Discovery of Novel Hepatitis C Virus NS5B Polymerase Inhibitors by Combining Random Forest, Multiple e-Pharmacophore Modeling and Docking

Wei, Yu; Li, Jinlong; Qing, Jie; Minyuan, Huang; Wu, Ming; Gao, Fenghua; Li, Dongmei; Hong, Zhangyong; Kong, Lingbao; Huang, Weiqiang; Lin, Jianping

doi:10.1371/journal.pone.0148181

Cited by 46 publications

(31 citation statements)

References 87 publications

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“…13). The structure-based docking approach played a major role in identification of mercaptobenzoxazole (42e2, IC 50 ¼ 2.01 mM) as polymerase inhibitor [60]. An allosteric site of NS5B emerged as attractive target for structure-based design and discovery of small antiviral agents.…”

Section: Nucleoside Non-nucleoside and Protease Inhibitors As Anti-hmentioning

confidence: 99%

A review on HCV inhibitors: Significance of non-structural polyproteins

Ganta¹,

Gedda

Rathnakar

et al. 2019

European Journal of Medicinal Chemistry

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a b s t r a c tHepatitis C virus (HCV) mortality and morbidity is a world health misery with an approximate 130e150 million chronically HCV tainted and suffering individuals and it initiate critical liver malfunction like cirrhosis, hepatocellular carcinoma or liver HCV cancer. HCV NS5B protein one of the best studied therapeutic target for the identification of new drug candidates to be added to the combination or multiple combination medication recently approved. During the past few years, NS5B has thus been an important object of attractive medicinal chemistry endeavors, which induced to the surfacing of betrothal preclinical drug molecules. In this scenario, the current review set limit to discuss research published on NS5B and few other therapeutic functional inhibitors concentrating on hit investigation, hit to lead optimization, ADME parameters evaluation, and the SAR data which was out for each compound type and similarity taken into consideration. The discussion outlined in this specific review will surly helpful and vital tool for those medicinal chemists investigators working with HCV research programs mainly pointing on NS5B and set broad spectrum identification of creative anti HCV compounds. This mini review also tells each and every individual compound ability related how much they are active against NS5B and few other targets.

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Section: Nucleoside Non-nucleoside and Protease Inhibitors As Anti-hmentioning

confidence: 99%

A review on HCV inhibitors: Significance of non-structural polyproteins

Ganta¹,

Gedda

Rathnakar

et al. 2019

European Journal of Medicinal Chemistry

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“…These are divided in two groups: structural proteins (highly basic core protein C and the glycoproteins E1 and E2) and nonstructural (NS) proteins (p7, NS2, NS3, NS4A, NS4B, NS5A, and NS5B) . NS5B has been shown to be a promising target for therapeutics due to its crucial role in replicating the viral genome . The fact that mammalian cells lack a homologous enzyme also makes NS5B an attractive drug target due to the potential for selective inhibition of viral replication.…”

Section: Introductionmentioning

confidence: 99%

Molecular simulations to delineate functional conformational transitions in the HCV polymerase

2016

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Hepatitis C virus (HCV) is a global health concern for which there is no vaccine available. The HCV polymerase is responsible for the critical function of replicating the RNA genome of the virus. Transitions between at least two conformations (open and closed) are necessary to allow the enzyme to replicate RNA. In this study, molecular dynamic simulations were initiated from multiple crystal structures to understand the free energy landscape (FEL) explored by the enzyme as it interconverts between these conformations. Our studies reveal the location of distinct states within the FEL as well as the molecular interactions associated with these states. Specific hydrogen bonds appear to play a key role in modulating conformational transitions. This knowledge is essential to elucidate the role of these conformations in replication and may also be valuable in understanding the basis by which this enzyme is inhibited by small molecules. © 2016 Wiley Periodicals, Inc.

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“…HIV-1 reverse transcriptase and integrase catalyze sequentially the synthesis and integration of proviral DNA into the host genome[5]. At the same time, HCV NS5B polymerase is an essential protein involved in the replication of viral positive strand genomic RNA and used as a key target for therapeutic intervention[47,48].…”

Section: Resultsmentioning

confidence: 99%

Targeting against HIV/HCV Co-infection using Machine Learning-based multitarget-quantitative structure-activity relationships (mt-QSAR) Methods

Wei

et al. 2019

Preprint

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24Co-infection between HIV-1 and HCV is common today in certain populations. However, treatment of 25 co-infection is full of challenges with special consideration for potential hepatic safety and drug-drug 26 interactions. Multitarget inhibitors with less toxicity may provide a promising therapeutic strategy for 27 HIV/HCV co-infection. However, identification of one molecule acting on multiple targets simultaneously by 28 experimental evaluation is costly and time-consuming. In silico target prediction tools provide more 29 opportunities for the development of multitarget inhibitors. In this study, by combining naive Bayesian (NB) 30 and support vector machine (SVM) algorithms with two types of molecular fingerprints (MACCS and ECFP6), 31 60 classification models were constructed to predict the active compounds toward 11 HIV-1 targets and 4 32 HCV targets based on the multitarget-quantitative structure-activity relationships (mt-QSAR). 5-fold cross-33 validation and test set validation was performed to confirm the performance of 60 classification models. Our 34 results show that 60 mt-QSAR models appeared to have high classification accuracy in terms of ROC-AUC 35 values ranging from 0.83 to 1 with a mean value of 0.97 for HIV-1 models, and ROC-AUC values ranging 36 from 0.84 to 1 with a mean value of 0.96 for HCV. Furthermore, the 60 models were applied to 37 comprehensively predict the potential targets for additional 46 compounds including 27 approved HIV-1 drugs, 38 10 approved HCV drugs and 9 selected compounds known to be active on one or more targets of HIV-1 or 39 those of HCV. Finally, 18 hits including 7 HIV-1 approved drugs, 4 HCV approved drugs and 7 compounds 40 were predicted to be HIV/HCV co-infection multitarget inhibitors. The reported bioactivity data confirmed 41 that 7 compounds actually interacted with HIV-1 and HCV targets simultaneously with diverse binding 42 affinities. Of those remaining predicted hits and chemical-protein interaction pairs involving the potential 43 ability to suppress HIV/HCV co-infection deserve further investigation by experiments. This investigation 44 shows that the mt-QSAR method is available to predict chemical-protein interaction for discovering 45 multitarget inhibitors and provide a unique perspective on HIV/HCV co-infection treatment. 3 46 48 syndrome (AIDS), a pandemic disease[1]. In addition, hepatitis C virus (HCV) infection causes acute and 49 chronic liver disease, including cirrhosis and hepatocellular carcinoma[2]. Unfortunately, since HIV-1 and 50 HCV have similar routes of transmission, the risk of HIV/HCV co-infection is very high[3]. According to the 51 World Health organization (WHO), about 2.3 million persons of the estimated 36.7 million living with HIV 52 had been infected with HCV globally in 2015. It is necessary for those people to be diagnosed and provided 53 with effective and reasonable treatment for both HIV and hepatitis as a priority[4]. However, in the treatment 54 of HIV/HCV co-infection, special considerations must be ...

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Discovery of Novel Hepatitis C Virus NS5B Polymerase Inhibitors by Combining Random Forest, Multiple e-Pharmacophore Modeling and Docking

Cited by 46 publications

References 87 publications

A review on HCV inhibitors: Significance of non-structural polyproteins

A review on HCV inhibitors: Significance of non-structural polyproteins

Molecular simulations to delineate functional conformational transitions in the HCV polymerase

Targeting against HIV/HCV Co-infection using Machine Learning-based multitarget-quantitative structure-activity relationships (mt-QSAR) Methods

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