Deciphering molecular properties and docking studies of hepatitis C and non-hepatitis C antiviral inhibitors – A computational approach

Venkatesan, Arthi; Dass, J. Febin Prabhu

doi:10.1016/j.lfs.2017.02.014

Cited by 3 publications

(2 citation statements)

References 29 publications

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“…Compounds with the least binding energy are known to be better hits (Venkatesan & Febin, 2017) (Vlietinck et al, 1998) and binds at the predicted active binding site forming strong hydrogen bonds. Visualising docking results revealed that ten amino acid residues are in contact with Compound 1 and 13 amino acids with compound 2.…”

Section: Molecular Dockingmentioning

confidence: 99%

Computational Drug Design against Ebola Virus Targeting Viral Matrix Protein VP30

2019

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Ebola viral disease (EVD) is a deadly infectious hemorrhagic viral fever caused by the Ebola virus with a high mortality rate. Until date, there is no effective drug or vaccination available to combat this condition. This study focuses on designing an effective antiviral drug for Ebola viral disease targeting viral protein 30 (VP30) of Ebola virus, highly required for transcription initiation. The lead molecules were screened for Lipinski rule of five, ADMET study following which molecular docking and bioactivity prediction was carried out. The compounds with the least binding energy were analyzed using interaction software. The results revealed that 6-Hydroxyluteolin and (-)-Arctigenin represent active lead compounds that inhibit the activity of VP30 protein and exhibits efficient pharmacokinetics. Both these compounds are plant-derived flavonoids and possess no known adverse effects on human health. In addition, they bind strongly to the predicted binding site centered on Lys180, suggesting that these two lead molecules can be imperative in designing a potential drug for EVD.

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Section: Molecular Dockingmentioning

confidence: 99%

Computational Drug Design against Ebola Virus Targeting Viral Matrix Protein VP30

2019

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“…Hepatitis C is one of the five (A, B, C, D, E) infectious diseases, which primarily affects the liver and causes both acute and chronic hepatitis (He et al, ). Hepatitis C virus (HCV) is a terrible virus with a positive‐ and single‐stranded RNA and is found in the Flaviviridae family (Venkatesan & Dass ). Statistically, the approximately 2.5% of people are affected by hepatitis C globally (Manfroni et al, ).…”

Section: Introductionmentioning

confidence: 99%

The activity prediction of indole inhibitors against HCV NS5B polymerase

Muhire

Zhai

et al. 2019

Chem Biol Drug Des

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Non-structural viral protein 5B (NS5B) is a viral protein in hepatitis C virus.Although various inhibitors against NS5B have been found, the activity prediction of similar untested inhibitors is still highly desirable. In this respect, the Tchebichef moments (TMs) calculated from the images of molecular structures were regarded as the independent variables while the inhibitory activity (pIC 50 ) was the dependent variable, and the predictive model was established by means of stepwise regression. The R-squared of leave-one-out cross-validation (Q 2 ) for the training set and the R-squared of prediction (R 2 p ) for external independent test set were 0.919 and 0.927, respectively. The obtained model was also evaluated strictly. Compared with the multivariate curve resolution with alternating least squares (MCR-ALS) and the QSAR approaches derived from the literature, the proposed method is more accurate and reliable. This study not only provides an effective approach to predict the biological activity of RNA replication's inhibitors, but also extends the QSAR modeling technique. K E Y W O R D Sbiological activity prediction model, hepatitis C virus, NS5B polymerase inhibitors, quantitative structure-activity relationship, Tchebichef image moments

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Structure-based drug design of novel peptidomimetic cellulose derivatives as HCV-NS3 protease inhibitors

Saleh

Elshemey

2017

Life Sciences

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Deciphering molecular properties and docking studies of hepatitis C and non-hepatitis C antiviral inhibitors – A computational approach

Cited by 3 publications

References 29 publications

Computational Drug Design against Ebola Virus Targeting Viral Matrix Protein VP30

Computational Drug Design against Ebola Virus Targeting Viral Matrix Protein VP30

The activity prediction of indole inhibitors against HCV NS5B polymerase

Structure-based drug design of novel peptidomimetic cellulose derivatives as HCV-NS3 protease inhibitors

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