EventsMOL2NET'19, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 5th ed.
Event submissions
Published
with-doi10.3390/mol2net-05-06715
This submission belongs to the session 03. NICEXSM-05: North-Ibero-American Congress on Exp. and Simul. Methods, Valencia, Bilbao, Spain-Miami, USA, 2019 of the event MOL2NET'19, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 5th ed.
Published date
27 Nov, 2019
Citation
Juan Alberto Castillo-Garit, Yuleidis González Pérez, Eberts M Albear, Elizabeth Rodríguez, Virginia Pérez-Doñate, Facundo Pérez-Giménez, Prediction of potential environmental toxicity of chemicals in Lactuca sativa seed germination using computational tools, in Proceedings of MOL2NET'19, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 5th ed., 20 March–20 December 2019, MDPI: Basel, Switzerland, doi: 10.3390/mol2net-05-06715
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Prediction of potential environmental toxicity of chemicals in Lactuca sativa seed germination using computational tools

Juan Alberto Castillo-Garit 1,2
Yuleidis González Pérez 3
Eberts M Albear 4
Elizabeth Rodríguez 4
Virginia Pérez-Doñate 5
Facundo Pérez-Giménez 6
1. Unidad de Toxicología Experimental, Universidad de Ciencias Médicas de Villa Clara, Santa Clara, Villa Clara, Cuba. CP: 50200, Cuba
2. Bioinformatic Research in Systems & Computer Engineering, Carleton University, Ottawa, Canada
3. Laboratorio de Ecotoxicología del Centro de Toxicología y Biomedicina de Santiago de Cuba
4. Laboratorio de Ecotoxicología del Centro de Toxicología y Biomedicina de Santiago de Cuba.
5. Departamento de Microbiología. Hospital Universitario de la Ribera (Valencia).
6. Unidad de Investigación de Diseño de Fármacos y Conectividad Molecular. Departamento de Química Física. Facultad de Farmacia. Universitat de València.
Abstract

The main aim of the study was to develop quantitative structure-activity relationship (QSAR) models for the prediction of phytotoxicity effects of chemical compounds on the Lactuca sativa seeds germination. A database of 73 compounds, assayed against L. sativa and Dragon’s molecular descriptors are used to obtain a QSAR model for the prediction of the phytotoxicity. The model is carried out with QSARINS software and validated according to OECD principles. The best model showed good value for the determination coefficient (R2 = 0.917) and others parameters appropriate for fitting (s = 0.256 and RMSEtr= 0.236). The validation results confirmed that the model has good robustness and stability (Q2LOO = 0.874 and Q2LMO= 0.875), an excellent predictive power (R2ext = 0.896) and was product of a non-random correlation (R2Y-scr = 0.130 and Q2Y-scr = -0.265). Finally, we can say that this model is a good predictor tool to predict the toxicity over L. sativa of chemical compounds.

Keywords
ecotoxicity
Lactuca sativa
phytotoxicity
QSARINS software
Manuscript
Mol2Net-Lactuca.pdf
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