Cargando…

In-Silico Prediction and Modeling of the Quorum Sensing LuxS Protein and Inhibition of AI-2 Biosynthesis in Aeromonas hydrophila

luxS is conserved in several bacterial species, including A. hydrophila, which causes infections in prawn, fish, and shrimp, and is consequently a great risk to the aquaculture industry and public health. luxS plays a critical role in the biosynthesis of the autoinducer-2 (AI-2), which performs wide...

Descripción completa

Detalles Bibliográficos
Autores principales: Ali, Farman, Yao, Zujie, Li, Wanxin, Sun, Lina, Lin, Wenxiong, Lin, Xiangmin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6222731/
https://www.ncbi.nlm.nih.gov/pubmed/30322111
http://dx.doi.org/10.3390/molecules23102627
_version_ 1783369274983710720
author Ali, Farman
Yao, Zujie
Li, Wanxin
Sun, Lina
Lin, Wenxiong
Lin, Xiangmin
author_facet Ali, Farman
Yao, Zujie
Li, Wanxin
Sun, Lina
Lin, Wenxiong
Lin, Xiangmin
author_sort Ali, Farman
collection PubMed
description luxS is conserved in several bacterial species, including A. hydrophila, which causes infections in prawn, fish, and shrimp, and is consequently a great risk to the aquaculture industry and public health. luxS plays a critical role in the biosynthesis of the autoinducer-2 (AI-2), which performs wide-ranging functions in bacterial communication, and especially in quorum sensing (QS). The prediction of a 3D structure of the QS-associated LuxS protein is thus essential to better understand and control A. hydrophila pathogenecity. Here, we predicted the structure of A. hydrophila LuxS and characterized it structurally and functionally with in silico methods. The predicted structure of LuxS provides a framework to develop more complete structural and functional insights and will aid the mitigation of A. hydrophila infection, and the development of novel drugs to control infections. In addition to modeling, the suitable inhibitor was identified by high through put screening (HTS) against drug like subset of ZINC database and inhibitor ((−)-Dimethyl 2,3-O-isopropylidene-l-tartrate) molecule was selected based on the best drug score. Molecular docking studies were performed to find out the best binding affinity between LuxS homologous or predicted model of LuxS protein for the ligand selection. Remarkably, this inhibitor molecule establishes agreeable interfaces with amino acid residues LYS 23, VAL 35, ILE76, and SER 90, which are found to play an essential role in inhibition mechanism. These predictions were suggesting that the proposed inhibitor molecule may be considered as drug candidates against AI-2 biosynthesis of A. hydrophila. Therefore, (−)-Dimethyl 2,3-O-isopropylidene-l-tartrate inhibitor molecule was studied to confirm its potency of AI-2 biosynthesis inhibition. The results shows that the inhibitor molecule had a better efficacy in AI-2 inhibition at 40 μM concentration, which was further validated using Western blotting at a protein expression level. The AI-2 bioluminescence assay showed that the decreased amount of AI-2 biosynthesis and downregulation of LuxS protein play an important role in the AI-2 inhibition. Lastly, these experiments were conducted with the supplementation of antibiotics via cocktail therapy of AI-2 inhibitor plus OXY antibiotics, in order to determine the possibility of novel cocktail drug treatments of A. hydrophila infection.
format Online
Article
Text
id pubmed-6222731
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-62227312018-11-13 In-Silico Prediction and Modeling of the Quorum Sensing LuxS Protein and Inhibition of AI-2 Biosynthesis in Aeromonas hydrophila Ali, Farman Yao, Zujie Li, Wanxin Sun, Lina Lin, Wenxiong Lin, Xiangmin Molecules Article luxS is conserved in several bacterial species, including A. hydrophila, which causes infections in prawn, fish, and shrimp, and is consequently a great risk to the aquaculture industry and public health. luxS plays a critical role in the biosynthesis of the autoinducer-2 (AI-2), which performs wide-ranging functions in bacterial communication, and especially in quorum sensing (QS). The prediction of a 3D structure of the QS-associated LuxS protein is thus essential to better understand and control A. hydrophila pathogenecity. Here, we predicted the structure of A. hydrophila LuxS and characterized it structurally and functionally with in silico methods. The predicted structure of LuxS provides a framework to develop more complete structural and functional insights and will aid the mitigation of A. hydrophila infection, and the development of novel drugs to control infections. In addition to modeling, the suitable inhibitor was identified by high through put screening (HTS) against drug like subset of ZINC database and inhibitor ((−)-Dimethyl 2,3-O-isopropylidene-l-tartrate) molecule was selected based on the best drug score. Molecular docking studies were performed to find out the best binding affinity between LuxS homologous or predicted model of LuxS protein for the ligand selection. Remarkably, this inhibitor molecule establishes agreeable interfaces with amino acid residues LYS 23, VAL 35, ILE76, and SER 90, which are found to play an essential role in inhibition mechanism. These predictions were suggesting that the proposed inhibitor molecule may be considered as drug candidates against AI-2 biosynthesis of A. hydrophila. Therefore, (−)-Dimethyl 2,3-O-isopropylidene-l-tartrate inhibitor molecule was studied to confirm its potency of AI-2 biosynthesis inhibition. The results shows that the inhibitor molecule had a better efficacy in AI-2 inhibition at 40 μM concentration, which was further validated using Western blotting at a protein expression level. The AI-2 bioluminescence assay showed that the decreased amount of AI-2 biosynthesis and downregulation of LuxS protein play an important role in the AI-2 inhibition. Lastly, these experiments were conducted with the supplementation of antibiotics via cocktail therapy of AI-2 inhibitor plus OXY antibiotics, in order to determine the possibility of novel cocktail drug treatments of A. hydrophila infection. MDPI 2018-10-12 /pmc/articles/PMC6222731/ /pubmed/30322111 http://dx.doi.org/10.3390/molecules23102627 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ali, Farman
Yao, Zujie
Li, Wanxin
Sun, Lina
Lin, Wenxiong
Lin, Xiangmin
In-Silico Prediction and Modeling of the Quorum Sensing LuxS Protein and Inhibition of AI-2 Biosynthesis in Aeromonas hydrophila
title In-Silico Prediction and Modeling of the Quorum Sensing LuxS Protein and Inhibition of AI-2 Biosynthesis in Aeromonas hydrophila
title_full In-Silico Prediction and Modeling of the Quorum Sensing LuxS Protein and Inhibition of AI-2 Biosynthesis in Aeromonas hydrophila
title_fullStr In-Silico Prediction and Modeling of the Quorum Sensing LuxS Protein and Inhibition of AI-2 Biosynthesis in Aeromonas hydrophila
title_full_unstemmed In-Silico Prediction and Modeling of the Quorum Sensing LuxS Protein and Inhibition of AI-2 Biosynthesis in Aeromonas hydrophila
title_short In-Silico Prediction and Modeling of the Quorum Sensing LuxS Protein and Inhibition of AI-2 Biosynthesis in Aeromonas hydrophila
title_sort in-silico prediction and modeling of the quorum sensing luxs protein and inhibition of ai-2 biosynthesis in aeromonas hydrophila
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6222731/
https://www.ncbi.nlm.nih.gov/pubmed/30322111
http://dx.doi.org/10.3390/molecules23102627
work_keys_str_mv AT alifarman insilicopredictionandmodelingofthequorumsensingluxsproteinandinhibitionofai2biosynthesisinaeromonashydrophila
AT yaozujie insilicopredictionandmodelingofthequorumsensingluxsproteinandinhibitionofai2biosynthesisinaeromonashydrophila
AT liwanxin insilicopredictionandmodelingofthequorumsensingluxsproteinandinhibitionofai2biosynthesisinaeromonashydrophila
AT sunlina insilicopredictionandmodelingofthequorumsensingluxsproteinandinhibitionofai2biosynthesisinaeromonashydrophila
AT linwenxiong insilicopredictionandmodelingofthequorumsensingluxsproteinandinhibitionofai2biosynthesisinaeromonashydrophila
AT linxiangmin insilicopredictionandmodelingofthequorumsensingluxsproteinandinhibitionofai2biosynthesisinaeromonashydrophila