Leveraging computer-aided design and artificial intelligence to develop a next-generation multi-epitope tuberculosis vaccine candidate

Leveraging computer-aided design and artificial intelligence to develop a next-generation multi-epitope tuberculosis vaccine candidate

Background: Tuberculosis (TB) remains a global public health challenge. The existing Bacillus Calmette–Guérin vaccine has limited efficacy in preventing adult pulmonary TB, necessitating the development of new vaccines with improved protective effects. Methods: Computer-aided design and artificial i...

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Bibliographic Details
Main Authors: Li Zhuang, Awais Ali, Ling Yang, Zhaoyang Ye, Linsheng Li, Ruizi Ni, Yajing An, Syed Luqman Ali, Wenping Gong
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Infectious Medicine
Subjects:
Tuberculosis
Multi-epitope vaccine
Computer-aided design
Artificial intelligence
Immunogenicity
Online Access:http://www.sciencedirect.com/science/article/pii/S2772431X24000625
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