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DeCAF—Discrimination, Comparison, Alignment Tool for 2D PHarmacophores

Stepniewska-Dziubinska, Marta M. and Zielenkiewicz, Piotr and Siedlecki, Paweł (2017) DeCAF—Discrimination, Comparison, Alignment Tool for 2D PHarmacophores. Molecules, 22 (7). p. 1128. ISSN 1420-3049

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Official URL: http://doi.org/10.3390/molecules22071128


Comparison of small molecules is a common component of many cheminformatics workflows, including the design of new compounds and libraries as well as side-effect predictions and drug repurposing. Currently, large-scale comparison methods rely mostly on simple fingerprint representation of molecules, which take into account the structural similarities of compounds. Methods that utilize 3D information depend on multiple conformer generation steps, which are computationally expensive and can greatly influence their results. The aim of this study was to augment molecule representation with spatial and physicochemical properties while simultaneously avoiding conformer generation. To achieve this goal, we describe a molecule as an undirected graph in which the nodes correspond to atoms with pharmacophoric properties and the edges of the graph represent the distances between features. This approach combines the benefits of a conformation-free representation of a molecule with additional spatial information. We implemented our approach as an open-source Python module called DeCAF (Discrimination, Comparison, Alignment tool for 2D PHarmacophores), freely available at http://bitbucket.org/marta-sd/decaf. We show DeCAF’s strengths and weaknesses with usage examples and thorough statistical evaluation. Additionally, we show that our method can be manually tweaked to further improve the results for specific tasks. The full dataset on which DeCAF was evaluated and all scripts used to calculate and analyze the results are also provided.

Item Type:Article
Subjects:Q Science > QA Mathematics > QA76 Computer software
Q Science > QD Chemistry
Divisions:Department of Bioinformatics
ID Code:1360
Deposited By: Marta M. Stepniewska-Dziubinska
Deposited On:11 Jul 2017 07:25
Last Modified:11 Jul 2017 07:25

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