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Varsou DD, Afantitis A, Tsoumanis A, Papadiamantis A, Valsami-Jones E, Lynch I, Melagraki G. Zeta-Potential Read-Across Model Utilizing Nanodescriptors Extracted via the NanoXtract Image Analysis Tool Available on the Enalos Nanoinformatics Cloud Platform. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2020; 16:e1906588. [PMID: 32174008 DOI: 10.1002/smll.201906588] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Revised: 02/07/2020] [Indexed: 06/10/2023]
Abstract
Zeta potential is one of the most critical properties of nanomaterials (NMs) which provides an estimation of the surface charge, and therefore electrostatic stability in medium and, in practical terms, influences the NM's tendency to form agglomerates and to interact with cellular membranes. This paper describes a robust and accurate read-across model to predict NM zeta potential utilizing as the input data a set of image descriptors derived from transmission electron microscopy (TEM) images of the NMs. The image descriptors are calculated using NanoXtract (http://enaloscloud.novamechanics.com/EnalosWebApps/NanoXtract/), a unique online tool that generates 18 image descriptors from the TEM images, which can then be explored by modeling to identify those most predictive of NM behavior and biological effects. NM TEM images are used to develop a model for prediction of zeta potential based on grouping of the NMs according to their nearest neighbors. The model provides interesting insights regarding the most important similarity features between NMs-in addition to core composition the main elongation emerged, which links to key drivers of NM toxicity such as aspect ratio. Both the NanoXtract image analysis tool and the validated model for zeta potential (http://enaloscloud.novamechanics.com/EnalosWebApps/ZetaPotential/) are freely available online through the Enalos Nanoinformatics platform.
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Affiliation(s)
- Dimitra-Danai Varsou
- Nanoinformatics Department, NovaMechanics Ltd., Nicosia, 1065, Cyprus
- School of Chemical Engineering, National Technical University of Athens, Athens, 15780, Greece
| | - Antreas Afantitis
- Nanoinformatics Department, NovaMechanics Ltd., Nicosia, 1065, Cyprus
| | - Andreas Tsoumanis
- Nanoinformatics Department, NovaMechanics Ltd., Nicosia, 1065, Cyprus
| | - Anastasios Papadiamantis
- School of Geography, Earth and Environmental Sciences, University of Birmingham, B152TT, Birmingham, UK
| | - Eugenia Valsami-Jones
- School of Geography, Earth and Environmental Sciences, University of Birmingham, B152TT, Birmingham, UK
| | - Iseult Lynch
- School of Geography, Earth and Environmental Sciences, University of Birmingham, B152TT, Birmingham, UK
| | - Georgia Melagraki
- Nanoinformatics Department, NovaMechanics Ltd., Nicosia, 1065, Cyprus
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Toropov AA, Toropova AP. Use of the index of ideality of correlation to improve predictive potential for biochemical endpoints. Toxicol Mech Methods 2018; 29:43-52. [PMID: 30064284 DOI: 10.1080/15376516.2018.1506851] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
The CORAL software is a tool to build up quantitative structure-property/activity relationships (QSPRs/QSARs). The project of updated version of the CORAL software is discussed in terms of practical applications for building up various models. The updating is the possibility to improve the predictive potential of models using the so-called Index of Ideality of Correlation (IIC) as a criterion of the predictive potential for QSPR/QSAR models. Efficacy of the IIC is examined with three examples of building up QSARs: (i) models for anticancer activity; (ii) models for mutagenicity; and (iii) models for toxicity of psychotropic drugs. The validation of these models has been carried out with several splits into the training, invisible training, calibration, and validation sets. The ability of IIC to be an indicator of predictive potential of QSAR models is confirmed. The updated version of the CORAL software (CORALSEA-2017, http://www.insilico.eu/coral ) is available on the Internet.
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Affiliation(s)
- Andrey A Toropov
- a Department of Environmental Health Science, Laboratory of Environmental Chemistry and Toxicology , Istituto di Ricerche Farmacologiche Mario Negri IRCCS , Milano , Italy
| | - Alla P Toropova
- a Department of Environmental Health Science, Laboratory of Environmental Chemistry and Toxicology , Istituto di Ricerche Farmacologiche Mario Negri IRCCS , Milano , Italy
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