QSAR analyses of organophosphates for insecticidal activity and its in-silico validation using molecular docking study

Copyright © 2015 Elsevier B.V. All rights reserved..

The present work was carried out to design and develop novel QSAR models using 2D-QSAR and 3D-QSAR with CoMFA methodology for prediction of insecticidal activity of organophosphate (OP) molecules. The models were validated on an entirely different external dataset of in-house generated combinatorial library of OPs, by completely different computational approach of molecular docking against the target AChE protein of Musca domestica. The dock scores were observed to be in good correlation with 2D-QSAR and 3D-QSAR with CoMFA predicted activities and had the correlation coefficients (r(2)) of -0.62 and -0.63, respectively. The activities predicted by 2D-QSAR and 3D-QSAR with CoMFA were also observed to be highly correlated with r(2)=0.82. Also, the combinatorial library molecules were screened for toxicity in non-target organisms and degradability using USEPA-EPI Suite. The work was first step towards computer aided design and development of novel OP pesticide candidates with good insecticidal property but lower toxicity in non-targeted organisms and having biodegradation potential.

Medienart:

E-Artikel

Erscheinungsjahr:

2015

Erschienen:

2015

Enthalten in:

Zur Gesamtaufnahme - volume:40

Enthalten in:

Environmental toxicology and pharmacology - 40(2015), 3 vom: 27. Nov., Seite 886-94

Sprache:

Englisch

Beteiligte Personen:

Niraj, Ravi Ranjan Kumar [VerfasserIn]
Saini, Vandana [VerfasserIn]
Kumar, Ajit [VerfasserIn]

Links:

Volltext

Themen:

Acetylcholinesterase
CoMFA
Combinatorial library
EC 3.1.1.7
EPI Suite
Homology modelling
Insect Proteins
Insecticides
Journal Article
Organophosphates
Small Molecule Libraries

Anmerkungen:

Date Completed 05.10.2016

Date Revised 30.12.2016

published: Print-Electronic

Citation Status MEDLINE

doi:

10.1016/j.etap.2015.09.021

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM253929393