Compound similarity visualization software tools | Drug discovery data analysis
Drug discovery projects in the pharmaceutical industry accumulate thousands of chemical structures and ten-thousands of data points from a dozen or more biological and pharmacological assays. A sufficient interpretation of the data requires understanding, which molecular families are present, which structural motifs correlate with measured properties, and which tiny structural changes cause large property changes. Data visualization and analysis software with sufficient chemical intelligence to support chemists in this task is rare.
Enables the users to interactively map and explore drug screening data. C-SPADE is a secure web-based application that permits biologists with little to no informatics skills to interactively visualize, annotate and investigate the relationships between the compounds’ structural similarities and phenotypic responses through compound centric bioactivity clustering. By merely requiring the compound names it also serves as a one click tool, thereby significantly reducing the time needed from drug screening to data analysis and interpretation.
Explores chemical space and mines the relationships between chemical structure, molecular properties, and biological activity. ChemTreeMap combines extended connectivity fingerprints and a neighbor-joining algorithm to produce a hierarchical tree with branch lengths proportional to molecular similarity. Compound properties are shown by leaf color, size, and outline to yield a user-defined visualization of the tree. Two representative analyses are included to demonstrate ChemTree's capabilities and utility: assessing dataset overlap and mining structure-activity relationships (SAR).
Enables exploration of the similarity of compounds in the HMS-LINCS collection to a reference compound. SimilaritySelectR is a web application that takes into account structural similarity and targets affinity spectrum (TAS) similarity and phenotypic fingerprint (PFP) correlation. The software allows users to download information on the reference compound plus three additional compounds.
A web service that identifies structurally similar compounds (structural analogs) in large-scale molecule databases. The service allows compounds to be queried in the widely used ChEMBL, DrugBank and the Connectivity Map databases. Rchemcpp utilizes the best performing similarity functions, i.e. molecule kernels, as measures for structural similarity. Molecule kernels have proven superior performance over other similarity measures and are currently excelling at machine learning challenges.
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