Literature DB >> 16710808

A topological substructural molecular design to predict soil sorption coefficients for pesticides.

Maykel Pérez González1, Aliuska Morales Helguera, Isidro G Collado.   

Abstract

A TOPological Sub-structural MOlecular DEsign (TOPS-MODE) approach was used to predict the soil sorption coefficients for a set of pesticide compounds. The obtained model accounted for more than 85% of the data variance and demonstrated the importance of the dipole moment, the standard distance, the polarizability, and the hydrophobicity in describing the property under study. In addition, we compared this new model to a previous one using different descriptors such as WHIM and molecular connectivity indices. Finally, the TOPS-MODE was used to calculate the contribution of different fragments to the soil sorption coefficient of the compounds studied. The present approximation proved to be a good method for studying the soil sorption coefficient for pesticides, but it could also be extended to other series of chemicals.

Entities:  

Mesh:

Substances:

Year:  2006        PMID: 16710808     DOI: 10.1007/s11030-005-9004-2

Source DB:  PubMed          Journal:  Mol Divers        ISSN: 1381-1991            Impact factor:   2.943


  5 in total

1.  Modelling and prediction of soil sorption coefficients of non-ionic organic pesticides by molecular descriptors.

Authors:  P Gramatica; M Corradi; V Consonni
Journal:  Chemosphere       Date:  2000-09       Impact factor: 7.086

2.  Reliable QSAR for estimating Koc for persistent organic pollutants: correlation with molecular connectivity indices.

Authors:  J R Baker; J R Mihelcic; A Sabljic
Journal:  Chemosphere       Date:  2001-10       Impact factor: 7.086

3.  TOPS-MODE based QSARs derived from heterogeneous series of compounds. Applications to the design of new herbicides.

Authors:  Maykel Pérez González; Humberto Gonzalez Díaz; Reinaldo Molina Ruiz; Miguel A Cabrera; Ronal Ramos de Armas
Journal:  J Chem Inf Comput Sci       Date:  2003 Jul-Aug

4.  A topological substructural approach applied to the computational prediction of rodent carcinogenicity.

Authors:  Aliuska Morales Helguera; Miguel Angel Cabrera Pérez; Maykel Pérez González; Reinaldo Molina Ruiz; Humberto González Díaz
Journal:  Bioorg Med Chem       Date:  2005-04-01       Impact factor: 3.641

5.  Quantitative structure-activity relationship to predict toxicological properties of benzene derivative compounds.

Authors:  Maykel Pérez González; Aliuska Morales Helguera; Miguel Angel Cabrera
Journal:  Bioorg Med Chem       Date:  2005-03-01       Impact factor: 3.641

  5 in total
  2 in total

1.  Estimating persistence of brominated and chlorinated organic pollutants in air, water, soil, and sediments with the QSPR-based classification scheme.

Authors:  T Puzyn; M Haranczyk; N Suzuki; T Sakurai
Journal:  Mol Divers       Date:  2010-04-13       Impact factor: 2.943

2.  QSAR for RNases and theoretic-experimental study of molecular diversity on peptide mass fingerprints of a new Leishmania infantum protein.

Authors:  Humberto González-Díaz; María A Dea-Ayuela; Lázaro G Pérez-Montoto; Francisco J Prado-Prado; Guillermín Agüero-Chapín; Francisco Bolas-Fernández; Roberto I Vazquez-Padrón; Florencio M Ubeira
Journal:  Mol Divers       Date:  2009-07-04       Impact factor: 2.943

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.