Current Topics in Medicinal Chemistry - Volume 22, Issue 29, 2022

The COVID-19 outbreak and the pandemic situation have hastened the research community to design a novel drug and vaccine against its causative organism, the SARS-CoV-2. The spike glycoprotein present on the surface of this pathogenic organism plays an immense role in viral entry and antigenicity. Hence, it is considered an important drug target in COVID-19 drug design. Several three-dimensional crystal structures of this SARS-CoV-2 spike protein have been identified and deposited in the Protein DataBank during the pandemic period. This accelerated the research in computer- aided drug designing, especially in the field of structure-based drug designing. This review summarizes various structure-based drug design approaches applied to this SARS-CoV-2 spike protein and its findings. Specifically, it is focused on different structure-based approaches such as molecular docking, high-throughput virtual screening, molecular dynamics simulation, drug repurposing, and target-based pharmacophore modelling and screening. These structural approaches have been applied to different ligands and datasets such as FDA-approved drugs, small molecular chemical compounds, chemical libraries, chemical databases, structural analogs, and natural compounds, which resulted in the prediction of spike inhibitors, spike-ACE-2 interface inhibitors, and allosteric inhibitors.

There is a need to explore natural compounds against COVID-19 due to their multitargeted actions against various targets of nCoV. They act on multiple sites rather than single targets against several diseases. Thus, there is a possibility that natural resources can be repurposed to combat COVID-19. However, the biochemical mechanisms of these inhibitors were not known. To reveal the mode of anti-nCoV action, structure-based docking plays a major role. The present study is an attempt to explore various potential targets of SARS-CoV-2 and the structure-based screening of various potential natural inhibitors to combat the novel coronavirus.

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.