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A fuzzy‐set approach to functional‐group comparisons based on an asymmetric similarity measure
Author(s) -
Maggiora Gerald M.,
Mezey Paul G.
Publication year - 1999
Publication title -
international journal of quantum chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.484
H-Index - 105
eISSN - 1097-461X
pISSN - 0020-7608
DOI - 10.1002/(sici)1097-461x(1999)74:5<503::aid-qua7>3.0.co;2-k
Subject(s) - similarity (geometry) , fuzzy logic , fuzzy set , pharmacophore , measure (data warehouse) , scaling , chemistry , set (abstract data type) , similarity measure , mathematics , computational chemistry , computer science , data mining , artificial intelligence , stereochemistry , image (mathematics) , geometry , programming language
A new, fuzzy‐set framework for molecular similarity analysis is proposed. Recent advances in the computation of ab initio quality fuzzy electron densities of molecular fragments, pharmacophoric moieties, and functional groups of both small and macromolecular systems have motivated the search for new approaches to the evaluation of molecular similarity. Fuzzy‐set methods appear especially suitable for the task for two reasons: the inherent fuzziness of electron densities due to Heisenberg's quantum mechanical uncertainty relation, and the fuzzy range of possible local molecular conformations which may correlate with a given chemical or biochemical function. In this contribution, a new, asymmetric similarity measure is proposed for local molecular moieties, such as functional groups or pharmacophores, based on a fuzzy‐set description of electron densities and a fuzzy‐set adaptation of earlier scaling–nesting similarity measures. ©1999 John Wiley & Sons, Inc. Int J Quant Chem 74: 503–514, 1999