As a standard, it uses a threshold of 2.0-meaning any bonds or angles with a z-score greater than 2.0 are classed as unusual. | z-score | is the number of standard deviations from the mean.
This is different from the statistical approach to quantify unusualness for bond lengths and covalent bond angles, which uses the | z-score |. By default, Mogul will classify as "unusual" any torsion angles where less than 5% of the distribution is within 10 degrees of the query value. Specifically, this refers to the percentage of observed values within a user-defined tolerance. Mogul uses "local density" to quantify the unusualness of torsion angles.How does Mogul describe unusual torsion angles? Contact us to discuss if this is a requirement. Only if you are an established CCDC Research Partner.Run reports programmatically via the CSD Python API or use CCDC's Mercury or Hermes visualization tools.Īssess the quality of intramolecular geometries as part of a standard workflow or run custom checks.Ĭan I include my own in-house database alongside the CSD as a supplemental knowledge base? Understand what parts of the structure are unusual at a glance.
#Coot software cite code
Tailor your analysis to a general or targeted review based on your research goals.Ĭolour code potentially concerning features for further analysis. Leverage the latest data in your analysis with the Mogul library, which is updated quarterly.įocus on the individual features of a molecule or generate reports on your whole structure. Have confidence in your results, which are based on up to 10,000 randomized structures from the CSD. Visually display the distribution of the geometrical features in easy-to-read, sharable histograms.Ĭompare observed features in your structure to averages found in the CSD. View a distribution of molecular geometries found in the CSD.īuild confidence in your structures by quickly identifying any unusual features, like torsions.ĭrill into each of the individual structures behind a distribution.ĭevelop a deep understanding of your structure with quick access to each experimentally derived, peer-reviewed structure that is behind an analysis. Academic researchers and industry leaders use it to validate the geometry of experimental or predicted structures and predict the likely conformations of chemistry before a structure has been determined. Mogul derives the quality of intramolecular geometries and can display distributions of important geometries based on the bond lengths, angles, ring geometries, and torsions of the expertly curated structures in the CSD. Mogul leverages the CSD as a knowledge base-highlighting any unusual features in your structure. Validate your experimental or predicted structures using experimentally-derived, peer-reviewed data.
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