Journal of Computer-Aided Molecular Design

, Volume 30, Issue 5, pp 425–446 | Cite as

Ring system-based chemical graph generation for de novo molecular design

  • Tomoyuki Miyao
  • Hiromasa Kaneko
  • Kimito Funatsu


Generating chemical graphs in silico by combining building blocks is important and fundamental in virtual combinatorial chemistry. A premise in this area is that generated structures should be irredundant as well as exhaustive. In this study, we develop structure generation algorithms regarding combining ring systems as well as atom fragments. The proposed algorithms consist of three parts. First, chemical structures are generated through a canonical construction path. During structure generation, ring systems can be treated as reduced graphs having fewer vertices than those in the original ones. Second, diversified structures are generated by a simple rule-based generation algorithm. Third, the number of structures to be generated can be estimated with adequate accuracy without actual exhaustive generation. The proposed algorithms were implemented in structure generator Molgilla. As a practical application, Molgilla generated chemical structures mimicking rosiglitazone in terms of a two dimensional pharmacophore pattern. The strength of the algorithms lies in simplicity and flexibility. Therefore, they may be applied to various computer programs regarding structure generation by combining building blocks.


Ring systems Structure generator Inverse QSPR/QSAR De novo design 



The authors are grateful to G. Schneider and D. Reker at the Department of Chemistry and Applied Biosciences, Institute of Pharmaceutical Sciences, ETH Zurich. G. Schneider supported the authors by giving valuable advice for the improvement of our structure generation algorithms, particularly the descriptor calculation and how to generate feasible structures in a chemistry point of view. D. Reker and the authors have discussed how to develop diversity-oriented generation algorithms. The authors also acknowledge the support of the Core Research for Evolutionary Science and Technology (CREST) Project ‘Development of a knowledge-generating platform driven by big data in drug discovery through production processes’ of the Japan Science and Technology Agency (JST). T.M. is a JSPS Research Fellow.

Supplementary material

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Tomoyuki Miyao
    • 1
  • Hiromasa Kaneko
    • 1
  • Kimito Funatsu
    • 1
  1. 1.Department of Chemical System EngineeringThe University of TokyoBunkyo-kuJapan

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