Canvass: A Crowd-Sourced, Natural-Product Screening Library for Exploring Biological Space

Abstract

Natural products and their derivatives continue to be wellsprings of nascent therapeutic potential. However, many laboratories have limited resources for biological evaluation, leaving their previously isolated or synthesized compounds largely or completely untested. To address this issue, the Canvass library of natural products was assembled, in collaboration with academic and industry researchers, for quantitative high-throughput screening (qHTS) across a diverse set of cell-based and biochemical assays. Characterization of the library in terms of physicochemical properties, structural diversity, and similarity to compounds in publicly available libraries indicates that the Canvass library contains many structural elements in common with approved drugs. The assay data generated were analyzed using a variety of quality control metrics, and the resultant assay profiles were explored using statistical methods, such as clustering and compound promiscuity analyses. Individual compounds were then sorted by structural class and activity profiles. Differential behavior based on these classifications, as well as noteworthy activities, are outlined herein. One such highlight is the activity of (-)-2(S)-cathafoline, which was found to stabilize calcium levels in the endoplasmic reticulum. The workflow described here illustrates a pilot effort to broadly survey the biological potential of natural products by utilizing the power of automation and high-throughput screening.

Figure 1

(a) Distribution of structural classes within the Canvass library. (b) Physicochemical properties of chemical libraries; MW = molecular weight, HBA = H-bond acceptor, HBD = H-bond donor, RotB = number of rotatable bonds, PBF = plane of best fit. (c) Chemical space overlap of the Canvass library with three other libraries in a 1024D fingerprint space reduced to two dimensions using tSNE. ECFP-6 fingerprints were computed using the CDK; tSNE = t-distributed stochastic neighbor embedding, ECFP-6 = extended connectivity fingerprint of diameter = 6, CDK = Chemistry Development Kit.

Figure 2

(a–c) Distribution of median assay quality control measures among the three assay classes (pathway, target, and viability). (d) Summary of quality control metrics for the Canvass assay panel, characterized as a pathway-based (pink), a target-based (blue), or a viability assay (green). For all metrics the median values, across all plates run in the assay, are reported.

Figure 3

Heatmap representation of the clustering of the assays, based on the Pearson correlation matrix computed from z-scored compound nAUCs. Pearson correlation can have a value between −1 and 1, where 0 means no correlation, 1 means completely positively correlated, and −1 means completely negatively correlated.

Figure 4

(a) Comparison of the cytotoxicity of each compound (rows) in 16 cancer cell lines (columns). The heatmap was generated based on the area under the dose–response curve (AUC). Dark red indicates a more potent and efficacious compound. (b) AUC correlation plot of KB-8-5-11 vs KB-3-1. AUC for each Canvass compound is represented by a dot with prospective P-gp substrates highlighted (pink) above the unity line (dashed). (c) Dose–response activity of (+)-chamaecypanone C, a prospective P-gp substrate identified in the Canvass library screen. This compound showed selective killing against KB-3-1 (black), resistance in KB-8-5-11 (gray), and reversal of resistance to levels approaching that of KB-3-1 in KB-8-5-11 + 1 μM tariquidar (pink).

Figure 5

Compounds that induce apoptosis: (a) 19 compounds were identified as able to induce apoptosis as they were active at all three time-points in the apoptosis assay. The graph shows the fraction of the 27 non-caspase viability assays in which these 19 compounds are active. Individual points are colored by the maximum reading (Max. Data) observed across the two caspase assays (cell lines: HPAF-II and HEK293). The observed maximum readings were grouped based on quartiles (low–less than equal to median; and high–greater than median). Inactive samples were assigned to category “low” for clarity. (b) Curve fit parameters for 15-Deoxygoyazensolide the most potent compound in the Canvass library exhibiting apoptotic activity at all three time-points in any of the two cell lines (HEK293, HPAF-II) and its structure; nAUC = normalized area under the curve.

Figure 6

(a) Dose–response curves for the CAR activator (NCGC00094872) identified in the Canvass library. The stable cell line treated with compound and CITCO for 24 h in 1536-well plates was treated with ONE-Glo, and the luminescence intensity was calculated (black). The efficacies were compared to the CITCO positive controls, and the viability was also detected using fluorescence in the same well (pink). Data are expressed as mean ± standard error of the mean for triplicate assays. (b) Dose–response curves for the CAR deactivator (NCGC00488482) using same method in part a, except cells were cotreated with PK11195 instead of CITCO, and PK11195 was used as positive controls. (c) 2(S)-Cathafoline is active in the secreted ER calcium-monitoring protein (SERCaMP) assay, indicating the compound stabilizes ER calcium. Activity was examined in the primary SERCaMP assay (pink), a secretion counter-screen (gray), and a viability counter-screen (black). Mean activity ± SD (n = 3) is shown.