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The number of experiments exploiting microarray technology has markedly increased in recent years. Not surprisingly, there are potential difficulties in navigating between different available data sets. Microarray expression data are deposited on servers, many of which are publicly accessible. Public plant microarray data are deposited in several databases including ArrayExpress [16], GEO [17], NASCarrays [18] and the Stanford Microarray Database [19-21]. Currently these databases store several thousands of individual datasets and some of these offer on-line tools for data normalization, filtering, statistical testing and pattern discovery [22-26].
aGFP database presents data normalised using two different algorithms, empirical MAS 4.0 and statistical MAS 5.0. Although MAS4.0 is believed to yields more false-positive calls [57], our analyses of four developmental stages of pollen development showed that the MAS5.0 detection algorithm tended to eliminate a number of genes originally detected as expressed by MAS4.0 and which were experimentally verified to be so [58]. This was often the case even for highly expressed genes (B. Honysová and D. Honys, unpublished results), highlighting the added value of the empirical MAS4.0 detection algorithm and comparative analysis.
The first challenge in the 2014 competition launched by the Teach-Discover-Treat (TDT) initiative asked for the development of a tutorial for ligand-based virtual screening, based on data from a primary phenotypic high-throughput screen (HTS) against malaria. The resulting Workflows were applied to select compounds from a commercial database, and a subset of those were purchased and tested experimentally for anti-malaria activity. Here, we present the two most successful Workflows, both using machine-learning approaches, and report the results for the 114 compounds tested in the follow-up screen. Excluding the two known anti-malarials quinidine and amodiaquine and 31 compounds already present in the primary HTS, a high hit rate of 57% was found.
The basis for the virtual screening workflows was a phenotypic high-throughput screen against Pf with 305,568 compounds, together with a confirmatory dose-response screen for 1524 compounds, which are reported in 23. The data is deposited in ChEMBL as part of the Neglected Tropical Diseases set ( ChEMBL-NTD) 24 . The data is also available on the TDT website ( -1---malaria-hts.html). In addition, an external held-out test set with 1056 molecules was provided for comparison of submissions 25 . This dataset was generated in the laboratory of R. K. Guy in 2014, following the same procedure as described in 23, at the time of the TDT competition. Results for this held-out set are given in the Supplementary material.
The tutorial was written in the form of an IPython notebook and a series of Python scripts for the computationally demanding tasks to be executed separately. The tutorial is available on the TDT website ( ) and on GitHub ( -tutorial-2014). The tutorial makes use of a number of open-source Python libraries: the cheminformatics toolkit RDKit version 2013.09 ( ), the machine-learning toolkit scikit-learn version 0.13 ( -learn.org), pandas for working with data tables, and libraries for scientific computing, numpy version 1.6.2 and scipy version 0.9.0. Figures are plotted using matplotlib version 1.1.0. The components of the Workflow are shown schematically in Figure 1.
The potency of new candidates was determined as reported earlier 23 . Plasmodium falciparum strain 3D7 was acquired from the Malaria Research and Reference Reagent Resource Center (MR4, catalog #MRA-102). Briefly, asynchronous parasites were maintained in culture based on the method of Trager 36 . Parasites were grown in presence of fresh group O-positive erythrocytes (Key Biologics, LLC, Memphis, TN) in Petri dishes at a hematocrite of 4-6% in RPMI based media (RPMI 1640 supplemented with 0.5% AlbuMAX II, 25 mM HEPES, 25 mM NaHCO 3 (pH 7.3), 100 µg/mL hypoxanthine, and 5 µg/mL gentamycin). Cultures were incubated at 37C in a gas mixture of 90% N 2, 5% O 2, 5% CO 2. For IC 50 determinations, 20 µl of RPMI 1640 with 5 µg/ml gentamycin were dispensed per well in an assay plate (Corning 384-well microtiter plate, clear bottom, tissue culture treated, catalog no. 8807BC). An amount of 60 nl of compound, previously serial diluted in a separate 384-well white polypropylene plate (Corning, catalog no. 8748BC), was dispensed to the assay plate by hydrodynamic pin transfer (FP1S50H, V&P Scientific Pin Head) and then an amount of 20 µl of a synchronized culture suspension (1% rings, 4% hematocrite) was added per well, thus making a final hematocrite and parasitemia of 2% and 1%, respectively. Assay plates were incubated for 72 h, and the parasitemia was determined by a method previously described 37 . An amount of 10 µl of the following solution in PBS (10X Sybr Green I, 0.5% v/v triton, 0.5 mg/ml saponin) was added per well. Assay plates were shaken for 1 min, incubated in the dark for 90 min, then read with the Envision spectrophotomer at Ex/Em of 485 nm/535 nm.
From the combined set of 2000 candidates predicted by Workflow 1 and Workflow 2, 114 were tested in a follow-up assay (80 from Workflow 1 and 38 from Workflow 2, four compounds were predicted by both Workflows). The identifiers, SMILES, EC 50 values and raw data for all 114 compounds are given in the Supplementary material. Of these, two were known anti-malarials (quinidine and amodiaquine) selected as positive control. In addition, 31 compounds (six from Workflow 1 and 28 from Workflow 2, three were in common) were already present in the primary HTS and confirmatory screen provided by the TDT challenge, as such molecules were not explicitly removed from the eMolecules catalog before the virtual screen ( Supplementary Table S1). One of these compounds, SJ000154494 ( Figure 3, EC 50 = 0.44 µM as measured in this study) was found inactive in the previous primary screen and confirmatory screen 23 , which was likely a false negative in the latter screen because dose-response testing immediately following the primary screen was done using compounds from stock solutions ranging in age, whereas the current experiment was performed on fresh powder. 2ff7e9595c
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