Dataset Information

MAIP: a web service for predicting blood-stage malaria inhibitors.

ABSTRACT: Malaria is a disease affecting hundreds of millions of people across the world, mainly in developing countries and especially in sub-Saharan Africa. It is the cause of hundreds of thousands of deaths each year and there is an ever-present need to identify and develop effective new therapies to tackle the disease and overcome increasing drug resistance. Here, we extend a previous study in which a number of partners collaborated to develop a consensus in silico model that can be used to identify novel molecules that may have antimalarial properties. The performance of machine learning methods generally improves with the number of data points available for training. One practical challenge in building large training sets is that the data are often proprietary and cannot be straightforwardly integrated. Here, this was addressed by sharing QSAR models, each built on a private data set. We describe the development of an open-source software platform for creating such models, a comprehensive evaluation of methods to create a single consensus model and a web platform called MAIP available at https://www.ebi.ac.uk/chembl/maip/ . MAIP is freely available for the wider community to make large-scale predictions of potential malaria inhibiting compounds. This project also highlights some of the practical challenges in reproducing published computational methods and the opportunities that open-source software can offer to the community.

SUBMITTER: Bosc N

PROVIDER: S-EPMC7898753 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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MAIP: a web service for predicting blood-stage malaria inhibitors.

Bosc Nicolas N Felix Eloy E Arcila Ricardo R Mendez David D Saunders Martin R MR Green Darren V S DVS Ochoada Jason J Shelat Anang A AA Martin Eric J EJ Iyer Preeti P Engkvist Ola O Verras Andreas A Duffy James J Burrows Jeremy J Gardner J Mark F JMF Leach Andrew R AR

Journal of cheminformatics 20210222 1

Malaria is a disease affecting hundreds of millions of people across the world, mainly in developing countries and especially in sub-Saharan Africa. It is the cause of hundreds of thousands of deaths each year and there is an ever-present need to identify and develop effective new therapies to tackle the disease and overcome increasing drug resistance. Here, we extend a previous study in which a number of partners collaborated to develop a consensus in silico model that can be used to identify n ...[more]

PMID: 33618772

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Project description:BackgroundSpiroindolone and pyrazoleamide antimalarial compounds target Plasmodium falciparum P-type ATPase (PfATP4) and induce disruption of intracellular Na+ homeostasis. Recently, a PfATP4 mutation was discovered that confers resistance to a pyrazoleamide while increasing sensitivity to a spiroindolone. Transcriptomic and metabolic adaptations that underlie this seemingly contradictory response of P. falciparum to sublethal concentrations of each compound were examined to understand the different cellular accommodation to PfATP4 disruptions.MethodsA genetically engineered P. falciparum Dd2 strain (Dd2A211V) carrying an Ala211Val (A211V) mutation in PfATP4 was used to identify metabolic adaptations associated with the mutation that results in decreased sensitivity to PA21A092 (a pyrazoleamide) and increased sensitivity to KAE609 (a spiroindolone). First, sublethal doses of PA21A092 and KAE609 causing substantial reduction (30-70%) in Dd2A211V parasite replication were identified. Then, at this sublethal dose of PA21A092 (or KAE609), metabolomic and transcriptomic data were collected during the first intraerythrocytic developmental cycle. Finally, the time-resolved data were integrated with a whole-genome metabolic network model of P. falciparum to characterize antimalarial-induced physiological adaptations.ResultsSublethal treatment with PA21A092 caused significant (p < 0.001) alterations in the abundances of 91 Plasmodium gene transcripts, whereas only 21 transcripts were significantly altered due to sublethal treatment with KAE609. In the metabolomic data, a substantial alteration (≥ fourfold) in the abundances of carbohydrate metabolites in the presence of either compound was found. The estimated rates of macromolecule syntheses between the two antimalarial-treated conditions were also comparable, except for the rate of lipid synthesis. A closer examination of parasite metabolism in the presence of either compound indicated statistically significant differences in enzymatic activities associated with synthesis of phosphatidylcholine, phosphatidylserine, and phosphatidylinositol.ConclusionThe results of this study suggest that malaria parasites activate protein kinases via phospholipid-dependent signalling in response to the ionic perturbation induced by the Na+ homeostasis disruptor PA21A092. Therefore, targeted disruption of phospholipid signalling in PA21A092-resistant parasites could be a means to block the emergence of resistance to PA21A092.

Project description:Spiroindolone and pyrazoleamide antimalarial compounds target Plasmodium falciparum P-type ATPase (PfATP4) and induce disruption of intra-cellular Na+ homeostasis. Recently, a PfATP4 mutation was discovered that confers resistance to a pyrazoleamide while increasing sensitivity to a spiroindolone. To understand the different cellular accommodation to PfATP4 disruptions, we examined biochemical and metabolic adaptations that underlie this seemingly contradictory response of P. falciparum to sublethal concentrations of each compound. We used a genetically engineered P. falciparum Dd2 strain (Dd2A211V) carrying an Ala211Val (A211V) mutation in PfATP4 to identify metabolic adaptations associated with the mutation that results in decreased sensitivity to PA21A092 (a pyrazoleamide) and increased sensitivity of KAE609 (a spiroindolone). We first identified sublethal doses of PA21A092 and KAE609 causing substantial reduction (30-70%) in Dd2A211V parasite replication. At this sublethal dose of PA21A092 (or KAE609), we collected metabolomic and transcriptomic data during the first intraerythrocytic developmental cycle (IDC). Finally, we integrated the time-resolved data with a whole-genome metabolic network model of P. falciparum to characterize antimalarial-induced physiological adaptations. We found that sublethal treatment with PA21A092 caused significant (p < 0.001) alterations in the abundances of 91 Plasmodium gene transcripts whereas only 21 transcripts were significantly altered due to sublethal treatment with KAE609. In the metabolomic data, we found a substantial alteration (fourfold) in the abundances of carbohydrate metabolites in the presence of either compounds. The estimated rates of macromolecule syntheses between the two antimalarial-treated conditions were also comparable, except for the rate of lipid synthesis. A closer examination of parasite metabolism in the presence of either compound indicated statistically significant differences in enzymatic activities associated with synthesis of phosphatidylcholine, phosphatidylserine, and phosphatidylinositol. Our results suggest that malaria parasites activate protein kinases via phospholipid-dependent signaling in response to the ionic perturbation induced by the Na+ homeostasis disruptor PA21A092. Therefore, we hypothesize that targeted disruption of phospholipid signaling in PA21A092-resistant parasites could be a means to block the emergence of resistance to PA21A092.

Dataset Information

MAIP: a web service for predicting blood-stage malaria inhibitors.

Publications

MAIP: a web service for predicting blood-stage malaria inhibitors.

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