Computational insights into tetracyclines as inhibitors against SARS-CoV-2 Mpro via combinatorial molecular simulation calculations.

The re-emerging Zika virus (ZIKV) is an arthropod-borne virus that has been described to have explosive potential as a worldwide pandemic. The initial transmission of the virus was through a mosquito vector, however, evolving modes of transmission has allowed the spread of the disease over continents. The virus has already been linked to irreversible chronic central nervous system conditions. The concerns of the scientific and clinical community are the consequences of Zika viral mutations, thus suggesting the urgent need for viral inhibitors. There have been large strides in vaccine development against the virus but there are still no FDA approved drugs available. Rapid rational drug design and discovery research is fundamental in the production of potent inhibitors against the virus that will not just mask the virus, but destroy it completely. In silico drug design allows for this prompt screening of potential leads, thus decreasing the consumption of precious time and resources. This study demonstrates an optimized and proven screening technique in the discovery of two potential small molecule inhibitors of ZIKV Methyltransferase and RNA dependent RNA polymerase. This in silico 'per-residue energy decomposition pharmacophore' virtual screening approach will be critical in aiding scientists in the discovery of not only effective inhibitors of Zika viral targets, but also a wide range of anti-viral agents.

Zika Virus NS5 Protein Potential Inhibitors: An Enhanced in silico Approach in Drug Discovery

Recent outbreak of COVID-19 pandemic caused by severe acute respiratory syndrome-Coronavirus-2 (SARS-CoV-2) has raised serious global concern for public health. The viral main 3-chymotrypsin-like c...

SARS-CoV-2 Mpro inhibitors: identification of anti-SARS-CoV-2 Mpro compounds from FDA approved drugs

De novo design of novel protease inhibitor candidates in the treatment of SARS-CoV-2 using deep learning, docking, and molecular dynamic simulations.

https://doi.org/10.1016/j.compbiomed.2022.105231

A multi-targeted approach to identify potential flavonoids against three targets in the SARS-CoV-2 life cycle

Recent Zika virus (ZIKV) outbreak and association with human diseases such as neurological disorders have raised global health concerns. However, in the absence of an approved anti-ZIKV drug has ge...

Structure-based screening and validation of bioactive compounds as Zika virus methyltransferase (MTase) inhibitors through first-principle density functional theory, classical molecular simulation and QM/MM affinity estimation

Akhilesh Kumar Rao

Papers

Structure-based screening and validation of bioactive compounds as Zika virus methyltransferase (MTase) inhibitors through first-principle density functional theory, classical molecular simulation and QM/MM affinity estimation