Turkish Journal of Agriculture and Forestry
Author ORCID Identifier
HIRA KAMAL 0000-0001-6503-2167
XUEFEI JIANG 0000-0002-0607-3847
MUHAMMAD MUBASHAR ZAFAR 0000-0002-5664-138X
ABDUL RAZZAQ 0000-0002-0106-0481
AQSA IJAZ 0009-0001-7526-732X
ZUNAIRA ANVAR 0000-0003-0155-3902
HAYAT TOPÇU 0000-0003-3108-4393
KHALID M. ELHINDI 0000-0003-0898-7252
ASIF SAEED 0000-0002-2017-9330
UROOJ FATIMA 0009-0007-7769-0416
DOI
10.55730/1300-011X.3191
Abstract
Using a bioinformatics approach to identify binding pockets between proteins is a preferable method before modifying the genome to delineate host interactions with viruses. Based on extensive proteomics data in numerous databases, several interaction prediction methods are available to identify binding sites between viruses and hosts at the individual residue level, but little is known about the interaction prediction strategy for plant viruses. Begomoviruses, belonging to the family Geminiviridae, constitute a group of circular single-stranded (ss) DNA viruses that encode multifunctional proteins responsible for viral replication, causing severe diseases in multiple host plants. These viruses usually escape through plant defense mechanism overcoming physical and chemical barriers to trigger the infection with all possible combinations of interaction in the target host protein partners. Here, we have applied our computational approach for plant virus interaction at domain level. Previous study showed that myristoylation-like motif in Begomovirus cotton leaf curl Multan associated betasatellite protein βC1 (CLCuMB- βC1) played an important role for interaction with ubiquitin conjugating enzyme protein (UBC3) in tomato. This kind of binding at residue level has been validated using in-vivo and in-vitro molecular approach. Here, an in-silico approach was utilized which is a combinatorial source of previous and recent protein prediction methods to determine all possible identified interface sites between βC1 and UBC3. This molecular interaction of CLCuMB-βC1 was further verified in the actual host i.e. cotton using bimolecular fluorescence complementation system and yeast two hybrid assay. This combinatorial approach of computational and molecular data will help to identify the interaction between virus and host before using any expensive and time consuming molecular techniques.
Keywords
Begomoviruses, Cotton leaf curl Multan betasatellite, ubiquitin-conjugating enzyme, virus-host interaction, βC1 gene
First Page
417
Last Page
429
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
KAMAL, HIRA; ZAFAR, MUHAMMAD MUBASHAR; RAZZAQ, ABDUL; IJAZ, AQSA; ANVAR, ZUNAIRA; TOPÇU, HAYAT; ELHINDI, KHALID M.; SAEED, ASIF; FATIMA, UROOJ; and JIANG, XUEFEI
(2024)
"Using computational modeling to design antiviral strategies and understand plant-virus interactions,"
Turkish Journal of Agriculture and Forestry: Vol. 48:
No.
3, Article 8.
https://doi.org/10.55730/1300-011X.3191
Available at:
https://journals.tubitak.gov.tr/agriculture/vol48/iss3/8