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Computational screening of medicinal plant phytochemicals to discover potent pan-serotype inhibitors against dengue virus.

ABSTRACT: Emergence of Dengue as one of the deadliest viral diseases prompts the need for development of effective therapeutic agents. Dengue virus (DV) exists in four different serotypes and infection caused by one serotype predisposes its host to another DV serotype heterotypic re-infection. We undertook virtual ligand screening (VLS) to filter compounds against DV that may inhibit inclusively all of its serotypes. Conserved non-structural DV protein targets such as NS1, NS3/NS2B and NS5, which play crucial role in viral replication, infection cycle and host interaction, were selected for screening of vital antiviral drug leads. A dataset of plant based natural antiviral derivatives was developed. Molecular docking was performed to estimate the spatial affinity of target compounds for the active sites of DV's NS1, NS3/NS2B and NS5 proteins. The drug likeliness of the screened compounds was followed by ADMET analysis whereas the binding behaviors were further elucidated through molecular dynamics (MD) simulation experiments. VLS screened three potential compounds including Canthin-6-one 9-O-beta-glucopyranoside, Kushenol W and Kushenol K which exhibited optimal binding with all the three conserved DV proteins. This study brings forth novel scaffolds against DV serotypes to serve as lead molecules for further optimization and drug development against all DV serotypes with equal effect against multiple disease causing DV proteins. We therefore anticipate that the insights given in the current study could be regarded valuable towards exploration and development of a broad-spectrum natural anti-dengue therapy.

SUBMITTER: Tahir Ul Qamar M

PROVIDER: S-EPMC6363786 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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Computational screening of medicinal plant phytochemicals to discover potent pan-serotype inhibitors against dengue virus.

Tahir Ul Qamar Muhammad M Maryam Arooma A Muneer Iqra I Xing Feng F Ashfaq Usman Ali UA Khan Faheem Ahmed FA Anwar Farooq F Geesi Mohammed H MH Khalid Rana Rehan RR Rauf Sadaf Abdul SA Siddiqi Abdul Rauf AR

Scientific reports 20190205 1

Emergence of Dengue as one of the deadliest viral diseases prompts the need for development of effective therapeutic agents. Dengue virus (DV) exists in four different serotypes and infection caused by one serotype predisposes its host to another DV serotype heterotypic re-infection. We undertook virtual ligand screening (VLS) to filter compounds against DV that may inhibit inclusively all of its serotypes. Conserved non-structural DV protein targets such as NS1, NS3/NS2B and NS5, which play cru ...[more]

PMID: 30723263

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Project description:Juniperus procera is a natural source of bioactive compounds with the potential of antitumor, antimicrobial, insecticidal, antifungal, and antioxidant activities. An optimization method was developed for total phenolic content (TPC), total flavonoid content (TFC), and total tannin content (TTC) in leaf and seed extract of Juniperus procera. Organic solvents (methanol (99.8%), ethanol (99%), and acetone (99.5%)), and deionized water (DI) were used for extraction. The estimation of TPC, TFC, and TTC in plant materials was carried out using UV-spectrophotometer and HPLC with the standards gallic acid, quercetin, and tannic acid. Recovery of TPC in leaf extract ranged from 2.9 to 9.7 mg GAE/g DW, TFC from 0.9 to 5.9 mg QE/g DW, and TTC ranged from 1.5 to 4.3 mg TA/g DW while the TPC value in the seed extract ranged from 0.53 to 2.6 mg GAE/g DW, TFC from 0.5 to 1.6 mg QE/g DW, and TTC ranged from 0.5 to 1.4 mg TA/g DW. This result revealed that methanol is the best solvent for recovery of the TPC value (9.7 mg) from leaf extract in comparison to other solvents. Ethanol recorded the highest result of TFC (5.9 mg) in leaf extract among the solvents whereas acetone was the best for TTC yield recovery from leaf extract (4.3 mg). In the case of the seed extract, ethanol was the best solvent for both TPC (2.6 mg), and TFC (1.6 mg) recovery in comparison to other solvents. Total tannin content in methanol resulted in significant recovery from seed extract (1.4 mg). Separation and quantification of gallic acid, quercetin, and tannic acid in plant materials were undertaken using HPLC. Gallic acid in leaf and seed of J. procera ranged from 6.6 to 9.2, 6.5 to 7.2 µg/g DW, quercetin from 6.3 to 18.2, 0.9 to 4.2 µg/g DW, and tannic acid from 16.2 to 29.3, 6.6 to 9.3 µg/g DW, respectively. Solvents have shown a significant effect in the extraction of phenolic compounds. Moreover, phytochemicals in plant materials were identified using GC-MS and resulted in very important bioactive compounds, which include anti-inflammatory, antibacterial, and antitumor agents such as ferruginol, phenanthrene, and n-hexadecanoic acid. In conclusion, the optimal solvent for extraction depends on the part of the plant material and the compounds that are to be isolated.

Project description:Background SARS-CoV-2 infection or COVID-19 is a major global public health issue that requires urgent attention in terms of drug development. Transmembrane Protease Serine 2 (TMPRSS2) is a good drug target against SARS-CoV-2 because of the role it plays during the viral entry into the cell. Virtual screening of phytochemicals as potential inhibitors of TMPRSS2 can lead to the discovery of drug candidates for the treatment of COVID-19. Purpose The study was designed to screen 132 phytochemicals from three medicinal plants traditionally used as antivirals; Zingiber officinalis Roscoe (Zingiberaceae), Artemisia annua L. (Asteraceae), and Moringa oleifera Lam. (Moringaceae), as potential inhibitors of TMPRSS2 for the purpose of finding therapeutic options to treat COVID-19. Methods Homology model of TMPRSS2 was built using the ProMod3 3.1.1 program of the SWISS-MODEL. Binding affinities and interaction between compounds and TMPRSS2 model was examined using molecular docking and molecular dynamics simulation. The drug-likeness and ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties of potential inhibitors of TMPRSS2 were also assessed using admetSAR web tool. Results Three compounds, namely, niazirin, quercetin, and moringyne from M. oleifera demonstrated better molecular interactions with binding affinities ranging from -7.1 to -8.0 kcal/mol compared to -7.0 kcal/mol obtained for camostat mesylate (a known TMPRSS2 inhibitor), which served as a control. All the three compounds exhibited good drug-like properties by not violating the Lipinski rule of 5. Niazirin and moringyne possessed good ADMET properties and were stable in their interactions with the TMPRSS2 based on the molecular dynamics simulation. However, the ADMET tool predicted the potential hepatotoxic and mutagenic effects of quercetin. Conclusion This study demonstrated the potentials of niazirin, quercetin, and moringyne from M. oleifera, to inhibit the activities of human TMPRSS2, thus probably being good candidates for further development as new drugs for the treatment or management of COVID-19. Graphical abstract Image, graphical abstract

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Computational screening of medicinal plant phytochemicals to discover potent pan-serotype inhibitors against dengue virus.

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Computational screening of medicinal plant phytochemicals to discover potent pan-serotype inhibitors against dengue virus.

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