Kaur Ekjot, Acharya Vishal
Artificial Intelligence for Computational Biology (AICoB) Lab, Biotechnology Division, CSIR-Institute of Himalayan Bioresource Technology (CSIR-IHBT), Palampur, Himachal Pradesh, India.
Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India.
Methods Mol Biol. 2025;2927:115-126. doi: 10.1007/978-1-0716-4546-8_6.
The realm of host-pathogen interactions (HPIs) spans a diverse spectrum of biological occurrences. Within this domain, hosts are represented by both humans and plants, while pathogens encompass a variety of agents, such as viruses, fungi, and bacteria. These interactions serve as foundational elements in the fields of immunology, microbiology, pathology, and medicine. They hold a central role in unveiling the intricate workings of pathogen invasion, host defense mechanisms, and the formulation of strategies for disease prevention and treatment. Computational approaches have emerged as potent tools for studying HPIs, especially in the case of human-virus protein-protein interactions (Hu-Vir PPI), enabling researchers to systematically explore how viruses invade and manipulate host cellular processes. This chapter serves as a comprehensive guide to the computational methods employed for the analysis of Hu-Vir PPI, offering insight into their utility and application.
宿主-病原体相互作用（HPI）的领域涵盖了各种各样的生物学现象。在这个领域中，宿主包括人类和植物，而病原体则涵盖多种病原体，如病毒、真菌和细菌。这些相互作用是免疫学、微生物学、病理学和医学领域的基础要素。它们在揭示病原体入侵的复杂机制、宿主防御机制以及疾病预防和治疗策略的制定方面起着核心作用。计算方法已成为研究HPI的有力工具，特别是在人类-病毒蛋白质-蛋白质相互作用（Hu-Vir PPI）方面，使研究人员能够系统地探索病毒如何入侵和操纵宿主细胞过程。本章作为分析Hu-Vir PPI所采用的计算方法的全面指南，深入介绍了它们的实用性和应用。
