Please use this identifier to cite or link to this item: http://223.31.159.10:8080/jspui/handle/123456789/1503
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dc.contributor.authorJaiswal, Mohini-
dc.contributor.authorKumar, Shailesh-
dc.date.accessioned2023-08-01T04:30:42Z-
dc.date.available2023-08-01T04:30:42Z-
dc.date.issued2024-
dc.identifier.citationJournal of Biomolecular Structure and Dynamics, (In Press)en_US
dc.identifier.issn0739-1102-
dc.identifier.issn1538-0254-
dc.identifier.otherhttps://doi.org/10.1080/07391102.2023.2235605-
dc.identifier.urihttps://www.tandfonline.com/doi/full/10.1080/07391102.2023.2235605-
dc.identifier.urihttp://223.31.159.10:8080/jspui/handle/123456789/1503-
dc.descriptionAccepted date: 6 July 2023en_US
dc.description.abstractThe pervasive repertoire of plant molecules with the potential to serve as a substitute for conventional antibiotics has led to obtaining better insights into plant-derived antimicrobial peptides (AMPs). The massive distribution of Small Open Reading Frames (smORFs) throughout eukaryotic genomes with proven extensive biological functions reflects their practicality as antimicrobials. Here, we have developed a pipeline named smAMPsTK to unveil the underlying hidden smORFs encoding AMPs for plant species. By applying this pipeline, we have elicited AMPs of various functional activity of lengths ranging from 5 to 100 aa by employing publicly available transcriptome data of five different angiosperms. Later, we studied the coding potential of AMPs-smORFs, the inclusion of diverse translation initiation start codons, and amino acid frequency. Codon usage study signifies no such codon usage biases for smORFs encoding AMPs. Majorly three start codons are prominent in generating AMPs. The evolutionary and conservational study proclaimed the widespread distribution of AMPs encoding genes throughout the plant kingdom. Domain analysis revealed that nearly all AMPs have chitin-binding ability, establishing their role as antifungal agents. The current study includes a developed methodology to characterize smORFs encoding AMPs, and their implications as antimicrobial, antibacterial, antifungal, or antiviral provided by SVM score and prediction status calculated by machine learning-based prediction models. The pipeline, complete package, and the results derived for five angiosperms are freely available at https://github.com/skbinfo/smAMPsTK.en_US
dc.description.sponsorshipMJ thanks the Council of Scientific and Industrial Research (CSIR), India, for research fellowships. DBT (Department of Biotechnology)-eLibrary Consortium (DeLCON), is acknowledged for providing e-resources. SK acknowledges the BT/PR40146/BTIS/137/4/2020 project grant from the Department of Biotechnology (DBT), Government of India. The authors acknowledge the Computational Biology & Bioinformatics Facility (CBBF) of the National Institute of Plant Genome Research (NIPGR).en_US
dc.language.isoen_USen_US
dc.publisherTaylor & Francis Groupen_US
dc.subjectSmall open reading framesen_US
dc.subjectantimicrobial peptidesen_US
dc.subjectpipelineen_US
dc.subjectplant-deriveden_US
dc.subjectsmORFsen_US
dc.subjecttranscriptomeen_US
dc.titlesmAMPsTK: a toolkit to unravel the smORFome encoding AMPs of plant speciesen_US
dc.typeArticleen_US
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