严重急性呼吸综合征相关冠状病毒中蛋白质编码基因的识别与分析

Recognition and analysis of protein-coding genes in severe acute respiratory syndrome associated coronavirus.

作者信息

Sharma Ramakant, Maheshwari Jitendra Kumar, Prakash Tulika, Dash Debasis, Brahmachari Samir K

机构信息

Institute of Genomics and Integrative Biology, CSIR, Mall Road, Delhi 110 007, India.

出版信息

Bioinformatics. 2004 May 1;20(7):1074-80. doi: 10.1093/bioinformatics/bth041. Epub 2004 Feb 5.

DOI:10.1093/bioinformatics/bth041

PMID:14764577

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7110108/

Abstract

MOTIVATION

The recent outbreak of severe acute respiratory syndrome (SARS) caused by SARS coronavirus (SARS-CoV) has necessitated an in-depth molecular understanding of the virus to identify new drug targets. The availability of complete genome sequence of several strains of SARS virus provides the possibility of identification of protein-coding genes and defining their functions. Computational approach to identify protein-coding genes and their putative functions will help in designing experimental protocols.

RESULTS

In this paper, a novel analysis of SARS genome using gene prediction method GeneDecipher developed in our laboratory has been presented. Each of the 18 newly sequenced SARS-CoV genomes has been analyzed using GeneDecipher. In addition to polyprotein 1ab(1), polyprotein 1a and the four genes coding for major structural proteins spike (S), small envelope (E), membrane (M) and nucleocapsid (N), six to eight additional proteins have been predicted depending upon the strain analyzed. Their lengths range between 61 and 274 amino acids. Our method also suggests that polyprotein 1ab, polyprotein 1a, S, M and N are proteins of viral origin and others are of prokaryotic. Putative functions of all predicted protein-coding genes have been suggested using conserved peptides present in their open reading frames.

AVAILABILITY

Detailed results of GeneDecipher analysis of all the 18 strains of SARS-CoV genomes are available at http://www.igib.res.in/sarsanalysis.html

摘要

研究动机

近期由严重急性呼吸综合征冠状病毒（SARS-CoV）引发的严重急性呼吸综合征（SARS）疫情爆发，有必要对该病毒进行深入的分子层面了解，以确定新的药物靶点。多种SARS病毒株完整基因组序列的可得性为鉴定蛋白质编码基因及其功能提供了可能。通过计算方法鉴定蛋白质编码基因及其推定功能将有助于设计实验方案。

研究结果

本文介绍了使用我们实验室开发的基因预测方法GeneDecipher对SARS基因组进行的一项新分析。已使用GeneDecipher对18个新测序的SARS-CoV基因组中的每一个进行了分析。除了多聚蛋白1ab(1)、多聚蛋白1a以及编码主要结构蛋白刺突（S）、小包膜（E）、膜（M）和核衣壳（N）的四个基因外，根据所分析的毒株不同，还预测出了另外六到八种蛋白质。它们的长度在61至274个氨基酸之间。我们的方法还表明，多聚蛋白1ab、多聚蛋白1a、S、M和N是病毒来源的蛋白质，其他则是原核生物来源的。已利用其开放阅读框中存在的保守肽段对所有预测的蛋白质编码基因的推定功能进行了推测。