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计算机与病毒性疾病。针对 SARS-CoV-2(2019-nCoV,COVID-19)冠状病毒的合成疫苗和预防性肽模拟拮抗剂的设计的初步生物信息学研究。

Computers and viral diseases. Preliminary bioinformatics studies on the design of a synthetic vaccine and a preventative peptidomimetic antagonist against the SARS-CoV-2 (2019-nCoV, COVID-19) coronavirus.

机构信息

Ingine Inc., Cleveland, Ohio, USA; The Dirac Foundation, Oxfordshire, UK.

出版信息

Comput Biol Med. 2020 Apr;119:103670. doi: 10.1016/j.compbiomed.2020.103670. Epub 2020 Feb 26.

Abstract

This paper concerns study of the genome of the Wuhan Seafood Market isolate believed to represent the causative agent of the disease COVID-19. This is to find a short section or sections of viral protein sequence suitable for preliminary design proposal for a peptide synthetic vaccine and a peptidomimetic therapeutic, and to explore some design possibilities. The project was originally directed towards a use case for the Q-UEL language and its implementation in a knowledge management and automated inference system for medicine called the BioIngine, but focus here remains mostly on the virus itself. However, using Q-UEL systems to access relevant and emerging literature, and to interact with standard publically available bioinformatics tools on the Internet, did help quickly identify sequences of amino acids that are well conserved across many coronaviruses including 2019-nCoV. KRSFIEDLLFNKV was found to be particularly well conserved in this study and corresponds to the region around one of the known cleavage sites of the SARS virus that are believed to be required for virus activation for cell entry. This sequence motif and surrounding variations formed the basis for proposing a specific synthetic vaccine epitope and peptidomimetic agent. The work can, nonetheless, be described in traditional bioinformatics terms, and readily reproduced by others, albeit with the caveat that new data and research into 2019-nCoV is emerging and evolving at an explosive pace. Preliminary studies using molecular modeling and docking, and in that context the potential value of certain known herbal extracts, are also described.

摘要

本文研究了武汉海鲜市场分离株的基因组,该分离株被认为是 COVID-19 疾病的病原体。目的是找到适合初步设计肽合成疫苗和肽模拟治疗方案的病毒蛋白序列的短片段或多个短片段,并探索一些设计可能性。该项目最初针对 Q-UEL 语言及其在名为 BioIngine 的医学知识管理和自动化推理系统中的应用,但这里的重点仍然主要集中在病毒本身。然而,使用 Q-UEL 系统来获取相关和新兴文献,并与互联网上标准的公共生物信息学工具进行交互,确实有助于快速识别出许多冠状病毒(包括 2019-nCoV)中高度保守的氨基酸序列。在这项研究中,KRSFIEDLLFNKV 被发现特别保守,它对应于 SARS 病毒已知的切割位点之一的区域,据信这些切割位点对于病毒激活和进入细胞是必需的。该序列基序及其周围的变异为提出特定的合成疫苗表位和肽模拟物提供了依据。然而,这项工作可以用传统的生物信息学术语来描述,并且可以由其他人重现,尽管需要注意的是,关于 2019-nCoV 的新数据和研究正在以爆炸式的速度不断涌现和发展。本文还描述了使用分子建模和对接进行的初步研究,以及在这种情况下某些已知草药提取物的潜在价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cf9/7094376/e49fe71d38e4/gr1_lrg.jpg

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