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Chemoinformatics Profiling of Ionic LiquidsuAutomatic and Chemically Interpretable Cytotoxicity Profiling, Virtual Screening, and Cytotoxicophore Identification

Title
Chemoinformatics Profiling of Ionic LiquidsuAutomatic and Chemically Interpretable Cytotoxicity Profiling, Virtual Screening, and Cytotoxicophore Identification
Type
Article in International Scientific Journal
Year
2013
Authors
Cruz Monteagudo, M
(Author)
Other
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Ancede Gallardo, E
(Author)
Other
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Jorge, M
(Author)
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Natalia N D S Cordeiro
(Author)
FCUP
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Journal
Vol. 136
Pages: 548-565
ISSN: 1096-6080
Other information
Authenticus ID: P-008-JS1
Abstract (EN): Ionic liquids (ILs) possess a unique physicochemical profile providing a wide range of applications. Their almost limitless structural possibilities allow the design of task-specific ILs. However, their greenness, specifically their claimed relative nontoxicity has been frequently questioned, hindering their REACH registration processes and, so, their final application. Because the vast majority of ILs is yet to be synthesized, the development of chemoinformatics tools efficiently profiling their hazardous potential becomes essential. In this work, we introduce a reliable, predictive, simple, and chemically interpretable Classification and Regression Trees (CART) classifier, enabling the prioritization of ILs with a favorable cytotoxicity profile. Besides a good predictive capability (81% or 75% or 83% of accuracy or sensitivity or specificity in an external evaluation set), the other salient feature of the proposed cytotoxicity CART classifier is their simplicity and transparent chemical interpretation based on structural molecular fragments. The essentials of the current structure-cytotoxicity relationships of ILs are faithfully reproduced by this model, supporting its biophysical relevance and the reliability of the resultant predictions. By inspecting the structure of the CART, several moieties that can be regarded as cytotoxicophores were identified and used to establish a set of SAR trends specifically aimed to prioritize low-cytotoxicity ILs. Finally, we demonstrated the suitability of the joint use of the CART classifier and a group fusion similarity search as a virtual screening strategy for the automatic prioritization of safe ILs disperse in a data set of ILs of moderate to very high cytotoxicity.
Language: English
Type (Professor's evaluation): Scientific
No. of pages: 18
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