ABSTRACT
Zoonoses have recently become the center of attention of the general population and scientific community. Notably, more than 30 new human pathogens have been identified in the last 30 years, 75% of which can be classified as zoonosis. The complete eradication of such types of infections is far out of reach, considering the limited understanding of animal determinants in zoonoses and their causes of emergence. Therefore, efforts must be doubled in examining the spread, persistence, and pathogenicity of zoonosis and studying possible clinical interventions and antimicrobial drug development. The search for antimicrobial bioactive compounds has assumed great emphasis, considering the emergence of multi-drug-resistant microorganisms. Among the biomolecules of emerging scientific interest are antimicrobial peptides (AMPs), potent biomolecules that can potentially act as important weapons against infectious diseases. Moreover, synthetic AMPs are easily tailored (bioinformatically) to target specific features of the pathogens to hijack, inducing no or very low resistance. Although very promising, previous studies on SAMPs' efficacy are still at their early stages. Indeed, further studies and better characterization on their mechanism of action with in vitro and in vivo assays are needed so as to proceed to their clinical application on human beings.
ABSTRACT
AIMS: Brazil is nowadays one of the epicentres of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic and new therapies are needed to face it. In the context of specific immune response against the virus, a correlation between Major Histocompatibility Complex Class I (MHC-I) and the severity of the disease in patients with COVID-19 has been suggested. Aiming at better understanding the biology of the infection and the immune response against the virus in the Brazilian population, we analysed SARS-CoV-2 protein S peptides in order to identify epitopes able to elicit an immune response mediated by the most frequent MHC-I alleles using in silico methods. METHODS: Our analyses consisted in searching for the most frequent Human Leukocyte Antigen (HLA)-A, HLA-B and HLA-C alleles in the Brazilian population, excluding the genetic isolates; then, we performed: molecular modelling for unsolved structures, MHC-I binding affinity and antigenicity prediction, peptide docking and molecular dynamics of the best fitted MHC-I/protein S complexes. RESULTS: We identified 24 immunogenic epitopes in the SARS-CoV-2 protein S that could interact with 17 different MHC-I alleles (namely, HLA-A*01:01; HLA-A*02:01; HLA-A*11:01; HLA-A*24:02; HLA-A*68:01; HLA-A*23:01; HLA-A*26:01; HLA-A*30:02; HLA-A*31:01; HLA-B*07:02; HLA-B*51:01; HLA-B*35:01; HLA-B*44:02; HLA-B*35:03; HLA-C*05:01; HLA-C*07:01 and HLA-C*15:02) in the Brazilian population. CONCLUSIONS: Being aware of the intrinsic limitations of in silico analysis (mainly the differences between the real and the Protein Data Bank (PDB) structure; and accuracy of the methods for simulate proteasome cleavage), we identified 24 epitopes able to interact with 17 MHC-I more frequent alleles in the Brazilian population that could be useful for the development of strategic methods for vaccines against SARS-CoV-2.