{"title":"Insight into virus movement mechanism using <i>in silico</i> approaches by employing SeMV as a model system.","authors":"Jyotilipsa Mohanty, Lukkani Laxman Kumar, Ayaluru Murali","doi":"10.1080/07391102.2025.2474063","DOIUrl":null,"url":null,"abstract":"<p><p>Viral infections in plants are a big threat to agriculture and the economy. Though the viral infection mechanism is well documented, the cell-to-cell trafficking of the virus is poorly understood. The plant virus is known to encode movement protein (MP) for trafficking the virus from an infected cell to a healthy cell. The movement protein is known to increase plant cells' size exclusion limit (SEL) of plasmodesmata (PD). However, the exact mechanism of the viral trafficking remained unclear. In this study, we proposed a possible mechanism of viral trafficking by using <i>Sesbania mosaic virus</i> (SeMV) as a model system. The movement protein and RNA-dependent RNA polymerase (RdRp) of SeMV were modeled using the <i>ab initio</i> method. It is also known that MP binds with VPg in the movement process and RdRp requires P10 for replication. The models of VPg and P10 were extracted from the structure of polyprotein 2a. The complexes MP-VPg and RdRp-P10 were built with the help of molecular docking and were subjected to molecular dynamic simulation to get stable complexes. The trafficking complex (MP+VPg + RdRp + P10) was obtained by performing the molecular docking of these two complexes. Through MDS, the stability of the trafficking complex was confirmed. For the first time, a trafficking complex was proposed to understand its role in navigation of the viral complex through the host's plasmodesmata.</p>","PeriodicalId":15272,"journal":{"name":"Journal of Biomolecular Structure & Dynamics","volume":" ","pages":"1-13"},"PeriodicalIF":2.7000,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Biomolecular Structure & Dynamics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1080/07391102.2025.2474063","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Viral infections in plants are a big threat to agriculture and the economy. Though the viral infection mechanism is well documented, the cell-to-cell trafficking of the virus is poorly understood. The plant virus is known to encode movement protein (MP) for trafficking the virus from an infected cell to a healthy cell. The movement protein is known to increase plant cells' size exclusion limit (SEL) of plasmodesmata (PD). However, the exact mechanism of the viral trafficking remained unclear. In this study, we proposed a possible mechanism of viral trafficking by using Sesbania mosaic virus (SeMV) as a model system. The movement protein and RNA-dependent RNA polymerase (RdRp) of SeMV were modeled using the ab initio method. It is also known that MP binds with VPg in the movement process and RdRp requires P10 for replication. The models of VPg and P10 were extracted from the structure of polyprotein 2a. The complexes MP-VPg and RdRp-P10 were built with the help of molecular docking and were subjected to molecular dynamic simulation to get stable complexes. The trafficking complex (MP+VPg + RdRp + P10) was obtained by performing the molecular docking of these two complexes. Through MDS, the stability of the trafficking complex was confirmed. For the first time, a trafficking complex was proposed to understand its role in navigation of the viral complex through the host's plasmodesmata.
期刊介绍:
The Journal of Biomolecular Structure and Dynamics welcomes manuscripts on biological structure, dynamics, interactions and expression. The Journal is one of the leading publications in high end computational science, atomic structural biology, bioinformatics, virtual drug design, genomics and biological networks.