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.
An open source chemistry toolbox. Open Babel is a chemical toolbox designed to speak the many languages of chemical data. Open Babel version 2.3 interconverts over 110 formats. It's an open, collaborative project allowing anyone to search, convert, analyze, or store data from molecular modeling, chemistry, solid-state materials, biochemistry, or related areas.
Allows users to find the maximum common subgraph (MCS) in small molecules. SMSD uses a combination of various algorithms to search the MCS and filters the results in a manner that is chemically relevant. This tool calculates the MCS between two molecules by combining the power of the VF+ Lib, the MCS+, and the Chemistry Development Kit (CDK) based MCS algorithm. It checks if two molecules are identical or dissimilar based on the atom count and bond count before performing the MCS search.
Compares alternative descriptor subsets. VIDEAN is an interactive visual analytics application that combines statistical methods with interactive visualizations for choosing a set of descriptors for predicting a target property. Coordinated visual representations are presented for capturing different relationships and interactions among descriptors, target properties and candidate subsets of descriptors. Some domain expertise can also be added to the feature selection process by means of an interactive visual exploration of data.
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).
Prepares and completes whole-organism screening at high-througput rates. ARQiv-HTS includes functions that fall into two categories - those applied to 'Pre-screening Assay Optimization' and 'Compound Analysis'. The functions allow the user to calculate background signal, determine sample size, run quality control tests, perform virtual experiments to simulate compound efficacy - and finally, to perform compound analysis during iterative drug screen cycles. ARQiv-HTS platform is adaptable to almost any reporter-based assay designed to evaluate the effects of chemical compounds in living small-animal models. ARQiv-HTS thus enables large-scale whole-organism drug discovery for a variety of model species and from numerous disease-oriented perspectives.
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