.tw/ProMotif/.
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http://dx.doi.org/10.1002/jcc.10332 | DOI Listing |
Nucleic Acids Res
January 2025
Biomolecular Sciences Institute, Florida International University, Miami, FL 33199, United States.
The mammalian high mobility group protein AT-hook 2 (HMGA2) is a small DNA-binding protein that specifically targets AT-rich DNA sequences. Structurally, HMGA2 is an intrinsically disordered protein (IDP), comprising three positively charged 'AT-hooks' and a negatively charged C-terminus. HMGA2 can form homodimers through electrostatic interactions between its 'AT-hooks' and C-terminus.
View Article and Find Full Text PDFNucleic Acids Res
January 2025
School of Biological Sciences, University of Edinburgh, Edinburgh, EH9 3JH, United Kingdom.
The growing demand for biological products drives many efforts to maximize expression of heterologous proteins. Advances in high-throughput sequencing can produce data suitable for building sequence-to-expression models with machine learning. The most accurate models have been trained on one-hot encodings, a mechanism-agnostic representation of nucleotide sequences.
View Article and Find Full Text PDFArch Biochem Biophys
January 2025
Microbial Biotechnology, Faculty of Biology and Biotechnology, Ruhr University Bochum, Universitaetsstrasse 150, 44780 Bochum, Germany.
4-Phenol oxidases are proposed to be involved in the utilization of lignin-derived aromatic compounds. While enzymes with selectivity towards 4-hydroxyphenyl and guaiacyl motifs are well described, we identified the first syringyl-specific oxidase from Streptomyces cavernae (Sc4ASO) only very recently. Here, in-depth studies were conducted to unravel the molecular origins of the outstanding selectivity of Sc4ASO.
View Article and Find Full Text PDFPLoS Pathog
January 2025
Joint Research Center for Human Retrovirus Infection, Kumamoto University, Kumamoto, Japan.
We have demonstrated that the cellular protein M-Sec promotes the transmission of human T-cell leukemia virus type 1 (HTLV-1) in vitro and in vivo. Here, we show how HTLV-1 utilizes M-Sec for its efficient transmission. HTLV-1-infected CD4+ T cells expressed M-Sec at a higher level than uninfected CD4+ T cells.
View Article and Find Full Text PDFNucleic Acids Res
January 2025
Department of Genome Sciences, University of Virginia, PO Box 800717, Charlottesville, VA 22908, USA.
Many transcription factors (TFs) have been shown to bind to super-enhancers, forming transcriptional condensates to activate transcription in various cellular systems. However, the genomic and epigenomic determinants of phase-separated transcriptional condensate formation remain poorly understood. Questions regarding which TFs tend to associate with transcriptional condensates and what factors influence their association are largely unanswered.
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