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Fragment-based identification of multi-target ligands by self-organizing map alignment

In the recent years the prevalent paradigm in drug discovery of „one drug – one target – one disease“, following the assumption that highly selective ligands would avoid unwandted side effects caused by binding to seconday non-theratpeutic targets, got reconsidered. The results of post-genomic and network biology showed that proteins rarely act in isolated systems but rather as a part of a highly connected network [1]. It was further shown that the efficacy of several approved drugs is traced back to the fact that they act on multiple targets [2]. Therefore inhibiting a single target of such a network might not lead to the desired therapeutic effect. These findings lead to a shift towards polypharmacology [3] and the rational design of selective multi-target drugs, which have often improved efficacy [4]. But the design of multi target drugs is still a great challenge in regard of a sufficient activity on each target as well as an adequate pharmacokinetic profile [5]. Early design strategies tried to link the pharmacophors of known inhibitors, however these methods often lead to high molecular weight and low ligand efficiency.

We present a new approach based on self-organizing maps [3, 6] (SOM) for the identification of multi-target fragments. We describe a workflow that initially identifies multi-target relevant substructures with a combination of maximum common substructure search and the alignment of multiple SOMs. Furthermore, these substructures are trained together with a fragment library on additional SOMs to find new multi-target fragments, validated by saturation transfer difference (STD)-NMR and biochemical assay systems. We used our approach for the identification of new dual-acting inhibitors of 5-Lipoxygenase (5-LO) and soluble Epoxide Hydrolase (sEH), both enzymes located in the arachidonic acid cascade and involved in inflammatory processes, pain and cadiovascular diseases.


  1. Jeong HM, Barabási A-L, Oltvai ZN: . Nature. 2001, 411: 41-42. 10.1038/35075138.

    Article  CAS  Google Scholar 

  2. Yildirim Ma, Goh K-I, Cusick ME, Barabási A-L, Vidal M: . Nature Biotechnology. 2007, 25: 1119-1126. 10.1038/nbt1338.

    Article  CAS  Google Scholar 

  3. Achenbach J, Tiikkainen P, Franke L, Proschak E: Future medicinal chemistry. 2011, 3: 961-968.

    Google Scholar 

  4. Morphy R, Rankovic Z: . J Med Chem. 2005, 48: 6523-6543. 10.1021/jm058225d.

    Article  CAS  Google Scholar 

  5. Morphy R, Kay C, Rankovic Z: . Drug discovery today. 2004, 9: 641-651. 10.1016/S1359-6446(04)03163-0.

    Article  CAS  Google Scholar 

  6. Kohonen T: Biological Cybernetics. 1982, 43: 59-69.

    Google Scholar 

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Achenbach, J., Klingler, FM., Hahn, S. et al. Fragment-based identification of multi-target ligands by self-organizing map alignment. J Cheminform 4 (Suppl 1), P57 (2012).

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