Dataset Information

In Silico Knockout Screening of Plasmodium falciparum Reactions and Prediction of Novel Essential Reactions by Analysing the Metabolic Network.

ABSTRACT: Malaria is an infectious disease that affects close to half a million individuals every year and Plasmodium falciparum is a major cause of malaria. The treatment of this disease could be done effectively if the essential enzymes of this parasite are specifically targeted. Nevertheless, the development of the parasite in resisting existing drugs now makes discovering new drugs a core responsibility. In this study, a novel computational model that makes the prediction of new and validated antimalarial drug target cheaper, easier, and faster has been developed. We have identified new essential reactions as potential targets for drugs in the metabolic network of the parasite. Among the top seven (7) predicted essential reactions, four (4) have been previously identified in earlier studies with biological evidence and one (1) has been with computational evidence. The results from our study were compared with an extensive list of seventy-seven (77) essential reactions with biological evidence from a previous study. We present a list of thirty-one (31) potential candidates for drug targets in Plasmodium falciparum which includes twenty-four (24) new potential candidates for drug targets.

SUBMITTER: Oyelade J

PROVIDER: S-EPMC5896307 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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In Silico Knockout Screening of <i>Plasmodium falciparum</i> Reactions and Prediction of Novel Essential Reactions by Analysing the Metabolic Network.

Oyelade Jelili J Isewon Itunuoluwa I Uwoghiren Efosa E Aromolaran Olufemi O Oladipupo Olufunke O

BioMed research international 20180329

Malaria is an infectious disease that affects close to half a million individuals every year and <i>Plasmodium falciparum</i> is a major cause of malaria. The treatment of this disease could be done effectively if the essential enzymes of this parasite are specifically targeted. Nevertheless, the development of the parasite in resisting existing drugs now makes discovering new drugs a core responsibility. In this study, a novel computational model that makes the prediction of new and validated a ...[more]

PMID: 29789805

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Project description:BackgroundEukaryotic cellular machineries are intricately regulated by several molecular mechanisms involving transcriptional control, post-translational control and post-translational modifications of proteins (PTMs). Reversible protein phosphorylation/dephosphorylation process, which involves kinases as well as phosphatases, represents an important regulatory mechanism for diverse pathways and systems in all organisms including human malaria parasite, Plasmodium falciparum. Earlier analysis on P. falciparum protein-phosphatome revealed presence of 34 phosphatases in Plasmodium genome. Recently, we re-analysed P. falciparum phosphatome aimed at identifying parasite specific phosphatases.ResultsPlasmodium database (PlasmoDB 9.2) search, combined with PFAM and CDD searches, revealed 67 candidate phosphatases in P. falciparum. While this number is far less than the number of phosphatases present in Homo sapiens, it is almost the same as in other Plasmodium species. These Plasmodium phosphatase proteins were classified into 13 super families based on NCBI CDD search. Analysis of proteins expression profiles of the 67 phosphatases revealed that 44 phosphatases are expressed in both schizont as well as gametocytes stages. Fourteen phosphatases are common in schizont, ring and trophozoite stages, four phosphatases are restricted to gametocytes, whereas another three restricted to schizont stage. The phylogenetic trees for each of the known phosphatase super families reveal a considerable phylogenetic closeness amongst apicomplexan organisms and a considerable phylogenetic distance with other eukaryotic model organisms included in the study. The GO assignments and predicted interaction partners of the parasite phosphatases indicate its important role in diverse cellular processes.ConclusionIn the study presented here, we reviewed the P. falciparum phosphatome to show presence of 67 candidate phosphatases in P. falciparum genomes/proteomes. Intriguingly, amongst these phosphatases, we could identify six Plasmodium specific phosphatases and 33 putative phosphatases that do not have human orthologs, thereby suggesting that these phosphatases have the potential to be explored as novel antimalarial drug targets.

Project description:BackgroundWith the sequence of the Plasmodium falciparum genome and several global mRNA and protein life cycle expression profiling projects now completed, elucidating the underlying networks of transcriptional control important for the progression of the parasite life cycle is highly pertinent to the development of new anti-malarials. To date, relatively little is known regarding the specific mechanisms the parasite employs to regulate gene expression at the mRNA level, with studies of the P. falciparum genome sequence having revealed few cis-regulatory elements and associated transcription factors. Although it is possible the parasite may evoke mechanisms of transcriptional control drastically different from those used by other eukaryotic organisms, the extreme AT-rich nature of P. falciparum intergenic regions (approximately 90% AT) presents significant challenges to in silico cis-regulatory element discovery.ResultsWe have developed an algorithm called Gene Enrichment Motif Searching (GEMS) that uses a hypergeometric-based scoring function and a position-weight matrix optimization routine to identify with high-confidence regulatory elements in the nucleotide-biased and repeat sequence-rich P. falciparum genome. When applied to promoter regions of genes contained within 21 co-expression gene clusters generated from P. falciparum life cycle microarray data using the semi-supervised clustering algorithm Ontology-based Pattern Identification, GEMS identified 34 putative cis-regulatory elements associated with a variety of parasite processes including sexual development, cell invasion, antigenic variation and protein biosynthesis. Among these candidates were novel motifs, as well as many of the elements for which biological experimental evidence already exists in the Plasmodium literature. To provide evidence for the biological relevance of a cell invasion-related element predicted by GEMS, reporter gene and electrophoretic mobility shift assays were conducted.ConclusionThis GEMS analysis demonstrates that in silico regulatory element discovery can be successfully applied to challenging repeat-sequence-rich, base-biased genomes such as that of P. falciparum. The fact that regulatory elements were predicted from a diverse range of functional gene clusters supports the hypothesis that cis-regulatory elements play a role in the transcriptional control of many P. falciparum biological processes. The putative regulatory elements described represent promising candidates for future biological investigation into the underlying transcriptional control mechanisms of gene regulation in malaria parasites.

Dataset Information

In Silico Knockout Screening of Plasmodium falciparum Reactions and Prediction of Novel Essential Reactions by Analysing the Metabolic Network.

Publications

In Silico Knockout Screening of <i>Plasmodium falciparum</i> Reactions and Prediction of Novel Essential Reactions by Analysing the Metabolic Network.

Similar Datasets

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