In Silico Structure-Based Vaccine Design

Sakshi Piplani, David Winkler, Yoshikazu Honda-Okubo, Varun Khanna, Nikolai Petrovsky

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Structure-based vaccine design (SBVD) is an important technique in computational vaccine design that uses structural information on a targeted protein to design novel vaccine candidates. This increasing ability to rapidly model structural information on proteins and antibodies has provided the scientific community with many new vaccine targets and novel opportunities for future vaccine discovery. This chapter provides a comprehensive overview of the status of in silico SBVD and discusses the current challenges and limitations. Key strategies in the field of SBVD are exemplified by a case study on design of COVID-19 vaccines targeting SARS-CoV-2 spike protein.

Original languageEnglish
Title of host publicationComputational Vaccine Design
EditorsPedro A. Reche
Place of PublicationNew York
PublisherSpringer Nature
Chapter26
Pages371-399
Number of pages29
ISBN (Electronic)9781071632390
ISBN (Print)9781071632383
DOIs
Publication statusPublished - 2023
Externally publishedYes

Publication series

NameMethods in molecular biology (Clifton, N.J.)

Keywords

  • Computer-aided vaccine design
  • COVID-19
  • De novo design
  • Focused library design
  • High-throughput virtual screening
  • Molecular docking
  • Protein modeling
  • SARS-CoV-2
  • Structure-based vaccine design
  • Target selection

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