Chemical Similarity

Chemical similarity is a concept that is not formally defined; it depends on the application for which similarity needs to be determined. Various similarity metrics exist that return a score indicating the level of similarity between molecules under comparison. Similarity can either be assessed between structures or descriptor values. In the latter case, the chosen descriptors should be relevant to the analysis.  The scores of these similarity metrics are usually highly correlated. Frequently used metrics are simple distance measures such as Hamming and Euclidean distance, and association coefficients such as Tanimoto, Dice and Cosine coefficients.

As mentioned by some authors, a basic difference between Hamming and Euclidean distances, versus, the Tanimoto, Dice and Cosine coefficients, is that the distance measures effectively consider a common absence of attributes (or common low values in the case of continuous variables) as evidence of similarity, whereas the coefficients do not. Also, it was commented that Hamming and Euclidean distances are useful only for ‘relative’ distance comparisons, (i.e., the distance of two molecules to the same target) but not for ‘absolute’ comparisons (between two independent pairs of molecules), for which Tanimoto coefficient is preferred. Further, Euclidean distance comparisons form the basis of Ward's hierarchical agglomerative clustering method, which has been shown to be effective on the basis of empirical studies. Tanimoto coefficient has been the measure of choice for fragment-based chemical similarity work, though the Hamming distance has its adherents while Euclidean distance remains the most popular measure for continuous data.

See Also:
Similarity Principle, Fingerprint-based Similarity, Descriptor-based Similarity.

References:
Glen, R. C. and Adams, S. E. Similarity Metrics and Descriptor Spaces - Which Combinations to Choose? QSAR Comb. Sci., 25(12), 1133-1142, 2006

Nikolova, N. and Jaworska, J. Approaches to Measure Chemical Similarity - a Review
QSAR Comb. Sci., 22(9-10), 1006-1026, 2003.

Willett, P., Barnard, J. M. and Downs, G. M.  Chemical Similarity Searching J. Chem. Inf. Comput. Sci., 38 (6), 983-996, 1998.

http://www.daylight.com/dayhtml/doc/theory/theory.finger.html

Cite This As:

Dogra, Shaillay K., "Chemical Similarity." From QSARWorld--A Strand Life Sciences Web Resource.
http://www.qsarworld.com/insilico-chemistry-chemical-similarity.php