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

Area of Science:

• Computational biology
• Vaccine development
• Bioinformatics

Background:

• Reverse Vaccinology (RV) revolutionized vaccine development by enabling computational screening of pathogens for vaccine candidates (VCs).
• The initial NERVE (New Enhanced RV Environment) software facilitated VC selection but had usability challenges for experimental vaccinologists.
• Existing RV programs often require significant bioinformatics expertise, limiting their widespread adoption.

Purpose of the Study:

• To introduce NERVE 2.0, an improved web-based platform for bacterial vaccine candidate analysis.
• To enhance the predictive performance and user-friendliness of RV software.
• To integrate advanced computational tools, including AI-based models, for more effective VC identification.

Main Methods:

• Development of NERVE 2.0 with an integrative and modular approach.
• Incorporation of new modules like Loop-Razor for fragment recovery and Epitope Prediction for binding affinities.
• Integration of two AI-based models: ESPAAN and Virulent.
• Transition to a tutored, web-based interface with a noSQL-database for enhanced user experience.

Main Results:

• NERVE 2.0 demonstrates higher predictive performance compared to its predecessor and other web-RV programs (Vaxign, Vaxijen).
• The new interface significantly improves user-friendliness, reducing the need for extensive bioinformatics skills.
• The platform enables efficient submission, retrieval, and analysis of vaccine candidate data.

Conclusions:

• NERVE 2.0 provides a customizable and refined environment for bacterial protein vaccine analysis.
• The updated software empowers a broader range of users, including experimental vaccinologists, in the vaccine design process.
• This enhanced RV tool facilitates more efficient and accessible vaccine development.