The aim of the research. In this work, in silico selection of DNA-aptamers to the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein was performed using molecular modeling methods. Material and methods. A new computational approach to aptamer in silico selection is based on a cycle of simulations, including the stages of molecular modeling, molecular docking, molecular dynamic simulations, and quantum chemical calculations. To verify the obtained calculated results flow cytometry, fluorescence polarization, and small-angle X-ray scattering methods were applied. Results. An initial library consisted of 256 16-mer oligonucleotides was modeled. Based on molecular docking results, the only one aptamer (Apt16) was selected from the library as a starting aptamer to the RBD protein. For Apt16/RBD complex, molecular dynamic and quantum chemical calculations revealed the pairs of nucleotides and amino acids whose contribution to the binding between aptamer and RBD is the largest. Taking into account these data, Apt16 was subjected to the structure modifi cations in order to increase the binding with the RBD. Th us, a new aptamer Apt25 was designed. Th e procedure of 1) aptamer structure modeling/modifi cation, 2) molecular docking, 3) molecular dynamic simulations, 4) quantum chemical calculations was performed several times. As a result, four aptamers (Apt16, Apt25, Apt27, Apt31) to the RBD were designed in silico without any preliminary experimental data. Binding of the each modeled aptamer to the RBD was studied in terms of interactions between residues in protein and nucleotides in the aptamers. Based on the simulation results, the strongest binding with the RBD was predicted for two Apt27 and Apt31aptamers. The calculated results are in good agreement with experimental data obtained by flow cytometry, fluorescence polarization, and small-angle X-ray scattering methods. Conclusion. Th e proposed computational approach to selection and refi nement of aptamers is universal and can be used for wide range of molecular ligands and targets
Glycosylation of Recombinant Antigenic Proteins from Mycobacterium tuberculosis: In Silico Prediction of Protein Epitopes and Ex Vivo Biological Evaluation of New Semi-Synthetic Glycoconjugates
