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罗非鱼湖病毒(TiLV)开放阅读框编码功能基因的结构特征。

Structural Characterization of Open Reading Frame-Encoded Functional Genes from Tilapia Lake Virus (TiLV).

机构信息

Biotechnology Laboratory, ICAR-Central Inland Fisheries Research Institute, Barrackpore, Kolkata, West Bengal, 700120, India.

Department of Bioinformatics, Odisha University of Agriculture and Technology, Bhubaneswar, Odisha, 751003, India.

出版信息

Mol Biotechnol. 2019 Dec;61(12):945-957. doi: 10.1007/s12033-019-00217-y.

Abstract

In recent years, large-scale mortalities are observed in tilapia due to infection with a novel orthomyxo-like virus named, tilapia lake virus (TiLV) which is marked to be a severe threat to universal tilapia industry. Currently, there are knowledge gaps relating to the antiviral peptide as well as there are no affordable vaccines or drugs available against TiLV yet. To understand the spreading of infection of TiLV in different organs of Oreochromis niloticus, RT-PCR analysis has been carried out. The gene segments of TiLV were retrieved from the NCBI database for computational biology analysis. The 14 functional genes were predicted from the 10 gene segments of TiLV. Phylogenetic analysis was employed to find out a better understanding for the evolution of tilapia lake virus genes. Out of 14 proteins, only six proteins show transmembrane helix region. Moreover, molecular modeling and molecular dynamics simulations of the predicted proteins revealed structural stability of the protein stabilized after 10-ns simulation. Overall, our study provided a basic bioinformatics on functional proteome of TiLV. Further, this study could be useful for development of novel peptide-based therapeutics to control TiLV infection.

摘要

近年来,由于一种名为“罗非鱼湖病毒(TiLV)”的新型正粘病毒样病毒感染,罗非鱼大规模死亡。这种病毒被认为是对全球罗非鱼产业的严重威胁。目前,关于抗病毒肽的知识还存在空白,而且还没有针对 TiLV 的经济实惠的疫苗或药物。为了了解 TiLV 在奥利亚罗非鱼不同器官中的感染传播情况,进行了 RT-PCR 分析。TiLV 的基因片段已从 NCBI 数据库中检索出来,用于计算生物学分析。从 TiLV 的 10 个基因片段中预测了 14 个功能基因。系统发育分析有助于更好地了解罗非鱼湖病毒基因的进化。在 14 种蛋白质中,只有 6 种蛋白质显示跨膜螺旋区。此外,预测蛋白质的分子建模和分子动力学模拟揭示了在经过 10-ns 模拟后稳定的蛋白质的结构稳定性。总的来说,我们的研究为 TiLV 的功能蛋白质组提供了基本的生物信息学基础。此外,这项研究可能有助于开发新型基于肽的疗法来控制 TiLV 感染。

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