RESUMO
Nucleic acid aptamers specific to S-protein and its receptor binding domain (RBD) of SARS-CoV-2 (severe acute respiratory syndrome-related coronavirus 2) virions are of high interest as potential inhibitors of viral infection and recognizing elements in biosensors. Development of specific therapy and biosensors is complicated by an emergence of new viral strains bearing amino acid substitutions and probable differences in glycosylation sites. Here, we studied affinity of a set of aptamers to two Wuhan-type RBD of S-protein expressed in Chinese hamster ovary cell line and Pichia pastoris that differ in glycosylation patterns. The expression system for the RBD protein has significant effects, both on values of dissociation constants and relative efficacy of the aptamer binding. We propose glycosylation of the RBD as the main force for observed differences. Moreover, affinity of a several aptamers was affected by a site of biotinylation. Thus, the robustness of modified aptamers toward new virus variants should be carefully tested.
Assuntos
Aptâmeros de Nucleotídeos/química , Aptâmeros de Nucleotídeos/metabolismo , Ácidos Nucleicos Imobilizados/metabolismo , Glicoproteína da Espícula de Coronavírus/química , Glicoproteína da Espícula de Coronavírus/metabolismo , Animais , Sítios de Ligação , Células CHO , Cricetulus , Glicosilação , Ligação Proteica , Domínios Proteicos , Domínios e Motivos de Interação entre Proteínas , Processamento de Proteína Pós-Traducional , Proteínas Recombinantes/química , Proteínas Recombinantes/metabolismo , SARS-CoV-2 , Saccharomycetales/genéticaRESUMO
Immune checkpoint inhibitors (ICI) are a standard in cancer therapy, but few patients respond to the treatment. The aim of the present study was the determination of immunological markers for monitoring response to ICI. The present study included 74 patients receiving ICI in subsequent [group 1; non-small cell lung cancer (NSCLC)] and first-line setting (group 2; melanoma) and 30 patients with NSCLC receiving first-line chemotherapy. In groups 1 and 2 ß-2 microglobulin (B2-MG), neopterin (NPT), IL-6, IL-18, HLA-DRB1 and autoantibodies were assessed after two months of ICI, and before the start of next administration in group 3. In group 1 low level of B2-MG (P<0.0001), NPT (P<0.0001), IL-6 (P<0.0001), IL-18 (P=0.0003), HLA-DRB1*03 (P=0.016) and anti-TPO antibodies (P=0.016) were associated with response >six months. In group 2 high level of B2-MG (P=0.0001), NPT (P=0.0016), IL-6 (P=0.013) and IL-18 (P=0.032) were associated with early disease progression (
RESUMO
Background: The ability of ErbB3 receptor to functionally complement ErbB1-2 and induce tumor resistance to their inhibitors makes it a unique target in cancer therapy by monoclonal antibodies. Here we report the expression, purification and structural analysis of a new anti-ErbB3 single-chain antibody. Methods: The VHH fragment of the antibody was expressed in E. coli SHuffle cells as a SUMO fusion, cleaved by TEV protease and purified to homogeneity. Binding to the extracellular domain of ErbB3 was studied by surface plasmon resonance. For structural studies, the antibody was crystallized by hanging-drop vapor diffusion in two different forms. Results: We developed a robust and efficient system for recombinant expression of single-domain antibodies. The purified antibody was functional and bound ErbB3 with K D =15±1 nM. The crystal structures of the VHH antibody in space groups C2 and P1 were solved by molecular replacement at 1.6 and 1.9 Å resolution. The high-quality electron density maps allowed us to build precise atomic models of the antibody and the putative paratope. Surprisingly, the CDR H2 existed in multiple distant conformations in different crystal forms, while the more complex CDR H3 had a low structural variability. The structures were deposited under PDB entry codes 6EZW and 6F0D. Conclusions: Our results may facilitate further mechanistic studies of ErbB3 inhibition by single-chain antibodies. Besides, the solved structures will contribute to datasets required to develop new computational methods for antibody modeling and design.