ISSN:
0192-8651
Keywords:
cluster analysis
;
SONHICA
;
conformational analysis
;
ITF1697
;
BQ123
;
molecular dynamics
;
Chemistry
;
Theoretical, Physical and Computational Chemistry
Source:
Wiley InterScience Backfile Collection 1832-2000
Topics:
Chemistry and Pharmacology
,
Computer Science
Notes:
We describe a new clustering program, SONHICA (Simple Optimized Non-HIerarchical Cluster Analysis), developed to analyze large data sets of molecular conformations. Unlike traditional clustering methods, SONHICA does not make use of an overall index, like a distance, to evaluate similarity between objects. Each descriptor variable is compared individually on the basis of a preset threshold value. This assures high control and sensitivity over the input variables. In addition, periodic and nonperiodic descriptors, such as dihedral angles and interatomic distances, can easily be used together. SONHICA generates clusters with the highest possible density and all pairs of objects within a cluster are similar. These features make SONHICA particularly suitable for the analysis of data sets which tend to form globular clusters. This method was applied to the analysis of a modified linear tetrapeptide, ITF1697, under investigation for its anti-ischemic properties, and a cyclic pentapeptide, BQ123, a potent antagonist of endothelin A. On the basis of the results presented here, SONHICA appears to be an interesting new tool in the field of the clustering methods applied to the analysis of molecular conformations. © 1997 John Wiley & Sons, Inc. J Comput Chem 18: 1295-1311, 1997
Additional Material:
11 Ill.
Type of Medium:
Electronic Resource
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