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

Abstract

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.

Updates on Drug Designing Approach Through Computational Strategies: a Review

“…Some advantages and disadvantages of SBVS are represented in Figure 5 . Recently, the SBVS approach has become a boon for the drug discovery process; due to the greater accuracy of the obtained results [ 82 ]. The following are the examples of a few drugs that were discovered using SBVS: Darolutamide (Nubeqa): used for the treatment of prostate cancer, was discovered in 2014 [ 83 ].…”

Structure-guided identification and characterization of potent inhibitors targeting PhoP and MtrA to combat mycobacteria

“…CADD methods include the structure-based drug design (SBDD) and ligand-based drug design (LBDD) methods. SBDD is more commonly used than LBDD because it relies on widely available crystallographic structures for various biological targets [34] , [35] , [36] . Conversely, LBDD requires structural information about the target, which may be limited [35] , [36] .…”

“…SBDD is more commonly used than LBDD because it relies on widely available crystallographic structures for various biological targets [34] , [35] , [36] . Conversely, LBDD requires structural information about the target, which may be limited [35] , [36] . SBDD methods can be further classified into pharmacophore modeling and molecular docking methods [37] .…”

Mechanisms underlying the therapeutic effects of Gang Huo Qing wen granules in the treatment of influenza based on network pharmacology, molecular docking and molecular dynamics

“…In 2007, Hopkins, a British pharmacologist, first proposed the concept of network pharmacology (NP), which is defined as a branch of pharmacology based on the theoretical foundation of systems biology and multidirectional pharmacology, and utilizing the method of biomolecular network analysis to select specific nodes for new drug design and target analysis 18 , 24 . Molecular docking is a computer-aided drug design (CADD) method 25 , which is an important tool in NP to predict the binding affinity between drugs and targets. They can predict the binding affinity between a drug and its target by constructing drug–target-pathway network models and simulating drug–target interactions, which can reveal the mechanism of action and potential side effects of the drug.…”