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In Silico Target Prediction for Small Molecules

  • Ryan Byrne
  • Gisbert Schneider
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1888)

Abstract

Drugs modulate disease states through their actions on targets in the body. Determining these targets aids the focused development of new treatments, and helps to better characterize those already employed. One means of accomplishing this is through the deployment of in silico methodologies, harnessing computational analytical and predictive power to produce educated hypotheses for experimental verification. Here, we provide an overview of the current state of the art, describe some of the well-established methods in detail, and reflect on how they, and emerging technologies promoting the incorporation of complex and heterogeneous data-sets, can be employed to improve our understanding of (poly)pharmacology.

Key words

Chemoinformatics Computer-assisted drug design Machine-learning Network pharmacology Polypharmacology 

Notes

Acknowledgment

This research was supported by the European Union Framework Programme for Research and Innovation (Horizon 2020, Marie Skłodowska-Curie ITN grant number 675555 ‘AEGIS’), and the OPO-Foundation Zurich.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Chemistry and Applied BiosciencesSwiss Federal Institute of Technology (ETH)ZurichSwitzerland

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