ookluc-plasmodium-berghei-line-for-identifying-transmission-blocking

<em>Ookluc</em>: A <em>Plasmodium berghei</em> Line for Identifying Transmission-blocking Compounds

Malaria remains a world health challenge; in 2023, 263 million cases and 597,000 deaths were reported around the globe. The parasite's life cycle is ...

University of São Paulo

Malaria is a life-threatening infectious disease caused by parasites of the genus , affecting more than 200 million people worldwide every year and leading to about a half million deaths. Malaria parasites of humans have evolved resistance to all current antimalarial drugs, urging for the discovery of new effective compounds. Given that the inhibition of deoxyuridine triphosphatase of  (dUTPase) induces wrong insertions in plasmodial DNA and consequently leading the parasite to death, this enzyme is considered an attractive antimalarial drug target. Using a combi-QSAR (quantitative structure-activity relationship) approach followed by virtual screening and  experimental evaluation, we report herein the discovery of novel chemical scaffolds with  potency against asexual blood stages of both  multidrug-resistant and sensitive strains and against sporogonic development of . We developed 2D- and 3D-QSAR models using a series of nucleosides reported in the literature as dUTPase inhibitors. The best models were combined in a consensus approach and used for virtual screening of the ChemBridge database, leading to the identification of five new virtual dUTPase inhibitors. Further  testing on  multidrug-resistant (W2) and sensitive (3D7) parasites showed that compounds LabMol-144 and LabMol-146 demonstrated fair activity against both strains and presented good selectivity versus mammalian cells. In addition, LabMol-144 showed good  inhibition of  ookinete formation, demonstrating that hit-to-lead optimization based on this compound may also lead to new antimalarials with transmission blocking activity.

QSAR-Driven Design and Discovery of Novel Compounds With Antiplasmodial and Transmission Blocking Activities.

Malaria remains an important parasitic disease with a large morbidity and mortality burden.  transmission-blocking (TB) compounds are essential for achieving malaria elimination efforts. Recent efforts to develop high-throughput screening (HTS) methods to identify compounds that inhibit or kill gametocytes, the  sexual stage infectious to mosquitoes, have yielded insight into new TB compounds. However, the activities of these compounds against gametes, formed in the first minutes of mosquito infection, are typically not assessed, unless screened in a standard membrane feeding assay, a labor-intensive assay. We demonstrate here the generation of a  model for drug screens against gametes and fertilization. The new  line, named , was genetically and pharmacologically validated and scalable for HTS. Screening the Pathogen Box from the Medicines for Malaria Venture using the new model identified promising TB compounds. The use of  in different libraries of compounds may aid in the identification of transmission-blocking drugs not assessed in screens against asexual stages or gametocytes.

Screening the Pathogen Box for Molecules Active against Plasmodium Sexual Stages Using a New Nanoluciferase-Based Transgenic Line of P. berghei Identifies Transmission-Blocking Compounds.

 Computer-aided drug design approaches were applied to identify chalcones with antiplasmodial activity.  The virtual screening was performed as follows: structural standardization of in-house database of chalcones; identification of potential  protein targets for the chalcones; homology modeling of the predicted  targets; molecular docking studies; and  experimental validation.  Using these models, we prioritized 16 chalcones with potential antiplasmodial activity, for further experimental evaluation. Among them, LabMol-86 and LabMol-87 showed potent  antiplasmodial activity against , while LabMol-63 and LabMol-73 were potent inhibitors of  progression into mosquito stages.  Our results encourage the exploration of chalcones in hit-to-lead optimization studies for tackling malaria.

Chalcones as a basis for computer-aided drug design: innovative approaches to tackle malaria.

Malaria is a tropical infectious disease that affects over 219 million people worldwide. Due to the constant emergence of parasitic resistance to the current antimalarial drugs, the discovery of new antimalarial drugs is a global health priority. Multi-target drug discovery is a promising and innovative strategy for drug discovery and it is currently regarded as one of the best strategies to face drug resistance. Aiming to identify new multi-target antimalarial drug candidates, we developed an integrative computational approach to select multi-kinase inhibitors for  calcium-dependent protein kinases 1 and 4 (CDPK1 and CDPK4) and protein kinase 6 (PK6). For this purpose, we developed and validated shape-based and machine learning models to prioritize compounds for experimental evaluation. Then, we applied the best models for virtual screening of a large commercial database of drug-like molecules. Ten computational hits were experimentally evaluated against asexual blood stages of both sensitive and multi-drug resistant  strains. Among them, LabMol-171, LabMol-172, and LabMol-181 showed potent antiplasmodial activity at nanomolar concentrations (EC ≤ 700 nM) and selectivity indices >15 folds. In addition, LabMol-171 and LabMol-181 showed good  inhibition of  ookinete formation and therefore represent promising transmission-blocking scaffolds. Finally, docking studies with protein kinases CDPK1, CDPK4, and PK6 showed structural insights for further hit-to-lead optimization studies.

Integrative Multi-Kinase Approach for the Identification of Potent Antiplasmodial Hits.

Widespread resistance against antimalarial drugs thwarts current efforts for controlling the disease and urges the discovery of new effective treatments. Drug repositioning is increasingly becoming an attractive strategy since it can reduce costs, risks, and time-to-market. Herein, we have used this strategy to identify novel antimalarial hits. We used a comparative  chemogenomics approach to select  and  proteins as potential drug targets and analyzed them using a computer-assisted drug repositioning pipeline to identify approved drugs with potential antimalarial activity. Among the seven drugs identified as promising antimalarial candidates, the anthracycline epirubicin was selected for further experimental validation. Epirubicin was shown to be potent  against sensitive and multidrug-resistant  strains and  field isolates in the nanomolar range, as well as being effective against an  murine model of  Transmission-blocking activity was observed for epirubicin  and  Finally, using yeast-based haploinsufficiency chemical genomic profiling, we aimed to get insights into the mechanism of action of epirubicin. Beyond the target predicted  (a DNA gyrase in the apicoplast), functional assays suggested a GlcNac-1-P-transferase (GPT) enzyme as a potential target. Docking calculations predicted the binding mode of epirubicin with DNA gyrase and GPT proteins. Epirubicin is originally an antitumoral agent and presents associated toxicity. However, its antiplasmodial activity against not only  but also  in different stages of the parasite life cycle supports the use of this drug as a scaffold for hit-to-lead optimization in malaria drug discovery.

Computational Chemogenomics Drug Repositioning Strategy Enables the Discovery of Epirubicin as a New Repurposed Hit for Plasmodium falciparum and P. vivax.

Correction for Ferreira et al., "Computational Chemogenomics Drug Repositioning Strategy Enables the Discovery of Epirubicin as a New Repurposed Hit for Plasmodium falciparum and P. vivax".

Increasing reports of multidrug-resistant malaria parasites urge the discovery of new effective drugs with different chemical scaffolds. Protein kinases play a key role in many cellular processes such as signal transduction and cell division, making them interesting targets in many diseases. Protein kinase 7 (PK7) is an orphan kinase from the Plasmodium genus, essential for the sporogonic cycle of these parasites. Here, we applied a robust and integrative artificial intelligence-assisted virtual-screening (VS) approach using shape-based and machine learning models to identify new potential PK7 inhibitors with in vitro antiplasmodial activity. Eight virtual hits were experimentally evaluated, and compound LabMol-167 inhibited ookinete conversion of Plasmodium berghei and blood stages of Plasmodium falciparum at nanomolar concentrations with low cytotoxicity in mammalian cells. As PK7 does not have an essential role in the Plasmodium blood stage and our virtual screening strategy aimed for both PK7 and blood-stage inhibition, we conducted an in silico target fishing approach and propose that this compound might also inhibit P. falciparum PK5, acting as a possible dual-target inhibitor. Finally, docking studies of LabMol-167 with P. falciparum PK7 and PK5 proteins highlighted key interactions for further hit-to lead optimization.

Artificial Intelligence Applied to the Rapid Identification of New Antimalarial Candidates with Dual-Stage Activity.

Safe and effective malaria transmission-blocking chemotherapeutics would allow a community-level approach to malaria control and eradication efforts by targeting the mosquito sexual stage of the parasite life cycle. However, only a single drug, primaquine, is currently approved for use in reducing transmission, and drug toxicity limits its widespread implementation. To address this limitation in antimalarial chemotherapeutics, we used a recently developed transgenic Plasmodium berghei line, Ookluc, to perform a series of high-throughput  screens for compounds that inhibit parasite fertilization, the initial step of parasite development within the mosquito. Screens of antimalarial compounds, approved drug collections, and drug-like molecule libraries identified 185 compounds that inhibit parasite maturation to the zygote form. Seven compounds were further characterized to block gametocyte activation or to be cytotoxic to formed zygotes. These were further validated in mosquito membrane-feeding assays using Plasmodium falciparum and P. vivax. This work demonstrates that high-throughput screens using the Ookluc line can identify compounds that are active against the two most relevant human  species and provides a list of compounds that can be explored for the development of new antimalarials to block transmission.

Novel Transmission-Blocking Antimalarials Identified by High-Throughput Screening of Plasmodium berghei Ookluc.

Malaria is a global parasitic infection that leads to substantial illness and death. The most commonly-used drugs for treatment of malaria vivax are primaquine and chloroquine, but they have limitations, such as poor adherence due to frequent oral administration and gastrointestinal side effects. To overcome these limitations, we have developed nano-sized solid dispersion-based dissolving microarray patches (MAPs) for the intradermal delivery of these drugs. In vitro testing showed that these systems can deliver to skin and receiver compartment up to ≈60% of the payload for CQ-based dissolving MAPs and a total of ≈42% of drug loading for PQ-based dissolving MAPs. MAPs also displayed acceptable biocompatibility in cell tests. Pharmacokinetic studies in rats showed that dissolving MAPs could deliver sustained plasma levels of both PQ and CQ for over 7 days. Efficacy studies in a murine model for malaria showed that mice treated with PQ-MAPs and CQ-MAPs had reduced parasitaemia by up to 99.2%. This pharmaceutical approach may revolutionise malaria vivax treatment, especially in developing countries where the disease is endemic. The development of these dissolving MAPs may overcome issues associated with current pharmacotherapy and improve patient outcomes.

Primaquine and chloroquine nano-sized solid dispersion-loaded dissolving microarray patches for the improved treatment of malaria caused by Plasmodium vivax.

In tropical and subtropical areas, malaria stands as a profound public health challenge, causing an estimated 247 million cases worldwide annually. Given the absence of a viable vaccine, the timely and effective treatment of malaria remains a critical priority. However, the growing resistance of parasites to currently utilized drugs underscores the critical need for the identification of new antimalarial therapies. Here, we aimed to identify potential new drug candidates against , the main causative agent of malaria, by analyzing the transcriptomes of different life stages of the parasite and identifying highly expressed genes. We searched for genes that were expressed in all stages of the parasite's life cycle, including the asexual blood stage, gametocyte stage, liver stage, and sexual stages in the insect vector, using transcriptomics data from publicly available databases. From this analysis, we found 674 overlapping genes, including 409 essential ones. By searching through drug target databases, we discovered 70 potential drug targets and 75 associated bioactive compounds. We sought to expand this analysis to similar compounds to known drugs. So, we found a list of 1557 similar compounds, which we predicted as actives and inactives using previously developed machine learning models against five life stages of  spp. From this analysis, two compounds were selected, and the reactions were experimentally evaluated. The compounds HSP-990 and silvestrol aglycone showed potent inhibitory activity at nanomolar concentrations against the  3D7 strain asexual blood stage. Moreover, silvestrol aglycone exhibited low cytotoxicity in mammalian cells, transmission-blocking potential, and inhibitory activity comparable to those of established antimalarials. These findings warrant further investigation of silvestrol aglycone as a potential dual-acting antimalarial and transmission-blocking candidate for malaria control.

Transcriptomics-Guided In Silico Drug Repurposing: Identifying New Candidates with Dual-Stage Antiplasmodial Activity.

Malaria presents a significant challenge to global public health, with around 247 million cases estimated to occur annually worldwide. The growing resistance of  parasites to existing therapies underscores the urgent need for new and innovative antimalarial drugs. This study leveraged artificial intelligence (AI) to tackle this complex challenge. We developed multistage Machine Learning Quantitative Structure-Activity Relationship (ML-QSAR) models to effectively analyze large datasets and predict the efficacy of chemical compounds against multiple life cycle stages of  parasites. We then selected 16 compounds for experimental evaluation, six of which showed at least dual-stage inhibitory activity and one inhibited all life cycle stages tested. Moreover, explainable AI (XAI) analysis provided insights into critical molecular features influencing model predictions, thereby enhancing our understanding of compound interactions. This study not only empowers the development of advanced predictive AI models but also accelerates the identification and optimization of potential antiplasmodial compounds.

Innovative Multistage ML-QSAR Models for Malaria: From Data to Discovery.

Artemisinin-based combination therapy (ACT) is the mainstay of effective treatment of Plasmodium falciparum malaria. However, the long-term utility of ACTs is imperiled by widespread partial artemisinin resistance in Southeast Asia and its recent emergence in parts of East Africa. This underscores the need to identify chemotypes with new modes of action (MoAs) to circumvent resistance to ACTs. In this study, we characterized the asexual blood stage antiplasmodial activity and resistance mechanisms of LDT-623, a 4-aminoquinoline (4-AQ). We also detected LDT-623 activity against multiple stages (liver schizonts, stage IV-V gametocytes, and ookinetes) of Plasmodium's life cycle, a feature unlike other 4-AQs such as chloroquine (CQ) and piperaquine (PPQ). Using heme fractionation profiling and drug uptake studies in PfCRT-containing proteoliposomes, we observed inhibition of hemozoin formation and PfCRT-mediated transport, which constitute characteristic features of 4-AQs' MoA. We also found minimal cross-resistance to LDT-623 in a panel of mutant pfcrt or pfmdr1 lines, but not the PfCRT F145I mutant that is highly resistant to PPQ resistance yet is very unfit. No P. falciparum parasites were recovered in an in vitro resistance selection study, suggesting a high barrier for resistance to emerge. Finally, a competitive growth assay comprising >50 barcoded parasite lines with mutated resistance mediators or major drug targets found no evidence of cross-resistance. Our findings support further exploration of this promising 4-AQ.

A novel 4-aminoquinoline chemotype with multistage antimalarial activity and lack of cross-resistance with PfCRT and PfMDR1 mutants.

Malaria control and elimination efforts would benefit from the identification and validation of new malaria chemotherapeutics. Recently, a transgenic  line was used to perform a series of high-throughput in vitro screens for new antimalarials acting against the parasite sexual stages. The screens identified pyrimidine azepine chemotypes with potent activity. Here, we validate the activity of , the most potent pyrimidine azepine chemotype identified, against  and  in the asexual and sexual stages.  blocked parasite transmission to the mosquito vector at nanomolar concentrations and inhibited in vitro asexual parasite multiplication with a fast-action profile. Through the generation of  resistant parasites and in vitro assays of mitochondrial activity, we identified cytochrome  as a molecular target of . This work characterizes a promising chemotype that can be explored for the future development of new antimalarials targeting the  cytochrome   complex.

Article	Year
QSAR-Driven Design and Discovery of Novel Compounds With Antiplasmodial and Transmission Blocking Activities. Frontiers in pharmacology\| PubMed ID: 29559909	2018
Screening the Pathogen Box for Molecules Active against Plasmodium Sexual Stages Using a New Nanoluciferase-Based Transgenic Line of P. berghei Identifies Transmission-Blocking Compounds. Antimicrobial agents and chemotherapy\| PubMed ID: 30181368	2018
Chalcones as a basis for computer-aided drug design: innovative approaches to tackle malaria. Future medicinal chemistry\| PubMed ID: 31556721	2019
Integrative Multi-Kinase Approach for the Identification of Potent Antiplasmodial Hits. Frontiers in chemistry\| PubMed ID: 31824917	2019
Computational Chemogenomics Drug Repositioning Strategy Enables the Discovery of Epirubicin as a New Repurposed Hit for Plasmodium falciparum and P. vivax. Antimicrobial agents and chemotherapy\| PubMed ID: 32601162	2020
Correction for Ferreira et al., "Computational Chemogenomics Drug Repositioning Strategy Enables the Discovery of Epirubicin as a New Repurposed Hit for Plasmodium falciparum and P. vivax". Antimicrobial agents and chemotherapy\| PubMed ID: 33082230	2020
Artificial Intelligence Applied to the Rapid Identification of New Antimalarial Candidates with Dual-Stage Activity. ChemMedChem\| PubMed ID: 33247522	2021
Novel Transmission-Blocking Antimalarials Identified by High-Throughput Screening of Plasmodium berghei Ookluc. Antimicrobial agents and chemotherapy\| PubMed ID: 36856421	2023
Primaquine and chloroquine nano-sized solid dispersion-loaded dissolving microarray patches for the improved treatment of malaria caused by Plasmodium vivax. Journal of controlled release : official journal of the Controlled Release Society\| PubMed ID: 37562555	2023
Transcriptomics-Guided In Silico Drug Repurposing: Identifying New Candidates with Dual-Stage Antiplasmodial Activity. ACS omega\| PubMed ID: 37744849	2023
Innovative Multistage ML-QSAR Models for Malaria: From Data to Discovery. ACS medicinal chemistry letters\| PubMed ID: 39140064	2024
A novel 4-aminoquinoline chemotype with multistage antimalarial activity and lack of cross-resistance with PfCRT and PfMDR1 mutants. PLoS pathogens\| PubMed ID: 39471233	2024
Pyrimidine Azepine Targets the Complex and Displays Multistage Antimalarial Activity. JACS Au\| PubMed ID: 39483245	2024

Juliana Calit

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