Agamah, Francis E., Damena, Delesa, Skelton, Michelle, Ghansah, Anita, Mazandu, Gaston K. and Chimusa, Emile Rugamika (2021) Network-driven analysis of human–Plasmodium falciparum interactome: processes for malaria drug discovery and extracting in silico targets. Malaria Journal, 20 (1). p. 421. ISSN 1475-2875
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Abstract
The emergence and spread of malaria drug resistance have resulted in the need to understand disease mechanisms and importantly identify essential targets and potential drug candidates. Malaria infection involves the complex interaction between the host and pathogen, thus, functional interactions between human and Plasmodium falciparum is essential to obtain a holistic view of the genetic architecture of malaria. Several functional interaction studies have extended the understanding of malaria disease and integrating such datasets would provide further insights towards understanding drug resistance and/or genetic resistance/susceptibility, disease pathogenesis, and drug discovery. Methods
This study curated and analysed data including pathogen and host selective genes, host and pathogen protein sequence data, protein–protein interaction datasets, and drug data from literature and databases to perform human-host and P. falciparum network-based analysis. An integrative computational framework is presented that was developed and found to be reasonably accurate based on various evaluations, applications, and experimental evidence of outputs produced, from data-driven analysis.
Results
This approach revealed 8 hub protein targets essential for parasite and human host-directed malaria drug therapy. In a semantic similarity approach, 26 potential repurposable drugs involved in regulating host immune response to inflammatory-driven disorders and/or inhibiting residual malaria infection that can be appropriated for malaria treatment. Further analysis of host–pathogen network shortest paths enabled the prediction of immune-related biological processes and pathways subverted by P. falciparum to increase its within-host survival.
Conclusions
Host–pathogen network analysis reveals potential drug targets and biological processes and pathways subverted by P. falciparum to enhance its within malaria host survival. The results presented have implications for drug discovery and will inform experimental studies.
Item Type: | Article |
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Additional Information: | Funding information: This work was supported through the DELTAS Africa Initiative [DELGEME grant 107740/Z/15/Z]. The DELTAS Africa Initiative is an independent funding scheme of the African Academy of Sciences (AAS)’s Alliance for Accelerating Excellence in Science in Africa (AESA) and supported by the New Partnership for Africa’s Development Planning and Coordinating Agency (NEPAD Agency) with funding from the Wellcome Trust [DELGEME grant 107740/Z/15/Z] and the UK government. Also, this work was supported through the University of Cape Town, internal funding, and the National Research Foundation of South Africa for funding (NRF) [grant # RA171111285157/119056]. This work was partially funded by an LSH HealthHolland grant to the TWOC consortium, a large-scale infrastructure grant from the Dutch Organization of Scientific Research (NWO) to the Netherlands X-omics initiative (184.034.019), and a Horizon2020 research grant from the European Union to the EATRIS-Plus infrastructure project (grant agreement: No 871096). Some of the authors are supported in part by the National Institutes of Health (NIH) Common Fund under grant numbers 1U2RTW012131-01 (COBIP), U24HG006941 (H3ABioNet) and 1U01HG007459-01 (SADaCC). The content of this publication is solely the responsibility of the authors and does not necessarily represent the official views of the funders. |
Uncontrolled Keywords: | Malaria, Drug resistance, Genomics, Multi-omics, Gene ontology, Protein–protein interaction |
Subjects: | C400 Genetics |
Department: | Faculties > Health and Life Sciences > Applied Sciences |
Depositing User: | Rachel Branson |
Date Deposited: | 02 Nov 2022 15:21 |
Last Modified: | 02 Nov 2022 15:30 |
URI: | https://nrl.northumbria.ac.uk/id/eprint/50520 |
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