The Library
In silico prediction and validations of domains involved in gossypium hirsutum SnRK1 protein interaction with cotton leaf curl multan betasatellite encoded βC1
Tools
Tools
Tools
Kamal, Hira, Minhas, Fayyaz ul Amir Afsar, Farooq, Muhammad, Tripathi, Diwaker, Hamza, Muhammad, Mustafa, Roma, Khan, Muhammad Zuhaib, Mansoor, Shahid, Pappu, Hanu R. and Amin, Imran (2019) In silico prediction and validations of domains involved in gossypium hirsutum SnRK1 protein interaction with cotton leaf curl multan betasatellite encoded βC1. Frontiers in Plant Science, 10 . 656. doi:10.3389/fpls.2019.00656
|
PDF
WRAP-in-silico-prediction-validations-domains-encoded-Minhas-2019.pdf - Published Version - Requires a PDF viewer. Available under License Creative Commons Attribution 4.0. Download (8Mb) | Preview |
Official URL: http://dx.doi.org/10.3389/fpls.2019.00656
Abstract
Cotton leaf curl disease (CLCuD) caused by viruses of genus Begomovirus is a major constraint to cotton (Gossypium hirsutum) production in many cotton-growing regions of the world. Symptoms of the disease are caused by Cotton leaf curl Multan betasatellite (CLCuMB) that encodes a pathogenicity determinant protein, βC1. Here, we report the identification of interacting regions in βC1 protein by using computational approaches including sequence recognition, and binding site and interface prediction methods. We show the domain-level interactions based on the structural analysis of G. hirsutum SnRK1 protein and its domains with CLCuMB-βC1. To verify and validate the in silico predictions, three different experimental approaches, yeast two hybrid, bimolecular fluorescence complementation and pull down assay were used. Our results showed that ubiquitin-associated domain (UBA) and autoinhibitory sequence (AIS) domains of G. hirsutum-encoded SnRK1 are involved in CLCuMB-βC1 interaction. This is the first comprehensive investigation that combined in silico interaction prediction followed by experimental validation of interaction between CLCuMB-βC1 and a host protein. We demonstrated that data from computational biology could provide binding site information between CLCuD-associated viruses/satellites and new hosts that lack known binding site information for protein–protein interaction studies. Implications of these findings are discussed.
| Item Type: | Journal Article | ||||||
|---|---|---|---|---|---|---|---|
| Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software Q Science > QH Natural history > QH301 Biology Q Science > QK Botany |
||||||
| Divisions: | Faculty of Science > Computer Science | ||||||
| Library of Congress Subject Headings (LCSH): | Yeast two-hybrid assay, Cotton -- Viruses, Plant proteins -- Analysis, Geminiviridae | ||||||
| Journal or Publication Title: | Frontiers in Plant Science | ||||||
| Publisher: | Frontiers Media S.A. | ||||||
| ISSN: | 1664-462X | ||||||
| Official Date: | 28 May 2019 | ||||||
| Dates: |
|
||||||
| Date of first compliant deposit: | 4 November 2019 | ||||||
| Volume: | 10 | ||||||
| Article Number: | 656 | ||||||
| DOI: | 10.3389/fpls.2019.00656 | ||||||
| Status: | Peer Reviewed | ||||||
| Publication Status: | Published | ||||||
| Access rights to Published version: | Open Access | ||||||
| RIOXX Funder/Project Grant: |
|
Request changes or add full text files to a record
Repository staff actions (login required)
 |
View Item |
Downloads
Downloads per month over past year
