Send to:

Choose Destination
See comment in PubMed Commons below
Bioorg Med Chem. 2010 Jan 1;18(1):320-9. doi: 10.1016/j.bmc.2009.10.052. Epub 2009 Oct 31.

In silico prediction of human carboxylesterase-1 (hCES1) metabolism combining docking analyses and MD simulations.

Author information

  • 1Dipartimento di Scienze Farmaceutiche Pietro Pratesi, Facolt√† di Farmacia, Universit√† degli Studi di Milano, Via Mangiagalli 25, I-20133 Milano, Italy.


Metabolic problems lead to numerous failures during clinical trials, and much effort is now devoted in developing in silico models predicting metabolic stability and metabolites. Such models are well known for cytochromes P450 and some transferases, whereas little has been done to predict the hydrolytic activity of human hydrolases. The present study was undertaken to develop a computational approach able to predict the hydrolysis of novel esters by human carboxylesterase hCES1. The study involves both docking analyses of known substrates to develop predictive models, and molecular dynamics (MD) simulations to reveal the in situ behavior of substrates and products, with particular attention being paid to the influence of their ionization state. The results emphasize some crucial properties of the hCES1 catalytic cavity, confirming that as a trend with several exceptions, hCES1 prefers substrates with relatively smaller and somewhat polar alkyl/aryl groups and larger hydrophobic acyl moieties. The docking results underline the usefulness of the hydrophobic interaction score proposed here, which allows a robust prediction of hCES1 catalysis, while the MD simulations show the different behavior of substrates and products in the enzyme cavity, suggesting in particular that basic substrates interact with the enzyme in their unprotonated form.

Copyright (c) 2009 Elsevier Ltd. All rights reserved.

[PubMed - indexed for MEDLINE]

LinkOut - more resources

Full Text Sources

Other Literature Sources

PubMed Commons home

PubMed Commons

How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for Elsevier Science
    Loading ...
    Write to the Help Desk