Phlorotannins as HIV Vpu inhibitors, an in silico virtual screening study of marine natural products

Targeting the HIV-1 Tat and Human Tat Protein Complex through Natural Products: An In Silico Docking and Molecular Dynamics Simulation Approach

Background:

Tat protein is considered essential for substantial HIV-1 replication, and is also required to break HIV-1 latency, resulting in productive HIV replication. The multifaceted regulatory role of HIV Tat and the fact that it is expressed in the early stages of HIV infection justify its potential as an anti-HIV drug target.

Objective:

The present study was undertaken with the aim to target HIV-1 Tat protein with natural compounds which could help in identifying potential inhibitors against HIV-1 Tat.

Methods:

In this study, we compared the binding of Tat protein and Human P-TEFb Tat protein complex (TPC) with phyto-steroids and terpenes to evaluate their potential for HIV-1 treatment. The docking ability of plant products with HIV-1 Tat and TPC was studied with respect to dissociation constant, geometric shape complementary score, approximate interface area, and binding energy using Patch dock and YASARA. Molecular dynamics simulation was set up to investigate the interactions of the natural compounds with Tat protein and human tat protein complex (TPC).

Results:

The binding energy and dissociation constant of Diosgenin, Catharanthine and Ginkgolide A with Tat and TPC were comparable to antiretroviral drugs, Maraviroc and Emtricitabine. The natural products, Diosgenin, Ginkgolide A and Catharanthine, showed the highest binding energy and were stable with Tat protein and TPC in the entire MD simulation run.

Conclusion:

The natural products, Diosgenin, Ginkgolide A and Catharanthine, showed highest binding energy and were stable with Tat protein and TPC in the entire MD simulation run. The binding energy and dissociation constant of Diosgenin, Catharanthine and Ginkgolide A with Tat and TPC were comparable to antiretroviral drugs, Maraviroc and Emtricitabine.

Aquatic Phlorotannins and Human Health: Bioavailability, Toxicity, and Future Prospects

Medicinal chemists and pharmacognosists have relied on terrestrial sources for bioactive phytochemicals to manage and treat disease conditions. However, minimal interest is given to sea life, especially macroalgae and their inherent phytochemical reserves. Phlorotannins are a special class of phytochemicals mainly predominant in brown algae of marine and estuarine habitats. Phlorotannins are formed through the polymerization of phloroglucinol residues and derivatives via the polyketide (acetate–malonate) pathway. Studies over the past decades have implicated phlorotannins with several bioactivities, including anti-herbivory, antioxidants, anti-inflammatory, anti-microbial, anti-proliferative, anti-diabetic, radio-protective, adipogenic, anti-allergic, and anti-human immunodeficiency virus (anti-HIV) properties. All these activities are reflected in their applications as nutraceuticals and cosmeceutical agents. This article reviews the chemical composition of phlorotannins, their biological roles, and their applications. Moreover, very few studies on phlorotannin bioavailability, safety, and toxicity have been thoroughly reviewed. The paper concludes by suggesting exciting research questions for further studies.

Discovery of new TLR7 agonists by a combination of statistical learning-based QSAR, virtual screening, and molecular dynamics

Search for new antiviral medications has surged in the past two years due to the COVID-19 crisis. Toll-like receptor 7 (TLR7) is among one of the most important TLR proteins of innate immunity that is responsible for broad antiviral response and immune system control. TLR7 agonists, as both vaccine adjuvants and immune response modulators, are among the top drug candidates for not only our contemporary viral pandemic but also other diseases. The agonists of TLR7 have been utilized as vaccine adjuvants and antiviral agents. In this study, we hybridized a statistical learning-based QSAR model with molecular docking and molecular dynamics simulation to extract new antiviral drugs by drug repurposing of the DrugBank database. First, we manually curated a dataset consisting of TLR7 agonists. The molecular descriptors of these compounds were extracted, and feature engineering was done to restrict the number of features to 45. We applied a statistically inspired modification of the partial least squares (SIMPLS) method to build our QSAR model. In the next stage, the DrugBank database was virtually screened structurally using molecular docking, and the top compounds for the guanosine binding site of TLR were identified. The result of molecular docking was again screened by the ligand-based approach of QSAR to eliminate compounds that do not display strong EC₅₀ values by the previously trained model. We then subjected the final results to molecular dynamics simulation and compared our compounds with imiquimod (an FDA-approved TLR7 agonist) and compound 1 (the most active compound against TLR7 in vitro, EC₅₀ = 0.2 nM). Our results evidently demonstrate that cephalosporins and nucleotide analogues (especially acyclic nucleotide analogues such as adefovir and cidofovir) are computationally potent agonists of TLR7. We finally reviewed some publications about cephalosporins that, just like pieces of a puzzle, completed our conclusion.