Research Projects

The interactions between proteins and nucleic acids are crucial for various cell operations, including DNA repair, transcription, replication, and RNA translation. However, achieving atomic level detection and characterization of these interactions has been challenging. This project aims to use high-throughput Molecular Dynamics (MD) simulations to study the SARS-CoV-2 genome, which is replicated and transcribed through the SARS-CoV-2 RNA dependent RNA polymerase (RdRp) and nsp13 helicase. These molecules are potential targets for antivirals. The use of supercomputers and speedy algorithms will enable a comprehensive study of the replication and transcription machinery of CoV viruses. This will lead to rational drug design and repurposing strategies, ultimately leading to rapid therapeutic development. The project aims to contribute to computer-aided drug development that can interfere with viral genomic replication mechanisms, boosting the host cell's capacity to eliminate viral material activity. Conventional molecular simulations and enhanced sampling techniques can be used to address the atomic and monomer level length scales and mechanisms active at these scales. The project proposes investigating the SARS-CoV-2 genome through all-atomistic MD simulations and machine learning/deep-learning algorithms to depict the intricate events occurring between the viral replication-transcription complex. This will allow therapeutic studies to focus on blocking the replication and transcription machinery.