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-Barre 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 His(51), Asp(75), and Ser(135), 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.