Document Detail

Scaffold hopping in drug discovery using inductive logic programming.
MedLine Citation:
PMID:  18457387     Owner:  NLM     Status:  MEDLINE    
In chemoinformatics, searching for compounds which are structurally diverse and share a biological activity is called scaffold hopping. Scaffold hopping is important since it can be used to obtain alternative structures when the compound under development has unexpected side-effects. Pharmaceutical companies use scaffold hopping when they wish to circumvent prior patents for targets of interest. We propose a new method for scaffold hopping using inductive logic programming (ILP). ILP uses the observed spatial relationships between pharmacophore types in pretested active and inactive compounds and learns human-readable rules describing the diverse structures of active compounds. The ILP-based scaffold hopping method is compared to two previous algorithms (chemically advanced template search, CATS, and CATS3D) on 10 data sets with diverse scaffolds. The comparison shows that the ILP-based method is significantly better than random selection while the other two algorithms are not. In addition, the ILP-based method retrieves new active scaffolds which were not found by CATS and CATS3D. The results show that the ILP-based method is at least as good as the other methods in this study. ILP produces human-readable rules, which makes it possible to identify the three-dimensional features that lead to scaffold hopping. A minor variant of a rule learnt by ILP for scaffold hopping was subsequently found to cover an inhibitor identified by an independent study. This provides a successful result in a blind trial of the effectiveness of ILP to generate rules for scaffold hopping. We conclude that ILP provides a valuable new approach for scaffold hopping.
Kazuhisa Tsunoyama; Ata Amini; Michael J E Sternberg; Stephen H Muggleton
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Publication Detail:
Type:  Journal Article     Date:  2008-05-06
Journal Detail:
Title:  Journal of chemical information and modeling     Volume:  48     ISSN:  1549-9596     ISO Abbreviation:  -     Publication Date:  2008 May 
Date Detail:
Created Date:  2008-05-30     Completed Date:  2008-07-02     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101230060     Medline TA:  J Chem Inf Model     Country:  United States    
Other Details:
Languages:  eng     Pagination:  949-57     Citation Subset:  IM    
Computational Bioinformatics Laboratory, Department of Computing, Imperial College London, 180 Queen's Gate, London SW7 2AZ, United Kingdom.
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MeSH Terms
Artificial Intelligence*
Computational Biology / methods*
Drug Design*

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