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izvor podataka: crosbi

Free and open source chemistry software in research of quantitative structure-toxicity relationship of pesticides (CROSBI ID 652612)

Prilog sa skupa u časopisu | izvorni znanstveni rad | međunarodna recenzija

Rastija, Vesna ; Agić, Dejan ; Brlas, Kristian ; Masand, Vijay Free and open source chemistry software in research of quantitative structure-toxicity relationship of pesticides // MATEC Web of Conferences / N. Mastorakis, V. Mladenov, A. Bulucea (ur.). 2017. str. 1-5 doi: 10.1051/matecconf/201712504001

Podaci o odgovornosti

Rastija, Vesna ; Agić, Dejan ; Brlas, Kristian ; Masand, Vijay

engleski

Free and open source chemistry software in research of quantitative structure-toxicity relationship of pesticides

Pesticides are toxic chemicals aimed for the destroying pest on crops. Numerous data evidence about toxicity of pesticides on aquatic organisms. Since pesticides with similar properties tend to have similar biological activities, toxicity may be predicted from structure. Their structure feature and properties are encoded my means of molecular descriptors. Molecular descriptors can capture quite simple two-dimensional (2D) chemical structures to highly complex three- dimensional (3D) chemical structures. Quantitative structure- toxicity relationship (QSTR) method uses linear regression analyses for correlation toxicity of chemical with their structural feature using molecular descriptors. Molecular descriptors were calculated using open source software PaDEL and in-house built PyMOL plugin (PyDescriptor). PyDescriptor is a new script implemented with the commonly used visualization software PyMOL for calculation of a large and diverse set of easily interpretable molecular descriptors encoding pharmacophoric patterns and atomic fragments. PyDescriptor has several advantages like free and open source, can work on all major platforms (Windows, Linux, MacOS). QSTR method allows prediction of toxicity of pesticides without experimental assay. In the present work, QSTR analysis for toxicity of a dataset of mixtures of 5 classes of pesticides comprising has been performed.

pesticides ; QSTR ; PyDescriptor

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Podaci o prilogu

1-5.

2017.

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objavljeno

10.1051/matecconf/201712504001

Podaci o matičnoj publikaciji

N. Mastorakis, V. Mladenov, A. Bulucea

Heraklion: EDP Sciences

2261-236X

Podaci o skupu

21st International Conference on Circuits, Systems, Communications and Computers (CSCC 2017)

pozvano predavanje

14.07.2017-17.07.2017

Heraklion, Grčka

Povezanost rada

Kemija, Poljoprivreda (agronomija), Računarstvo

Poveznice
Indeksiranost