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Ligand-Based Modeling Settings

Settings and Scoring

Settings and scoring
Figure 10.7. Settings and scoring

General Effect
Enable popup Enables/Disables the settings dialog popup for pharmacophore generation, conformer generation and clustering. (default: enabled)
Ligand-Based Generation Settings Effect
Pharmacophore name Sets the default name (prefix) for the resulting pharmacophores. (default: Model)
Scoring function During the ligand-based pharmacophore generation all intermediate alignment results are scored according to the selected scoring function. The Pharmacophore-Fit scoring function only considers pharmacophoric features and the feature RMS deviation. The Relative Pharmacophore-Fit scores the number of matching pharmacophore features and the RMSD of the pharmacophore alignment normalized to [0..1]. If you want to consider steric properties, you can choose the atom sphere overlap (fast shape) or Gaussian shape similarity scoring functions. The first implements a fast atom sphere counting algorithm to provide an overlap score. The latter, uses Gaussian functions to approximate atom spheres. By doing so the overlap can be calculated analytically. (default: Pharmacophore-Fit and atom overlap)
Pharmacophore type Two different types of pharmacophoric models can be derived due to different generation processes. The ligand-based pharmacophore generation is a pair-wise process. In each step one pharmacophore for two molecules is drained. This we can do by either taking all common features (Shared Feature Pharamacophore) or by taking all features (Merged Feature Pharmacophore). In the latter case each feature is scored and those are removed that do not match all input molecules (see number of omitted features for merged pharmacophore). The shared feature pharmacophore creates a pharmacophore that represents all common features of a ligand-set. If you want to take all features into account and assemble them into one pharmacophore, then the merged feature pharmacophore is your right choice. (default: Merged feature pharmcophore)
Number of omitted features for merged pharmacophore This setting specifies the number of features that need not match all input molecules if Merged feature pharmacophore type is turned on. (default: 3)
Partially matching features optional, threshold (%) If this threshold is exceeded, e.g. more than 20% of the molecules do not match a feature, the feature is declared as optional, otherwise it is handled like a normal feature. (default: 20)
Create exclusion volumes Excluded Volumes are generated. (default: enabled)
Apply custom feature settings Enables customized feature definitions. (default: disabled)
Feature tolerance scale factor This value is multiplied to the pre-defined feature tolerances. Lowering this scale factor would end up in more restrictive pharmacophoric models. (default: 1.0)
Max. number of resulting pharmacophores The maximum number of pharmacophores to be generated. (default: 10)

Conformer Generation

Customizing Conformation Settings allow you to tweak OMEGA settings.
Conformer generation
Figure 10.8. Conformer generation

Conformer Generation Settings Effect
Max. num. conformations Maximum number of conformations to output for each molecule. Raising this value samples the conformational space better. (default: 25)
Timeout [sec] After this time, the conformer generation for a molecule is stopped (and is considered to have failed!). If this occurs in the ligand-based pharmacophore generation, the whole process automatically fails. (default: 600 sec)
Max. search time The maximum time that is allowed for torsion search. (default: 30.0)
RMS threshold RMS threshold used to determine duplicate conformations. (default: 0.8)
Energy window Energy window used for conformer selection. (default: 10.0)
Max. num. generated conformations Maximum number of conformations to generate during the whole process. (default: 30 000)
Max. pool size Maximum size of intermediate pool of conformers. (default: 4000)
OE license file The OMEGA license file to use (if left blank the built-in license is used).
Enumerate rings If checked, ring conformers are enumerated. (default: enabled)
Enumerate nitrogens If checked, pyramidal invertible nitrogen geometries are enumerated. (default: enabled)
Replace unknown atom types If checked, atom types that are not supported by MMFF94 get replaced by closely supported analogues (e.g. Selenium by Sulfur). (default: enabled)
Skip molecules with existing conformations If this is enabled, molecules with already existing conformations are not overwritten with new conformations (default: disabled)
Tautomer conformation generation mode Sets the mode to generate tautomer conformation (Number of conformations distributed over tautomers or per tautomer. (default: Num. confs. distributed over tautomers)
Apply FAST Settings Fast Settings are the settings for OMEGA which will result in a fast generation of conformations but potentially of lower quality.
Apply BEST Settings Best Quality Settings are the settings which will result in longer processing time but higher quality resulting conformations.

Clustering

Clustering settings
Figure 10.9. Clustering settings

Settings Effect
Similarity measure The Pharmacophore RDF-Code similarity uses the similarity of the pharmacophore radial distribution function (RDF). The Pharmacophore Alignment Score uses the Relative Pharmacophore-Fit for measuring the ligand similarity. (default: Pharmacophore RDF-Code similarity)
Max. num. conformations Defines the maximum number of conformations to take from the pool of available ligand conformations. (default: 25)
Cluster distance Specifies the cluster distance. Low distances results in many clusters. (default: 0.4)
Cluster distance calculation method Choose the type of cluster distances to calculate (Maximum, Minimum or Average). (default: Average)

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Page designed & authored by G. Wolber

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