Researchers at SSSIHL worked — both indigenously and with healthcare partnerships — on a number of areas to better understand the coronavirus (COVID-19) in an effort to find solutions that helped protect our communities and offer expert advice to the local and national government.
Research Areas
Rapid Testing Platform
STAR Labs (SSSIHL Central Research Instruments Facility), under the SSSIHL-CSR Fund, worked on reliable testing platforms, based on plasmonics, towards the detection of COVID-19 antigen in nasopharyngeal swabs / saliva samples and COVID-19 antibodies in blood / serum / plasma samples. The test times for this platform were within a few minutes. The sensitive plasmonic platform translated into point-of-care technologies with detection limits that were significantly better than currently available testing platforms. These indigenously developed technologies with the core competency of lower reagent usage, economically viability and shorter test times aided in scaling up of the current screening/testing rates to serve one and all.
Invivo Mathematical Modeling of COVID-19
The COVID-19 pandemic affected over 212 countries and territories. Well-designed drugs and vaccines for the elimination of this virus were the need of the hour. Various drug interventions, such as Arbidol, Remdesivir, Inteferon, Ritonavir/Lopinavir, Hydroxycholoroquine (HCQ), BCG Vaccine, etc. — acting at multiple stages of pathogenesis of COVID-19 — can substantially reduce the mortality rates. We performed within-host mathematical modeling studies to understand the efficacy of these drug interventions and the role of crucial inflammatory mediators, and the behaviour of immune response towards this novel coronavirus. Our models identified different combinations of antiviral drugs to reduce the viral load and eliminate the infection. We also observed that combining HCQ and the BCG vaccination resulted in prevention of viral replication and activated innate immunity to eliminate virus from the host.
Drug Repurposing, Natural Products & Derivatives
Drug Repurposing
Nitrogen based compounds such as pyrazoles, pyrimidines, quinolines, and other phytochemical constituents from many medicinal plants and herbs have gained interest due to their potent medicinal values, especially anti-viral properties. In order to utilize these chemical entities, researchers performed in silico studies involving molecular docking and molecular dynamics of the drugs derived from the aforementioned sources against the COVID-19 virus in entry, replication and innate immune response stages in order to identify the potential candidates.
Natural Products
Bio-active constituents present in many medicinal plants that are known to possess anti-viral activity will be studied. They were first subjected to the computational studies in order to assess their probable efficacy. Once the potential of their activity were established against the COVID-19 virus, we isolated and characterized the active components from the plants and study their properties in vitro to verify the claims.
Semi-synthetic Derivatives
Once the bio-active components of the medicinal plants were isolated and studied, we carried out synthetic modifications to the active component, thus making further derivatives which helped us obtain a structure-activity based lead optimization. This in turn helped us increase the efficacy of the compounds. After the in vitro studies, the lead compounds were taken up for further in vivo studies.
Synthetic Derivatives
There are a library of compounds that have been synthesized by us. These include novel spirobibenzopyrans, benzopyrylium salts, azines, coumarins, chalcones, bis-chalcones, etc. We explored the in vitro potency of these molecules against the COVID-19 virus. Depending on results, further actions, which included lead optimization based on the structure-activity relationship and in vivo studies, were undertaken.
COVID-19 protease dual-inhibitors
Proteases of SARS-CoV-2 (3CLp and PLp) play an important role in its life cycle, making them ideal targets for drugs. One of the main problems with respect to identifying an inhibitor, is the capability of the virus to mutate, making it a necessity, to search for molecules that are capable of inhibiting both the proteases. This is achieved by the construction of a common pharmacophore model that defines the characteristic features of the pocket and the attributes of the ligand that make it a probable dual-inhibitor. Various databases of drugs and natural products were screened based on this model, and the best hits were subjected to molecular dynamics simulations.
Data Mining
At the time of publication, the global case-fatality rate of COVID-19 worldwide was 3.3%, but only 1.7% in India (Source: WHO). A theory on this is that the environmental temperature in India is on the higher side in comparison to the European continent (for example), and how this might influence case-fatality rate in COVID-19. We investigated this aspect in our research. COVID-19 related data released by public health agencies, along with sources of data reported in quality worldwide media, was leveraged to mine knowledge and identify patterns and themes related to the disease.
Teaching during the Pandemic – Best Practices
School closures in 2020 had impeded learning everywhere. International organizations like the UNICEF have recommended that educational institutions plan and evolve alternative modes of learning to ensure continuity. The research studied and grafted best practices of resilient schools that have successfully navigated the crisis and ensured continuity of learning onto select experiment schools. The practices that were examined spanned the spectrum of learning activities in school education, from content delivery to evaluation.