Volume 3 Supplement 1

6th German Conference on Chemoinformatics, GCC 2010

Open Access

Searching substructures in fragment spaces

Journal of Cheminformatics20113(Suppl 1):P11

https://doi.org/10.1186/1758-2946-3-S1-P11

Published: 19 April 2011

Introduction

Fragment spaces (FSs) are an elegant way to model a large or even infinite number of chemical compounds and their synthetic accessibility. A FS consists of molecular fragments and a set of rules defining how fragments can be combined to products. In virtual screening experiments, FSs might include products with undesired functional groups or inadequate central building blocks. The recognition of such products, especially when they span over multiple fragments, would require their explicit construction from the FS. Due to the generally huge number of possible products in an FS, the complete enumeration is undesired or even impossible. Therefore, algorithms that perform substructure search in FSs must be able to process fragments and joining rules rather than complete molecules. Even though some algorithms that work in FSs exist [1, 2], a method that excludes undesired products via substructure definition from a FS is still missing.

Method

We present and compare two algorithms to modify an FS such that no possible product can include a given functional group or substructure. The methods utilize a search procedure based on the Ullmann [3] respectively the VF2 algorithm [4] for subgraph isomorphism. Thereby, we find substructures that are present inside fragments or would be formed by joining two fragments. After the identification of such fragments, they are either removed from the FS or their joining rules are altered in a way that a formation of the substructure becomes impossible.

Results

The algorithms are tested on the BRICS fragment space [1]. We exclude substructures described by SMARTS patterns that where collected from literature [5]. The experiments show that the VF2 approach is superior in running time.

Authors’ Affiliations

(1)
Center for Bioinformatics, University of Hamburg

References

  1. Degen J, Wegscheid-Gerlach C, Zaliani A, Rarey M: On the art of compiling and using ’drug-like’ chemical fragment spaces. ChemMedChem. 2008, 3 (10): 1503-1507. 10.1002/cmdc.200800178.View ArticleGoogle Scholar
  2. Rarey M, Stahl M: Similarity searching in large combinatorial chemistry spaces. J Comput Aided Mol Des. 2001, 15 (6): 497-520. 10.1023/A:1011144622059.View ArticleGoogle Scholar
  3. Ullmann JR: An algorithm for subgraph isomorphism. J Assoc Comput Mach. 1976, 23: 31-42.View ArticleGoogle Scholar
  4. Cordella LP, Foggia P, Sansone C, Vento M: A (sub)graph isomorphism algorithm for matching large graphs. IEEE T-PAMI. 2004, 26 (10): 1367-1372.View ArticleGoogle Scholar
  5. Schomburg K, Ehrlich H-C, Stierand K, Rarey M: From structure diagrams to visual chemical patterns. J Chem Inf Model. 2010,Google Scholar

Copyright

© Ehrlich and Rarey; licensee BioMed Central Ltd. 2011

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.