Evidence map›Paper›PMID 19543755›Full record

ArticleJournal of molecular modeling2010

Docking and 3D QSAR studies of protoporphyrinogen oxidase inhibitor 3H-pyrazolo[3,4-d][1,2,3]triazin-4-one derivatives.

Kunal Roy, Somnath Paul

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Article in Journal of molecular modeling, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Kunal RoyDrug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata 700032, India. kunalroy_in@yahoo.com
Somnath Paul

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Docking and three dimensional quantitative structure - activity relationship (3D-QSAR) studies have been performed for protoporphyrinogen oxidase (PPO) inhibitor 3H-pyrazolo[3,4-d][1,2,3]triazin-4-one analogues which are potential herbicides to protect agricultural products from unwanted weeds. The 3D-QSAR studies have been carried out using shape, spatial, electronic and molecular field descriptors along with a few structural parameters. The chemometric tools used for the analyses are genetic function approximation (GFA), partial least squares (PLS) and genetic partial least squares (G/PLS). The whole data set (n = 34) was divided into a training set (75% of the data set) and a test set (remaining 25%) on the basis of K-means clustering technique applied on topological, spatial and electronic descriptor matrix. Models developed from the training set were used to predict the activity of the test set compounds. All the models have been validated internally, externally and by Y-randomization technique. Docking studies suggest that the molecules bind with a hydrophobic pocket of the enzyme formed by some nonpolar amino acid (Ile168, Ile311, Ile412, Met365, Phe65 and Val164) residues. The QSAR studies suggest that for better activity the molecules should have symmetrical shape in the 3D space. For better PPO inhibitory activity, there should be a balance between the electrophilic and nucleophilic characters of the inhibitors. The charged surface area descriptors suggest that, the positive charge distributed over a large surface area may enhance the activity. Molecular field probes reflect that increase in steric volume and positively charged surface area may enhance the herbicidal activity.

Indexed as

Quantitative Structure-Activity RelationshipComputer-Aided DesignEnzyme InhibitorsHerbicidesModels, MolecularMolecular StructureProtoporphyrinogen OxidasePyrazolesSmall Molecule LibrariesTriazinesEnzyme InhibitorsHerbicidesProtoporphyrinogen OxidasePyrazolesSmall Molecule LibrariesTriazines

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.