Volume 6 Supplement 1

9th German Conference on Chemoinformatics

Open Access

Combining pharmacophore- and MD-based modelling for phase II metabolism prediction

Journal of Cheminformatics20146(Suppl 1):O15

DOI: 10.1186/1758-2946-6-S1-O15

Published: 11 March 2014

As metabolism is considered a main cause for adverse drug reactions and failures of new drug candidates, our goal is to establish an in silico method to efficiently predict phase II metabolism – in particular sulfotransferase (SULT) activity. Since sulfotransferases exhibit low substrate specificities caused by their high degree of conformational freedom [1], activity prediction is a challenging task.

We therefore established a workflow based on molecular dynamics (MD) simulations to cover the whole spectrum of structural flexibility and incorporated it into multiple pharmacophores that represent specific modes of action. Using an ensemble of pharmacophores for virtual screening ensures accurate categorization of potential SULT ligands (e.g. substrates, inhibitors). Recent advances in MD technology [2] allowed for refinement of these pharmacophores by high-throughput MD simulations of ligand-target complexes. In addition, the initial binding process of a soluble ligand to the substrate-binding site of SULT was captured in unbiased 100 ns simulations using the software Desmond [3].

Authors’ Affiliations

(1)
Computer-Aided Drug Design, Pharmaceutical and Medicinal Chemistry, Institute of Pharmacy, Freie Universität Berlin

References

  1. Dong D, Ako R, Wu B: Crystal structures of human sulfotransferases: insights into the mechanisms of action and substrate selectivity. Expert Opin Drug Metab Toxicol. 2012, 8: 635-646. 10.1517/17425255.2012.677027.View ArticleGoogle Scholar
  2. Dror RO, et al: Biomolecular simulation: a computational microscope for molecular biology. Annu Rev Biophys. 2012, 41: 429-452. 10.1146/annurev-biophys-042910-155245.View ArticleGoogle Scholar
  3. Bowers KJ, et al: Scalable Algorithms for Molecular Dynamics Simulations on Commodity Clusters. SC 2006 Conference, Proceedings of the ACM/IEEE. 2006Google Scholar

Copyright

© Rakers and Wolber; licensee Chemistry Central Ltd. 2014

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.