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Molecule Set Comparator (MSC)

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  • Molecule Set Comparator (MSC) is designed as an application that enables a user to do a versatile and fast comparison of large molecule sets with a unique inter-set, molecule-to-molecule comparison, for the original set and a predicted set of molecules obtained by machine learning approaches.

  • The molecule-to-molecule comparison is based on chemical descriptors, which are included in the Chemistry Development Kit (CDK), such as Tanimoto similarities, atom/bond/ring counts, and physicochemical properties like logP. The results are presented graphically and summarized by interactive histograms that can be exported in publication quality

Contents of subfolders

  • Tutorials - a comprehensive step-by-step guide for the installation of MSC (MSC_Installation_Guide.pdf), a short introductory tutorial for MSC usage (MSC_1.0_Tutorial.pdf) and an application example (MSC_Application_Example.pdf)

  • src - all Java source files and resources

  • lib - open libraries used by MSC

  • installation - contains the installation folder MSC_1.0 to be copied to a local machine for MSC execution.

    • Note, that an additional JDK download is necessary (see instructions in subdirectory JDK-11.0.2).

    • For a guided installation look at the installation guide in the Tutorials folder

  • Gradle Project for Netbeans - a Gradle project that can be compiled and run with Gradle, the Netbeans IDE or any other IDE that supports Gradle (JDK 11 or higher is needed)

Running MSC

  • A precompiled fat jar file (that includes all dependent libraries) is already provided in this repository. To directly use it, please have a look at the steps provided under the installation directory.

  • Alternatively, the MSC can be compiled using Gradle. For this, have a look at the Gradle Project for Netbeans folder where additional information is provided

Citing the tool

Notes

  • MSC is not modularized due to its non-modularized library dependencies.

MSC (Screenshots)

  • Main window

  • Input selection

  • Results

  • Pairwise visualization