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Current progress on the computational methods for prediction of host-pathogen protein-protein interaction in the Ganoderma boninense-oil palm pathosystem


Citation

Khairi, Mohamad Hazwan Fikri and Nor Muhammad, Nor Azlan and Bunawan, Hamidun and Mohd Daud, Kauthar and Sulaiman, Suhaila and Mohamed-Hussein, Zeti Azura and Wong, Mui Yun and Ramzi, Ahmad Bazli (2024) Current progress on the computational methods for prediction of host-pathogen protein-protein interaction in the Ganoderma boninense-oil palm pathosystem. Physiological and Molecular Plant Pathology, 129. art. no. 102201. pp. 1-11. ISSN 0885-5765; eISSN: 1096-1178

Abstract

Ganoderma boninense is a major pathogen for basal stem rot disease that can depolymerize lignocellulosic materials of the oil palm plant by secreting the cell wall-degrading enzymes. The management of this disease is complicated by the asymptomatic phase mediated by the protein-protein interaction (PPI) between the pathogen’s effector and plant proteins. There is a lack of network-wide studies on the PPI to elucidate the action of effectors on plant pathways from a systemic perspective as the computational prediction of host-pathogen PPI (HP PPI) is focused on human interaction. Hence, this minireview explores the current computational methods for predicting HP PPI and proposes an approach to predict PPI between G. boninense and oil palm.


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Additional Metadata

Item Type: Article
Divisions: Faculty of Agriculture
Institute of Plantation Studies
DOI Number: https://doi.org/10.1016/j.pmpp.2023.102201
Publisher: Academic Press
Keywords: Oil palm; Ganoderma boninense; Host-pathogen interaction; Protein-protein interaction; Computational biology; Machine learning
Depositing User: Ms. Che Wa Zakaria
Date Deposited: 10 Mar 2025 07:51
Last Modified: 10 Mar 2025 07:51
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1016/j.pmpp.2023.102201
URI: http://psasir.upm.edu.my/id/eprint/115289
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