Next Article in Journal
Design, Synthesis and Bioactivities of Novel 1,4-Pentadien-3-one Derivatives Containing a Substituted Pyrazolyl Moiety
Previous Article in Journal
Substituted Caffeic and Ferulic Acid Phenethyl Esters: Synthesis, Leukotrienes Biosynthesis Inhibition, and Cytotoxic Activity
Article Menu
Issue 7 (July) cover image

Export Article

Open AccessArticle
Molecules 2017, 22(7), 1128;

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

Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Pawinskiego 5a, 02-106 Warsaw, Poland
Department of Systems Biology, Institute of Experimental Plant Biology and Biotechnology, University of Warsaw, Miecznikowa 1, 02-096 Warsaw, Poland
Author to whom correspondence should be addressed.
Received: 18 May 2017 / Revised: 30 June 2017 / Accepted: 4 July 2017 / Published: 6 July 2017
Full-Text   |   PDF [372 KB, uploaded 7 July 2017]   |  


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 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. View Full-Text
Keywords: molecule representation; ligand-based screening; pharmacophore; bioactivity prediction molecule representation; ligand-based screening; pharmacophore; bioactivity prediction

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Supplementary material


Share & Cite This Article

MDPI and ACS Style

Stepniewska-Dziubinska, M.M.; Zielenkiewicz, P.; Siedlecki, P. DeCAF—Discrimination, Comparison, Alignment Tool for 2D PHarmacophores. Molecules 2017, 22, 1128.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Molecules EISSN 1420-3049 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top