Seawater fungi-derived compound screening to identify novel small molecules against dengue virus NS5 methyltransferase and NS2B/NS3 protease

Computational evaluation of quinones of Nigella sativa L. as potential inhibitor of dengue virus NS5 methyltransferase

Aedes aegypti is the primary vector for the transmission of the dengue virus, which causes dengue fever, dengue hemorrhagic illness and dengue shock syndrome. There is now no antiviral medication available to treat DENV, which kills thousands of people each year and infects millions of individuals. A possible target for the creation of fresh and efficient dengue treatments is the DENV-3 NS5 MTase. So, Nigella sativa quinones were examined using in silico methods to find natural anti-DENV compounds. The in silico docking was conducted utilising the Discovery Studio software on the quinones of N. sativa and the active site of the target protein DENV-3 NS5 MTase. In addition, the druggability and pharmacokinetics of the lead compound were assessed. Dithymoquinone was comparable to the reference compound in terms of its ability to bind to the active site of target protein. Dithymoquinone met the requirements for drug likeness and Lipinski's principles, as demonstrated by the ADMET analysis and drug likeness results. The current study indicated that the dithymoquinone from N. sativa had anti-DENV activity, suggesting further drug development and dengue treatment optimisation.Communicated by Ramaswamy H. Sarma.

Computational approaches for innovative anti-viral drug discovery using Orthosiphon aristatus blume miq against dengue virus

Dengue virus has emerged as infectious mosquito borne disease involved in lowering platelets and white blood cells (WBC) count particularly. The genome structure is based on several structural and non-structural proteins essential for viral replication and progeny. One of the major proteins of replication is non-structural protein 3 (NS3) that transforms polyproteins into functional proteins with a cofactor non-structural protein (NS2B). Heat Shock Protein 70 (HSP70), is a human protein that assists in replication, viral entry and virion synthesis. Therefore, to inhibit the spread of dengue infection, there is a need of antivirals targeting replication proteins and other human proteins that help in dengue virus multiplication. By systemic approach based on molecular docking, ADMET (absorption, distribution, metabolism, excretion and toxicity) properties and molecular dynamic simulation (MD), potent inhibitors can be predicted. Inhibition of NS2B/NS3 dengue and HSP70 proteins involved in multiple steps in dengue virus progression can be prevented by using different phytochemicals. Molecular docking was performed using AutoDock Vina, PatchDock, and SwissDock. Interactions of obtained complex were observed in PyMOL and PLIP. Validation was checked by PROCHEK, simulation was performed using iMODS followed by preclinical testing by admetSAR. Ladanein, a flavonoid of Orthosiphon aristatus, was obtained as the lead compound to inhibit major replication protein of dengue virus with inhibitory potential against HSP70 protein. In summary, various in silico approaches were used to obtain the best phytochemical having anti-dengue potential.Communicated by Ramaswamy H. Sarma.

Exploring the inhibitory potential of Nigella sativa against dengue virus NS2B/NS3 protease and NS5 polymerase using computational approaches

Dengue fever, a highly infectious and rapidly spreading vector borne illness, is classified as a Neglected Tropical Disease (NTD) by WHO because they generally afflict the world's poor and historically have not received as much attention as other diseases. DENV NS2B/NS3 protease and NS5 polymerase are regarded as significant prospective therapeutic targets because of their critical involvement in the viral replication cycle. To date, no specific antiviral agents exist for dengue. The commonly used herbal plant Nigella sativa is known for its antibacterial, antiviral, anti-inflammatory, wound-healing, and dermatological properties. Nevertheless, not enough studies on the antiviral effects of Nigella sativa against DENV are reported. The current study used several prediction techniques to anticipate the oral bioavailability of substances, druglikeness, and non-toxic and non-mutagenic effects which could lead to the development of novel, safer medications. Therefore, the current study was conducted to explore the inhibitory potential of 18 phytochemicals from Nigella sativa against two important enzymes of dengue virus i.e., NS2B/NS3 and NS5. Promising results have been observed for NS2B/NS3 with Taraxerol (-9.1 kcal mol^-1), isoquercetin (8.4 kcal mol^-1), apigenin, and stigmasterol (-8.3 kcal mol^-1). Similarly, NS5 has shown favorable outcomes with apigenin (-9.9 kcal mol^-1), rutin (-9.3 kcal mol^-1), nigellicine (-9.1 kcal mol^-1), and stigmasterol (-8.8 kcal mol^-1). MD simulations validated the structural flexibility of the NS2B/NS3-taraxerol and NS5-apigenin docking complexes based on an RMSF value below 5 Å. The study concluded that among the understudied phytocomponents of N. sativa, apigenin, nigellicine, nigellidine, dithymoquinone, taraxerol, campesterol, cycloeucalenol, stigmasterol and beta-sitosterol have been revealed as potential drug candidates, expected to show antiviral activity and promising drug likeliness. Phytochemicals on the short list may serve as inspiration for the creation of new drugs in the future. Further in vitro examination will assist in elucidating the molecular complexity of therapeutic and antiviral capabilities, opening several opportunities for researchers to identify novel medications throughout the drug development process.

Advances in Computational Methods to Discover New NS2B-NS3 Inhibitors Useful Against Dengue and Zika Viruses

The Flaviviridae virus family consists of the genera Hepacivirus, Pestivirus, and Flavivirus, with approximately 70 viral types that use arthropods as vectors. Among these diseases, dengue (DENV) and zika virus (ZIKV) serotypes stand out, responsible for thousands of deaths worldwide. Due to the significant increase in cases, the World Health Organization (WHO) declared DENV a potential threat for 2019 due to being transmitted by infected travelers. Furthermore, ZIKV also has a high rate of transmissibility, highlighted in the outbreak in 2015, generating consequences such as Guillain-Barré syndrome and microcephaly. According to clinical outcomes, those infected with DENV can be asymptomatic, and in other cases, it can be lethal. On the other hand, ZIKV has severe neurological symptoms in newborn babies and adults. More serious symptoms include microcephaly, brain calcifications, intrauterine growth restriction, and fetal death. Despite these worrying data, no drug or vaccine is approved to treat these diseases. In the drug discovery process, one of the targets explored against these diseases is the NS2B-NS3 complex, which presents the catalytic triad His51, Asp75, and Ser135, with the function of cleaving polyproteins, with specificity for basic amino acid residues, Lys- Arg, Arg-Arg, Arg-Lys or Gln-Arg. Since NS3 is highly conserved in all DENV serotypes and plays a vital role in viral replication, this complex is an excellent drug target. In recent years, computer-aided drug discovery (CADD) is increasingly essential in drug discovery campaigns, making the process faster and more cost-effective, mainly explained by discovering new drugs against DENV and ZIKV. Finally, the main advances in computational methods applied to discover new compounds against these diseases will be presented here. In fact, molecular dynamics simulations and virtual screening is the most explored approach, providing several hit and lead compounds that can be used in further optimizations. In addition, fragment-based drug design and quantum chemistry/molecular mechanics (QM/MM) provides new insights for developing anti-DENV/ZIKV drugs. We hope that this review offers further helpful information for researchers worldwide and stimulates the use of computational methods to find a promising drug for treating DENV and ZIKV.