文献检索文档翻译深度研究
Suppr Zotero 插件Zotero 插件
邀请有礼套餐&价格历史记录

新学期,新优惠

限时优惠:9月1日-9月22日

30天高级会员仅需29元

1天体验卡首发特惠仅需5.99元

了解详情
不再提醒
插件&应用
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
高级版
套餐订阅购买积分包
AI 工具
文献检索文档翻译深度研究
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2025

In silico docking and molecular dynamics simulation of 3-dehydroquinate synthase (DHQS) from Mycobacterium tuberculosis.

作者信息

Isa Mustafa Alhaji, Majumdhar Rita Singh, Haider Shazia

机构信息

Department of Biotechnology, School of Engineering and Technology, Sharda University, Greater Noida, India.

出版信息

J Mol Model. 2018 May 11;24(6):132. doi: 10.1007/s00894-018-3637-4.


DOI:10.1007/s00894-018-3637-4
PMID:29752576
Abstract

The shikimate pathway is as an attractive target because it is present in bacteria, algae, fungi, and plants but does not occur in mammals. In Mycobacterium tuberculosis (MTB), the shikimate pathway is integral to the biosynthesis of naphthoquinones, menaquinones, and mycobactin. In these study, novel inhibitors of 3-dehydroquinate synthase (DHQS), an enzyme that catalyzes the second step of the shikimate pathway in MTB, were determined. 12,165 compounds were selected from two public databases through virtual screening and molecular docking analysis using PyRx 8.0 and Autodock 4.2, respectively. A total of 18 compounds with the best binding energies (-13.23 to -8.22 kcal/mol) were then selected and screened for absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis, and nine of those compounds were found to satisfy all of the ADME and toxicity criteria. Among those nine, the three compounds-ZINC633887 (binding energy = -10.29 kcal/mol), ZINC08983432 (-9.34 kcal/mol), and PubChem73393 (-8.61 kcal/mol)-with the best binding energies were further selected for molecular dynamics (MD) simulation analysis. The results of the 50-ns MD simulations showed that the two compounds ZINC633887 and PubChem73393 formed stable complexes with DHQS and that the structures of those two ligands remained largely unchanged at the ligand-binding site during the simulations. These two compounds identified through docking and MD simulation are potential candidates for the treatment of TB, and should undergo validation in vivo and in vitro.

摘要

相似文献

[1]
In silico docking and molecular dynamics simulation of 3-dehydroquinate synthase (DHQS) from Mycobacterium tuberculosis.

J Mol Model. 2018-5-11

[2]
In silico identification of potential inhibitors against shikimate dehydrogenase through virtual screening and toxicity studies for the treatment of tuberculosis.

Int Microbiol. 2018-8-16

[3]
IMB-T130 targets 3-dehydroquinate synthase and inhibits Mycobacterium tuberculosis.

Sci Rep. 2018-11-28

[4]
Shape-based virtual screening, docking, and molecular dynamics simulations to identify Mtb-ASADH inhibitors.

J Biomol Struct Dyn. 2015

[5]
Homology modeling and molecular dynamic simulation of UDP-N-acetylmuramoyl-l-alanine-d-glutamate ligase (MurD) from Mycobacterium tuberculosis H37Rv using in silico approach.

Comput Biol Chem. 2018-11-10

[6]
Drug targeted virtual screening and molecular dynamics of LipU protein of Mycobacterium tuberculosis and Mycobacterium leprae.

J Biomol Struct Dyn. 2018-3-30

[7]
Structure-based screening and molecular dynamics simulations offer novel natural compounds as potential inhibitors of Mycobacterium tuberculosis isocitrate lyase.

J Biomol Struct Dyn. 2017-6-26

[8]
Identification of novel PI3Kδ inhibitors by docking, ADMET prediction and molecular dynamics simulations.

Comput Biol Chem. 2018-12-7

[9]
Benzothiazole Derivative as a Novel Mycobacterium tuberculosis Shikimate Kinase Inhibitor: Identification and Elucidation of Its Allosteric Mode of Inhibition.

J Chem Inf Model. 2016-5-23

[10]
Comparative modeling and dynamic simulation of UDP-N-acetylmuramoyl-alanine ligase (MurC) from Mycobacterium tuberculosis through virtual screening and toxicity analysis.

Life Sci. 2020-9-19

引用本文的文献

[1]
Molecular detection of gene from methicillin-resistant isolated from clinical and environmental samples and its potential inhibition by phytochemicals using in vitro and in silico approach.

In Silico Pharmacol. 2025-2-10

[2]
Molecular Dynamic Simulations and Molecular Docking as a Potential Way for Designed New Inhibitor Drug without Resistance.

Tanaffos. 2022-1

[3]
Indian Ethnomedicinal Phytochemicals as Promising Inhibitors of RNA-Binding Domain of SARS-CoV-2 Nucleocapsid Phosphoprotein: An Study.

Front Mol Biosci. 2021-7-2

[4]
Interaction of gibberellin and other hormones in almond anthers: phenotypic and physiological changes and transcriptomic reprogramming.

Hortic Res. 2021-5-1

本文引用的文献

[1]
In silico designing of hyper-glycosylated analogs for the human coagulation factor IX.

J Mol Graph Model. 2016-7

[2]
Toward antituberculosis drugs: in silico screening of synthetic compounds against Mycobacterium tuberculosisl,d-transpeptidase 2.

Drug Des Devel Ther. 2016-3-11

[3]
Virtual screening studies to identify novel inhibitors for Sigma F protein of Mycobacterium tuberculosis.

Int J Mycobacteriol. 2015-12

[4]
μABC: a systematic microsecond molecular dynamics study of tetranucleotide sequence effects in B-DNA.

Nucleic Acids Res. 2014-10-29

[5]
admetSAR: a comprehensive source and free tool for assessment of chemical ADMET properties.

J Chem Inf Model. 2012-11-1

[6]
Defining and searching for structural motifs using DeepView/Swiss-PdbViewer.

BMC Bioinformatics. 2012-7-23

[7]
Automated minimization of steric clashes in protein structures.

Proteins. 2011-1

[8]
POLYVIEW-MM: web-based platform for animation and analysis of molecular simulations.

Nucleic Acids Res. 2010-5-26

[9]
A systematic molecular dynamics study of nearest-neighbor effects on base pair and base pair step conformations and fluctuations in B-DNA.

Nucleic Acids Res. 2009-10-22

[10]
Functional characterization by genetic complementation of aroB-encoded dehydroquinate synthase from Mycobacterium tuberculosis H37Rv and its heterologous expression and purification.

J Bacteriol. 2007-9

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

推荐工具

医学文档翻译智能文献检索