Computer Aided Drug Discovery and Proteomic Sequence Analysis of Tobacco Mosaic Virus

Abstract

Tobacco Mosaic Virus (TMV) stands as a persistent threat to global agriculture, particularly impacting tobacco crops and other solanaceous plants. Conventional control measures have faced challenges in effectively mitigating TMV infections, prompting the exploration of innovative strategies. This study investigates the synergistic application of computer-aided drug discovery (CADD) and proteomic sequence analysis to address TMV infections. Leveraging protein structure analysis and molecular docking simulations, potential antiviral compounds were screened, with MitoxantroneGlucuronide demonstrating promising binding affinity to TMV proteins. Additionally, proteomic sequence analysis uncovered critical molecular insights into TMV biology, shedding light on viral-host interactions and potential therapeutic targets. Through an integrative approach combining computational predictions with experimental validation, this study sight to advance our interpretation of TMV pathogenesis and accord to the development of productive antiviral approach. By bridging the gap between computational modeling and empirical research, this interdisciplinary effort holds promise in safeguarding global agriculture against the pervasive threat of TMV.