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Designing Potential Inhibitors of SARS-CoV-2 Mpro Using Deep-Learning and Steered-Molecular Dynamic Simulations 利用深度学习和可控分子动力学模拟设计潜在的严重急性呼吸系统综合征冠状病毒2型Mpro抑制剂
IF 2.2 4区 化学 Q3 CHEMISTRY, MULTIDISCIPLINARY Pub Date : 2023-03-10 DOI: 10.1142/s2737416523500242
N. M. Tam, L. Tran, Q. Vo, Minh Quan Pham, H. Phung
The COVID-19 pandemic raised an unprecedented race in biotechnology in search for effective therapies and a preventive vaccine. Scientists worldwide have been attempting to stop the viral infection by interfering with the biological function of the SARS-CoV-2 main protease (Mpro), a critical protein required for viral transcription and replication during infection. In this study, we employed an effective approach integrating deep learning model calculations and steered molecular dynamic simulations to generate highly promising inhibitors of SARS-CoV-2 Mpro. First, using deep learning calculations, a natural molecule that was identified as a potential inhibitor of SARS-CoV-2 Mpro was chemically altered to boost its ligand-binding affinity to the Mpro protease. The proposed compounds were then verified using steered molecular dynamic simulations to estimate their binding free energies to SARS-CoV-2 Mpro. The procedure was repeated until the binding free energies of the proposed compounds did not improve further. Overall, one proposed compound was shown to have a high nanomolar affinity, and two others were estimated to possess nanomolar affinities for SARS-CoV-2 Mpro, indicating that they are highly promising inhibitors of the protease. Absorption, distribution, metabolism, and excretion and toxicity analysis show that all three chemicals are drug-like compounds following the MACCS-II Drug Data Report database, orally absorbed, tightly attached to the plasma membrane, and noncarcinogenic in rats. The results obtained potentially support COVID-19 treatment. [ FROM AUTHOR] Copyright of Journal of Computational Biophysics & Chemistry is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
新冠肺炎大流行引发了生物技术领域前所未有的寻找有效疗法和预防性疫苗的竞赛。世界各地的科学家一直试图通过干扰严重急性呼吸系统综合征冠状病毒2型主要蛋白酶(Mpro)的生物功能来阻止病毒感染,Mpro是感染期间病毒转录和复制所需的关键蛋白。在这项研究中,我们采用了一种有效的方法,将深度学习模型计算和分子动力学模拟相结合,生成了极具前景的严重急性呼吸系统综合征冠状病毒2型Mpro抑制剂。首先,使用深度学习计算,一种被确定为严重急性呼吸系统综合征冠状病毒2型Mpro潜在抑制剂的天然分子被化学改变,以提高其与Mpro蛋白酶的配体结合亲和力。然后使用可控分子动力学模拟对所提出的化合物进行了验证,以估计其与严重急性呼吸系统综合征冠状病毒2 Mpro的结合自由能。重复该过程,直到所提出的化合物的结合自由能没有进一步提高。总体而言,一种提出的化合物被证明具有高纳摩尔亲和力,另外两种化合物被估计对严重急性呼吸系统综合征冠状病毒2型Mpro具有纳摩尔亲和性,这表明它们是非常有前途的蛋白酶抑制剂。吸收、分布、代谢和排泄以及毒性分析表明,根据MACCS-II药物数据报告数据库,这三种化学物质都是类药物化合物,经口吸收,紧密附着在质膜上,对大鼠无致癌作用。获得的结果可能支持新冠肺炎治疗。[发件人]《计算生物物理学与化学杂志》的版权归世界科学出版公司所有,未经版权持有人明确书面许可,不得将其内容复制或通过电子邮件发送到多个网站或发布到列表服务器。但是,用户可以打印、下载或通过电子邮件发送文章供个人使用。这可能会被删节。对复印件的准确性不作任何保证。用户应参考材料的原始发布版本以获取完整信息。(版权适用于所有人。)
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引用次数: 0
Developing high-resolution metastasis signatures for improved cancer prognosis and drug sensitivity prediction using single-cell RNA sequencing data: A case study in lung adenocarcinoma 利用单细胞RNA测序数据开发用于改善癌症预后和药物敏感性预测的高分辨率转移信号:肺腺癌病例研究
IF 2.2 4区 化学 Q3 CHEMISTRY, MULTIDISCIPLINARY Pub Date : 2023-03-08 DOI: 10.1142/s2737416523410016
Yeman Zhou, Hanlin Li, De'en Yu, Cheng Zhang, Heng Yang, Chunping Wang, Youhua Zhang, W. Deng, Bo Li, Shihua Zhang
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引用次数: 0
Neighborhood Path Complex for the Quantitative Analysis of the Structure and Stability of Carboranes 用于定量分析碳硼烷结构和稳定性的邻域路径复合体
IF 2.2 4区 化学 Q3 CHEMISTRY, MULTIDISCIPLINARY Pub Date : 2023-02-16 DOI: 10.1142/s2737416523500229
Jian Liu, Dong Chen, Feng Pan, Jie Wu
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引用次数: 1
In silico Identification of Triclosan Derivatives as Potential Inhibitors of Mutant Mycobacterium tuberculosis InhA 三氯生衍生物作为突变结核分枝杆菌InhA潜在抑制剂的计算机鉴定
IF 2.2 4区 化学 Q3 CHEMISTRY, MULTIDISCIPLINARY Pub Date : 2023-01-19 DOI: 10.1142/s2737416523500205
N. Panahi, N. Razzaghi-Asl
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引用次数: 0
Semi-analytical solution of nonlinear hydromagnetic multiphase flow of highly viscous fluid 高粘性流体非线性流磁多相流的半解析解
IF 2.2 4区 化学 Q3 CHEMISTRY, MULTIDISCIPLINARY Pub Date : 2023-01-11 DOI: 10.1142/s2737416523400112
M. Nazeer, F. Hussain, M. Turkyilmazoglu, Qasiar Shahzad
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引用次数: 3
Unsteady MHD flow of Casson fluid past vertical surface using Laplace transform solution 用拉普拉斯变换求解卡森流体垂直表面非定常MHD流动
IF 2.2 4区 化学 Q3 CHEMISTRY, MULTIDISCIPLINARY Pub Date : 2023-01-11 DOI: 10.1142/s2737416523400100
F. Ali, A. Zaib, M. Khalid, B. Hemalatha, T. Padmavathi
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引用次数: 0
In silico Study of Thiourea Derivatives as Potential Epidermal Growth Factor Receptor Inhibitors 硫脲衍生物作为潜在表皮生长因子受体抑制剂的计算机研究
IF 2.2 4区 化学 Q3 CHEMISTRY, MULTIDISCIPLINARY Pub Date : 2023-01-11 DOI: 10.1142/s2737416523500199
N. Roslan, K. Halim, Noraslinda M. Bunnori, M. Aluwi, K. Kassim, N. Ngah
{"title":"In silico Study of Thiourea Derivatives as Potential Epidermal Growth Factor Receptor Inhibitors","authors":"N. Roslan, K. Halim, Noraslinda M. Bunnori, M. Aluwi, K. Kassim, N. Ngah","doi":"10.1142/s2737416523500199","DOIUrl":"https://doi.org/10.1142/s2737416523500199","url":null,"abstract":"","PeriodicalId":15603,"journal":{"name":"Journal of Computational Biophysics and Chemistry","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45080024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Use of Apatinib as a Bait to Fish Its Unexpected Kinase Targets from the Hepatocellular Carcinoma Druggable Kinome 利用阿帕替尼作为诱饵,从肝细胞癌可用药的Kinome中寻找意想不到的激酶靶点
IF 2.2 4区 化学 Q3 CHEMISTRY, MULTIDISCIPLINARY Pub Date : 2023-01-06 DOI: 10.1142/s2737416523500187
R. Liu, Lijun Liu
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引用次数: 0
Computational analysis of the biophysics of mixed convection in blood-based hybrid nanoparticle under Boussinesq Approximation in a transient regime 基于Boussinesq近似的血液基混合纳米颗粒混合对流生物物理计算分析
IF 2.2 4区 化学 Q3 CHEMISTRY, MULTIDISCIPLINARY Pub Date : 2022-12-23 DOI: 10.1142/s2737416523400094
E. O. Ige, B. Falodun, Daniel Oluwamuyiwa Adebiyi, S. Khan
{"title":"Computational analysis of the biophysics of mixed convection in blood-based hybrid nanoparticle under Boussinesq Approximation in a transient regime","authors":"E. O. Ige, B. Falodun, Daniel Oluwamuyiwa Adebiyi, S. Khan","doi":"10.1142/s2737416523400094","DOIUrl":"https://doi.org/10.1142/s2737416523400094","url":null,"abstract":"","PeriodicalId":15603,"journal":{"name":"Journal of Computational Biophysics and Chemistry","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45790173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Negishi or Suzuki–Miyaura Pd-catalyzed cross-coupling reaction: Which reaction mechanism is ahead for the formation of well-known anticancer drug combretastatin A-4 analogue? 根石或铃木-宫浦Pd催化的交叉偶联反应:形成著名抗癌药物复方他汀A-4类似物的反应机制是什么?
IF 2.2 4区 化学 Q3 CHEMISTRY, MULTIDISCIPLINARY Pub Date : 2022-12-23 DOI: 10.1142/s2737416523500175
Zeinab Ahmadvand, M. Bayat
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引用次数: 0
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