Open-source discovery of chemical leads for next-generation chemoprotective antimalarials.

To discover leads for next-generation chemoprotective antimalarial drugs, we tested more than 500,000 compounds for their ability to inhibit liver-stage development of luciferase-expressing Plasmodium spp. parasites (681 compounds showed a half-maximal inhibitory concentration of less than 1 micromolar). Cluster analysis identified potent and previously unreported scaffold families as well as other series previously associated with chemoprophylaxis. Further testing through multiple phenotypic assays that predict stage-specific and multispecies antimalarial activity distinguished compound classes that are likely to provide symptomatic relief by reducing asexual blood-stage parasitemia from those which are likely to only prevent malaria. Target identification by using functional assays, in vitro evolution, or metabolic profiling revealed 58 mitochondrial inhibitors but also many chemotypes possibly with previously unidentified mechanisms of action.

A Fully Automated High-Throughput Flow Cytometry Screening System Enabling Phenotypic Drug Discovery.

The goal of high-throughput screening is to enable screening of compound libraries in an automated manner to identify quality starting points for optimization. This often involves screening a large diversity of compounds in an assay that preserves a connection to the disease pathology. Phenotypic screening is a powerful tool for drug identification, in that assays can be run without prior understanding of the target and with primary cells that closely mimic the therapeutic setting. Advanced automation and high-content imaging have enabled many complex assays, but these are still relatively slow and low throughput. To address this limitation, we have developed an automated workflow that is dedicated to processing complex phenotypic assays for flow cytometry. The system can achieve a throughput of 50,000 wells per day, resulting in a fully automated platform that enables robust phenotypic drug discovery. Over the past 5 years, this screening system has been used for a variety of drug discovery programs, across many disease areas, with many molecules advancing quickly into preclinical development and into the clinic. This report will highlight a diversity of approaches that automated flow cytometry has enabled for phenotypic drug discovery.

High-Throughput Assay and Discovery of Small Molecules that Interrupt Malaria Transmission.

Preventing transmission is an important element of malaria control. However, most of the current available methods to assay for malaria transmission blocking are relatively low throughput and cannot be applied to large chemical libraries. We have developed a high-throughput and cost-effective assay, the Saponin-lysis Sexual Stage Assay (SaLSSA), for identifying small molecules with transmission-blocking capacity. SaLSSA analysis of 13,983 unique compounds uncovered that >90% of well-characterized antimalarials, including endoperoxides and 4-aminoquinolines, as well as compounds active against asexual blood stages, lost most of their killing activity when parasites developed into metabolically quiescent stage V gametocytes. On the other hand, we identified compounds with consistent low nanomolar transmission-blocking activity, some of which showed cross-reactivity against asexual blood and liver stages. The data clearly emphasize substantial physiological differences between sexual and asexual parasites and provide a tool and starting points for the discovery and development of transmission-blocking drugs.

Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery.

Most malaria drug development focuses on parasite stages detected in red blood cells, even though, to achieve eradication, next-generation drugs active against both erythrocytic and exo-erythrocytic forms would be preferable. We applied a multifactorial approach to a set of >4000 commercially available compounds with previously demonstrated blood-stage activity (median inhibitory concentration < 1 micromolar) and identified chemical scaffolds with potent activity against both forms. From this screen, we identified an imidazolopiperazine scaffold series that was highly enriched among compounds active against Plasmodium liver stages. The orally bioavailable lead imidazolopiperazine confers complete causal prophylactic protection (15 milligrams/kilogram) in rodent models of malaria and shows potent in vivo blood-stage therapeutic activity. The open-source chemical tools resulting from our effort provide starting points for future drug discovery programs, as well as opportunities for researchers to investigate the biology of exo-erythrocytic forms.

In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.

The growing resistance to current first-line antimalarial drugs represents a major health challenge. To facilitate the discovery of new antimalarials, we have implemented an efficient and robust high-throughput cell-based screen (1,536-well format) based on proliferation of Plasmodium falciparum (Pf) in erythrocytes. From a screen of approximately 1.7 million compounds, we identified a diverse collection of approximately 6,000 small molecules comprised of >530 distinct scaffolds, all of which show potent antimalarial activity (<1.25 microM). Most known antimalarials were identified in this screen, thus validating our approach. In addition, we identified many novel chemical scaffolds, which likely act through both known and novel pathways. We further show that in some cases the mechanism of action of these antimalarials can be determined by in silico compound activity profiling. This method uses large datasets from unrelated cellular and biochemical screens and the guilt-by-association principle to predict which cellular pathway and/or protein target is being inhibited by select compounds. In addition, the screening method has the potential to provide the malaria community with many new starting points for the development of biological probes and drugs with novel antiparasitic activities.

Gene expression signatures and small-molecule compounds link a protein kinase to Plasmodium falciparum motility.

Calcium-dependent protein kinases play a crucial role in intracellular calcium signaling in plants, some algae and protozoa. In Plasmodium falciparum, calcium-dependent protein kinase 1 (PfCDPK1) is expressed during schizogony in the erythrocytic stage as well as in the sporozoite stage. It is coexpressed with genes that encode the parasite motor complex, a cellular component required for parasite invasion of host cells, parasite motility and potentially cytokinesis. A targeted gene-disruption approach demonstrated that pfcdpk1 seems to be essential for parasite viability. An in vitro biochemical screen using recombinant PfCDPK1 against a library of 20,000 compounds resulted in the identification of a series of structurally related 2,6,9-trisubstituted purines. Compound treatment caused sudden developmental arrest at the late schizont stage in P. falciparum and a large reduction in intracellular parasites in Toxoplasma gondii, which suggests a possible role for PfCDPK1 in regulation of parasite motility during egress and invasion.

Snapshot PK: a rapid rodent in vivo preclinical screening approach.

Described in this article are strategies implemented to increase the throughput of in vivo rodent pharmacokinetic (PK) studies using the snapshot PK study design and automated methods for compound submission, sample processing, data analysis and reporting. Applying snapshot PK studies to categorize the oral exposure of >1300 discovery compounds as low, moderate or high resulted in an attrition rate of 86%. The follow up full PK studies on the remaining compounds found that 98% of the compounds were predicted in the correct (69%) or adjacent (29%) oral exposure category by the snapshot PK studies. These results demonstrate that the snapshot PK screen in rodents can serve as an effective and efficient in vivo tool in the compound selection process in drug discovery.

Just-in-time purification: an effective solution for cherry-picking and purifying active compounds from large legacy libraries.

Many companies possess a compound collection consisting of purified compounds and of unpurified products from combinatorial libraries. Using commercial and proprietary compounds as examples, this report provides clear examples of the significant impact purification can have on the activity observed for a compound and highlights the need to retest the purified compounds prior to creating structure-activity relationships. Crude mixtures made with commercial compounds led to an increase in the number of false positives in the SXR-GAL4 assay as compared with their pure and purified counterparts. An examination of proprietary compounds in an HIV assay resulted in the purification of 61 active crude synthetic mixtures. Of these 61 compounds, 32 were 5-fold less active and 2 were 5-fold more active after purification. This report details a semiautomated process developed and implemented for cherry-picking, tracking, and selectively purifying compounds found active in high-throughput screening campaigns.

Learning from the data: mining of large high-throughput screening databases.

High-throughput screening (HTS) campaigns in pharmaceutical companies have accumulated a large amount of data for several million compounds over a couple of hundred assays. Despite the general awareness that rich information is hidden inside the vast amount of data, little has been reported for a systematic data mining method that can reliably extract relevant knowledge of interest for chemists and biologists. We developed a data mining approach based on an algorithm called ontology-based pattern identification (OPI) and applied it to our in-house HTS database. We identified nearly 1500 scaffold families with statistically significant structure-HTS activity profile relationships. Among them, dozens of scaffolds were characterized as leading to artifactual results stemming from the screening technology employed, such as assay format and/or readout. Four types of compound scaffolds can be characterized based on this data mining effort: tumor cytotoxic, general toxic, potential reporter gene assay artifact, and target family specific. The OPI-based data mining approach can reliably identify compounds that are not only structurally similar but also share statistically significant biological activity profiles. Statistical tests such as Kruskal-Wallis test and analysis of variance (ANOVA) can then be applied to the discovered scaffolds for effective assignment of relevant biological information. The scaffolds identified by our HTS data mining efforts are an invaluable resource for designing SAR-robust diversity libraries, generating in silico biological annotations of compounds on a scaffold basis, and providing novel target family specific scaffolds for focused compound library design.

An efficient rapid system for profiling the cellular activities of molecular libraries.

Rapid quantitative methods for characterizing small molecules, peptides, proteins, or RNAs in a broad array of cellular assays would allow one to discover new biological activities associated with these molecules and also provide a more comprehensive profile of drug candidates early in the drug development process. Here we describe a robotic system, termed the automated compound profiler, capable of both propagating a large number of cell lines in parallel and assaying large collections of molecules simultaneously against a matrix of cellular assays in a highly reproducible manner. To illustrate its utility, we have characterized a set of 1,400 kinase inhibitors in a panel of 35 activated tyrosine-kinase-dependent cellular assays in dose-response format in a single experiment. Analysis of the resulting multidimensional dataset revealed subclusters of both inhibitors and kinases with closely correlated activities. The approach also identified activities for the p38 inhibitor BIRB796 and the dual src/abl inhibitor BMS-354825 and exposed the expected side activities for Glivec/STI571, including cellular inhibition of c-kit and platelet-derived growth factor receptor. This methodology provides a powerful tool for unraveling the cellular biology and molecular pharmacology of both naturally occurring and synthetic chemical diversity.

Novel statistical approach for primary high-throughput screening hit selection.

The standard activity threshold-based method (the "top X" approach), currently widely used in the high-throughput screening (HTS) data analysis, is ineffective at identifying good-quality hits. We have proposed a novel knowledge-based statistical approach, driven by the hidden structure-activity relationship (SAR) within a screening library, for primary hit selection. Application to an in-house ultrahigh-throughput screening (uHTS) campaign has demonstrated it can directly identify active scaffolds containing valuable SAR information with a greatly improved confirmation rate compared to the standard "top X" method (from 55% to 85%). This approach may help produce high-quality leads and expedite the hit-to-lead process in drug discovery.