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

• Type: Article in International Scientific Journal
• Date: 2013

Authors

Cruz Monteagudo, M (Author) Other; Ancede Gallardo, E (Author) Other; Jorge, M (Author) Other; Natalia N D S Cordeiro (Author) FCUP

Journal

Title: Toxicological Sciences

Vol. 136

Pages: 548-565

ISSN: 1096-6080

Publisher: Oxford University Press

Indexing

ISI Web of Knowledge - 20 Citations

Scopus - 21 Citations

Other information

Authenticus ID: P-008-JS1

DOI: 10.1093/toxsci/kft209

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