Pub Date : 2025-02-21DOI: 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}
Pub Date : 2025-02-21DOI: 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":"<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.</","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}
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}
Pub Date : 2025-02-19DOI: 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}
Pub Date : 2025-02-18DOI: 10.1007/s11030-025-11140-7
Chunhui Ma, Fang Wang, Yiqing Wang, Fan Wu, Xuguang Zhang, Chuanhua Ding, Jifeng Zhao, Ying Ma, Wanzhong Li, Wenshan Liu
Lung cancer is the world's top ranked cancer, with non-small cell lung cancer accounting for over 80% of lung cancer, so it is an urgent need to find new treatment strategies for non-small cell lung cancer. Celastrol is one of the effective active ingredients in the plant Tripterygium wilfordii Hook. f., and research has found that celastrol has an inhibitory effect on non-small cell lung cancer. However, the significant toxic side effect of celastrol limits its clinical application. In this study, 9 novel celastrol derivatives were developed using PROTAC technology. Cell viability testing displayed that some compounds exhibited higher antiproliferative activity in cancer cells, and had lower toxicity to normal cells. Among them, compound MX-108 (11c) showed a high inhibitory activity with an IC50 value of 0.66 ± 0.07 μM against human non-small cell lung cancer NCI-H358 cells. The DIA-based quantitative proteomics and western blot analyses had confirmed that compound MX-108 could effectively degrade RAB9A protein in NCI-H358 cells. Compound MX-108 could downregulate the phosphorylation level of Akt and upregulate the expression of cleaved caspase 3. Molecular docking predicted that celastrol had a high binding ability with RAB9A protein. Furthermore, compound MX-108 could effectively inhibit tumor growth in xenografts model of NCI-H358 cells. This study provides new ideas for the development of novel celastrol derivatives to treat cancer.
{"title":"Discovery of the novel celastrol-based PROTACs for the treatment of non-small cell lung cancer.","authors":"Chunhui Ma, Fang Wang, Yiqing Wang, Fan Wu, Xuguang Zhang, Chuanhua Ding, Jifeng Zhao, Ying Ma, Wanzhong Li, Wenshan Liu","doi":"10.1007/s11030-025-11140-7","DOIUrl":"https://doi.org/10.1007/s11030-025-11140-7","url":null,"abstract":"<p><p>Lung cancer is the world's top ranked cancer, with non-small cell lung cancer accounting for over 80% of lung cancer, so it is an urgent need to find new treatment strategies for non-small cell lung cancer. Celastrol is one of the effective active ingredients in the plant Tripterygium wilfordii Hook. f., and research has found that celastrol has an inhibitory effect on non-small cell lung cancer. However, the significant toxic side effect of celastrol limits its clinical application. In this study, 9 novel celastrol derivatives were developed using PROTAC technology. Cell viability testing displayed that some compounds exhibited higher antiproliferative activity in cancer cells, and had lower toxicity to normal cells. Among them, compound MX-108 (11c) showed a high inhibitory activity with an IC<sub>50</sub> value of 0.66 ± 0.07 μM against human non-small cell lung cancer NCI-H358 cells. The DIA-based quantitative proteomics and western blot analyses had confirmed that compound MX-108 could effectively degrade RAB9A protein in NCI-H358 cells. Compound MX-108 could downregulate the phosphorylation level of Akt and upregulate the expression of cleaved caspase 3. Molecular docking predicted that celastrol had a high binding ability with RAB9A protein. Furthermore, compound MX-108 could effectively inhibit tumor growth in xenografts model of NCI-H358 cells. This study provides new ideas for the development of novel celastrol derivatives to treat cancer.</p>","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":" ","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143439690","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}
Pub Date : 2025-02-15DOI: 10.1007/s11030-025-11125-6
Shalini Mathpal, Tushar Joshi, P Priyamvada, Sudha Ramaiah, Anand Anbarasu
Penicillin-binding protein 4 (PBP4) is essential in imparting significant β-lactam antibiotics resistance in Staphylococcus aureus (S. aureus) and the mutation R200L in PBP4 is linked to β-lactam non-susceptibility in natural strains, complicating treatment options. Therefore, discovering novel therapeutics against the mutant PBP4 is crucial, and natural compounds from lichen have found relevance in this regard. The aim of our study was to identify novel inhibitors against the R200L mutation by applying machine learning (ML) approach. Predictive classification models were developed using six machine learning algorithms to categorize lichen-derived compounds as either active or inactive. The models were evaluated using ROC curves, confusion matrices, and relevant statistical parameters. Among these, the Extra Trees algorithm showed superior predictive accuracy at 81%. The model identified 115 potentially active compounds from lichen, which were further evaluated for drug-likeness and structural similarity to β-lactam antibiotics. The top 23 compounds, showing similarity to β-lactam drug, were subjected to molecular docking. Among the top 10 compounds, two compounds, Barbatolic acid and Orcinyl lecanorate, displayed promising results in 200 ns molecular dynamics (MD) simulations and MM-PBSA analysis, exhibiting better docking score compare to reference compound. Additionally, DFT calculations revealed negative binding energies and smaller HOMO-LUMO gaps for both compounds. The obtained results prove the utility of ML in screening natural compounds, and provide novel opportunities for the design of antimicrobial compounds in the future.
{"title":"Machine learning and cheminformatics-based Identification of lichen-derived compounds targeting mutant PBP4<sup>R200L</sup> in Staphylococcus aureus.","authors":"Shalini Mathpal, Tushar Joshi, P Priyamvada, Sudha Ramaiah, Anand Anbarasu","doi":"10.1007/s11030-025-11125-6","DOIUrl":"https://doi.org/10.1007/s11030-025-11125-6","url":null,"abstract":"<p><p>Penicillin-binding protein 4 (PBP4) is essential in imparting significant β-lactam antibiotics resistance in Staphylococcus aureus (S. aureus) and the mutation R200L in PBP4 is linked to β-lactam non-susceptibility in natural strains, complicating treatment options. Therefore, discovering novel therapeutics against the mutant PBP4 is crucial, and natural compounds from lichen have found relevance in this regard. The aim of our study was to identify novel inhibitors against the R200L mutation by applying machine learning (ML) approach. Predictive classification models were developed using six machine learning algorithms to categorize lichen-derived compounds as either active or inactive. The models were evaluated using ROC curves, confusion matrices, and relevant statistical parameters. Among these, the Extra Trees algorithm showed superior predictive accuracy at 81%. The model identified 115 potentially active compounds from lichen, which were further evaluated for drug-likeness and structural similarity to β-lactam antibiotics. The top 23 compounds, showing similarity to β-lactam drug, were subjected to molecular docking. Among the top 10 compounds, two compounds, Barbatolic acid and Orcinyl lecanorate, displayed promising results in 200 ns molecular dynamics (MD) simulations and MM-PBSA analysis, exhibiting better docking score compare to reference compound. Additionally, DFT calculations revealed negative binding energies and smaller HOMO-LUMO gaps for both compounds. The obtained results prove the utility of ML in screening natural compounds, and provide novel opportunities for the design of antimicrobial compounds in the future.</p>","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":" ","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143424483","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}
Pub Date : 2025-02-13DOI: 10.1007/s11030-024-11095-1
Yiming Wen, Peijia Xu, Yijie Chen, Jingyi Meng, Mingyue Zheng, Sulin Zhang, Dan Teng, Xutong Li
The p53 Y220C mutation, a prevalent structural variant in human cancers, compromises DNA binding and tumor suppressor functions by destabilizing the protein structure. Leveraging a combined approach of structure-based virtual screening, molecular dynamics simulations, and in vitro assays, we have identified C8, a racemic compound with an indole core and α, β-unsaturated carbonyl groups, as a covalent stabilizer for p53 Y220C. Protein thermal shift and homogeneous time-resolved fluorescence assays confirmed that C8 and its analogs selectively bind to p53 Y220C and restore its DNA binding ability. Subsequent molecular dynamics simulations and structure-activity relationship analyses showed that both enantiomers of C8 form covalent bonds with Cys124 and Cys220, stabilizing the mutant structure. C8 and its analogs emerge as promising lead candidates for restoring the Y220C mutant's transcriptional function, highlights the potential of this scaffold for further optimization into p53 Y220C-targeted therapeutics.
{"title":"Discovery of novel covalent stabilizers for p53 Y220C using structure-based drug discovery methods.","authors":"Yiming Wen, Peijia Xu, Yijie Chen, Jingyi Meng, Mingyue Zheng, Sulin Zhang, Dan Teng, Xutong Li","doi":"10.1007/s11030-024-11095-1","DOIUrl":"https://doi.org/10.1007/s11030-024-11095-1","url":null,"abstract":"<p><p>The p53 Y220C mutation, a prevalent structural variant in human cancers, compromises DNA binding and tumor suppressor functions by destabilizing the protein structure. Leveraging a combined approach of structure-based virtual screening, molecular dynamics simulations, and in vitro assays, we have identified C8, a racemic compound with an indole core and α, β-unsaturated carbonyl groups, as a covalent stabilizer for p53 Y220C. Protein thermal shift and homogeneous time-resolved fluorescence assays confirmed that C8 and its analogs selectively bind to p53 Y220C and restore its DNA binding ability. Subsequent molecular dynamics simulations and structure-activity relationship analyses showed that both enantiomers of C8 form covalent bonds with Cys124 and Cys220, stabilizing the mutant structure. C8 and its analogs emerge as promising lead candidates for restoring the Y220C mutant's transcriptional function, highlights the potential of this scaffold for further optimization into p53 Y220C-targeted therapeutics.</p>","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":" ","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143405094","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}
The low efficacy and toxicity of traditional chemotherapy, led by drug resistance of targeted anticancer therapies, have mandated the exploration and development of anticancer molecules. In this league, hybrid drugs, owing to their peculiar multitargeted functionality and structural diversity, could serve as vital leads in this quest for drug discovery. They are plausibly found to offer added advantages considering the improved efficacy, low toxicity, and improved patient compliance. Among numerous heterocycles explored, pyrimidine derivatives epitomize as a valuable resource for the hybrid drug development due to their validated efficacy and versatility. The present review discusses the role of pyrimidine, a diversified pharmacophore in drug development and concepts of hybrid drugs. The study covers the recent advancements in pyrimidine-based hybrid pharmacophores. It delves further into the challenges in hybrid drug development and ongoing research in hybrid drug discovery. Furthermore, the challenges faced in developing hybrid molecules, such as their design and optimization complexities, bioavailability and pharmacokinetics issues, target identification and validation, and off-target effects, are discussed.
{"title":"A review on pyrimidine-based pharmacophore as a template for the development of hybrid drugs with anticancer potential.","authors":"Shivam Sharma, M Arockia Babu, Roshan Kumar, Thakur Gurjeet Singh, Ashish Ranjan Dwivedi, Gazanfar Ahmad, Kapil Kumar Goel, Bhupinder Kumar","doi":"10.1007/s11030-025-11112-x","DOIUrl":"https://doi.org/10.1007/s11030-025-11112-x","url":null,"abstract":"<p><p>The low efficacy and toxicity of traditional chemotherapy, led by drug resistance of targeted anticancer therapies, have mandated the exploration and development of anticancer molecules. In this league, hybrid drugs, owing to their peculiar multitargeted functionality and structural diversity, could serve as vital leads in this quest for drug discovery. They are plausibly found to offer added advantages considering the improved efficacy, low toxicity, and improved patient compliance. Among numerous heterocycles explored, pyrimidine derivatives epitomize as a valuable resource for the hybrid drug development due to their validated efficacy and versatility. The present review discusses the role of pyrimidine, a diversified pharmacophore in drug development and concepts of hybrid drugs. The study covers the recent advancements in pyrimidine-based hybrid pharmacophores. It delves further into the challenges in hybrid drug development and ongoing research in hybrid drug discovery. Furthermore, the challenges faced in developing hybrid molecules, such as their design and optimization complexities, bioavailability and pharmacokinetics issues, target identification and validation, and off-target effects, are discussed.</p>","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":" ","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143397722","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}
Twenty-four amide compounds containing a sulfone moiety were synthesized and the antibacterial activity of the target compounds was tested. Some compounds show excellent antibacterial activity. For example, compound AC4 exhibited broad antibacterial activity with the EC50 of 0.55 mg/L for Xanthomonas axonopodis pv. citr (Xac), and 0.48 mg/L for Xanthomonas oryzae pv. oryzae (Xoo). In the greenhouse, compound AC4 with a concentration of 200 mg/L had good protective activity (39.3%) and curative activity (42.2%) against bacterial leaf blight, both were superior to the commercial antibacterial thiodiazole-copper (19.2% and 31.8%) and bismerthiazol (27.4% and 23.1%). The compound AC4 can inhibit the normal growth of Xoo by inhibiting the virality factors of Xoo (motility, exopolysaccharides, and biofilms). At the same time, molecular docking results showed that compound AC4 could interact with exopolysaccharides and quorum sensing-related proteins. This result was further supported by relative gene expression analysis. In addition, the compound AC4 can also increase membrane permeability, induce intracellular reactive oxygen species (ROS) levels to rise, and cause the surface of Xoo to change. The compound AC4 can be further studied as a potential antibacterial agent and this structure will continue to be optimized.
{"title":"Design, synthesis, and antibacterial activity of novel amide derivatives containing a sulfone moiety.","authors":"Yue Zou, Xing Liu, Zongnan Zhu, Chao Zhang, Yong Zhang, Yuanzheng Zhao, Xiang Zhu, Jixiang Chen","doi":"10.1007/s11030-024-11088-0","DOIUrl":"https://doi.org/10.1007/s11030-024-11088-0","url":null,"abstract":"<p><p>Twenty-four amide compounds containing a sulfone moiety were synthesized and the antibacterial activity of the target compounds was tested. Some compounds show excellent antibacterial activity. For example, compound AC4 exhibited broad antibacterial activity with the EC<sub>50</sub> of 0.55 mg/L for Xanthomonas axonopodis pv. citr (Xac), and 0.48 mg/L for Xanthomonas oryzae pv. oryzae (Xoo). In the greenhouse, compound AC4 with a concentration of 200 mg/L had good protective activity (39.3%) and curative activity (42.2%) against bacterial leaf blight, both were superior to the commercial antibacterial thiodiazole-copper (19.2% and 31.8%) and bismerthiazol (27.4% and 23.1%). The compound AC4 can inhibit the normal growth of Xoo by inhibiting the virality factors of Xoo (motility, exopolysaccharides, and biofilms). At the same time, molecular docking results showed that compound AC4 could interact with exopolysaccharides and quorum sensing-related proteins. This result was further supported by relative gene expression analysis. In addition, the compound AC4 can also increase membrane permeability, induce intracellular reactive oxygen species (ROS) levels to rise, and cause the surface of Xoo to change. The compound AC4 can be further studied as a potential antibacterial agent and this structure will continue to be optimized.</p>","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":" ","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143397523","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}
To further explore and discover natural products-based antifungal agents, seventeen tertiary amide-oleanolic acid hybrids were designed and synthesized, and structurally confirmed by 1H NMR, 13C NMR, HRMS, and melting point. Bioassay results illustrated that derivative 4 k exhibited prominent in vitro inhibitory activity against the mycelium growth of Gaeumannomyces graminis and Valsa mali with the EC50 values of 41.77 and 43.96 μg/mL, respectively. Meanwhile, the structure-activity relationships were also summarized. Moreover, in vivo control efficacy demonstrated that derivative 4 k displayed remarkable curative effect (CE) against V. mali at 200 μg/mL with the value of 52.6%, evidently superior to that of the positive control carbendazim (41.5%). Besides, derivative 4 k also exhibited good CE against Botrytis cinerea at 200 μg/mL with the value of 33.0%. Scanning electron microscope analysis initially indicated that derivative 4 k may exert its antifungal effect by leading to abnormal morphology on the mycelium surface, resulting in the aberrant hypha growth.
{"title":"Design and semisynthesis of novel oleanolic acid-based tertiary amide derivatives as promising antifungal agents against phytopathogenic fungi.","authors":"Guoqing Sui, Jiayi Sun, Ailing Zhang, Shuhua Cao, Xiaobo Huang","doi":"10.1007/s11030-025-11123-8","DOIUrl":"https://doi.org/10.1007/s11030-025-11123-8","url":null,"abstract":"<p><p>To further explore and discover natural products-based antifungal agents, seventeen tertiary amide-oleanolic acid hybrids were designed and synthesized, and structurally confirmed by <sup>1</sup>H NMR, <sup>13</sup>C NMR, HRMS, and melting point. Bioassay results illustrated that derivative 4 k exhibited prominent in vitro inhibitory activity against the mycelium growth of Gaeumannomyces graminis and Valsa mali with the EC<sub>50</sub> values of 41.77 and 43.96 μg/mL, respectively. Meanwhile, the structure-activity relationships were also summarized. Moreover, in vivo control efficacy demonstrated that derivative 4 k displayed remarkable curative effect (CE) against V. mali at 200 μg/mL with the value of 52.6%, evidently superior to that of the positive control carbendazim (41.5%). Besides, derivative 4 k also exhibited good CE against Botrytis cinerea at 200 μg/mL with the value of 33.0%. Scanning electron microscope analysis initially indicated that derivative 4 k may exert its antifungal effect by leading to abnormal morphology on the mycelium surface, resulting in the aberrant hypha growth.</p>","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":" ","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143397522","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}