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Generalized proteochemometric model of multiple cytochrome P450 enzymes and their inhibitors
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics. (Proteochemometric group)
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. (Proteochemometric group)
2008 (English)In: Journal of chemical information and modeling, ISSN 1549-9596, Vol. 48, no 9, 1840-1850 p.Article in journal (Refereed) Published
Abstract [en]

Cytochrome P450 enzymes are a superfamily of heme-containing enzymes responsible for the oxidation of structurally diverse chemical Compounds. Inhibition of CYP enzymes is probably the most common mechanism underlying acute drug toxicity, loss of therapeutic drug efficacy, and drug-drug interactions. The presence of polymorphic genetic variants of CYPs among the population makes it difficult to foresee undesired effects of drugs and is a common cause of drug candidate failure. Computational models that can predict early drug failures due to the inhibition of CYP isoforms can substantially reduce the cost of drug development. Although several computational models for CYP inhibition have been developed recently, all were constructed for one CYP isoform at a time, thus limiting their use for comprehensive analysis and generalizations to other CYP isoforms and polymorphisms. Here we report a novel approach based on the principles of proteochemometrics for the generalized concomitant modeling of multiple CYP isoforms and their inhibitors. We created a predictive and statistically valid proteochemometric model for CYP enzymes by combining data from a large number of publicly available reports that describe the interactions of 14 CYP enzyme subtypes and 375 structurally diverse inhibitors. Our results demonstrate that Our model is capable of predicting the potential of new drug candidates to inhibit Multiple CYP enzymes. Analysis of the CYP model also revealed molecular properties of CYP enzymes and xenobiotics that are important for CYP inhibition. This approach may aid in the selection of novel drug, candidates that are unlikely to inhibit multiple CYP subtypes.

Place, publisher, year, edition, pages
2008. Vol. 48, no 9, 1840-1850 p.
National Category
Pharmaceutical Sciences
Identifiers
URN: urn:nbn:se:uu:diva-97335DOI: 10.1021/ci8000953ISI: 000259398500011PubMedID: 18693719OAI: oai:DiVA.org:uu-97335DiVA: diva2:172222
Available from: 2008-05-15 Created: 2008-05-15 Last updated: 2009-08-28Bibliographically approved
In thesis
1. Modeling the Interaction Space of Biological Macromolecules: A Proteochemometric Approach: Applications for Drug Discovery and Development
Open this publication in new window or tab >>Modeling the Interaction Space of Biological Macromolecules: A Proteochemometric Approach: Applications for Drug Discovery and Development
2008 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Molecular interactions lie at the heart of myriad biological processes. Knowledge of molecular recognition processes and the ability to model and predict interactions of any biological molecule to any chemical compound are the key for better understanding of cell functions and discovery of more efficacious medicines.

This thesis presents contributions to the development of a novel chemo-bioinformatics approach called proteochemometrics; a general method for interaction space analysis of biological macromolecules and their ligands. In this work we explore proteochemometrics-based interaction models over broad groups of protein families, evaluate their validity and scope, and compare proteochemometrics to traditional modeling approaches.

Through the proteochemometric analysis of large interaction data sets of multiple retroviral proteases from various viral species we investigate complex mechanisms of drug resistance in HIV-1 and discover general physicochemical determinants of substrate cleavage efficiency and binding in retroviral proteases. We further demonstrate how global proteochemometric models can be used for design of protease inhibitors with broad activity on drug-resistant viral mutants, for monitoring drug resistance mechanisms in the physicochemical sense and prediction of potential HIV-1 evolution trajectories. We provide novel insights into the complexity of HIV-1 protease specificity by constructing a generalized IF-THEN rule model based on bioinformatics analysis of the largest set of HIV-1 protease substrates and non-substrates.

We discuss how proteochemometrics can be used to map recognition sites of entire protein families in great detail and demonstrate how it can incorporate target variability into drug discovery process. Finally, we assess the utility of the proteochemometric approach in evaluation of ADMET properties of drug candidates with a special focus on inhibition of cytochrome P450 enzymes and investigate application of the approach in the pharmacogenomics field.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2008. 77 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 444
Keyword
Bioinformatics, proteochemometrics, bioinformatics, chemoinformatics, chemical space, QSAR, retroviral proteases, HIV-1, drug resistance, pharmacogenomics, cytochrome P450, GPCRs, melanocortin receptors, interactome, machine-learning, rough sets, Bioinformatik
Identifiers
urn:nbn:se:uu:diva-8916 (URN)978-91-554-7229-0 (ISBN)
Public defence
2008-06-04, C10:305, BMC, Husargatan 3, Uppsala, 09:00
Opponent
Supervisors
Available from: 2008-05-15 Created: 2008-05-15Bibliographically approved

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