Development of Fully Human, Bispecific Antibodies that Effectively Block Omicron Variant Pseudovirus Infections (preprint)

The emergence of highly immune invasive and transmissible variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has decreased the effectiveness of existing vaccines. It is, therefore, critical to develop effective and safe therapeutics for SARS-CoV-2 infections, especially for the most vulnerable and immunocompromised patients. Neutralizing antibodies have been shown to be successful at preventing severe disease from early SARS-CoV-2 strains, although their efficacy has diminished with the emergence of new variants. Here, we aim to develop fully human and broadly neutralizing monoclonal (mAb) and bispecific (BsAb) antibodies against SARS-CoV-2 and its variants. Specifically, we first identified two antibodies from human transgenic mice that bind to the receptor binding domain (RBD) of the SARS-CoV-2 spike protein and are capable of neutralizing SARS-CoV-2 and variants of concern with high to moderate affinity. Two non-competing clones with the highest affinity and functional blocking of ACE2 binding were then selected to be engineered into two BsAbs, which were then demonstrated to have relatively improved affinity, ACE2 blocking ability, and pseudovirus inhibition against several variants, including Omicron (B.1.1.529). Our findings provide one mAb candidate and two bsAb candidates for consideration of further clinical development and suggest that the bispecific format may be more effective than mAbs for SARS-CoV-2 treatment.

Interrelationship Between 2019-nCov Receptor DPP4 and Diabetes Mellitus Targets Based on Protein Interaction Network (preprint)

Objective: Exploring the relationship between diabetes mellitus targets and DPP4 of the receptor of novel coronavirus (2019-nCoV) through a protein interaction network to provide new perspective for clinical medication. Methods: Diabetes mellitus targets were obtained from GeneCards database. Targets with a relevance score exceeding 20 were included, and DPP4 protein was added manually. The initial protein interaction network was obtained through String. The targets directly related to DPP4 were selected as the final analysis targets. Importing them into String again to obtain the protein interaction network. Module identification, GO analysis and KEGG pathway analysis were carried out respectively. The impact of DPP4 on the whole network was analyzed by scoring the module where it located. Results: 43 DPP4-related proteins were finally selected from the diabetes mellitus targets and three functional modules were found by the cluster analysis. Module 1 was involved in insulin secretion and glucagon signaling pathway, module 2 and module 3 were involved in signaling receptor binding. The scoring results showed that LEP and apoB in module 1 were the highest, and the scores of INS, IL6 and ALB of cross module associated proteins of module 1 were the highest.Conclusions: DPP4 is widely associated with key proteins in diabetes mellitus. COVID-19 may affect DPP4 in patients with diabetes mellitus, leading to high mortality of diabetes mellitus combined with COVID-19. DPP4 inhibitors and IL-6 antagonists can be considered to reduce the effect of COVID-19 infection on diabetic patients.