Current Trends in Computational Strategies for Vaccine Development

Dear Colleagues,

Vaccine development is a complex and time-consuming process that involves many stages, from identifying potential vaccine targets to testing and manufacturing the final product. In recent years, computational strategies have emerged as a powerful tool for accelerating the vaccine development process. Computational strategies for vaccine development can help to identify potential vaccine targets at a much faster pace, aid in the design and optimization of vaccine candidates, and predict and analyze the immune response to specific antigens. Researchers can use molecular modeling techniques to create three-dimensional models of vaccine antigens and adjuvants and use these models to design more effective and stable vaccine formulations. Machine learning and artificial intelligence algorithms can also be used to analyze large datasets of immune response data and identify patterns that can help to optimize vaccine design. Overall, the use of computational strategies for vaccine development has the potential to greatly improve the speed, efficiency, and success rate of vaccine development and ultimately improve public health outcomes.

This Special Issue aims to provide a comprehensive overview of the various computational strategies used in vaccine development. This includes but is not limited to topics such as:

• In silico prediction of vaccine targets;
• Structural modeling of vaccine antigens and adjuvants;
• Immunoinformatics approaches to antigen design and selection;
• Machine learning and artificial intelligence for vaccine design and optimization;
• Simulation and modeling of vaccine-induced immune responses;
• Computational approaches to vaccine safety and efficacy evaluation.

Dr. Abhinav Kaushik
Dr. Deepika Rai
Dr. José Manuel Pérez De La Lastra
Guest Editors

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• vaccines
• epitope
• structural vaccinology
• reverse vaccinology immunoinformatics
• bioinformatics