Molecular insights into host protein interactions with viral βC1 in Arabidopsis thaliana and Gossypium hirsutum

The begomovirus-induced cotton leaf curl disease (CLCuD) is a major roadblock to cotton production in many cotton-growing regions globally. In order to establish successful infection, Cotton leaf curl Multan betasatellite (CLCuMuB) hijacks the host’s key regulatory and signaling networks via their pathogenicity determinant protein, βC1. The evolution of bioinformatics and high-throughput technologies has provided extensive gene expression data, unveiling host’s resistance and susceptible genes against Cotton leaf curl virus (CLCuV) infections on a genome-wide scale. However, limited research has been conducted on how specific viral effector proteins interact with and hijack these host proteins to propagate viral infection. This study aimed at in-silico investigation of complex protein–protein interactions (PPI) between CLCuMuB-βC1 and central host proteins ( A. thaliana and G. hirsutum ) to unravel the best-performing PPI complexes for future gene targets against CLCuD. Using cross-species orthologus data, this study reveals evolutionarily conserved protein–protein complexes highlighting fundamental plant defense and susceptibility mechanisms. Multiple sequence and structure based analytical tools were employed including physiochemical investigation, domain-based interaction analysis, interface prediction and site-directed mutagenesis. We identified six genes AOC1, CSN3, deltaCOP, NSI, GRAB2, SAHH1 in Arabidopsis and three genes AOC1, deltaCOP, GRAB2 in cotton forming highly stable protein complexes with βC1. The lowest binding energies (up to -99.76 kcal/mol), docking scores (up to -1017.8 kcal/mol) and interface residues for βC1 interaction were assessed through multiple docking and energy prediction platforms including PRISM, PRODIGY, MM/GBSA, metaPPISP, ZDOCK, HADDOCK, MOE and ClusPro. The predicted interacting residues for these proteins were then analyzed using computational mutagenesis study and in-silico interface alanine scanning. To best of our knowledge, this is the first computational analysis providing consistent evidence of interaction potential and molecular interfaces between host and βC1 proteins across multiple predictive tools. Disrupting these critical host-virus interactions via CRISPR-mediated genome editing would help in developing durable CLCuD resistance in cotton (Fig. 1 ).