Dataset Information

Antimalarial drug targets in Plasmodium falciparum predicted by stage-specific metabolic network analysis.

ABSTRACT:

Background

Despite enormous efforts to combat malaria the disease still afflicts up to half a billion people each year of which more than one million die. Currently no approved vaccine is available and resistances to antimalarials are widely spread. Hence, new antimalarial drugs are urgently needed.

Results

Here, we present a computational analysis of the metabolism of Plasmodium falciparum, the deadliest malaria pathogen. We assembled a compartmentalized metabolic model and predicted life cycle stage specific metabolism with the help of a flux balance approach that integrates gene expression data. Predicted metabolite exchanges between parasite and host were found to be in good accordance with experimental findings when the parasite's metabolic network was embedded into that of its host (erythrocyte). Knock-out simulations identified 307 indispensable metabolic reactions within the parasite. 35 out of 57 experimentally demonstrated essential enzymes were recovered and another 16 enzymes, if additionally the assumption was made that nutrient uptake from the host cell is limited and all reactions catalyzed by the inhibited enzyme are blocked. This predicted set of putative drug targets, shown to be enriched with true targets by a factor of at least 2.75, was further analyzed with respect to homology to human enzymes, functional similarity to therapeutic targets in other organisms and their predicted potency for prophylaxis and disease treatment.

Conclusions

The results suggest that the set of essential enzymes predicted by our flux balance approach represents a promising starting point for further drug development.

SUBMITTER: Huthmacher C

PROVIDER: S-EPMC2941759 | biostudies-literature | 2010 Aug

REPOSITORIES: biostudies-literature

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Publications

Antimalarial drug targets in Plasmodium falciparum predicted by stage-specific metabolic network analysis.

Huthmacher Carola C Hoppe Andreas A Bulik Sascha S Holzhütter Hermann-Georg HG

BMC systems biology 20100831

<h4>Background</h4>Despite enormous efforts to combat malaria the disease still afflicts up to half a billion people each year of which more than one million die. Currently no approved vaccine is available and resistances to antimalarials are widely spread. Hence, new antimalarial drugs are urgently needed.<h4>Results</h4>Here, we present a computational analysis of the metabolism of Plasmodium falciparum, the deadliest malaria pathogen. We assembled a compartmentalized metabolic model and predi ...[more]

PMID: 20807400

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Project description:Malaria, especially Plasmodium falciparum infection, remains an enormous problem, and its treatment and control are seriously challenged by drug resistance. New antimalarial drugs are needed. To characterize the Medicines for Malaria Venture pipeline of antimalarials under development, we assessed the ex vivo drug susceptibilities to 19 compounds targeting or potentially impacted by mutations in P. falciparum ABC transporter I family member 1, acetyl-CoA synthetase, cytochrome b, dihydroorotate dehydrogenase, elongation factor 2, lysyl-tRNA synthetase, phenylalanyl-tRNA synthetase, plasmepsin X, prodrug activation and resistance esterase, and V-type H+ ATPase of 998 fresh P. falciparum clinical isolates collected in eastern Uganda from 2015 to 2022. Drug susceptibilities were assessed by 72-h growth inhibition (half-maximum inhibitory concentration [IC50]) assays using SYBR green. Field isolates were highly susceptible to lead antimalarials, with low- to midnanomolar median IC50s, near values previously reported for laboratory strains, for all tested compounds. However, outliers with decreased susceptibilities were identified. Positive correlations between IC50 results were seen for compounds with shared targets. We sequenced genes encoding presumed targets to characterize sequence diversity, search for polymorphisms previously selected with in vitro drug pressure, and determine genotype-phenotype associations. We identified many polymorphisms in target genes, generally in <10% of isolates, but none were those previously selected in vitro with drug pressure, and none were associated with significantly decreased ex vivo drug susceptibility. Overall, Ugandan P. falciparum isolates were highly susceptible to 19 compounds under development as next-generation antimalarials, consistent with a lack of preexisting or novel resistance-conferring mutations in circulating Ugandan parasites. IMPORTANCE Drug resistance necessitates the development of new antimalarial drugs. It is important to assess the activities of compounds under development against parasites now causing disease in Africa, where most malaria cases occur, and to determine if mutations in these parasites may limit the efficacies of new agents. We found that African isolates were generally highly susceptible to the 19 studied lead antimalarials. Sequencing of the presumed drug targets identified multiple mutations in these genes, but these mutations were generally not associated with decreased antimalarial activity. These results offer confidence that the activities of the tested antimalarial compounds now under development will not be limited by preexisting resistance-mediating mutations in African malaria parasites.

Project description:BackgroundTherapeutic efficacy studies in uncomplicated Plasmodium falciparum malaria are confounded by new infections, which constitute competing risk events since they can potentially preclude/pre-empt the detection of subsequent recrudescence of persistent, sub-microscopic primary infections.MethodsAntimalarial studies typically report the risk of recrudescence derived using the Kaplan-Meier (K-M) method, which considers new infections acquired during the follow-up period as censored. Cumulative Incidence Function (CIF) provides an alternative approach for handling new infections, which accounts for them as a competing risk event. The complement of the estimate derived using the K-M method (1 minus K-M), and the CIF were used to derive the risk of recrudescence at the end of the follow-up period using data from studies collated in the WorldWide Antimalarial Resistance Network data repository. Absolute differences in the failure estimates derived using these two methods were quantified. In comparative studies, the equality of two K-M curves was assessed using the log-rank test, and the equality of CIFs using Gray's k-sample test (both at 5% level of significance). Two different regression modelling strategies for recrudescence were considered: cause-specific Cox model and Fine and Gray's sub-distributional hazard model.ResultsData were available from 92 studies (233 treatment arms, 31,379 patients) conducted between 1996 and 2014. At the end of follow-up, the median absolute overestimation in the estimated risk of cumulative recrudescence by using 1 minus K-M approach was 0.04% (interquartile range (IQR): 0.00-0.27%, Range: 0.00-3.60%). The overestimation was correlated positively with the proportion of patients with recrudescence [Pearson's correlation coefficient (?): 0.38, 95% Confidence Interval (CI) 0.30-0.46] or new infection [?: 0.43; 95% CI 0.35-0.54]. In three study arms, the point estimates of failure were greater than 10% (the WHO threshold for withdrawing antimalarials) when the K-M method was used, but remained below 10% when using the CIF approach, but the 95% confidence interval included this threshold.ConclusionsThe 1 minus K-M method resulted in a marginal overestimation of recrudescence that became increasingly pronounced as antimalarial efficacy declined, particularly when the observed proportion of new infection was high. The CIF approach provides an alternative approach for derivation of failure estimates in antimalarial trials, particularly in high transmission settings.

Project description:BackgroundInadequate treatment practices with antimalarials are considered major contributors to Plasmodium falciparum resistance to chloroquine, pyrimethamine and sulfadoxine. The longitudinal survey conducted in Dielmo, a rural Senegalese community, offers a unique frame to explore the impact of strictly controlled and quantified antimalarial use for diagnosed malaria on drug resistance.Methodology/principal findingsWe conducted on a yearly basis a retrospective survey over a ten-year period that included two successive treatment policies, namely quinine during 1990-1994, and chloroquine (CQ) and sulfadoxine/pyrimethamine (SP) as first and second line treatments, respectively, during 1995-1999. Molecular beacon-based genotyping, gene sequencing and microsatellite analysis showed a low prevalence of Pfcrt and Pfdhfr-ts resistance alleles of Southeast Asian origin by the end of 1994 and their effective dissemination within one year of CQ and SP implementation. The Pfcrt resistant allele rose from 9% to 46% prevalence during the first year of CQ reintroduction, i.e., after a mean of 1.66 CQ treatment courses/person/year. The Pfdhfr-ts triple mutant rose from 0% to 20% by end 1996, after a mean of 0.35 SP treatment courses/person in a 16-month period. Both resistance alleles were observed at a younger age than all other alleles. Their spreading was associated with enhanced in vitro resistance and rapidly translated in an increased incidence of clinical malaria episodes during the early post-treatment period.Conclusion/significanceIn such a highly endemic setting, selection of drug-resistant parasites took a single year after drug implementation, resulting in a rapid progression of the incidence of clinical malaria during the early post-treatment period. Controlled antimalarial use at the community level did not prevent dissemination of resistance haplotypes. This data pleads against reintroduction of CQ in places where resistant allele frequency has dropped to a very low level after CQ use has been discontinued, unless drastic measures are put in place to prevent selection and spreading of mutants during the post-treatment period.

Dataset Information

Antimalarial drug targets in Plasmodium falciparum predicted by stage-specific metabolic network analysis.

Background

Results

Conclusions

Publications

Antimalarial drug targets in Plasmodium falciparum predicted by stage-specific metabolic network analysis.

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