Dataset Information

Identification of novel antimalarial chemotypes via chemoinformatic compound selection methods for a high-throughput screening program against the novel malarial target, PfNDH2: increasing hit rate via virtual screening methods.

ABSTRACT: Malaria is responsible for approximately 1 million deaths annually; thus, continued efforts to discover new antimalarials are required. A HTS screen was established to identify novel inhibitors of the parasite's mitochondrial enzyme NADH:quinone oxidoreductase (PfNDH2). On the basis of only one known inhibitor of this enzyme, the challenge was to discover novel inhibitors of PfNDH2 with diverse chemical scaffolds. To this end, using a range of ligand-based chemoinformatics methods, ~17000 compounds were selected from a commercial library of ~750000 compounds. Forty-eight compounds were identified with PfNDH2 enzyme inhibition IC(50) values ranging from 100 nM to 40 μM and also displayed exciting whole cell antimalarial activity. These novel inhibitors were identified through sampling 16% of the available chemical space, while only screening 2% of the library. This study confirms the added value of using multiple ligand-based chemoinformatic approaches and has successfully identified novel distinct chemotypes primed for development as new agents against malaria.

SUBMITTER: Sharma R

PROVIDER: S-EPMC3324984 | biostudies-literature | 2012 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identification of novel antimalarial chemotypes via chemoinformatic compound selection methods for a high-throughput screening program against the novel malarial target, PfNDH2: increasing hit rate via virtual screening methods.

Sharma Raman R Lawrenson Alexandre S AS Fisher Nicholas E NE Warman Ashley J AJ Shone Alison E AE Hill Alasdair A Mbekeani Alison A Pidathala Chandrakala C Amewu Richard K RK Leung Suet S Gibbons Peter P Hong David W DW Stocks Paul P Nixon Gemma L GL Chadwick James J Shearer Joanne J Gowers Ian I Cronk David D Parel Serge P SP O'Neill Paul M PM Ward Stephen A SA Biagini Giancarlo A GA Berry Neil G NG

Journal of medicinal chemistry 20120322 7

Malaria is responsible for approximately 1 million deaths annually; thus, continued efforts to discover new antimalarials are required. A HTS screen was established to identify novel inhibitors of the parasite's mitochondrial enzyme NADH:quinone oxidoreductase (PfNDH2). On the basis of only one known inhibitor of this enzyme, the challenge was to discover novel inhibitors of PfNDH2 with diverse chemical scaffolds. To this end, using a range of ligand-based chemoinformatics methods, ~17000 compou ...[more]

PMID: 22380711

Similar Datasets

Project description:The parasite Plasmodium falciparum is the most lethal species of Plasmodium to cause serious malaria infection in humans, and with resistance developing rapidly novel treatment modalities are currently being sought, one of which being combinations of existing compounds. The discovery of combinations of antimalarial drugs that act synergistically with one another is hence of great importance; however an exhaustive experimental screen of large drug space in a pairwise manner is not an option. In this study we apply our machine learning approach, Combination Synergy Estimation (CoSynE), which can predict novel synergistic drug interactions using only prior experimental combination screening data and knowledge of compound molecular structures, to a dataset of 1,540 antimalarial drug combinations in which 22.2% were synergistic. Cross validation of our model showed that synergistic CoSynE predictions are enriched 2.74 × compared to random selection when both compounds in a predicted combination are known from other combinations among the training data, 2.36 × when only one compound is known from the training data, and 1.5 × for entirely novel combinations. We prospectively validated our model by making predictions for 185 combinations of 23 entirely novel compounds. CoSynE predicted 20 combinations to be synergistic, which was experimentally validated for nine of them (45%), corresponding to an enrichment of 1.70 × compared to random selection from this prospective data set. Such enrichment corresponds to a 41% reduction in experimental effort. Interestingly, we found that pairwise screening of the compounds CoSynE individually predicted to be synergistic would result in an enrichment of 1.36 × compared to random selection, indicating that synergy among compound combinations is not a random event. The nine novel and correctly predicted synergistic compound combinations mainly (where sufficient bioactivity information is available) consist of efflux or transporter inhibitors (such as hydroxyzine), combined with compounds exhibiting antimalarial activity alone (such as sorafenib, apicidin, or dihydroergotamine). However, not all compound synergies could be rationalized easily in this way. Overall, this study highlights the potential for predictive modeling to expedite the discovery of novel drug combinations in fight against antimalarial resistance, while the underlying approach is also generally applicable.

Project description:BackgroundEven though malaria is a completely preventable and treatable disease, it remains a threat to human life and a burden to the global economy due to the emergence of multiple-drug resistant malaria parasites. According to the World Malaria Report 2013, in 2012 there were an estimated 207 million malaria cases and 627,000 deaths. Thus, the discovery and development of new, effective anti-malarial drugs are required. To achieve this goal, the Department of Chemistry at the University of the Free State has synthesized a number of novel amino-alkylated chalcones and analogues, which showed in vitro anti-malarial activity against both chloroquine-sensitive and chloroquine-resistant Plasmodium falciparum strains. The lead compound (NP046) was selected for a comprehensive pharmacokinetic (PK) and in vivo efficacy evaluation in a mouse model.MethodsIn vivo efficacy: Water solutions of NP046 were administered orally at 50 and 10 mg/kg using oral gavage and IV at 5 and 1 mg/kg via the dorsal penile vein to Plasmodium berghei (ANKA strain) infected male C57BL/6 mice (n?=?5), once a day for four days. Blood samples were collected via tail bleeding in tubes containing phosphate buffer saline (PBS) on day five to determine the % parasitaemia by flow cytometry.In vivo PK: NP046 solutions in water were administered orally (50 and 10 mg/kg) and IV (5 mg/kg) to male C57BL/6 mice (n?=?5). Blood samples were collected via tail bleeding into heparinized tubes and analysed using a validated LC-MS/MS assay. Data obtained from the concentration-time profile was evaluated using Summit PK software to determine the PK parameters of NP046.ResultsNP046 inhibited parasite growth for the oral and IV groups. Better parasite growth inhibition was observed for the IV group. The PK evaluation of NP046 showed low oral bioavailability (3.2% and 6% at 50 mg/kg and 10 mg/kg dose, respectively and a moderate mean half-life ranging from 3.1 to 4.4 hours.ConclusionEven though the oral bioavailability of NP046 is low, its percentage parasite growth inhibition is promising, but in order to improve the oral bioavailability, structure-activity-relationship (SAR) optimization studies are currently being conducted.

Dataset Information

Identification of novel antimalarial chemotypes via chemoinformatic compound selection methods for a high-throughput screening program against the novel malarial target, PfNDH2: increasing hit rate via virtual screening methods.

Publications

Identification of novel antimalarial chemotypes via chemoinformatic compound selection methods for a high-throughput screening program against the novel malarial target, PfNDH2: increasing hit rate via virtual screening methods.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets