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Novel sulfonyl hydrazide based β-carboline derivatives as potential α-glucosidase inhibitors: design, synthesis, and biological evaluation. 新型磺酰肼基 β-咔啉衍生物作为潜在的 α-葡萄糖苷酶抑制剂:设计、合成和生物学评价。
IF 3.9 2区 化学 Q2 CHEMISTRY, APPLIED Pub Date : 2024-08-14 DOI: 10.1007/s11030-024-10943-4
Jinping Sun, Di Xiao, Ming Lang, Xuetao Xu

A series of novel sulfonyl hydrazide based β-carboline derivatives (SX1-SX32) were designed and synthesized, and their structures were characterized on NMR and HRMS. Their α-glucosidase inhibitory screening results found that compounds (SX1-SX32) presented potential α-glucosidase inhibitory: IC50 values being 2.12 ± 0.33-19.37 ± 1.49 μM. Compound SX29 with a para-phenyl (IC50: 2.12 ± 0.33 μM) presented the strongest activity and was confirmed as a noncompetitive inhibitor. Fluorescence spectra, CD spectra and molecular docking were conducted to describe the inhibition mechanism of SX29 against α-glucosidase. Cells cytotoxicity indicated SX29 (0-32 μM) had no cytotoxicity on 293T cells. In particular, in vivo experiments revealed that oral administration of SX29 could regulate hyperglycemia and glucose tolerance of diabetic mice. These achieved findings indicated that sulfonyl hydrazide based β-carboline derivatives bore promising potential for discovering new α-glucosidase inhibitors with hypoglycemic activity.

设计并合成了一系列新型磺酰肼基 β-咔啉衍生物(SX1-SX32),并通过核磁共振和 HRMS 对其结构进行了表征。其α-葡萄糖苷酶抑制筛选结果表明,化合物(SX1-SX32)具有潜在的α-葡萄糖苷酶抑制作用:IC50 值为 2.12 ± 0.33-19.37 ± 1.49 μM。具有对位苯基的化合物 SX29 的活性最强(IC50:2.12 ± 0.33 μM),被确认为非竞争性抑制剂。研究人员通过荧光光谱、CD光谱和分子对接来描述 SX29 对α-葡萄糖苷酶的抑制机制。细胞毒性表明,SX29(0-32 μM)对 293T 细胞无细胞毒性。体内实验表明,口服 SX29 能调节糖尿病小鼠的高血糖和葡萄糖耐量。这些研究结果表明,磺酰肼基 β-咔啉衍生物具有发现具有降糖活性的新型 α-葡萄糖苷酶抑制剂的潜力。
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引用次数: 0
Computational drug repositioning for IL6 triggered JAK3 in rheumatoid arthritis using FDA database. 利用 FDA 数据库计算类风湿性关节炎中 IL6 触发 JAK3 的药物重新定位。
IF 3.9 2区 化学 Q2 CHEMISTRY, APPLIED Pub Date : 2024-08-14 DOI: 10.1007/s11030-024-10958-x
Kaushani Banerjee, Bavya Chandrasekar, Sruthy Sathish, Honglae Sohn, Thirumurthy Madhavan

Rheumatoid Arthritis (RA) is a persistent autoimmune disease affecting approximately 0.5-1 percent of the world population. RA prevalence is higher in woman aged between 35 and 50 years than in age matched men, though this difference is less evident among elderly patients. The profound immune specific effects of disrupted JAK 3 (Janus kinase 3) signaling highlight the possibility of therapeutic targeting of JAK3 as a highly specific mode of immune system suppression. To address the above problem which is unendurable to patients and in the hope to cater some respite to such suffering we have targeted JAK 3 protein and JAK/STAT signaling pathway with compounds downloaded from FDA database, and performed screening of all available compounds docked against JAK3 protein. The difference between the target protein and other proteins of the same family was studied using cross docking and the compounds having higher binding affinity to JAK3 protein also showed more selectivity towards the particular protein. Density functional theory and molecular dynamics simulation study was done to study the compounds at their atomic level to know more about their drug likeliness. At the end of the study and based on our analysis we have come up with three FDA approved drugs that can be proposed as a treatment option for Rheumatoid Arthritis.

类风湿性关节炎(RA)是一种顽固的自身免疫性疾病,约占世界总人口的 0.5%-1%。35至50岁女性的类风湿关节炎发病率高于年龄匹配的男性,但这一差异在老年患者中并不明显。JAK 3(Janus 激酶 3)信号传导紊乱会产生深远的免疫特异性影响,这凸显了以 JAK3 为治疗靶点作为高度特异性免疫系统抑制模式的可能性。为了解决上述令患者难以忍受的问题,并希望为这种痛苦提供一些喘息的机会,我们从 FDA 数据库中下载了针对 JAK 3 蛋白和 JAK/STAT 信号通路的化合物,并对所有与 JAK3 蛋白对接的可用化合物进行了筛选。利用交叉对接法研究了目标蛋白与同族其他蛋白之间的差异,结果表明,与 JAK3 蛋白结合亲和力较高的化合物对该特定蛋白具有更高的选择性。密度泛函理论和分子动力学模拟研究从原子水平对化合物进行了研究,以进一步了解它们的药物相容性。研究结束后,根据我们的分析,我们得出了三种经 FDA 批准的药物,可作为类风湿关节炎的治疗方案。
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引用次数: 0
Prediction of Mycobacterium tuberculosis cell wall permeability using machine learning methods 利用机器学习方法预测结核分枝杆菌细胞壁的渗透性。
IF 3.9 2区 化学 Q2 CHEMISTRY, APPLIED Pub Date : 2024-08-12 DOI: 10.1007/s11030-024-10952-3
Aritra Banerjee, Anju Sharma, Pradnya Kamble, Prabha Garg

Tuberculosis (TB) caused by the bacteria Mycobacterium tuberculosis (M. tb), continues to pose a significant worldwide health threat. The advent of drug-resistant strains of the disease highlights the critical need for novel treatments. The unique cell wall of M. tb provides an extra layer of protection for the bacteria and hence only compounds that can penetrate this barrier can reach their targets within the bacterial cell wall. The creation of a reliable machine learning (ML) model to predict the mycobacterial cell wall permeability of small molecules is presented in this work and four ML algorithms, including Random Forest, Support Vector Machines (SVM), k-nearest Neighbour (k-NN) and Logistic Regression were trained on a dataset of 5368 compounds. RDKit and Mordred toolkits were used to calculate features. To determine the most effective model, various performance metrics were used such as accuracy, precision, recall, F1 score, and area under the receiver operating characteristic curve. The best-performing model was further refined with hyperparameter tuning and tenfold cross-validation. The SVM model with filtering outperformed the other machine learning models and demonstrated 80.26% and 81.13% accuracy on the test and validation datasets, respectively. The study also provided insights into the molecular descriptors that play the most important role in predicting the ability of a molecule to pass the M. tb cell wall, which could guide future compound design. The model is available at https://github.com/PGlab-NIPER/MTB_Permeability.

由结核分枝杆菌(M. tb)引起的结核病(TB)继续对全世界的健康构成重大威胁。耐药菌株的出现凸显了对新型疗法的迫切需要。结核杆菌独特的细胞壁为细菌提供了一层额外的保护,因此只有能够穿透这层屏障的化合物才能到达细菌细胞壁内的目标。本文介绍了如何创建一个可靠的机器学习(ML)模型来预测小分子的分枝杆菌细胞壁渗透性,并在一个包含 5368 种化合物的数据集上训练了四种 ML 算法,包括随机森林、支持向量机(SVM)、k-最近邻(k-NN)和逻辑回归。RDKit 和 Mordred 工具包用于计算特征。为了确定最有效的模型,使用了各种性能指标,如准确度、精确度、召回率、F1 分数和接收者工作特征曲线下面积。通过超参数调整和十倍交叉验证,进一步完善了表现最佳的模型。带有过滤功能的 SVM 模型在测试数据集和验证数据集上的表现优于其他机器学习模型,准确率分别为 80.26% 和 81.13%。该研究还深入揭示了在预测分子通过结核杆菌细胞壁的能力方面发挥最重要作用的分子描述符,这可以为未来的化合物设计提供指导。该模型可在 https://github.com/PGlab-NIPER/MTB_Permeability 上查阅。
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引用次数: 0
Discovery of novel 4-trifluoromethyl-2-anilinoquinoline derivatives as potential anti-cancer agents targeting SGK1. 发现新型 4-三氟甲基-2-苯胺喹啉衍生物作为靶向 SGK1 的潜在抗癌剂。
IF 3.9 2区 化学 Q2 CHEMISTRY, APPLIED Pub Date : 2024-08-09 DOI: 10.1007/s11030-024-10951-4
Guangcan Xu, Lanlan Li, Mengfan Lv, Cheng Li, Jia Yu, Xiaoping Zeng, Xueling Meng, Gang Yu, Kun Liu, Sha Cheng, Heng Luo, Bixue Xu

Given the critical necessity for the development of more potent anti-cancer drugs, a series of novel compounds incorporating trifluoromethyl groups within the privileged 2-anilinoquinoline scaffold was designed, synthesized, and subjected to biological evaluation through a pharmacophore hybridization strategy. Upon evaluating the in vitro anti-cancer characteristics of the target compounds, it became clear that compound 8b, which contains a (4-(piperazin-1-yl)phenyl)amino substitution at the 2-position of the quinoline skeleton, displayed superior efficacy against four cancer cell lines by inducing apoptosis and cell cycle arrest. Following research conducted in a PC3 xenograft mouse model, it was found that compound 8b exhibited significant anti-cancer efficacy while demonstrating minimal toxicity. Additionally, the analysis of a 217-kinase panel pinpointed SGK1 as a potential target for this compound class with anti-cancer capabilities. This finding was further verified through molecular docking analysis and cellular thermal shift assays. To conclude, our results emphasize that compound 8b can be used as a lead compound for the development of anti-cancer drugs that target SGK1.

鉴于开发更有效的抗癌药物的迫切需要,我们设计、合成了一系列新型化合物,并通过药效杂交策略对这些化合物进行了生物学评价。在对目标化合物的体外抗癌特性进行评估后发现,化合物 8b 在喹啉骨架的 2 位上含有(4-(哌嗪-1-基)苯基)氨基取代,通过诱导细胞凋亡和细胞周期停滞,对四种癌细胞株显示出卓越的疗效。在对 PC3 异种移植小鼠模型进行研究后发现,化合物 8b 具有显著的抗癌功效,同时毒性极低。此外,对 217 激酶面板的分析将 SGK1 确定为该化合物类具有抗癌能力的潜在靶点。分子对接分析和细胞热转移实验进一步验证了这一发现。总之,我们的研究结果表明,化合物 8b 可以作为先导化合物,用于开发靶向 SGK1 的抗癌药物。
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引用次数: 0
Green synthesis and cytotoxic activity of functionalized naphthyridine. 功能化萘啶的绿色合成和细胞毒性活性。
IF 3.9 2区 化学 Q2 CHEMISTRY, APPLIED Pub Date : 2024-08-08 DOI: 10.1007/s11030-024-10929-2
Somayeh Soleimani-Amiri, Mahsa Hojjati, Zinatossadat Hossaini

A multicomponent synthesis of 1,8-naphthyridine with high yields utilizing benzaldehydes, malononitrile, phenol, and acetylenic esters in aqueous solution at room temperature in the presence of SiO2/Fe3O4 as a reusable catalyst is reported. Using the MTT test, the cytotoxic properties of all the produced compounds were assessed in vitro against cancer cell lines (MCF-7 and A549) and normal cell lines (BEAS-2B). It was discovered that the most effective cytotoxic agent, doxorubicin-like in its lack of selectivity, was the derivative 5h. On the other hand, the compound 5c might be regarded as an equipotent molecule with greater selectivity in relation to doxorubicin. Also, this study investigates the antioxidant effects of 1,8-naphthyridine carboxylates, along with other studies conducted in this study.

本研究采用 SiO2/Fe3O4 作为可重复使用的催化剂,在室温下利用水溶液中的苯甲醛、丙二腈、苯酚和乙炔酯,以高收率多组分合成了 1,8-萘啶。利用 MTT 试验,在体外评估了所有生成化合物对癌细胞株(MCF-7 和 A549)和正常细胞株(BEAS-2B)的细胞毒性。结果发现,最有效的细胞毒剂是衍生物 5h,它具有类似多柔比星的选择性。另一方面,化合物 5c 可被视为与多柔比星具有更大选择性的等效分子。此外,本研究还调查了 1,8-萘啶羧酸盐的抗氧化作用,以及本研究中进行的其他研究。
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引用次数: 0
Natural product-derived ALK inhibitors for treating ALK-driven lung cancers: an in silico study. 用于治疗 ALK 驱动型肺癌的天然产物衍生 ALK 抑制剂:一项硅学研究。
IF 3.9 2区 化学 Q2 CHEMISTRY, APPLIED Pub Date : 2024-08-08 DOI: 10.1007/s11030-024-10953-2
Saud O Alshammari, Qamar A Alshammari

Anaplastic lymphoma kinase (ALK)-driven lung cancer represents a critical therapeutic target, demanding innovative approaches for the identification of effective inhibitors. Anaplastic lymphoma kinase (ALK), a key protein involved in the pathogenesis of ALK-driven lung cancers, has been the focus of extensive drug discovery efforts. This study employed a comprehensive computational drug discovery approach, integrating virtual screening with the Lipinski filter, re-docking, molecular dynamics (MD) simulations, and free energy calculations to identify potential inhibitors from a natural compound library. Utilizing the MTiOpenScreen web server, we screened for compounds that exhibit favorable interactions with ALK, resulting in 1227 compounds with virtual screening scores ranging from - 10.2 to - 3.7 kcal/mol. Subsequent re-docking of three selected compounds (ZINC000059779788, ZINC000043552589, and ZINC000003594862) and one reference compound against ALK yielded docking scores - 10.4, - 10.2, - 10.2, and - 10.1 kcal/mol, respectively. These compounds demonstrated promising interactions with ALK, suggesting potential inhibitory effects. Advanced analyses, including MD simulation and binding free energy calculations, further supported the potential efficacy of these compounds. MD simulations, particularly the root mean square deviation (RMSD) and root mean square fluctuation (RMSF) analyses, revealed that compounds ZINC000059779788 and ZINC000003594862 achieved better stability compared to compound ZINC000043552589. These stable conformations suggest effective binding over time. Free energy calculations using the MM/GBSA method showed that ZINC000059779788 had the most favorable binding energy, indicating a strong and stable interaction with the ALK protein. The promising computational findings from this study emphasize the necessity for additional experimental testing to verify the therapeutic efficacy of these natural compounds for treating lung cancers.

无性淋巴瘤激酶(ALK)驱动的肺癌是一个关键的治疗靶点,需要创新的方法来确定有效的抑制剂。无性淋巴瘤激酶(ALK)是参与 ALK 驱动型肺癌发病机制的关键蛋白,一直是广泛药物发现工作的重点。这项研究采用了一种全面的计算药物发现方法,将虚拟筛选与利宾斯基过滤器、再对接、分子动力学(MD)模拟和自由能计算结合起来,从天然化合物库中找出潜在的抑制剂。利用 MTiOpenScreen 网络服务器,我们筛选出了与 ALK 有良好相互作用的化合物,结果发现了 1227 种化合物,其虚拟筛选得分在 - 10.2 到 - 3.7 kcal/mol 之间。随后对三个选定化合物(ZINC000059779788、ZINC000043552589 和 ZINC000003594862)和一个参考化合物与 ALK 进行了重新对接,对接得分分别为 - 10.4、- 10.2、- 10.2 和 - 10.1 kcal/mol。这些化合物表现出与 ALK 的良好相互作用,表明它们具有潜在的抑制作用。包括 MD 模拟和结合自由能计算在内的高级分析进一步证实了这些化合物的潜在功效。MD 模拟,特别是均方根偏差(RMSD)和均方根波动(RMSF)分析表明,与化合物 ZINC000043552589 相比,化合物 ZINC000059779788 和 ZINC000003594862 具有更好的稳定性。这些稳定的构象表明它们能长期有效地结合在一起。使用 MM/GBSA 方法进行的自由能计算显示,ZINC000059779788 的结合能最高,表明其与 ALK 蛋白的相互作用强烈而稳定。这项研究的计算结果前景广阔,因此有必要进行更多的实验测试,以验证这些天然化合物对治疗肺癌的疗效。
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引用次数: 0
Synthesis of novel 4-substituted isatin Schiff base derivatives as potential autophagy inducers and evaluation of their antitumour activity. 合成新型 4-取代靛红席夫碱衍生物作为潜在的自噬诱导剂并评估其抗肿瘤活性。
IF 3.9 2区 化学 Q2 CHEMISTRY, APPLIED Pub Date : 2024-08-07 DOI: 10.1007/s11030-024-10954-1
Huayuan Tan, Guanglong Zhang, Chenlu Xu, Xue Lei, Jiayi Chen, Haitao Long, Xuemei Qiu, Wenhang Wang, Yue Zhou, Danping Chen, Chengpeng Li, Zhurui Li, Zhenchao Wang

Induction of autophagic death in cancer cells is one of the promising strategies for the development of anti-cancer therapeutics. In the present study, we designed and synthesized a series of isatin Schiff base derivatives containing thioether structures. After discovering the highly active target compound H13 (IC50 = 4.83 μM) based on in vitro antiproliferation, we also found it had a high safety against normal cells HEK293 with CC50 of 69.01 μM, indicating a sufficient therapeutic window. In addition, to provide reference for subsequent studies, a model was successfully constructed by Sybyl software. Preliminary mechanistic studies suggested that H13-induced apoptosis may be closely related to ROS accumulation and mitochondrial dysfunction. Subsequent studies revealed that H13 inhibited cell proliferation by inducing cellular autophagy mainly through blocking signal of the PI3K/AKT/mTOR pathway. Altogether, these results suggested that H13 was potentially valuable as a lead compound.

诱导癌细胞自噬死亡是开发抗癌疗法的一种有前途的策略。在本研究中,我们设计并合成了一系列含有硫醚结构的isatin席夫碱衍生物。在发现了体外抗增殖的高活性靶向化合物 H13(IC50 = 4.83 μM)之后,我们还发现它对正常细胞 HEK293 具有很高的安全性,CC50 为 69.01 μM,这表明它具有足够的治疗窗口期。此外,为了给后续研究提供参考,我们还利用 Sybyl 软件成功构建了一个模型。初步机理研究表明,H13诱导的细胞凋亡可能与ROS积累和线粒体功能障碍密切相关。随后的研究发现,H13主要通过阻断PI3K/AKT/mTOR通路信号诱导细胞自噬,从而抑制细胞增殖。总之,这些结果表明,H13 是一种有潜在价值的先导化合物。
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引用次数: 0
Recent developments in the design of functional derivatives of edaravone and exploration of their antioxidant activities. 依达拉奉功能衍生物设计及其抗氧化活性探索的最新进展。
IF 3.9 2区 化学 Q2 CHEMISTRY, APPLIED Pub Date : 2024-08-05 DOI: 10.1007/s11030-024-10940-7
R Divya Mohan, Naveen V Kulkarni

Edaravone, a pyrazalone derivative, is an antioxidant and free radical scavenger used to treat oxidative stress-related diseases. It is a proven drug to mitigate conditions prevailing to oxidative stress by inhibiting lipid peroxidation, reducing inflammation, and thereby preventing endothelial cell death. In recent years, considerable interest has been given by researchers in the derivatization of edaravone by adding varieties of substituents of versatile steric and functional properties to improve its antioxidant and pharmacological activity. This review accounts all the important methods developed for the derivatization of edaravone and the impacts of the structural modifications on the antioxidant activity of the motif.

依达拉奉是一种吡唑酮衍生物,是一种抗氧化剂和自由基清除剂,用于治疗与氧化应激有关的疾病。它是一种行之有效的药物,可通过抑制脂质过氧化、减少炎症从而防止内皮细胞死亡,从而缓解氧化应激导致的疾病。近年来,研究人员对依达拉奉的衍生化产生了浓厚的兴趣,他们在依达拉奉中加入了各种具有多种立体和功能特性的取代基,以提高其抗氧化性和药理活性。本综述介绍了对依达拉奉进行衍生化的所有重要方法,以及结构修饰对其抗氧化活性的影响。
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引用次数: 0
Application progress of deep generative models in de novo drug design 深度生成模型在新药设计中的应用进展。
IF 3.9 2区 化学 Q2 CHEMISTRY, APPLIED Pub Date : 2024-08-04 DOI: 10.1007/s11030-024-10942-5
Yingxu Liu, Chengcheng Xu, Xinyi Yang, Yanmin Zhang, Yadong Chen, Haichun Liu

The deep molecular generative model has recently become a research hotspot in pharmacy. This paper analyzes a large number of recent reports and reviews these models. In the central part of this paper, four compound databases and two molecular representation methods are compared. Five model architectures and applications for deep molecular generative models are emphatically introduced. Three evaluation metrics for model evaluation are listed. Finally, the limitations and challenges in this field are discussed to provide a reference and basis for developing and researching new models published in future.

Graphical abstract

Artificial intelligence has made significant leaps with the rapid development of big data and high-performance computing technology. As a technical means, artificial intelligence and deep learning have been deeply applied in all aspects of drug research, equipping researchers with innovative solutions and insights.

深度分子生成模型近来已成为药学领域的研究热点。本文分析了近期的大量报道,并对这些模型进行了评述。在本文的中心部分,比较了四个化合物数据库和两种分子表示方法。重点介绍了深度分子生成模型的五种模型架构和应用。列出了模型评估的三个评价指标。最后,讨论了该领域的局限性和挑战,为今后开发和研究新模型提供参考和依据。
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引用次数: 0
Suppressing Mycobacterium tuberculosis virulence and drug resistance by targeting Eis protein through computational drug discovery 通过计算药物发现靶向 Eis 蛋白抑制结核分枝杆菌的毒力和耐药性
IF 3.8 2区 化学 Q2 CHEMISTRY, APPLIED Pub Date : 2024-08-03 DOI: 10.1007/s11030-024-10946-1
Geethu S. Kumar, Amaresh Kumar Sahoo, Nishant Ranjan, Vivek Dhar Dwivedi, Sharad Agrawal

Tuberculosis (TB) remains a critical health threat, particularly with the emergence of multidrug-resistant strains. This demands attention from scientific communities and healthcare professionals worldwide to develop effective treatments. The enhanced intracellular survival (Eis) protein is an acetyltransferase enzyme of Mycobacterium tuberculosis that functions by adding acetyl groups to aminoglycoside antibiotics, which interferes with their ability to bind to the bacterial ribosome, thereby preventing them from inhibiting protein synthesis and killing the bacterium. Therefore, targeting this protein accelerates the chance of restoring the aminoglycoside drug activity, thereby reducing the emergence of drug-resistant TB. For this, we have screened 406,747 natural compounds from the Coconut database against Eis protein. Based on MM/GBSA rescoring binding energy, the top 5 most prominent natural compounds, viz. CNP0187003 (− 96.14 kcal/mol), CNP0176690 (− 93.79 kcal/mol), CNP0136537 (− 92.31 kcal/mol), CNP0398701 (− 91.96 kcal/mol), and CNP0043390 (− 91.60 kcal/mol) were selected. These compounds exhibited the presence of a substantial number of hydrogen bonds and other significant interactions confirming their strong binding affinity with the Eis protein during the docking process. Subsequently, the MD simulation of these compounds exhibited that the Eis-CNP0043390 complex was the most stable, followed by Eis-CNP0187003 and Eis-CNP0176690 complex, further verified by binding free energy calculation, principal component analysis (PCA), and Free energy landscape analysis. These compounds demonstrated the most favourable results in all parameters utilised for this investigation and may have the potential to inhibit the Eis protein. There these findings will leverage computational techniques to identify and develop a natural compound inhibitor as an alternative for drug-resistant TB.

结核病(TB)仍然是一个严重的健康威胁,尤其是随着耐多药菌株的出现。这需要全世界的科学界和医疗保健专业人员给予关注,以开发出有效的治疗方法。增强细胞内生存(Eis)蛋白是结核分枝杆菌的一种乙酰转移酶,其功能是在氨基糖苷类抗生素上添加乙酰基,干扰其与细菌核糖体结合的能力,从而阻止其抑制蛋白质合成并杀死细菌。因此,以这种蛋白质为靶点可以加快恢复氨基糖苷类药物活性的机会,从而减少耐药性结核病的出现。为此,我们从椰子数据库中筛选了 406,747 种针对 Eis 蛋白的天然化合物。根据 MM/GBSA 重排结合能,选出了前 5 个最突出的天然化合物,即 CNP0187003(- 96.14 kcal/mol)、CNP0176690(- 93.79 kcal/mol)、CNP0136537(- 92.31 kcal/mol)、CNP0398701(- 91.96 kcal/mol)和 CNP0043390(- 91.60 kcal/mol)。在对接过程中,这些化合物显示出大量氢键和其他重要的相互作用,证实它们与 Eis 蛋白具有很强的结合亲和力。随后,对这些化合物进行的 MD 模拟显示,Eis-CNP0043390 复合物最稳定,其次是 Eis-CNP0187003 和 Eis-CNP0176690 复合物,结合自由能计算、主成分分析(PCA)和自由能景观分析进一步验证了这一点。这些化合物在本次研究使用的所有参数中都显示出最有利的结果,可能具有抑制 Eis 蛋白的潜力。这些发现将利用计算技术确定和开发一种天然化合物抑制剂,作为抗药性结核病的替代疗法。
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引用次数: 0
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Molecular Diversity
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