Dengue fever is a viral illness caused by the dengue virus, which belongs to the flavivirus family. The virus is transmitted through the bite of infected Aedes mosquitoes and is commonly found in tropical and subtropical regions. The dengue virus has four different serotypes: DENV 1, DENV 2, DENV 3, and DENV 4, and it can infect people in any of these four forms. The most common symptoms of dengue fever include high fever, headache, and muscle pain. However, in many cases, the disease may be asymptomatic or cause only mild fever, which can be indistinguishable from other viral infections. In severe cases, the infection can progress to dengue hemorrhagic fever (DHF) or dengue shock syndrome [1, 2].
Over the past few decades, dengue infections have dramatically increased and are now prevalent in 100 countries across Africa, the Americas, the Eastern Mediterranean, Southeast Asia, and the Western Pacific regions. This means that half of the world's population is at risk of contracting dengue fever. In Bangladesh, last year, the Ministry of Health & Family Welfare reported a total of 52807 laboratory-confirmed dengue cases with 230 associated deaths. Despite the increasing number and severity of dengue infections each year, there is no specific treatment available, and vector control is the primary strategy to combat the spread of dengue infections [3, 4].
The levels of dengue virus infection are classified into primary, secondary, and concurrent infections. Current evidence suggests that concurrent infections result in the most severe form of dengue infection, followed by secondary infections that also cause a higher percentage of severe cases compared to primary infections [5]. Following primary infection, the antibody immunity provides long-term protection against re-infection by the same serotype. However, this protection is temporary to infections caused by other dengue serotypes [6]. The existence of multiple serotypes poses a significant challenge to the development of a dengue vaccine [7].
The mitigation of Dengue Hemorrhagic Fever (DHF) and Dengue Shock Syndrome is directly proportional to the level of viral infection in the human body [8]. Therefore, it is imperative that antiviral drugs are developed to reduce the viral load by impeding replication during the early stages of the infection. Researchers are currently exploring varied techniques for the development of antiviral drugs to alleviate the symptoms of dengue infections [9]. Despite the discovery of certain compounds that have exhibited the potential to inhibit the replication of the dengue virus, none of them have been successful in the clinical treatment of DENV infections [10, 11]. Presently, the lead discovery process relies heavily on high-throughput screening (HTS), which requires a vast collection of compounds to be physically available for testing [12]. For instance, the discovery of antiviral leads such as ST-148 necessitated the HTS of approximately 200,000 and 5,600 compounds for VGTI-A3. Although VGTI-A3 has high antiviral activity, the synthesis of a series of its analogues was needed to improve solubility. After testing the new analogues, another lead, VGTI-A3-03, was obtained [13, 14].
The pharmaceutical industry has leveraged Artificial Intelligence (AI) to expedite drug discovery. The availability of an extensive collection of biological, chemical, and biochemical interaction data makes prediction scores more reliable. Network pharmacology, molecular docking, and the computation of pharmacodynamics and pharmacokinetic properties are deployed to discover potential hits for the development of antiviral drugs to treat dengue infections. AI can assist in selecting suitable macromolecular targets and structure-based screening for hit identification, which reduces costs and time in the rational drug discovery processes [15].
Herein, network pharmacology, molecular docking, and computation of pharmacodynamics and pharmacokinetic properties are applied to discover potential hits for the development of antiviral drugs for the treatment of dengue infections.
In the process of drug discovery, target identification is a crucial step that requires the accumulation of biomedical research data to describe protein roles in infection and their therapeutic modulation potential [11, 16, 17]. One such protein of interest is the C protein of the dengue virus. This structural protein plays a significant role in the viral life cycle and the infected host cells by accumulating viral RNA into a nucleocapsid and forming a virus particle. When mature, the 12-kDa capsid C protein of DENV, with its small size and highly basic nature, plays a crucial role in virion assembly. Correct encapsidation of the RNA genome via DENV C generates a circular nucleocapsid with one ssRNA molecule [18–21].
Although flavivirus replication mainly occurs in the endoplasmic reticulum's perinuclear area and cytoplasm, the C protein has been observed to travel to the nucleus and nucleoli of infected cells via three nuclear localization signals (NLS) in some cases [22–24]. Flaviviral C interacts and binds with several nuclear proteins, including alpha-importin, allowing the virus to enter the nucleus [25]. However, the full biological significance of flaviviral C's presence in the nucleus during infection is still not fully understood.
To better understand the roles of viral proteins in viral infections, virus-host PPI networks provide a functional association of the viral proteins [26]. A network pharmacology approach was employed to analyze protein-protein interactions between the dengue virus and the human host. This approach identified potential targets that could help knock down the viral structure and minimize the viral load, leading to the rational selection of a suitable protein target [27].
Another important aspect of selecting capsid protein for this project is the availability of the crystal structure of the protein-inhibitor complex (6vg5), which provided a valid druggable binding pocket in the protein [28]. The molecular docking hypothesis was designed to guide the selected compounds in binding to that reference binding pocket. The field of in silico docking is booming as it becomes more important to scientists, with new algorithms and techniques being developed at an exponential rate [29]. Molecular docking is a computer simulation approach for predicting the structure of a receptor-ligand complex, in which the receptor is often a protein or a nucleic acid molecule (DNA or RNA) and the ligand is either a tiny molecule or another protein. It can also be described as a simulation method in which a ligand position in a hypothesized or pre-specified binding site is predicted [30]. Drug-like compounds in the library were screened by using a molecular docking approach and the stability of hit compounds was determined by molecular dynamics simulation of the protein-NP complexes. After identifying the hit, physicochemical properties, medicinal chemistry, ADME and safety profiles, possible off-target binding, and other biological activity were analysed using chemoinformatics and bioinformatics databases.
The capsid protein was subjected to an in silico screening process against a library of natural products from Azadirachta indica. Azadirachta indica, commonly known as the neem tree, is a medicinal plant widely used in South Asia and Africa. Its leaves, bark, fruit, flowers, oil, and gum have been historically used to treat various ailments, including cardiovascular diseases, neoplasia, and diabetes. Solvent extracts and compounds of the neem tree have been shown to possess pharmacological properties, such as antibacterial, antimicrobial, insecticidal, anti-diabetic, anti-cancerous, anti-inflammatory and antioxidant effects. These natural products can modulate different cellular and molecular mechanisms or signalling pathways, including free radical scavenging, detoxification, DNA repair, cell cycle alteration, programmed cell death mitigation and autophagy, immune surveillance, anti-inflammatory, anti-angiogenic, and anti-metastatic activities [31].
Research has shown that an aqueous extract of the leaves of Azadirachta indica can inhibit dengue virus (serotype 2) in in vitro and in vivo assays [32]. The findings from this study could provide a basis for the discovery of new antiviral therapeutic agents for the treatment of dengue infections.