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A focused small-molecule screen identifies 14 compounds with distinct effects on Toxoplasma gondii.

ABSTRACT: Toxoplasma gondii is a globally ubiquitous pathogen that can cause severe disease in immunocompromised humans and the developing fetus. Given the proven role of Toxoplasma-secreted kinases in the interaction of Toxoplasma with its host cell, identification of novel kinase inhibitors could precipitate the development of new anti-Toxoplasma drugs and define new pathways important for parasite survival. We selected a small (n = 527) but diverse set of putative kinase inhibitors and screened them for effects on the growth of Toxoplasma in vitro. We identified and validated 14 noncytotoxic compounds, all of which had 50% effective concentrations in the nanomolar to micromolar range. We further characterized eight of these compounds, four inhibitors and four enhancers, by determining their effects on parasite motility, invasion, and the likely cellular target (parasite or host cell). Only two compounds had an effect on parasite motility and invasion. All the inhibitors appeared to target the parasite, and interestingly, two of the enhancers appeared to rather target the host cell, suggesting modulation of host cell pathways beneficial for parasite growth. For the four inhibitors, we also tested their efficacy in a mouse model, where one compound proved potent. Overall, these 14 compounds represent a new and diverse set of small molecules that are likely targeting distinct parasite and host cell pathways. Future work will aim to characterize their molecular targets in both the host and parasite.

SUBMITTER: Kamau ET

PROVIDER: S-EPMC3486605 | biostudies-literature | 2012 Nov

REPOSITORIES: biostudies-literature

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A focused small-molecule screen identifies 14 compounds with distinct effects on Toxoplasma gondii.

Kamau Edwin T ET Srinivasan Ananth R AR Brown Mark J MJ Fair Matthew G MG Caraher Erin J EJ Boyle Jon P JP

Antimicrobial agents and chemotherapy 20120820 11

Toxoplasma gondii is a globally ubiquitous pathogen that can cause severe disease in immunocompromised humans and the developing fetus. Given the proven role of Toxoplasma-secreted kinases in the interaction of Toxoplasma with its host cell, identification of novel kinase inhibitors could precipitate the development of new anti-Toxoplasma drugs and define new pathways important for parasite survival. We selected a small (n = 527) but diverse set of putative kinase inhibitors and screened them fo ...[more]

PMID: 22908155

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Project description:The urgent need to develop new antimicrobial therapies has spawned the development of repurposing screens in which well-studied drugs and other types of compounds are tested for potential off-label uses. As a proof-of-principle screen to identify compounds effective against Toxoplasma gondii, we screened a collection of 1,120 compounds for the ability to significantly reduce Toxoplasma replication. A total of 94 compounds blocked parasite replication with 50% inhibitory concentrations of <5 µM. A significant number of these compounds are established inhibitors of dopamine or estrogen signaling. Follow-up experiments with the dopamine receptor inhibitor pimozide revealed that the drug impacted both parasite invasion and replication but did so independently of inhibition of dopamine or other neurotransmitter receptor signaling. Tamoxifen, which is an established inhibitor of the estrogen receptor, also reduced parasite invasion and replication. Even though Toxoplasma can activate the estrogen receptor, tamoxifen inhibits parasite growth independently of this transcription factor. Tamoxifen is also a potent inducer of autophagy, and we find that the drug stimulates recruitment of the autophagy marker light chain 3-green fluorescent protein onto the membrane of the vacuolar compartment in which the parasite resides and replicates. In contrast to other antiparasitic drugs, including pimozide, tamoxifen treatment of infected cells leads to a time-dependent elimination of intracellular parasites. Taken together, these data suggest that tamoxifen restricts Toxoplasma growth by inducing xenophagy or autophagic destruction of this obligate intracellular parasite. IMPORTANCE There is an urgent need to develop new therapies to treat microbial infections, and the repurposing of well-characterized compounds is emerging as one approach to achieving this goal. Using the protozoan parasite Toxoplasma gondii, we screened a library of 1,120 compounds and identified several compounds with significant antiparasitic activities. Among these were pimozide and tamoxifen, which are well-characterized drugs prescribed to treat patients with psychiatric disorders and breast cancer, respectively. The mechanisms by which these compounds target these disorders are known, but we show here that these drugs kill Toxoplasma through novel pathways, highlighting the potential utility of off-target effects in the treatment of infectious diseases.

Project description:Scientists rely on high-throughput screening tools to identify promising small-molecule compounds for the development of biochemical probes and drugs. This study focuses on the identification of promiscuous bioactive compounds, which are compounds that appear active in many high-throughput screening experiments against diverse targets but are often false-positives which may not be easily developed into successful probes. These compounds can exhibit bioactivity due to nonspecific, intractable mechanisms of action and/or by interference with specific assay technology readouts. Such "frequent hitters" are now commonly identified using substructure filters, including pan assay interference compounds (PAINS). Herein, we show that mechanistic modeling of small-molecule reactivity using deep learning can improve upon PAINS filters when modeling promiscuous bioactivity in PubChem assays. Without training on high-throughput screening data, a deep learning model of small-molecule reactivity achieves a sensitivity and specificity of 18.5% and 95.5%, respectively, in identifying promiscuous bioactive compounds. This performance is similar to PAINS filters, which achieve a sensitivity of 20.3% at the same specificity. Importantly, such reactivity modeling is complementary to PAINS filters. When PAINS filters and reactivity models are combined, the resulting model outperforms either method alone, achieving a sensitivity of 24% at the same specificity. However, as a probabilistic model, the sensitivity and specificity of the deep learning model can be tuned by adjusting the threshold. Moreover, for a subset of PAINS filters, this reactivity model can help discriminate between promiscuous and nonpromiscuous bioactive compounds even among compounds matching those filters. Critically, the reactivity model provides mechanistic hypotheses for assay interference by predicting the precise atoms involved in compound reactivity. Overall, our analysis suggests that deep learning approaches to modeling promiscuous compound bioactivity may provide a complementary approach to current methods for identifying promiscuous compounds.

Dataset Information

A focused small-molecule screen identifies 14 compounds with distinct effects on Toxoplasma gondii.

Publications

A focused small-molecule screen identifies 14 compounds with distinct effects on Toxoplasma gondii.

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