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NERVE 2.0:通过人工智能和用户友好的网络界面推动新型增强型反向疫苗学环境的发展

NERVE 2.0: boosting the new enhanced reverse vaccinology environment via artificial intelligence and a user-friendly web interface.

作者信息

Conte Andrea, Gulmini Nicola, Costa Francesco, Cartura Matteo, Bröhl Felix, Patanè Francesco, Filippini Francesco

机构信息

Synthetic Biology and Biotechnology Unit, Department of Biology, University of Padua, Padua, Italy.

EMBL-European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridge, UK.

出版信息

BMC Bioinformatics. 2024 Dec 18;25(1):378. doi: 10.1186/s12859-024-06004-0.

Abstract

BACKGROUND

Vaccines development in this millennium started by the milestone work on Neisseria meningitidis B, reporting the invention of Reverse Vaccinology (RV), which allows to identify vaccine candidates (VCs) by screening bacterial pathogens genome or proteome through computational analyses. When NERVE (New Enhanced RV Environment), the first RV software integrating tools to perform the selection of VCs, was released, it prompted further development in the field. However, the problem-solving potential of most, if not all, RV programs is still largely unexploited by experimental vaccinologists that impaired by somehow difficult interfaces, requiring bioinformatic skills.

RESULTS

We report here on the development and release of NERVE 2.0 (available at: https://nerve-bio.org ) which keeps the original integrative and modular approach of NERVE, while showing higher predictive performance than its previous version and other web-RV programs (Vaxign and Vaxijen). We renewed some of its modules and added innovative ones, such as Loop-Razor, to recover fragments of promising vaccine candidates or Epitope Prediction for the epitope prediction binding affinities and population coverage. Along with two newly built AI (Artificial Intelligence)-based models: ESPAAN and Virulent. To improve user-friendliness, NERVE was shifted to a tutored, web-based interface, with a noSQL-database to consent the user to submit, obtain and retrieve analysis results at any moment.

CONCLUSIONS

With its redesigned and updated environment, NERVE 2.0 allows customisable and refinable bacterial protein vaccine analyses to all different kinds of users.

摘要

背景

本世纪疫苗研发始于针对B群脑膜炎奈瑟菌的里程碑式研究,该研究报道了反向疫苗学(RV)的发明,即通过计算分析筛选细菌病原体基因组或蛋白质组来鉴定候选疫苗(VC)。当首个集成了用于筛选VC工具的RV软件NERVE(新增强型RV环境)发布时,推动了该领域的进一步发展。然而,大多数(即便不是全部)RV程序解决问题的潜力仍未被实验疫苗学家充分利用,因为这些程序界面有些复杂,需要生物信息学技能。

结果

我们在此报告NERVE 2.0(可在https://nerve-bio.org获取)的开发与发布情况。NERVE 2.0保留了NERVE原有的集成式和模块化方法,同时其预测性能高于前一版本及其他网络RV程序(Vaxign和Vaxijen)。我们更新了一些模块并添加了创新模块,如Loop-Razor,用于找回有前景的候选疫苗片段,或进行表位预测以分析表位结合亲和力和群体覆盖率。此外还新增了两个基于人工智能(AI)的模型:ESPAAN和Virulent。为提高用户友好性,NERVE转变为一个有指导的基于网络的界面,并设有一个非关系型数据库,允许用户随时提交、获取和检索分析结果。

结论

凭借其重新设计和更新的环境,NERVE 2.0允许各类用户进行可定制和可优化的细菌蛋白疫苗分析。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1f42/11654298/5999b70860a7/12859_2024_6004_Fig1_HTML.jpg

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