SONHICA (Simple optimized non-HIerarchical Cluster Analysis): A new tool for analysis of molecular conformations
✍ Scribed by Bravi, Gianpaolo; Gancia, Emanuela; Zaliani, Andrea; Pegna, Monica
- Publisher
- John Wiley and Sons
- Year
- 1997
- Tongue
- English
- Weight
- 400 KB
- Volume
- 18
- Category
- Article
- ISSN
- 0192-8651
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✦ Synopsis
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.