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Active search for computer-aided drug design

Oglic, Dino; Oatley, Steven A.; Macdonald, Simon J.F.; McInally, Thomas; Garnett, Roman; Hirst, Jonathan D.; Gärtner, Thomas


Dino Oglic

Steven A. Oatley

Simon J.F. Macdonald

Roman Garnett

Thomas Gärtner


We consider lead discovery as active search in a space of labelled graphs. In particular, we extend our recent data-driven adaptive Markov chain approach, and evaluate it on a focused drug design problem, where we search for an antagonist of an av integrin, the target protein that belongs to a group of Arg-Gly-Asp integrin receptors. This group of integrin receptors is thought to play a key role in idiopathic pulmonary fibrosis, a chronic lung disease of significant pharmaceutical interest. As an in silico proxy of the binding affinity, we use a molecular docking score to an experimentally determined avb6 protein structure. The search is driven by a probabilistic surrogate of the activity of all molecules from that space. As the process evolves and the algorithm observes the activity scores of the previously designed molecules, the hypothesis of the activity is refined. The algorithm is guaranteed to converge in probability to the best hypothesis from an a priori specified hypothesis space. In our empirical evaluations, the approach achieves a large structural variety of designed molecular structures for which the docking score is better than the desired threshold. Some novel molecules, suggested to be active by the surrogate model, provoke a significant interest from the perspective of medicinal chemistry and warrant prioritization for synthesis. Moreover, the approach discovered 19 out of the 24 active compounds which are known to be active from previous biological assays.

Journal Article Type Article
Journal Molecular Informatics
Print ISSN 1868-1743
Electronic ISSN 1868-1743
Publisher Wiley-VCH Verlag
Peer Reviewed Peer Reviewed
Volume 37
APA6 Citation Oglic, D., Oatley, S. A., Macdonald, S. J., McInally, T., Garnett, R., Hirst, J. D., & Gärtner, T. (in press). Active search for computer-aided drug design. Molecular Informatics, 37, doi:10.1002/minf.201700130
Keywords active search ; antagonist ; cheminformatics ; drug design ; integrin
Publisher URL
Copyright Statement Copyright information regarding this work can be found at the following address: http://eprints.nottingh.../end_user_agreement.pdf
Additional Information This is the peer reviewed version of the following article: Oglic, D., Oatley, S. A., Macdonald, S. J. F., Mcinally, T., Garnett, R., Hirst, J. D. and Gärtner, T. (2018), Active Search for Computer-Aided Drug Design. Mol. Inf.. doi:10.1002/minf.201700130 which has been published in final form at http://onlinelibrary.wi...minf.201700130/abstract

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