Prediction of protein-protein interaction network in malaria biomarkers and implication as therapeutic target

Heikal, Muhammad Fikri and Putra, Wira Eka and Sustiprijatno, S. and Permatasari, Galuh Wening and Tirto Sari, Dewi Ratih and Ningsih, Febby Nurdiya and Susanto, Hendra and Hidayatullah, Arief and Yusuf, Alyana Mahdavikia Rosyada and Arizona, Aliyya Suci and Shuib, Adawiyah Suriza (2021) Prediction of protein-protein interaction network in malaria biomarkers and implication as therapeutic target. Malaysian Journal of Biochemistry and Molecular Biology, 24 (2). pp. 61-67. ISSN 15112616,

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Malaria is a major global health concern, claiming thousands of lives each year. Numerous proteins are involved in the parasitic infection of the host body by malaria. Several of these proteins, including mucin 13 protein (MUC13), Plasmodium falciparum lactate dehydrogenase (PfLDH), plasmodium glutamate dehydrogenase (GDH), and liver-derived glutamate dehydrogenase (GDH), have been implicated as biomarkers. These proteins interact with other proteins throughout the liver and blood stages of the plasmodium life cycle. We used computational analysis to uncover protein-protein interactions (PPIs) that might be used to discover new therapeutic targets. Bioinformatics analysis utilizing the stringDB webserver was used to gather PPIs data. The PPIs data set contains the interaction of biomarkers with many proteins as well as the false discovery rate (FDR) for each biological process. Data is provided in the form of an interactive graphic and a table of PPIs. MUC13, PfLDH, Plasmodium GDH, and LISP2 were co-expressed with several proteins in 12 biological processes. In the homeostatic process, the interaction of MUC13 with MUC4, MUC17, and MUC6 has the lowest FDR value of 0.0299. Furthermore, we relate our findings to previous research and predict the implications of these proteins' inhibition. © 2021 Malaysian Society for Biochemistry and Molecular Biology. All rights reserved.

Item Type: Article
Funders: Universitas Negeri Malang [Grant No.: 5.3.517/UN32.14.1/LT/2021]
Uncontrolled Keywords: Bioinformatics analysis; Biomarker; Drug target; Malaria; PPI
Subjects: Q Science > QH Natural history > QH301 Biology
Divisions: Faculty of Science > Institute of Biological Sciences
Depositing User: Ms Zaharah Ramly
Date Deposited: 06 Dec 2023 10:49
Last Modified: 06 Dec 2023 10:49

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