Heterogeneous Network Model to Identify Potential Associations Between Plasmodium vivax and Human Proteins

Abstract

Integration of multiple sources and data levels provides a great insight into the complex associations between human and malaria systems. In this study, a meta-analysis framework was developed based on a heterogeneous network model for integrating human-malaria protein similarities, a human protein interaction network, and a Plasmodium vivax protein interaction network. An iterative network propagation was performed on the heterogeneous network until we obtained stabilized weights. The association scores were calculated for qualifying a novel potential human-malaria protein association. This method provided a better performance compared to random experiments. After that, the stabilized network was clustered into association modules. The potential association candidates were then thoroughly analyzed by statistical enrichment analysis with protein complexes and known drug targets. The most promising target proteins were the succinate dehydrogenase protein complex in the human citrate (TCA) cycle pathway and the nicotinic acetylcholine receptor in the human central nervous system. Promising associations and potential drug targets were also provided for further studies and designs in therapeutic approaches for malaria at a systematic level. In conclusion, this method is efficient to identify new human-malaria protein associations and can be generalized to infer other types of association studies to further advance biomedical science.

Prediction of Human-Plasmodium vivaxProtein Associations From Heterogeneous Network Structures Based on Machine-Learning Approach

“…[14][15][16][17] In Plasmodium, several studies have investigated the PPI networks with the aim of revealing many important aspects of protein interactions. 10,[18][19][20][21][22][23][24] Most studies of PPI networks have applied the calculation of degree and centralities, focusing on a single organism in their analyses. In addition, PPI networks have also been used to study the associations between proteins and diseases 14,[25][26][27] and host-parasite protein associations.…”

“…In addition, PPI networks have also been used to study the associations between proteins and diseases 14,[25][26][27] and host-parasite protein associations. 10,18,19,24,28 Saha et al 24 investigated the characteristics of a host-pathogen protein interaction network based on interconnectivity and centrality properties. They analyzed the significance of central, peripheral, hub and non-hub protein nodes in the infection process of malaria.…”

Meta-Path Based Gene Ontology Profiles for Predicting Drug-Disease Associations

“…With drug-drug similarities based on chemical structures and disease-disease similarities based on disease phenotypes, Wang et al constructed a three-layer heterogeneous network model (TL_HGBI) by integrating drug target information to infer new drug-disease associations [6]. The heterogeneous network model was also applied to infer parasite-host protein associations and identify potential drug targets [7]. Luo et al inferred missing links between drugs and diseases on a network of drug and disease similarities using a bi-random walk method (MBiRW) [8].…”

Hybrid Deep Learning Based on a Heterogeneous Network Profile for Functional Annotations of Plasmodium falciparum Genes

“…Genetic data alone are often not enough to provide information for functional annotations. Instead of using only genetic data, therefore, other information, such as associations and interactions between proteins, can be used to identify proteins in large-scale multiple connection views, which assist in inferring the functions of uncharacterized proteins [ 16 , 17 ], associations of proteins and drugs [ 18 , 19 ], and associations among diseases [ 20 ]. This knowledge potentially helps to reveal novel therapeutic approaches to treating malaria.…”

“…This knowledge potentially helps to reveal novel therapeutic approaches to treating malaria. A heterogeneous network—that is, a network connecting two or more different types of networks—has been applied in several studies [ 16 , 21 , 22 ]. Suratanee et al [ 16 ] used a network propagation algorithm on a heterogeneous network to find associations between Plasmodium vivax and human proteins.…”