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Mean of Circular Quantities (MCQ)

Mean of Circular Quantities (MCQ) is a dissimilarity measure useful in comparison of 3D protein and/or RNA structures. It calculates an average difference between corresponding torsion angle values (rotations around bonds). More information can be found in:

Zok, T., Popenda, M., & Szachniuk, M. (2014). MCQ4Structures to compute similarity of molecule structures. Central European Journal of Operations Research, 22(3), 457–473. https://doi.org/10.1007/s10100-013-0296-5

Installation

git clone https://github.com/tzok/mcq4structures.git
cd mcq4structures
mvn install

Contents

This project consists of a few subprojets:

  • mcq-common: base functionality
  • mcq-clustering: partitional and hierarchical clustering
  • mcq-cli: command-line interface
  • mcq-gui: graphical interface

Main Ideas

  • Use pl.poznan.put.comparison.MCQ#compareGlobally to compare two 3D structures and obtain a global value of dissimilarity. You can use pl.poznan.put.comparison.global.ParallelGlobalComparator to process multiple inputs in parallel
  • Use pl.poznan.put.comparison.MCQ#comparePair to obtain detailed information about dissimilarity of two 3D structures
  • Use pl.poznan.put.comparison.MCQ#compareModels in a situation where a distinguished reference 3D structure is known and you want to know how 3D models compare to it

Clustering

  • Use pl.poznan.put.clustering.hierarchical.Clusterer to construct dendrograms from a distance matrix (with COMPLETE, SINGLE or AVERAGE linkage option)
  • Use pl.poznan.put.clustering.partitional.KMedoids to perform partitional clustering based on distance matrix
  • Use pl.poznan.put.clustering.partitional.KScanner#parallelScan to find optimum number of clusters with respect to silhouette score