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Mechanistic study of α-mangostin derivatives as potent α-glucosidase inhibitors.
IF 3.9 2区 化学 Q2 CHEMISTRY, APPLIED Pub Date : 2025-02-25 DOI: 10.1007/s11030-025-11141-6
Kamonpan Sanachai, Supakarn Chamni, Bodee Nutho, Saranyu Khammuang, Juthamat Ratha, Kiattawee Choowongkomon, Ploenthip Puthongking

α-Glucosidase inhibitors (AGIs) are pharmacological agents commonly used to manage postprandial hyperglycemia associated with type 2 diabetes mellitus (T2DM). Developing novel, potent AGIs remains a significant area of research. In this study, we investigated a series of derivatives of the natural product from α-mangostin as potential AGIs. A combined experimental and computational approach was employed to characterize promising compounds with potent α-glucosidase inhibitory activity. We found that α-mangostin (AM) and its derivatives (AM1 - 3) exhibited micromolar range α-glucosidase inhibition (IC50 ranging from 15.14 to 67.81 µM), surpassing the known drug acarbose (IC50 of 197.09 µM). Among the derivatives, AM1 exhibited the most promising α-glucosidase inhibition, displaying competitive inhibition kinetics with a Ki value of 47.04 µM. Molecular docking and molecular dynamics (MD) simulations provided mechanistic insights into the binding interactions between AM1 and the α-glucosidase active site. AM1 was observed to form hydrogen bonds and hydrophobic interactions with key amino acid residues within the enzyme's active site. The introduction of amine groups in compound AM1 enhanced activity compared to AM, the parent compound. This study highlights the potential of α-mangostin derivatives as potent AGIs. The identified lead compound, AM1, warrants further investigation to assess its efficacy and safety in managing T2DM.

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引用次数: 0
Identification of effective synthetic molecules against viral-induced cytokine release syndrome using in silico and in vitro approaches.
IF 3.9 2区 化学 Q2 CHEMISTRY, APPLIED Pub Date : 2025-02-25 DOI: 10.1007/s11030-025-11136-3
Hira Noor Malik, Almas Jabeen, Sajda Ashraf, Saba Farooq, Hana'a Iqbal, Zaheer Ul-Haq

Acute respiratory distress syndrome (ARDS) is the leading cause of mortality in pathogen-mediated lung inflammation. Viral-induced cytokine release syndrome (CRS) has emerged as a global pandemic, characterized by a hyperactive immune response and excessive cytokine production causing irreversible lung injury. This study aimed to evaluate FDA-approved drugs for their potential to target hyperactive immune response and SARS-CoV-2 viral replication simultaneously. Six potential 3-CLpro inhibitors were identified by molecular docking using MOE software, including ebastine (1), orlistat (2), atracurium besylate (3), piperaquine phosphate (4), valsartan (5), and acarbose (6), among which 1-3 binds strongly to the target protein with binding affinity of - 8.22, - 9.12, and - 7.81, kcal/mol, respectively. Additionally, all identified inhibitors except 4 revealed significant anti-viral potential, with a 50-100% reduction in SARS-CoV-2 plaques. Significant attenuation of phagocyte oxidative burst and inflammatory cytokines (IFN-γ, GM-CSF, IL-6, IL-2, IL-1β, TNF-α) demonstrated the immunomodulatory potential of these drugs. This study demonstrates the potential of pre-existing drugs to ameliorate the cytokine storm and oxidative damage with simultaneous anti-viral effects. The data provide pre-clinical support to develop these drugs as potential therapeutic agent against ARDS.

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引用次数: 0
Pterostilbene as a potent ESR-1 in breast cancer therapy: insights from network pharmacology, molecular docking, dynamics simulations, ADMET, and in vitro analysis.
IF 3.9 2区 化学 Q2 CHEMISTRY, APPLIED Pub Date : 2025-02-24 DOI: 10.1007/s11030-025-11144-3
Harneet Marwah, Hitesh Kumar Dewangan

This study investigated the molecular targets and pathways modulated by pterostilbene in breast cancer using network pharmacology and in vitro analysis. The structure of chemicals of pterostilbene was retrieved from PubChem, and gene targets were predicted through Swiss Target Prediction. Human-specific targets were validated using UniProtKB and breast cancer-related targets were identified using GeneCards and BioVenn. Protein-protein interaction (PPI) networks were created using STRING and visualized using Cytoscape, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses to elucidate biological functions. Molecular docking studies using AutoDock Vina were used to assess the binding interactions of pterostilbene with key nuclear receptors (PTGS2, ESR1, EGFR, and BCL2). Molecular dynamics (MD) simulations over 200 ns in GROMACS confirmed the stability of the ESR1-pterostilbene complex and highlighted significant hydrogen bonding. ADME/T was assessed using the Protox software. In vitro cytotoxicity was assessed using the MTT assay in MCF-7 cells. Sixteen key genes, including PTGS2, ESR1, EGFR, and BCL2, were identified as key targets connecting pterostilbene to breast cancer. PPI analysis identified ESR1, EGFR, and BCL2 as central nodes in the network. Molecular docking revealed robust binding of pterostilbene (below - 8.1 kcal/mol), suggesting potential modulation of estrogen receptor signaling. MD simulations confirmed the stability of the complex with favorable structural dynamics. Toxicity analysis suggested a low risk, and MTT assays revealed selective cytotoxicity of pterostilbene toward MCF-7 breast cancer cells (IC50 = 14.8 µM) with a Selectivity Index of 2.85 compared to normal HEL 299 cells. These findings highlight the potential of pterostilbene as a treatment option for breast cancer, which merits additional exploration in experimental models and human studies.

本研究利用网络药理学和体外分析方法研究了紫檀芪在乳腺癌中的分子靶点和调控通路。研究人员从 PubChem 中检索了紫檀芪的化学结构,并通过 Swiss Target Prediction 预测了紫檀芪的基因靶点。利用 UniProtKB 验证了人类特异性靶点,并利用 GeneCards 和 BioVenn 确定了乳腺癌相关靶点。使用 STRING 创建了蛋白质-蛋白质相互作用(PPI)网络,并使用 Cytoscape 将其可视化,随后进行了基因本体(GO)和京都基因组百科全书(KEGG)通路分析,以阐明生物功能。使用 AutoDock Vina 进行的分子对接研究评估了紫檀芪与关键核受体(PTGS2、ESR1、表皮生长因子受体和 BCL2)的结合相互作用。在 GROMACS 中进行了 200 ns 的分子动力学(MD)模拟,证实了 ESR1-紫檀芪复合物的稳定性,并强调了重要的氢键作用。ADME/T 采用 Protox 软件进行评估。在 MCF-7 细胞中使用 MTT 试验评估了体外细胞毒性。包括 PTGS2、ESR1、表皮生长因子受体和 BCL2 在内的 16 个关键基因被确定为连接紫檀芪与乳腺癌的关键靶点。PPI分析确定ESR1、表皮生长因子受体和BCL2是网络中的中心节点。分子对接显示紫檀芪的结合力很强(低于 - 8.1 kcal/mol),这表明它有可能调节雌激素受体的信号传导。MD 模拟证实了该复合物具有良好的结构动力学稳定性。毒性分析表明其风险较低,MTT 试验显示紫檀芪对 MCF-7 乳腺癌细胞具有选择性细胞毒性(IC50 = 14.8 µM),与正常 HEL 299 细胞相比,选择性指数为 2.85。这些发现凸显了紫檀芪作为乳腺癌治疗选择的潜力,值得在实验模型和人体研究中进一步探索。
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引用次数: 0
Design, synthesis and biological evaluation of novel dualaction statin conjugates with triglyceride and cholesterol lowering activities.
IF 3.9 2区 化学 Q2 CHEMISTRY, APPLIED Pub Date : 2025-02-23 DOI: 10.1007/s11030-025-11134-5
Zheng Qu, Ye-Cheng Liu, Qi Suo, Xu Wang, Jin-Wen Huang, Zhuo Wu, Fan-Hong Wu

A series of novel dual-action statin conjugates, which exhibit both triglyceride and cholesterol lowering activities, have been systematically designed, synthesized, and subjected to comprehensive pharmacological evaluation. All the target compounds were characterized by 1HNMR, 13CNMR, and HRMS. Biological evaluation demonstrated that the majority of the synthesized compounds exhibited significant lipid-lowering and cholesterol-reducing activities. In particular, ligand 8a demonstrated significant potency, resulting in a marked reduction in cholesterol and triglyceride levels in a dose-dependent manner. Its minimum response has lowered 2.778 mmol/L (cholesterol level) and 0.699 mmol/L (triglycerides level), surpassing the positive control. For the preliminary assessment of the safety of the target compound, the ADMETlab 2.0 predictive software was utilized. Data show that compared to the combination of drugs used clinically, the safety of the target compounds may be improved. These findings suggest that compound 8a holds promise as a potential candidate for the treatment of hyperlipidemia.

我们系统地设计、合成了一系列新型双效他汀共轭物,它们同时具有降低甘油三酯和胆固醇的活性,并对其进行了全面的药理学评价。所有目标化合物都通过 1HNMR、13CNMR 和 HRMS 进行了表征。生物学评价表明,合成的大多数化合物都具有显著的降血脂和降低胆固醇的活性。其中,配体 8a 表现出显著的效力,以剂量依赖的方式显著降低了胆固醇和甘油三酯的水平。其最低反应降低了 2.778 毫摩尔/升(胆固醇水平)和 0.699 毫摩尔/升(甘油三酯水平),超过了阳性对照。为了初步评估目标化合物的安全性,我们使用了 ADMETlab 2.0 预测软件。数据显示,与临床上使用的联合用药相比,目标化合物的安全性可能有所提高。这些研究结果表明,化合物 8a 有希望成为治疗高脂血症的潜在候选药物。
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引用次数: 0
Molecular dynamics simulation-driven focused virtual screening and experimental validation of Fisetin as an inhibitor of Helicobacter pylori HtrA protease.
IF 3.9 2区 化学 Q2 CHEMISTRY, APPLIED Pub Date : 2025-02-23 DOI: 10.1007/s11030-025-11137-2
Li Gao, Xianqiong Jiang, Hongtao Duan, Yan Shen, Kui Gu, Kuilong Huang, Yuanqiang Wang, Mao Shu, Rui Zhang, Zhihua Lin

Helicobacter pylori (H. pylori, Hp) is a primary contributor to various stomach diseases, including gastritis and gastric cancer. This bacterium can colonize gastric epithelial cells, compromising their integrity and leading to the development of these conditions. While antibiotics are the mainstay of treatment for H. pylori infections, their widespread use has led to serious issues with drug resistance. High-temperature requirement A (HtrA) protein is an active serine protease secreted by H. pylori, which can destroy gastric epithelium, thus helping H. pylori to colonize gastric mucosa efficiently. In this study, we identified three compounds-Quercetin, Fisetin, and Geniposide-as potential natural compounds that might specifically interact with the HtrA protein, based on molecular docking and molecular dynamics simulations (MDs). The casein hydrolysis experiment indicated that Fisetin could inhibit the activity of HtrA in hydrolyzing casein at the concentration of 50 μM m. Additionally, our in vitro antibacterial experiments further showed that Fisetin could effectively inhibit the growth of H. pylori in a concentration-dependent manner, with an inhibition rate of 80% achieved at a concentration of 10 μM. In summary, these results suggest that Fisetin has an inhibitory effect on the growth of H. pylori, and this study may be the first to reveal its obviously inhibitory effect on HtrA protein. Our findings imply that Fisetin could be a potential candidate for further research as a therapeutic agent targeting protein HtrA, providing a new direction for the exploration of lead compounds and potential drugs against H. pylori infections.

幽门螺杆菌(Hp)是导致胃炎和胃癌等各种胃病的主要因素。这种细菌会在胃上皮细胞中定植,损害上皮细胞的完整性,导致这些疾病的发生。虽然抗生素是治疗幽门螺杆菌感染的主要药物,但抗生素的广泛使用导致了严重的耐药性问题。高温要求 A(HtrA)蛋白是幽门螺杆菌分泌的一种活性丝氨酸蛋白酶,它能破坏胃上皮细胞,从而帮助幽门螺杆菌有效地定植于胃粘膜。在本研究中,我们根据分子对接和分子动力学模拟(MDs)确定了三种化合物--槲皮素、鱼腥草素和染料木苷--作为可能与 HtrA 蛋白发生特异性相互作用的潜在天然化合物。此外,体外抗菌实验进一步表明,Fisetin 能以浓度依赖的方式有效抑制幽门螺杆菌的生长,浓度为 10 μM 时抑制率达到 80%。总之,这些结果表明,鱼腥草素对幽门螺杆菌的生长具有抑制作用,而本研究可能是首次揭示其对 HtrA 蛋白的明显抑制作用。我们的研究结果表明,鱼腥草素有可能作为一种靶向 HtrA 蛋白的治疗剂而被进一步研究,这将为探索先导化合物和治疗幽门螺杆菌感染的潜在药物提供一个新的方向。
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引用次数: 0
Design and synthesis of novel pyrimidine-pyrazole hybrids with dual anticancer and anti-inflammatory effects targeting BRAFV600E and JNK.
IF 3.9 2区 化学 Q2 CHEMISTRY, APPLIED Pub Date : 2025-02-22 DOI: 10.1007/s11030-025-11121-w
Mohammed S Abdel-Maksoud, Hebatollah E Eitah, Rasha M Hassan, Walaa Hamada Abd-Allah

Two new series of pyrimidinyl ethyl pyrazoles derivatives 13a-f and 14a-f were designed and synthesized to possess both anticancer effect by inhibiting BRAFV600E and anti-inflammatory effect by inhibiting JNK isoforms. The structure of the new compounds was generated from hybridization of two main moieties. The pyrimidinyl moiety from reported BRAFV600E inhibitors, and the pyrazole moiety from JNK isoforms inhibitors. The new final compounds were tested on BRAFV600E, JNK1, JNK2, and JNK3 to measure their kinases inhibitory effect. Compound 14c showed the highest activity on JNK isoforms and BRAFV600E with IC50 = 0.51 μM, 0.53 μM, 1.02 μM, 0.009 μM on JNK1, JNK2, JNK3,and BRAFV600E, respectively. All final compounds were tested over four cancer cell lines related to the target enzymes. Compound 14d showed the most potent activity on all tested cell lines with IC50 = 0.87 μM, 0.91, 0.42 μM and 0.63 μM on MOLT-4, K-562, SK-MEL-28, and A375 cell lines, respectively. The ability of 14d and 14c to inhibit MEK1/2 and ERK1/2 phosphorylation was performed by using western blot. The cell cycle analysis of compound 14d on A375 cell line revealed that compound 14d arrested cell growth at G0-G1 phase. Compound 14d remarkably decreased cell migration compared to control group in traditional migration test. Compounds 13a-f and 14a-f showed significant ability to inhibit nitric oxide release and PGE2 production on raw 264.7 macrophages. Compounds 13d and 14d exhibited high inhibitory effect on iNOS and COX-2 compared to COX-1. Finally, the effect of most potent compounds on TNF-alpha and IL-6 was determined.

{"title":"Design and synthesis of novel pyrimidine-pyrazole hybrids with dual anticancer and anti-inflammatory effects targeting BRAFV600E and JNK.","authors":"Mohammed S Abdel-Maksoud, Hebatollah E Eitah, Rasha M Hassan, Walaa Hamada Abd-Allah","doi":"10.1007/s11030-025-11121-w","DOIUrl":"https://doi.org/10.1007/s11030-025-11121-w","url":null,"abstract":"<p><p>Two new series of pyrimidinyl ethyl pyrazoles derivatives 13a-f and 14a-f were designed and synthesized to possess both anticancer effect by inhibiting BRAFV600E and anti-inflammatory effect by inhibiting JNK isoforms. The structure of the new compounds was generated from hybridization of two main moieties. The pyrimidinyl moiety from reported BRAFV600E inhibitors, and the pyrazole moiety from JNK isoforms inhibitors. The new final compounds were tested on BRAFV600E, JNK1, JNK2, and JNK3 to measure their kinases inhibitory effect. Compound 14c showed the highest activity on JNK isoforms and BRAFV600E with IC<sub>50</sub> = 0.51 μM, 0.53 μM, 1.02 μM, 0.009 μM on JNK1, JNK2, JNK3,and BRAFV600E, respectively. All final compounds were tested over four cancer cell lines related to the target enzymes. Compound 14d showed the most potent activity on all tested cell lines with IC<sub>50</sub> = 0.87 μM, 0.91, 0.42 μM and 0.63 μM on MOLT-4, K-562, SK-MEL-28, and A375 cell lines, respectively. The ability of 14d and 14c to inhibit MEK1/2 and ERK1/2 phosphorylation was performed by using western blot. The cell cycle analysis of compound 14d on A375 cell line revealed that compound 14d arrested cell growth at G0-G1 phase. Compound 14d remarkably decreased cell migration compared to control group in traditional migration test. Compounds 13a-f and 14a-f showed significant ability to inhibit nitric oxide release and PGE2 production on raw 264.7 macrophages. Compounds 13d and 14d exhibited high inhibitory effect on iNOS and COX-2 compared to COX-1. Finally, the effect of most potent compounds on TNF-alpha and IL-6 was determined.</p>","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":" ","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143476115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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
Understanding the conformational dynamics of PI3Kα due to helical domain mutations: insights from Markov state model analysis.
IF 3.9 2区 化学 Q2 CHEMISTRY, APPLIED Pub Date : 2025-02-21 DOI: 10.1007/s11030-025-11138-1
Vinod Jani, Uddhavesh Sonavane, Sangeeta Sawant

Phosphoinositide 3-kinases (PI3Ks) phosphorylate phosphoinositides on the membrane, which act as secondary signals for various cellular processes. PI3Kα, a heterodimer of the p110α catalytic subunit and the p85α regulatory subunit, is activated by growth factor receptors or mutations. Among these mutations, E545K present in the helical domain is strongly associated with cancer, and is known to disrupt interactions between the regulatory and catalytic subunits, leading to its constitutive activation. However, while the mutation's role in disrupting autoinhibition is well documented, the molecular mechanisms linking this mutation in the helical domain to the structural changes in the kinase domain remain poorly understood. This study aims to understand the conformational events triggered by the E545K mutation, elucidate how these changes propagate from the helical domain to the kinase domain, and identify crucial residues involved in the activation process. Molecular dynamics (MD) simulations combined with Markov state modeling (MSM) were employed to explore the conformational landscapes of both the wild-type and mutant systems. Structural and energetic analyses, including Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) calculations, revealed that the E545K mutation significantly reduces the binding affinity between the regulatory and catalytic subunits. The mutation was found to induce a sliding motion of the regulatory subunit along the catalytic subunit, leading to the disruption of key salt-bridges between these domains. This disruption releases the inhibitory effect of the regulatory subunit, resulting in increased domain motion, particularly in the adaptor-binding domain (ABD). Enhanced flexibility in the ABD, helical, and C2 domains facilitates the rearrangement of the two lobes of kinase domain, thereby promoting activation. Additionally, the mutation appears to enhance PI3Kα's membrane affinity via the Ras-binding domain (RBD). Network analysis helped to identify key residues that may involve in allosteric signaling pathways, providing insights into the communication between domains. Druggable pockets in the metastable states were predicted followed by its docking with a PI3K inhibitor library. Docking studies revealed the crucial residues that may be participating in inhibitor binding. The identification of residues and regions involved in activation mechanisms using MSM helped to reveal the conformational events and the knowledge on probable allosteric pockets, which may be helpful in designing better therapeutics.

{"title":"Understanding the conformational dynamics of PI3Kα due to helical domain mutations: insights from Markov state model analysis.","authors":"Vinod Jani, Uddhavesh Sonavane, Sangeeta Sawant","doi":"10.1007/s11030-025-11138-1","DOIUrl":"https://doi.org/10.1007/s11030-025-11138-1","url":null,"abstract":"<p><p>Phosphoinositide 3-kinases (PI3Ks) phosphorylate phosphoinositides on the membrane, which act as secondary signals for various cellular processes. PI3Kα, a heterodimer of the p110α catalytic subunit and the p85α regulatory subunit, is activated by growth factor receptors or mutations. Among these mutations, E545K present in the helical domain is strongly associated with cancer, and is known to disrupt interactions between the regulatory and catalytic subunits, leading to its constitutive activation. However, while the mutation's role in disrupting autoinhibition is well documented, the molecular mechanisms linking this mutation in the helical domain to the structural changes in the kinase domain remain poorly understood. This study aims to understand the conformational events triggered by the E545K mutation, elucidate how these changes propagate from the helical domain to the kinase domain, and identify crucial residues involved in the activation process. Molecular dynamics (MD) simulations combined with Markov state modeling (MSM) were employed to explore the conformational landscapes of both the wild-type and mutant systems. Structural and energetic analyses, including Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) calculations, revealed that the E545K mutation significantly reduces the binding affinity between the regulatory and catalytic subunits. The mutation was found to induce a sliding motion of the regulatory subunit along the catalytic subunit, leading to the disruption of key salt-bridges between these domains. This disruption releases the inhibitory effect of the regulatory subunit, resulting in increased domain motion, particularly in the adaptor-binding domain (ABD). Enhanced flexibility in the ABD, helical, and C2 domains facilitates the rearrangement of the two lobes of kinase domain, thereby promoting activation. Additionally, the mutation appears to enhance PI3Kα's membrane affinity via the Ras-binding domain (RBD). Network analysis helped to identify key residues that may involve in allosteric signaling pathways, providing insights into the communication between domains. Druggable pockets in the metastable states were predicted followed by its docking with a PI3K inhibitor library. Docking studies revealed the crucial residues that may be participating in inhibitor binding. The identification of residues and regions involved in activation mechanisms using MSM helped to reveal the conformational events and the knowledge on probable allosteric pockets, which may be helpful in designing better therapeutics.</p>","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":" ","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143466499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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
Explainable AI-driven prediction of APE1 inhibitors: enhancing cancer therapy with machine learning models and feature importance analysis. 可解释的人工智能驱动的 APE1 抑制剂预测:利用机器学习模型和特征重要性分析加强癌症治疗。
IF 3.9 2区 化学 Q2 CHEMISTRY, APPLIED Pub Date : 2025-02-21 DOI: 10.1007/s11030-025-11133-6
Aga Basit Iqbal, Tariq Ahmad Masoodi, Ajaz A Bhat, Muzafar A Macha, Assif Assad, Syed Zubair Ahmad Shah
<p><p>The viability of cells and the integrity of the genome depend on the detection and repair of damaged DNA through intricate mechanisms. Cancer treatment employs chemotherapy or radiation therapy to eliminate neoplastic cells by causing substantial damage to their DNA. In many cases, improved DNA repair mechanisms lead to resistance to these medicines; therefore, it is essential to expand efforts to develop drugs that can sensitise cells to these treatments by inhibiting the DNA repair process. Multiple studies have demonstrated a correlation between the overexpression of Apurinic/Apyrimidinic Endonuclease (APE1), the primary mammalian enzyme responsible for excising apurinic or apyrimidinic sites in DNA, and the resistance of cells to cancer therapies; in contrast, APE1 downregulation increases cellular susceptibility to DNA-damaging agents. Thus, the effectiveness of existing therapies can be improved by promoting the targeted sensitization of cancer cells while protecting healthy cells. The current study aims to employ explainable artificial intelligence (XAI) to enhance the accuracy and reliability of machine learning models for the prediction of APE1 inhibitors. Various ML-based regression models are employed to predict the pIC50 value of different medicines. Bayesian optimization and the Permutation Feature Importance (PFI) approach are employed to determine the best hyperparameters of machine learning models and to discover the most significant features for recognizing drug candidates that target APE1 enzymes, respectively. To acquire comprehensive elucidations for the predictive models in our research, two XAI methodologies, namely SHAP and LIME, are used. The SHAP analysis reveals that the features 'C1SP2' and 'ASP-2' are essential in influencing the model's predictions. The SHAP values demonstrate variability for features such as 'maxHBint2' and 'GATS1s,' signifying that their impact is dependent on specific instances within the dataset. The LIME study corroborates these findings, demonstrating that 'C1SP2' and 'ASP-2' are the most significant positive contributors, whereas features like 'SHCHnX,' 'nHdCH2,' and 'GATS1s' result in a decrease in the predicted values. Due to the limited sample size of the APE1 dataset, direct training on this dataset posed challenges in model generalization and reliability. To overcome this limitation, the BACE-1 dataset is leveraged for model training, enabling the ML models to learn from a more extensive and diverse chemical space. Among the tested algorithms, XGBoost demonstrated superior predictive performance, achieving R<sup>2</sup> = 0.890, MAE = 0.186, and RMSE = 0.245, significantly surpassing state-of-the-art methods, such as LightGBM and QSAR-ML, which attained R<sup>2</sup> scores of 0.798 and 0.630, respectively. These results highlight the robustness of our approach, demonstrating its enhanced generalization capability and superior predictive accuracy compared to existing methodologies.</
{"title":"Explainable AI-driven prediction of APE1 inhibitors: enhancing cancer therapy with machine learning models and feature importance analysis.","authors":"Aga Basit Iqbal, Tariq Ahmad Masoodi, Ajaz A Bhat, Muzafar A Macha, Assif Assad, Syed Zubair Ahmad Shah","doi":"10.1007/s11030-025-11133-6","DOIUrl":"https://doi.org/10.1007/s11030-025-11133-6","url":null,"abstract":"&lt;p&gt;&lt;p&gt;The viability of cells and the integrity of the genome depend on the detection and repair of damaged DNA through intricate mechanisms. Cancer treatment employs chemotherapy or radiation therapy to eliminate neoplastic cells by causing substantial damage to their DNA. In many cases, improved DNA repair mechanisms lead to resistance to these medicines; therefore, it is essential to expand efforts to develop drugs that can sensitise cells to these treatments by inhibiting the DNA repair process. Multiple studies have demonstrated a correlation between the overexpression of Apurinic/Apyrimidinic Endonuclease (APE1), the primary mammalian enzyme responsible for excising apurinic or apyrimidinic sites in DNA, and the resistance of cells to cancer therapies; in contrast, APE1 downregulation increases cellular susceptibility to DNA-damaging agents. Thus, the effectiveness of existing therapies can be improved by promoting the targeted sensitization of cancer cells while protecting healthy cells. The current study aims to employ explainable artificial intelligence (XAI) to enhance the accuracy and reliability of machine learning models for the prediction of APE1 inhibitors. Various ML-based regression models are employed to predict the pIC50 value of different medicines. Bayesian optimization and the Permutation Feature Importance (PFI) approach are employed to determine the best hyperparameters of machine learning models and to discover the most significant features for recognizing drug candidates that target APE1 enzymes, respectively. To acquire comprehensive elucidations for the predictive models in our research, two XAI methodologies, namely SHAP and LIME, are used. The SHAP analysis reveals that the features 'C1SP2' and 'ASP-2' are essential in influencing the model's predictions. The SHAP values demonstrate variability for features such as 'maxHBint2' and 'GATS1s,' signifying that their impact is dependent on specific instances within the dataset. The LIME study corroborates these findings, demonstrating that 'C1SP2' and 'ASP-2' are the most significant positive contributors, whereas features like 'SHCHnX,' 'nHdCH2,' and 'GATS1s' result in a decrease in the predicted values. Due to the limited sample size of the APE1 dataset, direct training on this dataset posed challenges in model generalization and reliability. To overcome this limitation, the BACE-1 dataset is leveraged for model training, enabling the ML models to learn from a more extensive and diverse chemical space. Among the tested algorithms, XGBoost demonstrated superior predictive performance, achieving R&lt;sup&gt;2&lt;/sup&gt; = 0.890, MAE = 0.186, and RMSE = 0.245, significantly surpassing state-of-the-art methods, such as LightGBM and QSAR-ML, which attained R&lt;sup&gt;2&lt;/sup&gt; scores of 0.798 and 0.630, respectively. These results highlight the robustness of our approach, demonstrating its enhanced generalization capability and superior predictive accuracy compared to existing methodologies.&lt;/","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":" ","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143466396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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
Discovery of highly effective antiviral agents based on flavonoid-benzothiazole against TMV.
IF 3.9 2区 化学 Q2 CHEMISTRY, APPLIED Pub Date : 2025-02-19 DOI: 10.1007/s11030-025-11126-5
Jiao Tian, Chunmei Hu, Tianyu Deng, Qing Zhou, Xingping Luo, Jieyu Li, Haotao Pu, Ying Yang, Da Liu, Wei Xue

A series of flavonol derivatives containing benzothiazole were designed and synthesized. The structures of all the compounds were characterized by NMR and HRMS. The results of the activity assay showed that some of the target compounds possessed outstanding in vivo antiviral activity against the tobacco mosaic virus (TMV). Among them, the median effective concentration (EC50) of L20 was 90.5 and 202.2 μg/mL for curative and protective activity against TMV, respectively, which was better than that of ningnanmycin (NNM: 252.0 and 204.2 μg/mL). The results of microcalorimetric thermophoresis (MST) and molecular docking experiments indicate that L20 binds TMV-CP more strongly than NNM; density functional theory (DFT) calculation the indicating that L20 is more chemical reactivity than NNM. In addition, malondialdehyde (MDA) and superoxide dismutase assay (SOD) activity measurements also fully confirmed that L20 stimulated the plant immune system and strengthened the plant's resistance to diseases by lowering the MDA content and increasing the SOD activity. Furthermore, the chlorophyll content test experiment found that L20 could reduce the destructive effect of viruses on chloroplasts, increase the content of chlorophyll, and promote photosynthesis. In conclusion, above experimental results suggested that flavonol derivatives containing benzothiazole could be further investigated as new plant virus antiviral drugs.

{"title":"Discovery of highly effective antiviral agents based on flavonoid-benzothiazole against TMV.","authors":"Jiao Tian, Chunmei Hu, Tianyu Deng, Qing Zhou, Xingping Luo, Jieyu Li, Haotao Pu, Ying Yang, Da Liu, Wei Xue","doi":"10.1007/s11030-025-11126-5","DOIUrl":"https://doi.org/10.1007/s11030-025-11126-5","url":null,"abstract":"<p><p>A series of flavonol derivatives containing benzothiazole were designed and synthesized. The structures of all the compounds were characterized by NMR and HRMS. The results of the activity assay showed that some of the target compounds possessed outstanding in vivo antiviral activity against the tobacco mosaic virus (TMV). Among them, the median effective concentration (EC<sub>50</sub>) of L20 was 90.5 and 202.2 μg/mL for curative and protective activity against TMV, respectively, which was better than that of ningnanmycin (NNM: 252.0 and 204.2 μg/mL). The results of microcalorimetric thermophoresis (MST) and molecular docking experiments indicate that L20 binds TMV-CP more strongly than NNM; density functional theory (DFT) calculation the indicating that L20 is more chemical reactivity than NNM. In addition, malondialdehyde (MDA) and superoxide dismutase assay (SOD) activity measurements also fully confirmed that L20 stimulated the plant immune system and strengthened the plant's resistance to diseases by lowering the MDA content and increasing the SOD activity. Furthermore, the chlorophyll content test experiment found that L20 could reduce the destructive effect of viruses on chloroplasts, increase the content of chlorophyll, and promote photosynthesis. In conclusion, above experimental results suggested that flavonol derivatives containing benzothiazole could be further investigated as new plant virus antiviral drugs.</p>","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":" ","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143447481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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
Computational exploration in search for novel natural product-derived EZH2 inhibitors for advancing anti-cancer therapy.
IF 3.9 2区 化学 Q2 CHEMISTRY, APPLIED Pub Date : 2025-02-19 DOI: 10.1007/s11030-025-11128-3
Sagar Singh Shyamal

Epigenetic regulation intricately governs cellular mechanisms, including proliferation, death, differentiation, and cell cycle orchestration. One such target, Enhancer of zeste homolog 2 (EZH2), is essential for epigenetic regulation. EZH2 trimethylates histone H3 lys27 (H3K27me3), inhibiting target gene transcription and promoting chromatin condensation, thereby initiating tumorigenesis, thus a potentially plausible target to disrupt cancer progression. In this virtual screening study, we utilized two large, open-source natural product libraries, NPASS and LOTUS, to search for potential natural product scaffolds capable of EZH2 inhibition. The merged library was filtered through increasingly rigorous criteria at each stage, including Medchem-based rule filters, 2D Tanimoto similarity, sequential rounds of docking, rescoring via ML-based functions, and binding pose visualization, funneling down to the most promising candidates for further pharmacokinetics and toxicological profiles. The best hits were analyzed for their binding stability through molecular dynamics simulation and their binding free energy estimations. Exploratory chemical analysis was conducted to understand the similarity of hits with known EZH2 chemical space. This comprehensive workflow identified one potential inhibitor, LTS0131784, which exhibited favorable pharmacokinetic toxicity profiling with binding stability and free energy better than the FDA-approved EZH2 inhibitor, Tazemetostat. Furthermore, the plausible binding mechanism was also elucidated by analyzing the per residue-free decomposition of the simulated trajectories, which indicated the involvement of the LTS0131784 with the key residues TYR:111, TRP:521, CYS:560, ASN:585, and SER:561.

{"title":"Computational exploration in search for novel natural product-derived EZH2 inhibitors for advancing anti-cancer therapy.","authors":"Sagar Singh Shyamal","doi":"10.1007/s11030-025-11128-3","DOIUrl":"https://doi.org/10.1007/s11030-025-11128-3","url":null,"abstract":"<p><p>Epigenetic regulation intricately governs cellular mechanisms, including proliferation, death, differentiation, and cell cycle orchestration. One such target, Enhancer of zeste homolog 2 (EZH2), is essential for epigenetic regulation. EZH2 trimethylates histone H3 lys27 (H3K27me3), inhibiting target gene transcription and promoting chromatin condensation, thereby initiating tumorigenesis, thus a potentially plausible target to disrupt cancer progression. In this virtual screening study, we utilized two large, open-source natural product libraries, NPASS and LOTUS, to search for potential natural product scaffolds capable of EZH2 inhibition. The merged library was filtered through increasingly rigorous criteria at each stage, including Medchem-based rule filters, 2D Tanimoto similarity, sequential rounds of docking, rescoring via ML-based functions, and binding pose visualization, funneling down to the most promising candidates for further pharmacokinetics and toxicological profiles. The best hits were analyzed for their binding stability through molecular dynamics simulation and their binding free energy estimations. Exploratory chemical analysis was conducted to understand the similarity of hits with known EZH2 chemical space. This comprehensive workflow identified one potential inhibitor, LTS0131784, which exhibited favorable pharmacokinetic toxicity profiling with binding stability and free energy better than the FDA-approved EZH2 inhibitor, Tazemetostat. Furthermore, the plausible binding mechanism was also elucidated by analyzing the per residue-free decomposition of the simulated trajectories, which indicated the involvement of the LTS0131784 with the key residues TYR:111, TRP:521, CYS:560, ASN:585, and SER:561.</p>","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":" ","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143447477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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
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Molecular Diversity
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