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ChemGPS-NP mapping of chemical compounds for prediction of anticancer mode of action
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Medicinal Chemistry, Division of Pharmacognosy.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Clinical Pharmacology. (Cancer Pharmacology and Informatics/Rolf Larsson)
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Medicinal Chemistry, Division of Pharmacognosy.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Clinical Pharmacology. (Cancer Pharmacology and Informatics/Rolf Larsson)
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2009 (English)In: QSAR & combinatorial science (Print), ISSN 1611-020X, E-ISSN 1611-0218, Vol. 28, no 4, 436-446 p.Article in journal (Refereed) Published
Abstract [en]

A combined graph describing the growth inhibition values from a number of human cancer cell lines represents an activity profile for a compound. The fact that compounds with similar activity profiles often show similar mode of action (MOA) has frequently been used in prediction of MOA. Obtaining the profiles is demanding with respect to both time and resources. Therefore, as a work and time efficient alternative, we explore the central premise of medicinal chemistry that structurally similar molecules often have similar biological activity. In this study we investigate correlations between chemical structure and MOA, and subsequently use this as a complementing basis for prediction. The correlations between MOA and activity profile on one hand and between MOA and chemical structure on the other were analyzed for anticancer agents, classified with regard to MOA, using principal component analysis (PCA), chemographic mapping with ChemGPS-NP, and orthogonal partial least squares discriminant analysis (OPLS-DA). The compounds clustered according to MOA both based on chemical structures and activity profiles. The subsequent validation with external test sets showed that initial PCA scores prediction or chemographic mapping followed by OPLS-DA could be used for prediction of MOA as well as identification of novel MOAs in a highly accurate way. An efficient and straight forward procedure for prediction of MOA of anticancer agents is suggested. With today’s resistance problems in cancer therapy, there is a need for new anticancer agents and mechanisms. We believe that the fast initial virtual guidance this procedure implies, especially the novel step using ChemGPS-NP, could be of general use in early stages of cancer research.

Place, publisher, year, edition, pages
2009. Vol. 28, no 4, 436-446 p.
Keyword [en]
ChemGPS-NP, prediction, mode of action, anticancer agent
National Category
Pharmaceutical Sciences
Research subject
Pharmacognosy
Identifiers
URN: urn:nbn:se:uu:diva-89350DOI: 10.1002/qsar.200810162ISI: 000265462900005OAI: oai:DiVA.org:uu-89350DiVA: diva2:160191
Available from: 2009-02-12 Created: 2009-02-12 Last updated: 2017-12-14Bibliographically approved
In thesis
1. ChemGPS-NP and the Exploration of Biologically Relevant Chemical Space
Open this publication in new window or tab >>ChemGPS-NP and the Exploration of Biologically Relevant Chemical Space
2009 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Chemical space is basically infinite, and comprises all molecules that could possibly exist. Intelligent ways to efficiently navigate through chemical space and to select promising compounds in drug discovery are important tasks, and the focus of this thesis.

In this work a new model for chemical space navigation, ChemGPS-NP, was developed. This model is based on a methodology where a global chemical space map is defined through principal component analysis of physico-chemical properties of a reference set of compounds. Through interpolation from the reference set, positions of novel compounds can be defined on this map and interpreted as chemical properties.

ChemGPS-NP was demonstrated to be able to chart the entire biologically relevant chemical space, including both drug-like and natural compounds. This is an important improvement considering the present interest in natural products (NPs) in the pharmaceutical industry, as well as the track record of NPs to serve as basis for more than 50% of all marketed drugs. ChemGPS-NP proved able to handle and process large data sets, to aid in efficient selection of test objects, and to extract useful information from the results of high-throughput screening campaigns. Using ChemGPS-NP, it was shown that NPs occupy unique regions of chemical property space in comparison to drug-like compounds, and a number of features distinguishing NPs from medicinal chemistry compounds were identified.

ChemGPS-NP was also shown to be able to reliably predict mode of action of anticancer agents based on chemical structure, a finding that has potential to improve cancer research efficiency. Applying a property based similarity search based on calculated eight dimensional Euclidean distances from ChemGPS-NP rendered a tool to identify NP inspired potential leads for drug discovery.

Furthermore, ChemGPS-NPWeb, an online version of ChemGPS-NP, was developed, which provides scientists with open access to the tool via http://chemgps.bmc.uu.se/.

 

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2009. 71 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 89
National Category
Pharmaceutical Sciences
Research subject
Pharmacognosy
Identifiers
urn:nbn:se:uu:diva-89364 (URN)978-91-554-7431-7 (ISBN)
Public defence
2009-03-27, B42, BMC, Husargatan 3, Uppsala, 09:15 (English)
Opponent
Supervisors
Available from: 2009-03-04 Created: 2009-02-12 Last updated: 2009-09-04Bibliographically approved

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Backlund, AndersBohlin, LarsLarsson, Rolf

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