High resolution cryo-EM structures of two potently SARS-CoV-2 neutralizing monoclonal antibodies of same donor origin that vary in neutralizing Omicron variants (preprint)

While vaccines have by large been found to effective against the evolving SARS-CoV-2 variants, the profound and rapid effectivity of monoclonal antibodies (mAbs) in significantly reducing hospitalization to severe disease outcomes have also been demonstrated. In the present study, by high resolution cryo-electron microscopy (cryo-EM), we examined the structural insights of two trimeric spike (S) protein bound mAbs isolated from an Indian convalescent individual infected with ancestral SARS-CoV-2 which we recently reported to potently neutralize SARS-CoV-2 from its ancestral form through highly virulent Delta form however different in their ability to neutralize Omicron variants. Our findings showed binding and conformational heterogeneities of both the mAbs (THSC20.HVTR04 and THSC20.HVTR26) bound to S trimer in its apo and hACE-2 bound forms. Additionally, cryo-EM resolved structure assisted modeling highlighted key residues associated with the ability of these two mAbs to neutralize Omicron variants. Our findings highlighted key interacting features modulating antigen-antibody interacting that can further aid in structure guided antibody engineering to enhance their breadth and potency.

Identifying pandemic-related stress factors from social-media posts -- effects on students and young-adults (preprint)

The COVID-19 pandemic has thrown natural life out of gear across the globe. Strict measures are deployed to curb the spread of the virus that is causing it, and the most effective of them have been social isolation. This has led to wide-spread gloom and depression across society but more so among the young and the elderly. There are currently more than 200 million college students in 186 countries worldwide, affected due to the pandemic. The mode of education has changed suddenly, with the rapid adaptation of e-learning, whereby teaching is undertaken remotely and on digital platforms. This study presents insights gathered from social media posts that were posted by students and young adults during the COVID times. Using statistical and NLP techniques, we analyzed the behavioral issues reported by users themselves in their posts in depression-related communities on Reddit. We present methodologies to systematically analyze content using linguistic techniques to find out the stress-inducing factors. Online education, losing jobs, isolation from friends, and abusive families emerge as key stress factors.

Effect of lockdown interventions to control the COVID-19 epidemic in India (preprint)

The pandemic caused by the novel Coronavirus SARS-CoV2 has been responsible for life threatening health complications, and extreme pressure on healthcare systems. While preventive and definite curative medical interventions are yet to arrive, Non-Pharmaceutical Interventions (NPIs) like physical isolation, quarantine and drastic social measures imposed by governing agencies are effective in arresting the spread of infections in a population. In densely populated countries like India, lockdown interventions are partially effective due to social and administrative complexities. Using detailed demographic data, we present an agent based model to imitate the behavior of the population and its mobility features, even under intervention. We demonstrate the effectiveness of contact tracing policies and how our model efficiently relates to empirical findings on testing efficiency. We also present various lockdown intervention strategies for mitigation - using the bare number of infections, the effective reproduction rate, as well as using reinforcement learning. Our analysis can help assess the socio-economic consequences of such interventions, and provide useful ideas and insights to policy makers for better decision making.

A Large-scale Drug Repositioning Survey for SARS-CoV-2 Antivirals (preprint)

The emergence of novel SARS coronavirus 2 (SARS-CoV-2) in 2019 has triggered an ongoing global pandemic of severe pneumonia-like disease designated as coronavirus disease 2019 (COVID-19). To date, more than 2.1 million confirmed cases and 139,500 deaths have been reported worldwide, and there are currently no medical countermeasures available to prevent or treat the disease. As the development of a vaccine could require at least 12-18 months, and the typical timeline from hit finding to drug registration of an antiviral is >10 years, repositioning of known drugs can significantly accelerate the development and deployment of therapies for COVID-19. To identify therapeutics that can be repurposed as SARS-CoV-2 antivirals, we profiled a library of known drugs encompassing approximately 12,000 clinical-stage or FDA-approved small molecules. Here, we report the identification of 30 known drugs that inhibit viral replication. Of these, six were characterized for cellular dose-activity relationships, and showed effective concentrations likely to be commensurate with therapeutic doses in patients. These include the PIKfyve kinase inhibitor Apilimod, cysteine protease inhibitors MDL-28170, Z LVG CHN2, VBY-825, and ONO 5334, and the CCR1 antagonist MLN-3897. Since many of these molecules have advanced into the clinic, the known pharmacological and human safety profiles of these compounds will accelerate their preclinical and clinical evaluation for COVID-19 treatment.