Skip to content
2000
Volume 3, Issue 1
  • ISSN: 1570-1638
  • E-ISSN: 1875-6220

Abstract

Modelling of drug targets requires the reliable selection of an accurate and representative structure from large ensembles of alternate models. Statistical potentials developed to discriminate native protein structures generally represent pairwise interactions between atoms, which are less sensitive to local conformational details. The discrimination of local distortions is therefore particularly difficult. Local interaction preferences, expressed through torsion angles, are rarely used, as some controversy exists in the literature regarding their discrimination power. The present study aims to benchmark the efficiency of different implementations of torsion angle propensities for selecting the native structure from ensembles of well-constructed decoys. Several statistical potentials derived from fine-grained discretisations of torsion angle space are constructed and evaluated. Results from a comparison with nine widely used statistical scoring functions show the torsion angle potentials to be more effective in recognising native structures and to improve with the number of torsion angles considered. These data suggest local structural propensities to be important for estimating the overall quality of native-like models.

Loading

Article metrics loading...

/content/journals/cddt/10.2174/157016306776637591
2006-03-01
2024-11-01
Loading full text...

Full text loading...

/content/journals/cddt/10.2174/157016306776637591
Loading
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test