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Vaxi-DL: An Artificial Intelligence-Enabled Platform for Vaccine Development

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Computational Vaccine Design

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2673))

Abstract

Vaccine development is a complex and long process. It involves several steps, including computational studies, experimental analyses, animal model system studies, and clinical trials. This process can be accelerated by using in silico antigen screening to identify potential vaccine candidates. In this chapter, we describe a deep learning-based technique which utilizes 18 biological and 9154 physicochemical properties of proteins for finding potential vaccine candidates. Using this technique, a new web-based system, named Vaxi-DL, was developed which helped in finding new vaccine candidates from bacteria, protozoa, viruses, and fungi. Vaxi-DL is available at: https://vac.kamalrawal.in/vaxidl/.

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Acknowledgments

The computational facility used in this work was supported by Robert J. Kleberg Jr. and Helen C. Kleberg Foundation. We are also thankful to Amity University and ICMR [BMI/12(66)/2021 2021-6442] for the support provided during the conduct of this study. Preeti P has received financial support from SERB [File Number: CVD/2020/000842]. The computational facility used for hosting the server was provided by DBT, Government of India [BT/PR17252/BID/7/708/2016].

Author information

Authors and Affiliations

  1. Centre for Computational Biology and Bioinformatics, AIB, Amity University, Noida, Uttar Pradesh, India

    P. Preeti, Swarsat Kaushik Nath, Nevidita Arambam, Trapti Sharma, Priyanka Ray Choudhury, Alakto Choudhury, Vrinda Khanna & Kamal Rawal

  2. Department of Pediatrics, Division of Tropical Medicine, Baylor College of Medicine, Houston, TX, USA

    Ulrich Strych, Peter J. Hotez & Maria Elena Bottazzi

  3. Texas Children’s Hospital Center for Vaccine Development, Houston, TX, USA

    Ulrich Strych, Peter J. Hotez & Maria Elena Bottazzi

  4. Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA

    Peter J. Hotez & Maria Elena Bottazzi

  5. Department of Biology, Baylor University, Waco, TX, USA

    Peter J. Hotez & Maria Elena Bottazzi

Authors
  1. P. Preeti
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  2. Swarsat Kaushik Nath
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  3. Nevidita Arambam
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  4. Trapti Sharma
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  5. Priyanka Ray Choudhury
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  6. Alakto Choudhury
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  7. Vrinda Khanna
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  8. Ulrich Strych
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  9. Peter J. Hotez
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  10. Maria Elena Bottazzi
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  11. Kamal Rawal
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Corresponding author

Correspondence to Kamal Rawal .

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Editors and Affiliations

  1. School of Medicine, Department of Immunology, Complutense University of Madrid, Madrid, Spain

    Pedro A. Reche

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Preeti, P. et al. (2023). Vaxi-DL: An Artificial Intelligence-Enabled Platform for Vaccine Development. In: Reche, P.A. (eds) Computational Vaccine Design. Methods in Molecular Biology, vol 2673. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3239-0_21

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  • DOI: https://doi.org/10.1007/978-1-0716-3239-0_21

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-3238-3

  • Online ISBN: 978-1-0716-3239-0

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