Objective: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) became one of the most important health problems of the 21st century. Non-structural protein-13 (nsp13/helicase) plays an important role in the replication of the viral genome and the viral life cycle. The SARS-CoV-2 genome has undergone thousands of mutations since the disease first appeared. Mutations pose a threat to the validity of therapeutics due to changes in protein structure. Modeling alterations caused by mutations in the viral proteome contributes to the development of effective antivirals. The changes in protein structure and stability caused by mutations seen in European isolates of SARS-CoV-2 were analyzed in the study with the aim of contributing to studies on the development of new anti-virals and the validity of existing therapeutics.
Methods: The changes in protein structure after mutation were modeled with deep learning algorithms. The alterations in protein stability were analyzed by SDM2, mCSM, DUET and DynaMut2.
Results: The mutation analysis revealed four (Pro77Leu, Gly170Ser, Tyr324Cys, and Arg392Cys) missense mutations in the nsp13 protein in European isolates of SARS-CoV-2. Mutations caused changes in protein structure (rmsd 0.294 Å) and stability (-.58 ≤ ΔΔG ≤ .003 kcal.mol-1). The atomic interactions formed by the mutant residues in the three-dimensional conformation of the protein have changed.
Conclusion: The mutations seen in European isolates for nsp13 of SARS-CoV-2 may lead to the emergence of different phenotypes in terms of viral activity. For this reason, the study may contribute to the success of the fight against the virus with different treatment approaches in different regions.