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Introduction: Computational antibody engineering, affinity maturation, and screening greatly aid in vaccine and therapeutic antibody development by increasing the speed and accuracy of predictions. This study presents a protocol for designing affinity enhancing mutants of antibodies through in silico mutagenesis. A SARS-CoV-2 cross-reactive neutralizing antibody, CR3022, is considered as a case study.Methods: Our study aimed at generating antibody candidates from the human antibody CR3022 (derived from convalescent SARS patient) against the RBD of SARS-CoV-2 via in silico affinity maturation using site-directed mutagenesis in mutation hotspots. We optimized the paratope of the CR3022 antibody towards the RBD of SARS-CoV-2 for better binding affinity and stability, employing molecular modeling, docking, dynamics simulations, and molecular mechanics energies combined with generalized Born and surface area (MM-GBSA). Results: Nine antibody candidates were generated post in silico site-directed mutagenesis followed by preliminary screening. Molecular dynamics simulation of 100 nanoseconds and MM-GBSA analysis confirmed L-K45S as a lead antibody with the highest binding affinity against the RBD compared to wild-type and mutant counterparts. Three out of the remaining mutants were also found to have distinct epitopes and binding, possessing a potential to be developed against emerging SARS-CoV-2 variants of concern. Conclusion: The study demonstrates the use of an integrative antibody engineering protocol for enhancing affinity and neutralization potential through mutagenesis using robust open-source computational tools and predictors. This study highlights unique scoring and ranking methods for evaluating docking efficiency. It also underscores the importance of framework mutations for developing broadly neutralizing antibodies.

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Background: The coronavirus disease 2019 (COVID-19) has unequivocally affected the lives of people across the planet and has imposed an unprecedented burden on our healthcare systems. With no potent regimen for treatment, there is a dire need for finding promising candidates. Receptor binding domain (RBD) of the spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, has proven to be a promising target owing to its role in viral invasion. Methods: Our study aimed at generating antibody candidates from the human antibody CR3022 (derived from convalescent SARS patient) against the RBD of SARS-CoV-2 via in silico affinity maturation. We optimized the paratope of the CR3022 antibody towards the RBD of SARS-CoV-2 for better binding affinity and stability, employing molecular modeling, docking, and dynamics simulations. Results: Out of seven antibody leads generated post in silico site-directed mutagenesis followed by preliminary screening, antibody named SAM3 was predicted to have the highest binding affinity towards RBD. However, molecular dynamics simulation of fifty nanoseconds set the seal on SAM1 and SAM2. Both demonstrated a higher binding affinity and stability compared to other counterparts and CR3022. Conclusion: We hypothesize that SAM1, SAM2, and SAM3 antibody candidates can bind to the RBD and potentially disrupt the viral invasion. All three antibody candidates to bind residues on the human ACE-2 binding site of SARS-CoV-2 which were not conserved from SARS-CoV. Our study calls for further in vitro and in vivo testing of SAM1, SAM2, and SAM3 candidates for COVID-19 treatment.

High mortality in COVID-19 patients has been encountered with acute respiratory distress syndrome (ARDS). Cytokine storm has been observed as a reason for this severity in critical cases showcasing high levels of circulating cytokines along with a pronounced decrease in cytotoxic T lymphocytes and Natural Killer Cell populations. The Interleukin-6 amplifier, the activation of IL-6-signal transducer and activator of transcription 3 (STAT3) and NF-κB signaling in non-immune cells has been widely discussed as an initiator of this cytokine release syndrome. The anti-IL-6α receptor antibody tocilizumab has shown success in recovery when administered to critical COVID-19 patients. Additionally, increased release of IL-6 is shown to elicit immune cell disproportionation by upregulating inhibitory NKG2A receptors on NK cell surface, causing blunting of the host’s antiviral response. This study proposes a bispecific immuno-modulatory antibody with one Fab blocking IL-6α-receptor and the other blocking NKG2A receptor to counter hyper-inflammatory cascades and recruit NK cells to the site of viral infection, respectively. Computational site directed mutagenesis was performed to design a library of increased binding affinity mutants of tocilizumab and NKG2A inhibitory monalizumab, followed by docking studies, molecular dynamics simulations, MM-PBSA analysis to study stability of the bispecific assembly in physiologically relevant conditions. This approach utilizing immunomodulation for simultaneous recruitment of antiviral immunity and regulation of hyper-inflammatory host responses may present a potent strategy for combatting critical stage COVID-19 and thereby help in curbing COVID-19 related mortality.