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Discovering Novel Alternaria solani Succinate Dehydrogenase Inhibitors by in Silico Modeling and Virtual Screening Strategies to Combat Early Blight

Overview of attention for article published in Frontiers in Chemistry, November 2017
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Title
Discovering Novel Alternaria solani Succinate Dehydrogenase Inhibitors by in Silico Modeling and Virtual Screening Strategies to Combat Early Blight
Published in
Frontiers in Chemistry, November 2017
DOI 10.3389/fchem.2017.00100
Pubmed ID
Authors

Sehrish Iftikhar, Ahmad A. Shahid, Sobia A. Halim, Pieter J. Wolters, Vivianne G. A. A. Vleeshouwers, Ajmal Khan, Ahmed Al-Harrasi, Shahbaz Ahmad

Abstract

Alternaria blight is an important foliage disease caused by Alternaria solani. The enzyme Succinate dehydrogenase (SDH) is a potential drug target because of its role in tricarboxylic acid cycle. Hence targeting Alternaria solani SDH enzyme could be efficient tool to design novel fungicides against A. solani. We employed computational methodologies to design new SDH inhibitors using homology modeling; pharmacophore modeling and structure based virtual screening. The three dimensional SDH model showed good stereo-chemical and structural properties. Based on virtual screening results twelve commercially available compounds were purchased and tested in vitro and in vivo. The compounds were found to inhibit mycelial growth of A. solani. Moreover in vitro trials showed that inhibitory effects were enhanced with increase in concentrations. Similarly increased disease control was observed in pre-treated potato tubers. Hence the applied in silico strategy led us to identify novel fungicides.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 32 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 19%
Student > Master 4 13%
Student > Bachelor 3 9%
Student > Doctoral Student 3 9%
Researcher 2 6%
Other 4 13%
Unknown 10 31%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 44%
Biochemistry, Genetics and Molecular Biology 3 9%
Chemistry 2 6%
Unspecified 1 3%
Medicine and Dentistry 1 3%
Other 1 3%
Unknown 10 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 November 2017.
All research outputs
#20,452,930
of 23,008,860 outputs
Outputs from Frontiers in Chemistry
#2,934
of 6,008 outputs
Outputs of similar age
#366,946
of 431,641 outputs
Outputs of similar age from Frontiers in Chemistry
#34
of 55 outputs
Altmetric has tracked 23,008,860 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,008 research outputs from this source. They receive a mean Attention Score of 2.0. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 55 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.