Journal
JOURNAL OF COMPUTATIONAL CHEMISTRY
Volume 36, Issue 19, Pages 1456-1466Publisher
WILEY-BLACKWELL
DOI: 10.1002/jcc.23947
Keywords
molecular similarity; molecular alignment; global descriptors; local rotation-invariant features
Categories
Funding
- CONACyT [169338]
- Eusko Jaurlaritza (Basque Government)
- Moshinsky Foundation
- REA-FP7-IRSES TEMM1P [GA 295172]
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A new hierarchical method to determine molecular similarity is introduced. The goal of this method is to detect if a pair of molecules has the same structure by estimating a rigid transformation that aligns the molecules and a correspondence function that matches their atoms. The algorithm firstly detect similarity based on the global spatial structure. If this analysis is not sufficient, the algorithm computes novel local structural rotation-invariant descriptors for the atom neighborhood and uses this information to match atoms. Two strategies (deterministic and stochastic) on the matching based alignment computation are tested. As a result, the atom-matching based on local similarity indexes decreases the number of testing trials and significantly reduces the dimensionality of the Hungarian assignation problem. The experiments on well-known datasets show that our proposal outperforms state-of-the-art methods in terms of the required computational time and accuracy. (C) 2015 Wiley Periodicals, Inc.
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