High-throughput virtual screening of drug databanks for potential inhibitors of SARS-CoV-2 spike glycoprotein.

COVID-19, which is caused by a novel coronavirus known as SARS-CoV-2, has spread rapidly around the world, and it has infected more than 29 million individuals as recorded on 16 September 2020. Much effort has been made to stop the virus from spreading, and there are currently no approved pharmaceutical products to treat COVID-19. Here, we apply an approach to investigate more than 3800 FDA approved drugs on the viral RBD S-ACE2 interface as a target.

Discovery of potent inhibitors for SARS-CoV-2's main protease by ligand-based/structure-based virtual screening, MD simulations, and binding energy calculations.

COVID-19 has caused lockdowns all over the world in early 2020, as a global pandemic. Both theoretical and experimental efforts are seeking to find an effective treatment to suppress the virus. In silico drug design can play a vital role in identifying promising drug candidates against COVID-19.

Molecular level investigation of curcumin self-assembly induced by trigonelline and nanoparticle formation.

Nanoparticle-facilitated drug delivery forms the core of medicine nowadays with the drug being delivered right at the target, reducing side effects and enhancing therapeutic value. Nanoparticles derived from natural compounds are further a point of focus being biocompatible and safe by and large. In this study, we have performed HF/6-31G calculations coupled with intermolecular interaction calculations and nanoscale molecular dynamics simulations to investigate self-assemblage in curcumin induced by trigonelline.