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    Using computational modeling to design antiviral strategies and understand plant-virus interactions
    (2024) Kamal, Hira; Zafar, Muhammad Mubashar; Razzaq, Abdul; Ijaz, Aqsa; Anwar, Zunaira; Topçu, Hayat; Elhındı, Khalid M.
    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 ?C1 (CLCuMB- ?C1) played an important role in 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 ?C1 and UBC3. This molecular interaction of CLCuMB- ?C1 was further verified in the actual host i.e. cotton using a bimolecular fluorescence complementation system and yeast two-hybrid assay. This computational and molecular data will help to identify the interaction between virus and host before using any expensive and time-consuming molecular techniques.
  • Küçük Resim Yok
    Öğe
    Using computational modeling to design antiviral strategies and understand plant-virus interactions
    (Tubitak Scientific & Technological Research Council Turkey, 2024) Kamal, Hira; Zafar, Muhammad Mubashar; Razzaq, Abdul; Ijaz, Aqsa; Anwar, Zunaira; Topcu, Hayat; Elhindi, Khalid M.
    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 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.