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Biology subjects

Athar, M.

Publications and source records attributed to Athar, M..

2 recordsLinked to original sources

Integrative Network Biology Framework Elucidates Molecular Mechanisms of SARS-CoV-2 Pathogenesis

COVID-19 (Coronavirus disease 2019) is a respiratory illness caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). While the pathophysiology of this deadly virus is complex and largely unknown, we employ a network biology-fueled approach and integrated multiomics data pertaining to lung epithelial cells-specific coexpression network and human interactome to generate Calu-3-specific human-SARS-CoV-2 Interactome (CSI). Topological clustering and pathway enrichment analysis show that SARS-CoV-2 target central nodes of host-viral network that participate in core functional pathways. Network centrality analyses discover 28 high-value SARS-CoV-2 targets, which are possibly involved in viral entry, proliferation and survival to establish infection and facilitate disease progression. Our probabilistic modeling framework elucidates critical regulatory circuitry and molecular events pertinent to COVID-19, particularly the host modifying responses and cytokine storm. Overall, our network centric analyses reveal novel molecular components, uncover structural and functional modules, and provide molecular insights into SARS-CoV-2 pathogenicity.

systems biology

Exploring Ruthenium-based organometallic inhibitors against Plasmodium Calcium Dependent Kinase 2 (PfCDPK2): a combined ensemble docking, QM paramterization and molecular dynamics study

Recent advances in the metal-organic framework (MOF) have accelerated the discovery of novel metal-based anticancer, antibacterial and antimalarial compounds. This is substantiated by many serendipitously discovered metals (Ru, Rh, and Ir) based inhibitors that established the importance of metal inserted into the known organic scaffold. Conversely, it is possible to design novel bioactive compounds by mimicking hypervalent carbon atoms by transition metals. This process can be facilitated by computational drug discovery by treating metal center using optimized parameters that can be used for molecular docking and molecular dynamics simulations. Further, the method can be plugged with high computational power and refined algorithms to interpret chemical phenomena with atomic-level insights. In the present work, we have demonstrated an approach for parameterizing three organometallic ligands (FLL, E52, and staurosporine) using MCPB.py. In particular, we report that E52 and FLL have a better shape complimentary and affinity compared to staurosporine identified inhibitor (staurosporine) against Calcium-dependent protein kinases 2 (CDPK2). This study also revealed that a flexible approach (ensemble) outperforms for the given target with dynamic movements. The calculated MMPBSA energies for staurosporine, FLL and E52 were -66.461 {+/-} 2.192, -67.182 {+/-} 1.971 and -91.339 {+/-} 2.745 kcal/mol respectively.

biochemistry