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Rhodes N, Willett P, Calvet A, et al. CLIP: similarity searching of 3D databases using clique detection. J Chem Inf Comput Sci. 2003;43(2):443-8doi: 10.1021/ci025605o.
Rhodes, N., Willett, P., Calvet, A., Dunbar, J. B., & Humblet, C. (2003). CLIP: similarity searching of 3D databases using clique detection. Journal of chemical information and computer sciences, 43(2), 443-8. https://doi.org/10.1021/ci025605o
Rhodes, Nicholas, et al. "CLIP: similarity searching of 3D databases using clique detection." Journal of chemical information and computer sciences vol. 43,2 (2003): 443-8. doi: https://doi.org/10.1021/ci025605o
Rhodes N, Willett P, Calvet A, Dunbar JB, Humblet C. CLIP: similarity searching of 3D databases using clique detection. J Chem Inf Comput Sci. 2003 Mar-Apr;43(2):443-8. doi: 10.1021/ci025605o. PMID: 12653507.
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J Chem Inf Comput Sci. 2003 Mar-Apr;43(2):443-8. doi: 10.1021/ci025605o.

CLIP: similarity searching of 3D databases using clique detection.

Journal of chemical information and computer sciences

Nicholas Rhodes, Peter Willett, Alain Calvet, James B Dunbar, Christine Humblet

Affiliations

  1. Krebs Institute for Biomolecular Research and Department of Information Studies, University of Sheffield, Western Bank, Sheffield S10 2TN, United Kingdom.

PMID: 12653507 DOI: 10.1021/ci025605o

Abstract

This paper describes a program for 3D similarity searching, called CLIP (for Candidate Ligand Identification Program), that uses the Bron-Kerbosch clique detection algorithm to find those structures in a file that have large structures in common with a target structure. Structures are characterized by the geometric arrangement of pharmacophore points and the similarity between two structures calculated using modifications of the Simpson and Tanimoto association coefficients. This modification takes into account the fact that a distance tolerance is required to ensure that pairs of interatomic distances can be regarded as equivalent during the clique-construction stage of the matching algorithm. Experiments with HIV assay data demonstrate the effectiveness and the efficiency of this approach to virtual screening.

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