Literature DB >> 18484912

Computational prediction of drug binding and rationalisation of selectivity towards cytochromes P450.

Eva Stjernschantz1, Nico P E Vermeulen, Chris Oostenbrink.   

Abstract

BACKGROUND: Early in-vitro consideration of metabolism and inhibition of cytochrome P450 has proven its merits over the last 15 years. Simultaneously, many computational drug-design methods have been developed, and are being applied to study the interactions between drug candidates and cytochrome P450 enzymes (P450s).
OBJECTIVE: This review discusses the recent advances of these methods and the implications that are specific for P450s.
METHODS: Mainly focusing on the prediction of binding affinity and ligand selectivity, we outline the applicability of the different methods to answer specific questions. Special emphasis is put on the different levels of theory that are being used in recent computational descriptions of ligand-P450 interactions.
CONCLUSION: P450s offer an additional challenge for computational methods, considering the ambiguities of the catalytic cycle and the significant flexibility of the active site. Different computational methods display different limitations, which is crucial to take into account when choosing the method appropriate to each application.

Mesh:

Substances:

Year:  2008        PMID: 18484912     DOI: 10.1517/17425255.4.5.513

Source DB:  PubMed          Journal:  Expert Opin Drug Metab Toxicol        ISSN: 1742-5255            Impact factor:   4.481


  21 in total

1.  Improved ligand-protein binding affinity predictions using multiple binding modes.

Authors:  Eva Stjernschantz; Chris Oostenbrink
Journal:  Biophys J       Date:  2010-06-02       Impact factor: 4.033

2.  Combination of docking, molecular dynamics and quantum mechanical calculations for metabolism prediction of 3,4-methylenedioxybenzoyl-2-thienylhydrazone.

Authors:  Rodolpho C Braga; Vinícius M Alves; Carlos A M Fraga; Eliezer J Barreiro; Valéria de Oliveira; Carolina H Andrade
Journal:  J Mol Model       Date:  2011-09-08       Impact factor: 1.810

3.  Comparative proteomics among cytochrome p450 family 1 for differential substrate specificity.

Authors:  Siddharth S Kesharwani; Prajwal P Nandekar; Preeti Pragyan; Abhay T Sangamwar
Journal:  Protein J       Date:  2014-12       Impact factor: 2.371

4.  Homology modeling and metabolism prediction of human carboxylesterase-2 using docking analyses by GriDock: a parallelized tool based on AutoDock 4.0.

Authors:  Giulio Vistoli; Alessandro Pedretti; Angelica Mazzolari; Bernard Testa
Journal:  J Comput Aided Mol Des       Date:  2010-07-11       Impact factor: 3.686

5.  SMARTCyp: A 2D Method for Prediction of Cytochrome P450-Mediated Drug Metabolism.

Authors:  Patrik Rydberg; David E Gloriam; Jed Zaretzki; Curt Breneman; Lars Olsen
Journal:  ACS Med Chem Lett       Date:  2010-03-15       Impact factor: 4.345

6.  Potentially increasing the metabolic stability of drug candidates via computational site of metabolism prediction by CYP2C9: The utility of incorporating protein flexibility via an ensemble of structures.

Authors:  Matthew L Danielson; Prashant V Desai; Michael A Mohutsky; Steven A Wrighton; Markus A Lill
Journal:  Eur J Med Chem       Date:  2011-06-23       Impact factor: 6.514

7.  Predicting Mouse Liver Microsomal Stability with "Pruned" Machine Learning Models and Public Data.

Authors:  Alexander L Perryman; Thomas P Stratton; Sean Ekins; Joel S Freundlich
Journal:  Pharm Res       Date:  2015-09-28       Impact factor: 4.200

Review 8.  Computational prediction of metabolism: sites, products, SAR, P450 enzyme dynamics, and mechanisms.

Authors:  Johannes Kirchmair; Mark J Williamson; Jonathan D Tyzack; Lu Tan; Peter J Bond; Andreas Bender; Robert C Glen
Journal:  J Chem Inf Model       Date:  2012-02-17       Impact factor: 4.956

9.  In silico toxicology - non-testing methods.

Authors:  Hannu Raunio
Journal:  Front Pharmacol       Date:  2011-06-30       Impact factor: 5.810

Review 10.  Modeling of interactions between xenobiotics and cytochrome P450 (CYP) enzymes.

Authors:  Hannu Raunio; Mira Kuusisto; Risto O Juvonen; Olli T Pentikäinen
Journal:  Front Pharmacol       Date:  2015-06-12       Impact factor: 5.810

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