{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T10:37:21Z","timestamp":1772966241152,"version":"3.50.1"},"reference-count":34,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2022,9,27]],"date-time":"2022-09-27T00:00:00Z","timestamp":1664236800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Natural Science Foundation of Shandong Province in China","award":["ZR2021MB024"],"award-info":[{"award-number":["ZR2021MB024"]}]},{"name":"Natural Science Foundation of Shandong Province in China","award":["21778047"],"award-info":[{"award-number":["21778047"]}]},{"name":"Natural Science Foundation of Shandong Province in China","award":["21675138"],"award-info":[{"award-number":["21675138"]}]},{"name":"Natural Science Foundation of Shandong Province in China","award":["21705139"],"award-info":[{"award-number":["21705139"]}]},{"name":"National Natural Science Foundation of China","award":["ZR2021MB024"],"award-info":[{"award-number":["ZR2021MB024"]}]},{"name":"National Natural Science Foundation of China","award":["21778047"],"award-info":[{"award-number":["21778047"]}]},{"name":"National Natural Science Foundation of China","award":["21675138"],"award-info":[{"award-number":["21675138"]}]},{"name":"National Natural Science Foundation of China","award":["21705139"],"award-info":[{"award-number":["21705139"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Molecules"],"abstract":"<jats:p>Modern industrialization has led to the creation of a wide range of organic chemicals, especially in the form of multicomponent mixtures, thus making the evaluation of environmental pollution more difficult by normal methods. In this paper, we attempt to use forward stepwise multiple linear regression (MLR) and nonlinear radial basis function neural networks (RBFNN) to establish quantitative structure\u2013activity relationship models (QSARs) to predict the toxicity of 79 binary mixtures of aquatic organisms using different hypothetical descriptors. To search for the proper mixture descriptors, 11 mixture rules were performed and tested based on preliminary modeling results. The statistical parameters of the best derived MLR model were Ntrain = 62, R2 = 0.727, RMS = 0.494, F = 159.537, Q2LOO = 0.727, and Q2pred = 0.725 for the training set; and Ntest = 17, R2 = 0.721, RMS = 0.508, F = 38.773, and q2ext = 0.720 for the external test set. The RBFNN model gave the following statistical results: Ntrain = 62, R2 = 0.956, RMS = 0.199, F = 1279.919, Q2LOO = 0.955, and Q2pred = 0.855 for the training set; and Ntest = 17, R2 = 0.880, RMS = 0.367, F = 110.980, and q2ext = 0.853 for the external test set. The quality of the models was assessed by validating the relevant parameters, and the final results showed that the developed models are predictive and can be used for the toxicity prediction of binary mixtures within their applicability domain.<\/jats:p>","DOI":"10.3390\/molecules27196389","type":"journal-article","created":{"date-parts":[[2022,9,28]],"date-time":"2022-09-28T03:30:37Z","timestamp":1664335837000},"page":"6389","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Toxicity Assessment of the Binary Mixtures of Aquatic Organisms Based on Different Hypothetical Descriptors"],"prefix":"10.3390","volume":"27","author":[{"given":"Meng","family":"Ji","sequence":"first","affiliation":[{"name":"College of Chemistry and Chemical Engineering, Yantai University, Yantai 264005, China"}]},{"given":"Lihong","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Chemistry and Chemical Engineering, Yantai University, Yantai 264005, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8466-5071","authenticated-orcid":false,"given":"Xuming","family":"Zhuang","sequence":"additional","affiliation":[{"name":"College of Chemistry and Chemical Engineering, Yantai University, Yantai 264005, China"}]},{"given":"Chunyuan","family":"Tian","sequence":"additional","affiliation":[{"name":"College of Chemistry and Chemical Engineering, Yantai University, Yantai 264005, China"}]},{"given":"Feng","family":"Luan","sequence":"additional","affiliation":[{"name":"College of Chemistry and Chemical Engineering, Yantai University, Yantai 264005, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3375-8670","authenticated-orcid":false,"given":"Maria Nat\u00e1lia D. S.","family":"Cordeiro","sequence":"additional","affiliation":[{"name":"LAQV@REQUIMTE\/Department of Chemistry and Biochemistry, Faculty of Sciences, University of Porto, 4169-007 Porto, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1016\/j.etap.2012.02.008","article-title":"Using molecular docking between organic chemicals and lipid membrane to revise the well known octanol\u2013water partition coefficient of the mixture","volume":"34","author":"Wang","year":"2012","journal-title":"Environ. Toxicol. Pharmacol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"414","DOI":"10.1039\/C6EM00692B","article-title":"General baseline toxicity QSAR for nonpolar, polar and ionisable chemicals and their mixtures in the bioluminescence inhibition assay with Aliivibrio fischeri","volume":"19","author":"Escher","year":"2017","journal-title":"Environ. Sci. Processes Impacts"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1072","DOI":"10.1126\/science.1127291","article-title":"The challenge of micropollutants in aquatic systems","volume":"313","author":"Schwarzenbach","year":"2006","journal-title":"Science"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Rand, G.M., Wells, P.G., and McCarty, L.S. (2020). Introduction to Aquatic Toxicology\/\/Fundamentals of Aquatic Toxicology, CRC Press.","DOI":"10.1201\/9781003075363"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1385","DOI":"10.1289\/ehp.98106s61385","article-title":"Approaches to developing alternative and predictive toxicology based on PBPK\/PD and QSAR modeling","volume":"106","author":"Yang","year":"1998","journal-title":"Environ. Health Perspect."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"47844","DOI":"10.1039\/C6RA05406D","article-title":"Risk assessment of environmental mixture effects","volume":"6","author":"Heys","year":"2016","journal-title":"RSC Adv."},{"key":"ref_7","first-page":"34014","article-title":"Guidelines for the health risk assessment of chemical mixtures","volume":"51","author":"Usepa","year":"1986","journal-title":"Fed. Regist."},{"key":"ref_8","first-page":"94","article-title":"State of the art report on mixture toxicity","volume":"70307","author":"Kortenkamp","year":"2009","journal-title":"Contract"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2341","DOI":"10.1002\/etc.5620190926","article-title":"Predictability of the toxicity of multiple chemical mixtures to Vibrio fischeri: Mixtures composed of similarly acting chemicals","volume":"19","author":"Altenburger","year":"2000","journal-title":"Environ. Toxicol. Chem. Int. J."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"585","DOI":"10.1111\/j.1744-7348.1939.tb06990.x","article-title":"The toxicity of poisons jointly applied","volume":"26","author":"Bliss","year":"1939","journal-title":"Ann. Appl. Biol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"115885","DOI":"10.1016\/j.envpol.2020.115885","article-title":"Toxicity of binary mixtures of pesticides and pharmaceuticals toward Vibrio fischeri: Assessment by quantitative structure-activity relationships","volume":"275","year":"2021","journal-title":"Environ. Pollut."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1980","DOI":"10.1016\/j.chemosphere.2012.10.065","article-title":"Prediction of the baseline toxicity of non-polar narcotic chemical mixtures by QSAR approach","volume":"90","author":"Luan","year":"2013","journal-title":"Chemosphere"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Roy, K., Kar, S., and Das, R.N. (2015). A Primer on QSAR\/QSPR Modeling: Fundamental Concepts, Springer.","DOI":"10.1007\/978-3-319-17281-1"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"124936","DOI":"10.1016\/j.jhazmat.2020.124936","article-title":"Prediction of aquatic toxicity of chemical mixtures by the QSAR approach using 2D structural descriptors","volume":"408","author":"Chatterjee","year":"2021","journal-title":"J. Hazard. Mater."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"13374","DOI":"10.1021\/acsomega.8b01834","article-title":"QSPR modeling of the refractive index for diverse polymers using 2D descriptors","volume":"3","author":"Khan","year":"2018","journal-title":"ACS Omega"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"151089","DOI":"10.1016\/j.scitotenv.2021.151089","article-title":"Aquatic toxicity and aquatic ecological risk assessment of wastewater-derived halogenated phenolic disinfection byproducts","volume":"809","author":"Wang","year":"2022","journal-title":"Sci. Total Environ."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1177\/026119291304100107","article-title":"Evaluation of CADASTER QSAR models for the aquatic toxicity of (benzo) triazoles and prioritisation by consensus prediction","volume":"41","author":"Cassani","year":"2013","journal-title":"Altern. Lab. Anim."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1016\/j.ecoenv.2018.10.060","article-title":"Consensus QSAR modeling of toxicity of pharmaceuticals to different aquatic organisms: Ranking and prioritization of the DrugBank database compounds","volume":"168","author":"Khan","year":"2019","journal-title":"Ecotoxicol. Environ. Saf."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1238","DOI":"10.1021\/jm00196a017","article-title":"Chance factors in studies of quantitative structure-activity relationships","volume":"22","author":"Topliss","year":"1979","journal-title":"J. Med. Chem."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1169","DOI":"10.1016\/j.chemosphere.2013.01.081","article-title":"Using molecular docking-based binding energy to predict toxicity of binary mixture with different binding sites","volume":"92","author":"Yao","year":"2013","journal-title":"Chemosphere"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"e3171","DOI":"10.1002\/cem.3171","article-title":"Estimation of predictive performance for test data in applicability domains using y-randomization","volume":"33","author":"Kaneko","year":"2019","journal-title":"J. Chemom."},{"key":"ref_22","unstructured":"Roy, K., Kar, S., and Das, R.N. (2015). Understanding the Basics of QSAR for Applications in Pharmaceutical Sciences and Risk Assessment, Academic Press."},{"key":"ref_23","unstructured":"(2011). ChemDraw Professional 20.0.0.41, PerkinElmer Informatics, Inc."},{"key":"ref_24","unstructured":"(2000). HyperChem 6.01, Hypercube, Inc."},{"key":"ref_25","unstructured":"Stewart, J.P.P. (1989). MOPAC6.0, Quantum Chemistry Program Exchange, No.455, Indiana University."},{"key":"ref_26","unstructured":"Katritzky, A.R., Lobanov, V.S., and Karelson, M. (1995). CODESSA 2.63: T Raining Manual, University of Florida."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"202","DOI":"10.1002\/minf.201100129","article-title":"Existing and developing approaches for QSAR analysis of mixtures","volume":"31","author":"Muratov","year":"2012","journal-title":"Mol. Inform."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"2043","DOI":"10.1021\/ci050559o","article-title":"Application of QSPR to mixtures","volume":"46","author":"Ajmani","year":"2006","journal-title":"J. Chem. Inf. Modeling"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"6596","DOI":"10.1021\/acs.iecr.5b01457","article-title":"Mixture descriptors toward the development of quantitative structure\u2013property relationship models for the flash points of organic mixtures","volume":"54","author":"Gaudin","year":"2015","journal-title":"Ind. Eng. Chem. Res."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1016\/j.chemosphere.2018.01.142","article-title":"QSAR prediction of additive and non-additive mixture toxicities of antibiotics and pesticide","volume":"198","author":"Qin","year":"2018","journal-title":"Chemosphere"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/j.chemolab.2016.04.007","article-title":"A new structure-based model for estimation of true critical volume of multi-component mixtures","volume":"155","author":"Sobati","year":"2016","journal-title":"Chemom. Intell. Lab. Syst."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"2200","DOI":"10.1016\/j.neucom.2017.10.055","article-title":"A feature selection approach based on sensitivity of RBFNNs","volume":"275","author":"Zeng","year":"2018","journal-title":"Neurocomputing"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/0169-7439(95)80039-C","article-title":"Robustness analysis of radial base function and multi-layered feed-forward neural network models","volume":"28","author":"Derks","year":"1995","journal-title":"Chemom. Intell. Lab. Syst."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Wang, T., Tang, L., Luan, F., and Cordeiro, M.N.D.S. (2018). Prediction of the toxicity of binary mixtures by QSAR approach using the hypothetical descriptors. Int. J. Mol. Sci., 19.","DOI":"10.3390\/ijms19113423"}],"container-title":["Molecules"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1420-3049\/27\/19\/6389\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:40:35Z","timestamp":1760143235000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1420-3049\/27\/19\/6389"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,27]]},"references-count":34,"journal-issue":{"issue":"19","published-online":{"date-parts":[[2022,10]]}},"alternative-id":["molecules27196389"],"URL":"https:\/\/doi.org\/10.3390\/molecules27196389","relation":{},"ISSN":["1420-3049"],"issn-type":[{"value":"1420-3049","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,27]]}}}