Using computational modeling to design antiviral strategies and understand plant-virus interactions

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dc.authoridKAMAL, HIRA/0000-0001-6503-2167
dc.contributor.authorKamal, Hira
dc.contributor.authorZafar, Muhammad Mubashar
dc.contributor.authorRazzaq, Abdul
dc.contributor.authorIjaz, Aqsa
dc.contributor.authorAnwar, Zunaira
dc.contributor.authorTopcu, Hayat
dc.contributor.authorElhindi, Khalid M.
dc.date.accessioned2024-10-29T17:59:48Z
dc.date.available2024-10-29T17:59:48Z
dc.date.issued2024
dc.departmentTekirdağ Namık Kemal Üniversitesi
dc.description.abstractUsing 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 beta C1 (CLCuMB- beta C1) 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 beta C1 and UBC3. This molecular interaction of CLCuMB-beta C1 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.
dc.description.sponsorshipKing Saud University, Riyadh, Saudi Arabia [RSPD2024R952]
dc.description.sponsorshipThis research was supported by The Researchers Supporting Project number (RSPD2024R952) , King Saud University, Riyadh, Saudi Arabia.
dc.identifier.doi10.55730/1300-011X.3191
dc.identifier.issn1300-011X
dc.identifier.issn1303-6173
dc.identifier.issue3en_US
dc.identifier.scopus2-s2.0-85197114030
dc.identifier.scopusqualityQ2
dc.identifier.trdizinid#BAŞV!
dc.identifier.urihttps://doi.org/10.55730/1300-011X.3191
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay/1242820
dc.identifier.urihttps://hdl.handle.net/20.500.11776/14841
dc.identifier.volume48
dc.identifier.wosWOS:001249988000008
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakTR-Dizin
dc.language.isoen
dc.publisherTubitak Scientific & Technological Research Council Turkey
dc.relation.ispartofTurkish Journal of Agriculture and Forestry
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectBegomoviruses
dc.subjectcotton leaf curl Multan betasatellite
dc.subjectbeta C1
dc.subjectvirus-host interaction
dc.subjectubiquitin-conjugating enzyme
dc.titleUsing computational modeling to design antiviral strategies and understand plant-virus interactions
dc.title.alternativeUsing computational modeling to design antiviral strategies and understand plant-virus interactions
dc.typeArticle

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