C-SPADE: a web-tool for interactive analysis and visualization of drug screening experiments through compound-specific bioactivity dendrograms

Abstract

The advent of polypharmacology paradigm in drug discovery calls for novel chemoinformatic tools for analyzing compounds' multi-targeting activities. Such tools should provide an intuitive representation of the chemical space through capturing and visualizing underlying patterns of compound similarities linked to their polypharmacological effects. Most of the existing compound-centric chemoinformatics tools lack interactive options and user interfaces that are critical for the real-time needs of chemical biologists carrying out compound screening experiments. Toward that end, we introduce C-SPADE, an open-source exploratory web-tool for interactive analysis and visualization of drug profiling assays (biochemical, cell-based or cell-free) using compound-centric similarity clustering. C-SPADE allows the users to visually map the chemical diversity of a screening panel, explore investigational compounds in terms of their similarity to the screening panel, perform polypharmacological analyses and guide drug-target interaction predictions. C-SPADE requires only the raw drug profiling data as input, and it automatically retrieves the structural information and constructs the compound clusters in real-time, thereby reducing the time required for manual analysis in drug development or repurposing applications. The web-tool provides a customizable visual workspace that can either be downloaded as figure or Newick tree file or shared as a hyperlink with other users. C-SPADE is freely available at http://cspade.fimm.fi/.

Figure 1.

An infographic illustration of C-SPADE web-tool and its functionalities. (A) Various types of biological drug screening assays (biochemical, cell-based, cell-free or target-based assays) can be analyzed. (B) The key functionalities implemented in C-SPADE. (C) The input consists of a tab-delimited text file of drug screening data, with compound names and bioactivity values, where a wide range of activity measurements are supported. (D) On the server-side, the compound name is used to retrieve the compound structural information from the PubChem database and various compound features are calculated using the RDKit package. (E) The client-side options provide an interactive interface to visualize and customize the compound clusters. (F) The output visualization from C-SPADE can be either shared with collaborators or downloaded as publication-quality images or as a Newick tree file.

Figure 2.

(A) Compound-centric bioactivity dendrogram visualization of the example drug screening data (25). The drug panel contained a total of 250 compounds screened across three cytarabine-resistant SHI-1 cell-line variants (Parental, 320 Ara-C and 1280 Ara-C) to identify drugs that could counteract cytarabine resistance. A subset of 75 compounds were selected and their chemical space was visualized using the C-SPADE web-tool. The nodes are the compounds and the distance between the nodes represents the degree of their structural similarity based on the selected ECFP4 fingerprints. The bioactivity measurements (DSS) of each compound are represented as circles, where the radius of the circle is proportional to the bioactivity level. Inset: the distinct sub-clusters of glucocorticoids (d) and nucleoside analogues (e). (B) The provided bioactivities, activity classes and compound annotations, if available, are color-coded and displayed in the legend. (C) The types of dendrogram layouts and styles that are currently available in C-SPADE. The glucocorticoids (D) showed an increased sensitivity in the cytarabine resistant cell-lines, whereas the nucleoside analogues (E) showed a co-resistance pattern in the cytarabine resistant SHI-1 cells. In this example, C-SPADE enables the user to (i) map the chemical space of the compounds screened, (ii) explain the sub-clustering patterns that one commonly encounters in such drug-screening data analysis, and (iii) investigate and predict structurally similar compounds that cluster into a desired activity cluster prior to a future compound screening application.