Mosquito-borne viruses of Flaviviridae virus family are dangerous for human. To develop drugs and vaccines and drugs against Flaviviridae viruses, promising targets must be identified.
The genomes and biochemistry of Yellow fever (YFV), West Nile (WNV), and Zika (ZIKV) viruses are similar. Therefore, the main aim of this project was to identify lead compounds which could simultaneously inhibit all three viruses targeting one or more viral proteins. Activation of non-structural proteins NS1, NS2A, NS3 and NS5 inside of mosquito-borne viruses is necessary for virial replication, as well as structural envelope E is responsible for entry of viral particles into the cell. Hence, the inhibition of at least one type of protein could neutralize the entire virus.
RCSB Protein Data Bank (https://www.rcsb.org/) was used to extracted data on sequences variations for 10 target proteins: structural envelope (E), non-structural hydrolase and transferase for YFV, non-structural hydrolase and methyltransferase for WNV and non-structural methyltransferase, helicase, protease RNA-dependent polymerase and structural envelope for ZIKV. These proteins contained bonded ligands, so locations of these ligands were used as a reference for initial search of possible binding pockets. In addition to it, allosteric sites binding were analyzed.
At the first step, BLAST online tool was applied to find similarity between studied proteins of YFV, WNV, and ZIKV. While genomes of YFV, WNV, and ZIKV are quite similar, the qualitative analysis of developed models revealed, that the best binding sites for promising hits were located in different places for same types of proteins. Using BLAST tool it was found, that in some cases differences are drastic. For instance, similarities between non-structural NS1 proteins were: ~ 55 % for ZIKA and DENV, ~50 % for ZIKA and YFV, ~ 55 % for ZIKA and WNV, ~ 45 % for YFV and DENV, ~ 45 % for YFV and WNV, and ~ 50 % for DNV and WNV.
A series of FDA approved drugs from Binding database (https://www.bindingdb.org) and DrugBank (http://www.drugbank.ca/drugs) were screened. Molecular docking was performed for more than 6000 drug-like compounds. The active sites of the enzymes were defined to include residues within 8.5 Å radius around inhibitor. Both crystallography-based and suggested allosteric sites were considered for docking. Final scores were used for database ranking.
The best pose with the highest score was selected to analyze the interactions between ligand and protein. Results were compared with literature data and some additional drugs (such as niclosamide and berberine) were added to the list of hits. At the next step, hits were used as references for deeper screening of ZINK database. Free energies of binding varied from −35 kJ/mol to -6 kJ/mol for hits.
A series of compounds were identified as inhibitors for proteins of certain type. For example, quinacrine and its derivatives acted in the same way against all nonstructural NS3 proteins. Another examples are nanchangmycin and lovastatin, that interacted with allosteric sites of NS2A and NS3 proteins. Specific poses were identified and analyzed. For instance, in the case of Zika, selected drugs mainly bonded to Glu234, Gln396, and Glu 231 inside of NS3 protein.
