利用3D-QSAR、ADMET特性、分子对接和分子动力学对2-芳氧基-1,4-萘醌衍生物作为抗大肠杆菌抗菌剂的计算机研究

IF 2.218 Q2 Chemistry Chemical Data Collections Pub Date : 2023-10-01 DOI:10.1016/j.cdc.2023.101060
Khaoula Mkhayar , Rachid Haloui , Ossama Daoui , Kaouakeb Elkhattabi , Samir Chtita , Souad Elkhattabi
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引用次数: 1

摘要

在这项研究中,我们使用3D-QSAR,药物相似,ADMET,分子对接和动力学技术在硅中研究了30个萘醌衍生物。目的是利用CoMFA建立稳健的3D-QSAR模型,以发现新的抗大肠杆菌抗菌剂。QSAR模型具有较高的预测能力(Q2 = 0.613, R2 = 0.902, SEE = 0.063)。利用QSAR模型预测,设计了四种新的分子结构。下一步,我们检查了这四种化合物的药物相似性和ADMET预测。两种化合物具有良好的ADMET预测和药物相似性。分子对接用于检测新设计的分子1和分子2与蛋白质之间建立的结合。结果表明,化合物2具有较高的稳定性。为了证实这种稳定性,我们在三种不同的温度条件下进行了100 ns的分子动力学。通过分子动力学模拟证实了其高稳定性。
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In silico studies of 2-aryloxy-1,4- naphthoquinone derivatives as antibacterial agents against Escherichia coli using 3D-QSAR, ADMET properties, molecular docking, and molecular dynamics

In this study, we investigated 30 derivatives of naphthoquinone using 3D-QSAR, drug-likeness, ADMET, molecular docking, and dynamics techniques in silico. The objective is carried out to elaborate the robust 3D-QSAR models using the CoMFA to discover new antibacterial agents against Escherichia coli. High predictive power has been demonstrated by the QSAR models based on their evaluations (Q2 = 0.613, R2 = 0.902, SEE = 0.063). Using the QSAR model predictions, new four molecular structures are designed. As a next step, we examined the four compounds' drug-likeness and ADMET predictions. Two compounds have excellent ADMET predictions and drug-likeness. Molecular docking was used to examine the bindings established between the newly designed molecule 1 and 2 with the protein. Based on the obtained results, the compound 2 exhibits high stability. To confirm this stability, we performed molecular dynamics during 100 ns under three different temperature conditions. High stability was confirmed by molecular dynamics simulations.

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来源期刊
Chemical Data Collections
Chemical Data Collections Chemistry-Chemistry (all)
CiteScore
6.10
自引率
0.00%
发文量
169
审稿时长
24 days
期刊介绍: Chemical Data Collections (CDC) provides a publication outlet for the increasing need to make research material and data easy to share and re-use. Publication of research data with CDC will allow scientists to: -Make their data easy to find and access -Benefit from the fast publication process -Contribute to proper data citation and attribution -Publish their intermediate and null/negative results -Receive recognition for the work that does not fit traditional article format. The research data will be published as ''data articles'' that support fast and easy submission and quick peer-review processes. Data articles introduced by CDC are short self-contained publications about research materials and data. They must provide the scientific context of the described work and contain the following elements: a title, list of authors (plus affiliations), abstract, keywords, graphical abstract, metadata table, main text and at least three references. The journal welcomes submissions focusing on (but not limited to) the following categories of research output: spectral data, syntheses, crystallographic data, computational simulations, molecular dynamics and models, physicochemical data, etc.
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