In silico tools used for the prediction of the environmental risk of pesticides under the EU legislation

• Autores: Juan José Villaverde
• Directores de la Tesis: Al Mokhtar Lamsabhi Belmeknassi (dir. tes.), Pilar Sandín España (codir. tes.), Manuel Alcamí Pertejo (tut. tes.)
• Lectura: En la Universidad Autónoma de Madrid ( España ) en 2022
• Idioma: inglés
• Número de páginas: 267
• Títulos paralelos:
  • Herramientas in silico utilizadas para la predicción del riesgo medioambiental de los pesticidas según la legislación de la UE
• Tribunal Calificador de la Tesis: Ibon Alkorta Osoro (presid.), Sergio Díaz-Tendero Victoria (secret.), Thierry Dagnac (voc.), José Oriol Magrans Soria (voc.), Fabienne Bessac (voc.)
• Programa de doctorado: Programa de Doctorado en Química Teórica y Modelización Computacional/Theoretical Chemistry and Computational Modelling por la Universidad Autónoma de Madrid; la Universidad Complutense de Madrid; la Universidad de Barcelona; la Universidad de Cantabria; la Universidad de Extremadura; la Universidad de las Illes Balears; la Universidad de Murcia; la Universidad de Oviedo; la Universidad de Sevilla; la Universidad de Vigo; la Universidad del País Vasco/Euskal Herriko Unibertsitatea; la Universidad Jaume I de Castellón y la Universitat de València (Estudi General)
• Materias:
  • Física
    • Física molecular
      • Estructura molecular
• Enlaces
  • Tesis en acceso abierto en: Biblos-e Archivo
• Resumen

  • The work developed in this thesis aims to contribute to the improvement of the risk assessment process of active substances used to the protection of crops and their formulations and consequently also to their respective approval and authorization processes, especially at European level. To achieve this, it is analysed how computational-based chemical technologies can contribute to the study of the degradation processes suffered by these chemical compounds, reducing the number of experimental tests to be performed and avoiding those performed on vertebrate animals. In this sense, Ab initio calculations using the Density Functional Theory (DFT) and the use of models based on Quantitative Structure-Activity / Structure-Property Relationships (QSARs / QSPRs) have made possible to estimate and explain the behaviour of cyclohexanedione oximes (CHD) as a particular case of study. In addition, they have been of special interest for the study of their degradation products (DPs), which in many cases have a persistence and / or (eco) toxicity higher than that of the substance of origin and it is not possible to approach their study from an exclusively experimental point of view. Finally, these computational tools have also shown a great capacity to obtain data of interest that could be used in exposure models, to then perform an estimation of their risk for the environment and human and animal health (non-target species).