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Rational, computer-aided design of multi-target ligands

Over the past two decades the “one drug – one target – one disease” concept became the prevalent paradigm in drug discovery. The main idea of this approach is the identification of a single protein target whose inhibition leads to a successful treatment of the examined disease. The predominant assumption is that highly selective ligands would avoid unwanted side effects caused by binding to secondary non-therapeutic targets.

In recent years 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]. In addition this connectivity leads to more robust systems that cannot be interfered by the inhibition of a single target of that network and consequently might not lead to the desired therapeutic effect [2]. Furthermore studies prove that robust systems are rather affected by weak inhibitions of several parts than by a complete inhibition of a single selected element of that system [3].

Therefore there is an increasing interest in developing drugs that take effect on multiple targets simultaneously but is concurrently a great challenge for medicinal chemists. There has to be a sufficient activity on each target as well as an adequate pharmacokinetic profile [4]. Early design strategies tried to link the pharmacophors of known inhibitors, however these methods often lead to high molecular weight and low ligand efficacy.

We present a new rational approach based on a retrosynthetic combinatorial analysis procedure [5] on approved ligands of multiple targets. These RECAP fragments are used to design a large combinatorial library containing molecules featuring chemical properties of each ligand class. The molecules are further validated by machine learning models, like random forests and self-organizing maps, regarding their activity on the targets of interest.

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    Kitano H: Towards a theory of biological robustness. Molecular Systems Biology. 2007, 3: 137-10.1038/msb4100179.

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    Agoston V, Csermely P, Pongor S: Multiple weak hits confuse complex systems: a transcriptional regulatory network as an example. Phys Rev E. 2005, 71: 051909-10.1103/PhysRevE.71.051909.

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    Morphy R, Rankovic Z: Designing multiple ligands - medicinal chemistry strategies and challenges. Curr Pharm Design. 2009, 15: 587-600. 10.2174/138161209787315594.

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    Lewell XQ, Judd DB, Watson SP, Hann MM: RECAP - retrosynthetic combinatorial analysis procedure: a powerful new technique for identifying privileged molecular fragments with useful applications in combinatorial chemistry. J Chem Inf Comput Sci. 1998, 18: 511-522.

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Correspondence to J Achenbach.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Achenbach, J., Proschak, E. Rational, computer-aided design of multi-target ligands. J Cheminform 3, P10 (2011). https://doi.org/10.1186/1758-2946-3-S1-P10

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Keywords

  • Random Forest
  • Isolate System
  • Multiple Target
  • Weak Inhibition
  • Unwanted Side Effect