A Computational study of clades and drug adaptation to remdesivir in SARS-CoV-2

The first patient of Coronavirus disease 2019 (COVID-19) was detected in December 2019. This infectious disease is caused by a virus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and infecting people globally. Many researchers have been investigating to elucidate the characteristics of this virus from many aspects since the beginning of the outbreak. However, there is still limited information about this virus. In this thesis, we focused on the differences between clades and drug adaptations in SARS-CoV-2.

The second chapter focused on the differences between clades in SARS-CoV-2 by applying the method of differentially conserved positions (DCPs). DCPs can identify the differences between two groups of proteins by only amino acid sequences. We have used nomenclatures introduced by two organizations, GISAID and Nextstrain, to classify into clades. We identified DCPs between clades in SARS-CoV-2, which may reflect the differences of the phenotypes between clades.

The third chapter focused on drug adaptation to remdesivir in SARS-CoV-2 in vitro. The collaborator in Frankfurt cultured two strains of the virus until it adapted to remdesivir, and genomic sequencing was performed by Public Health England. By comparing the genomic data between the resistant virus and the control virus, we identified a number of mutations that may be considered as the adaptation factor to remdesivir. We also assessed the effect that may occur on the structure of the proteins by mutations.

The findings in this thesis provided information of DCPs between clades and information about the mutation that may cause an effect to the adaptation to remdesivir for future study of polymerase targeting drugs for SARS-CoV-2.