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Sengottiyan S, Mikolajczyk A, Jagiełło K, Swirog M, Puzyn T. Core, Coating, or Corona? The Importance of Considering Protein Coronas in nano-QSPR Modeling of Zeta Potential. ACS Nano 2023; 17:1989-1997. [PMID: 36651824 PMCID: PMC9933600 DOI: 10.1021/acsnano.2c06977] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 01/04/2023] [Indexed: 06/17/2023]
Abstract
To control stability in a biological medium, several factors affecting the zeta potential (ζ) of nanoparticles (NPs) must be considered, including complex interactions between the nanostructure and the composition of the protein corona (PC). Effective in silico methods (based on machine learning and quantitative structure-property relationship (QSPR) models) could help predict and characterize the relationship between the physicochemical properties of NP and the formation of PC and biological outcomes in the medium at an early stage of the experiment. However, the models currently developed are limited to simple descriptors that do not represent the complex interactions between the core, the coating, and their PC fingerprints. To be useful, the models developed should be described as a function of both the structural properties determined by the core and coating of the NPs and the biological medium determined by the formation of the protein corona. We have developed a set of complex descriptors that describe the quantitative relationship between the value of the zeta potential (ζ), core, the coating of NPs, and their PC fingerprints (the so-called nano-QSPR model). The nano-QSPR model was developed based on a genetic algorithm using a partial least-squares regression method (GA-PLS), which is characterized by high external predictive power (Q2EXT = 0.89). The GA-PLS model was developed using descriptors that describe (i) the core structure (determined by 7 different types of polymer-based NMs in the range of 20 different sizes), (ii) the coating structure with 7 different functional groups, and (iii) 80 different types of protein compositions adsorbed on the surface of the NPs. The presented study answers the question of how complex interactions between the corona and NP determine the zeta potential (ζ) of NP in a given medium. Moreover, our current study is a proof-of-concept that the zeta potential of NPs modeled on the original structure depends not only on the NPs themselves but also on the structure and properties determined by the NP core and coating, as well as the biological medium determined by the formation of the protein corona. On the basis of these results, our studies will be useful in determining the stability and mechanism of cell uptake, toxicity, and ability to predict the zeta potential of compounds not yet tested.
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Affiliation(s)
- Selvaraj Sengottiyan
- Laboratory
of Environmental Chemoinformatics, Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, Gdansk80-308, Poland
| | - Alicja Mikolajczyk
- Laboratory
of Environmental Chemoinformatics, Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, Gdansk80-308, Poland
- QSARLab, Trzy Lipy 3, 80-172Gdansk, Poland
| | - Karolina Jagiełło
- Laboratory
of Environmental Chemoinformatics, Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, Gdansk80-308, Poland
- QSARLab, Trzy Lipy 3, 80-172Gdansk, Poland
| | - Marta Swirog
- Laboratory
of Environmental Chemoinformatics, Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, Gdansk80-308, Poland
| | - Tomasz Puzyn
- Laboratory
of Environmental Chemoinformatics, Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, Gdansk80-308, Poland
- QSARLab, Trzy Lipy 3, 80-172Gdansk, Poland
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Swirog M, Mikolajczyk A, Jagiello K, Jänes J, Tämm K, Puzyn T. Predicting electrophoretic mobility of TiO 2, ZnO, and CeO 2 nanoparticles in natural waters: The importance of environment descriptors in nanoinformatics models. Sci Total Environ 2022; 840:156572. [PMID: 35710003 DOI: 10.1016/j.scitotenv.2022.156572] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 05/16/2022] [Accepted: 06/05/2022] [Indexed: 06/15/2023]
Abstract
Natural and engineered nanoparticles (NPs) entering the environment are influenced by many physicochemical processes and show various behavior in different systems (e.g., natural waters showing different characteristics). Determining the physicochemical characteristics and predicting the behavior of nanoparticles ending up in the natural aquatic environment are key aspects of their risk assessment. Here, we show that the quantitative structure-property relationship modeling method used in nanoinformatics (nano-QSPR) can be successfully applied to predict environmental fate-relevant properties (electrophoretic mobility) of TiO2, ZnO, and CeO2 nanoparticles. However, in contrast to the previous works, we postulate to use, in parallel: (i) the nanoparticles' structure descriptors (S-descriptors) and (ii) the environment descriptors (E-descriptors) as the input variables. Thus, the method should be abbreviated more precisely as nano-QSEPR ("E" stands for the "environment"). As a proof-of-the-concept, we have developed a group of models (including MLR, GA-PLS, PCR, and Meta-Consensus models) with high predictive capabilities (QEXT2 = 0.931 for the GA-PLS model), where the S-descriptors are represented by the core-shell model descriptor and the E-descriptors - by different ambient water features (including ions concentration and the ionic strength). The newly proposed nano-QSEPR modeling scheme can be efficiently used to design safe and sustainable nanomaterials.
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Affiliation(s)
- Marta Swirog
- Laboratory of Environmental Chemoinformatics, Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, 80-308 Gdańsk, Poland
| | - Alicja Mikolajczyk
- Laboratory of Environmental Chemoinformatics, Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, 80-308 Gdańsk, Poland; QSAR Lab Sp. Z o. o., Trzy Lipy 3, 80-172, Poland.
| | - Karolina Jagiello
- Laboratory of Environmental Chemoinformatics, Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, 80-308 Gdańsk, Poland; QSAR Lab Sp. Z o. o., Trzy Lipy 3, 80-172, Poland
| | - Jaak Jänes
- Institute of Chemistry, University of Tartu, Ravila 14A, Tartu 50411, Estonia
| | - Kaido Tämm
- Institute of Chemistry, University of Tartu, Ravila 14A, Tartu 50411, Estonia
| | - Tomasz Puzyn
- Laboratory of Environmental Chemoinformatics, Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, 80-308 Gdańsk, Poland; QSAR Lab Sp. Z o. o., Trzy Lipy 3, 80-172, Poland.
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Jagiello K, Grzonkowska M, Swirog M, Ahmed L, Rasulev B, Avramopoulos A, Papadopoulos MG, Leszczynski J, Puzyn T. Advantages and limitations of classic and 3D QSAR approaches in nano-QSAR studies based on biological activity of fullerene derivatives. J Nanopart Res 2016; 18:256. [PMID: 27642255 PMCID: PMC5003910 DOI: 10.1007/s11051-016-3564-1] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2016] [Accepted: 08/18/2016] [Indexed: 05/19/2023]
Abstract
In this contribution, the advantages and limitations of two computational techniques that can be used for the investigation of nanoparticles activity and toxicity: classic nano-QSAR (Quantitative Structure-Activity Relationships employed for nanomaterials) and 3D nano-QSAR (three-dimensional Quantitative Structure-Activity Relationships, such us Comparative Molecular Field Analysis, CoMFA/Comparative Molecular Similarity Indices Analysis, CoMSIA analysis employed for nanomaterials) have been briefly summarized. Both approaches were compared according to the selected criteria, including: efficiency, type of experimental data, class of nanomaterials, time required for calculations and computational cost, difficulties in the interpretation. Taking into account the advantages and limitations of each method, we provide the recommendations for nano-QSAR modellers and QSAR model users to be able to determine a proper and efficient methodology to investigate biological activity of nanoparticles in order to describe the underlying interactions in the most reliable and useful manner.
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Affiliation(s)
- Karolina Jagiello
- Laboratory of Environmental Chemometrics, Faculty of Chemistry, Institute for Environmental and Human Health Protection, University of Gdansk, Wita Stwosza 63, 80-308 Gdansk, Poland
| | - Monika Grzonkowska
- Laboratory of Environmental Chemometrics, Faculty of Chemistry, Institute for Environmental and Human Health Protection, University of Gdansk, Wita Stwosza 63, 80-308 Gdansk, Poland
| | - Marta Swirog
- Laboratory of Environmental Chemometrics, Faculty of Chemistry, Institute for Environmental and Human Health Protection, University of Gdansk, Wita Stwosza 63, 80-308 Gdansk, Poland
| | - Lucky Ahmed
- Interdisciplinary Nanotoxicity Center, Department of Chemistry and Biochemistry, Jackson State University, 1400 JR Lynch Street, Jackson, MS 39217-0510 USA
| | - Bakhtiyor Rasulev
- Interdisciplinary Nanotoxicity Center, Department of Chemistry and Biochemistry, Jackson State University, 1400 JR Lynch Street, Jackson, MS 39217-0510 USA
- Center for Computationally Assisted Science and Technology, North Dakota State University, 1805 NDSU Research Park Drive, Post Office Box 6050, Fargo, ND 58108 USA
| | - Aggelos Avramopoulos
- Institute of Biology, Pharmaceutical Chemistry and Biotechnology, National Hellenic Research Foundation, 48 Vas. Constantinou Ave., 11635 Athens, Greece
| | - Manthos G. Papadopoulos
- Institute of Biology, Pharmaceutical Chemistry and Biotechnology, National Hellenic Research Foundation, 48 Vas. Constantinou Ave., 11635 Athens, Greece
| | - Jerzy Leszczynski
- Interdisciplinary Nanotoxicity Center, Department of Chemistry and Biochemistry, Jackson State University, 1400 JR Lynch Street, Jackson, MS 39217-0510 USA
| | - Tomasz Puzyn
- Laboratory of Environmental Chemometrics, Faculty of Chemistry, Institute for Environmental and Human Health Protection, University of Gdansk, Wita Stwosza 63, 80-308 Gdansk, Poland
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