Computer-Aided Discovery and Characterization of Novel Ebola Virus Inhibitors

Capuzzi, Stephen J.; Sun, Wei; Muratov, Eugene; Martínez-Romero, Carles; He, Shihua; Zhu, Wenjun; Li, Hao; Tawa, Gregory J.; Fisher, Ethan G; Xu, Miao; Shinn, Paul; Qiu, Xiangguo; Garcı́a-Sastre, Adolfo; Zheng, Wei; Tropsha, Alexander

doi:10.1021/acs.jmedchem.8b00035

Cited by 34 publications

(24 citation statements)

References 62 publications

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“…Tetrandrine, also known as Han‐Fang‐Ji‐Jia‐Su in Chinese, is a natural product belongs to the bis‐benzylisoquinoline alkaloid family that was originally isolated and purified from the roots of the traditional Chinese medicinal herb Stephania tetrandra S. Moore of the Menispermaceae family (see Figure 1). [ 37–40 ] Numerous investigations have demonstrated that this natural compound possesses a very broad‐spectrum of distinct pharmacological activities, including anticancer, [ 41 ] anti‐inflammatory, [ 42 ] anti‐nociceptive, [ 43,44 ] anti‐fibrotic, [ 45 ] anti‐depressant, [ 46 ] anti‐rheumatoid arthritis, [ 47,48 ] anti‐adipogenic, [ 49 ] anti‐microbial, [ 50,51 ] neuroprotective [ 52 ] and memory‐improving activities. [ 53,54 ]…”

Section: Introductionmentioning

confidence: 99%

Tetrandrine: a review of its anticancer potentials, clinical settings, pharmacokinetics and drug delivery systems

Luan

Zeng

2020

Journal of Pharmacy and Pharmacology

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Objectives Tetrandrine, a natural bisbenzylisoquinoline alkaloid, possesses promising anticancer activities on diverse tumours. This review provides systematically organized information on cancers of tetrandrine in vivo and in vitro, discuss the related molecular mechanisms and put forward some new insights for the future investigations. Key findings Anticancer activities of tetrandrine have been reported comprehensively, including lung cancer, colon cancer, bladder cancer, prostate cancer, ovarian cancer, gastric cancer, breast cancer, pancreatic cancer, cervical cancer and liver cancer. The potential molecular mechanisms corresponding to the anticancer activities of tetrandrine might be related to induce cancer cell apoptosis, autophagy and cell cycle arrest, inhibit cell proliferation, migration and invasion, ameliorate metastasis and suppress tumour cell growth. Pharmaceutical applications of tetrandrine combined with nanoparticle delivery system including liposomes, microspheres and nanoparticles with better therapeutic efficiency have been designed and applied encapsulate tetrandrine to enhance its stability and efficacy in cancer treatment. Summary Tetrandrine was proven to have definite antitumour activities. However, the safety, bioavailability and pharmacokinetic parameter studies on tetrandrine are very limited in animal models, especially in clinical settings. Our present review on anticancer potentials of tetrandrine would be necessary and highly beneficial for providing guidelines and directions for further research of tetrandrine.

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Section: Introductionmentioning

confidence: 99%

Tetrandrine: a review of its anticancer potentials, clinical settings, pharmacokinetics and drug delivery systems

Luan

Zeng

2020

Journal of Pharmacy and Pharmacology

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“…Some of these inhibitors are shown in Figure . Other studies include the identification of coumarin‐based antihistamine‐like molecules, benzoquinoline compounds (SW456 compound reported to be the most potent compound in the infectious EBOV assay, IC 50 = 0.5 μM), ellagic acid (IC 50 = 1.4 μM), and vindesine (IC 50 = 0.34 μM), that proved to have potential EBOV inhibition.…”

Section: Introductionmentioning

confidence: 99%

Perspectives towards antiviral drug discovery against Ebola virus

Mirza

Vanmeert

Ali

et al. 2019

Journal of Medical Virology

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Ebola virus disease (EVD), caused by Ebola viruses, resulted in more than 11 500 deaths according to a recent 2018 WHO report. With mortality rates up to 90%, it is nowadays one of the most deadly infectious diseases. However, no Food and Drug Administration‐approved Ebola drugs or vaccines are available yet with the mainstay of therapy being supportive care. The high fatality rate and absence of effective treatment or vaccination make Ebola virus a category‐A biothreat pathogen. Fortunately, a series of investigational countermeasures have been developed to control and prevent this global threat. This review summarizes the recent therapeutic advances and ongoing research progress from research and development to clinical trials in the development of small‐molecule antiviral drugs, small‐interference RNA molecules, phosphorodiamidate morpholino oligomers, full‐length monoclonal antibodies, and vaccines. Moreover, difficulties are highlighted in the search for effective countermeasures against EVD with additional focus on the interplay between available in silico prediction methods and their evidenced potential in antiviral drug discovery.

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“…The following metrics were computed and assessed by nested cross-validation: balanced accuracy (BA), mean misclassification error (MMCE), sensitivity (true positive rate (TPR)), specificity (true negative rate (TNR)), positive predictive value (PPV), and Area Under the Receiver Operating Characteristics Curve (AUC) with their widely known definitions and equations [121,122]. We were interested in predicting whether a particular substance may induce DILI; therefore, we focused on increasing the balanced accuracy, as well as PPV.…”

Section: Performance Evaluationmentioning

confidence: 99%

Computational Models Using Multiple Machine Learning Algorithms for Predicting Drug Hepatotoxicity with the DILIrank Dataset

Ancuceanu

Hovaneț

Anghel

et al. 2020

IJMS

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Drug-induced liver injury (DILI) remains one of the challenges in the safety profile of both authorized and candidate drugs, and predicting hepatotoxicity from the chemical structure of a substance remains a task worth pursuing. Such an approach is coherent with the current tendency for replacing non-clinical tests with in vitro or in silico alternatives. In 2016, a group of researchers from the FDA published an improved annotated list of drugs with respect to their DILI risk, constituting “the largest reference drug list ranked by the risk for developing drug-induced liver injury in humans” (DILIrank). This paper is one of the few attempting to predict liver toxicity using the DILIrank dataset. Molecular descriptors were computed with the Dragon 7.0 software, and a variety of feature selection and machine learning algorithms were implemented in the R computing environment. Nested (double) cross-validation was used to externally validate the models selected. A total of 78 models with reasonable performance were selected and stacked through several approaches, including the building of multiple meta-models. The performance of the stacked models was slightly superior to other models published. The models were applied in a virtual screening exercise on over 100,000 compounds from the ZINC database and about 20% of them were predicted to be non-hepatotoxic.

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Computer-Aided Discovery and Characterization of Novel Ebola Virus Inhibitors

Cited by 34 publications

References 62 publications

Tetrandrine: a review of its anticancer potentials, clinical settings, pharmacokinetics and drug delivery systems

Tetrandrine: a review of its anticancer potentials, clinical settings, pharmacokinetics and drug delivery systems

Perspectives towards antiviral drug discovery against Ebola virus

Computational Models Using Multiple Machine Learning Algorithms for Predicting Drug Hepatotoxicity with the DILIrank Dataset

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