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Insight into the molecular mechanism of yeast acetyl-coenzyme A carboxylase mutants F510I, N485G, I69E, E477R, and K73R resistant to soraphen A

Overview of attention for article published in Perspectives in Drug Discovery and Design, February 2018
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Title
Insight into the molecular mechanism of yeast acetyl-coenzyme A carboxylase mutants F510I, N485G, I69E, E477R, and K73R resistant to soraphen A
Published in
Perspectives in Drug Discovery and Design, February 2018
DOI 10.1007/s10822-018-0108-z
Pubmed ID
Authors

Jian Gao, Li Liang, Qingqing Chen, Ling Zhang, Tonghui Huang

Abstract

Acetyl-coenzyme A carboxylases (ACCs) is the first committed enzyme of fatty acid synthesis pathway. The inhibition of ACC is thought to be beneficial not only for diseases related to metabolism, such as type-2 diabetes, but also for infectious disease like bacterial infection disease. Soraphen A, a potent allosteric inhibitor of BC domain of yeast ACC, exhibit lower binding affinities to several yeast ACC mutants and the corresponding drug resistance mechanisms are still unknown. We report here a theoretical study of binding of soraphen A to wild type and yeast ACC mutants (including F510I, N485G, I69E, E477R, and K73R) via molecular dynamic simulation and molecular mechanics/generalized Born surface area free energy calculations methods. The calculated binding free energies of soraphen A to yeast ACC mutants are weaker than to wild type, which is highly consistent with the experimental results. The mutant F510I weakens the binding affinity of soraphen A to yeast ACC mainly by decreasing the van der Waals contributions, while the weaker binding affinities of Soraphen A to other yeast ACC mutants including N485G, I69E, E477R, and K73R are largely attributed to the decreased net electrostatic (ΔEele + ΔGGB) interactions. Our simulation results could provide important insights for the development of more potent ACC inhibitors.

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Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 22%
Researcher 1 11%
Other 1 11%
Student > Master 1 11%
Unknown 4 44%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 2 22%
Nursing and Health Professions 1 11%
Energy 1 11%
Medicine and Dentistry 1 11%
Unknown 4 44%
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 22 February 2018.
All research outputs
#22,834,739
of 25,461,852 outputs
Outputs from Perspectives in Drug Discovery and Design
#868
of 949 outputs
Outputs of similar age
#305,097
of 344,559 outputs
Outputs of similar age from Perspectives in Drug Discovery and Design
#10
of 12 outputs
Altmetric has tracked 25,461,852 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 949 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. 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 12 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.