Literature DB >> 24724897

Assessing the validity of QSARs for ready biodegradability of chemicals: an applicability domain perspective.

Faizan Sahigara, Davide Ballabio, Roberto Todeschini, Viviana Consonni1.   

Abstract

Several classical and two recently proposed Applicability Domain (AD) approaches were implemented on a set of three classification models retrieved from a published study to assess the ready biodegradability of chemicals. Each model was associated with an optimal AD approach based on its ability to a) retain maximum test molecules within the model's AD, b) be appropriate for the strategy used towards model development and c) show reasonably converging results with those derived with other AD approaches used. A decision criterion was also set to evaluate the AD of two consensus models that were developed in the original study. An overview of test molecules excluded from the AD of all the five biodegradability models was provided including an attempt to identify the major structural features and molecular descriptors possibly relevant in deciding upon their ready biodegradability. Apart from the test set, an overview of the results derived on the external validation set molecules was provided.

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Year:  2014        PMID: 24724897     DOI: 10.2174/1573409910666140410110241

Source DB:  PubMed          Journal:  Curr Comput Aided Drug Des        ISSN: 1573-4099            Impact factor:   1.606


  4 in total

1.  In Silico Prediction of Physicochemical Properties of Environmental Chemicals Using Molecular Fingerprints and Machine Learning.

Authors:  Qingda Zang; Kamel Mansouri; Antony J Williams; Richard S Judson; David G Allen; Warren M Casey; Nicole C Kleinstreuer
Journal:  J Chem Inf Model       Date:  2017-01-09       Impact factor: 4.956

2.  Sequential and Mixed Genetic Algorithm and Learning Automata (SGALA, MGALA) for Feature Selection in QSAR.

Authors:  Habib MotieGhader; Sajjad Gharaghani; Yosef Masoudi-Sobhanzadeh; Ali Masoudi-Nejad
Journal:  Iran J Pharm Res       Date:  2017       Impact factor: 1.696

3.  Molecular Modeling Studies of N-phenylpyrimidine-4-amine Derivatives for Inhibiting FMS-like Tyrosine Kinase-3.

Authors:  Suparna Ghosh; Seketoulie Keretsu; Seung Joo Cho
Journal:  Int J Mol Sci       Date:  2021-11-19       Impact factor: 5.923

4.  Binding Studies and Lead Generation of Pteridin-7(8H)-one Derivatives Targeting FLT3.

Authors:  Suparna Ghosh; Seung Joo Cho
Journal:  Int J Mol Sci       Date:  2022-07-12       Impact factor: 6.208

  4 in total

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