In silico screening of SARS-CoV2 helicase using African natural products: Docking and molecular dynamics approaches.

In the current medical era, there is an urgent necessity to identify new effective drugs to enrich the COVID-19's therapeutic arsenal. The SARS-COV-2 NSP13/helicase enzyme has been identified as a potential target for developing novel COVID-19 inhibitors. In this work, we aimed at endorsing effective natural products with potential inhibitory action towards the NSP13 through the virtual screening of 1012 natural products of botanical and marine origin from the South African Natural Compounds Database (SANCDB). The molecules were docked into the NTPase active site, and the best twelve compounds were chosen for further analysis. Thereafter, a combination of molecular dynamics simulations and MM-GBSA free energy calculations were carried out for a subset of best hits complexed with NSP13 helicase. We believe that the findings of this work will pave the way for additional research and experimental validation of some natural products as viable NSP13 helicase inhibitors.

Structural and dynamic determinants for highly selective RET kinase inhibition reveal cryptic druggability.

INTRODUCTION: The structural and dynamic determinants that confer highly selective RET kinase inhibition are poorly understood. OBJECTIVES: To explore the druggability landscape of the RET active site in order to uncover structural and dynamic vulnerabilities that can be therapeutically exploited. METHODS: We apply an integrated structural, computational and biochemical approach in order to explore the druggability landscape of the RET active site. RESULTS: We demonstrate that the that the druggability landscape of the RET active site is determined by the conformational setting of the ATP-binding (P-) loop and its coordination with the αC helix. Open and intermediate P-loop structures display additional druggable vulnerabilities within the active site that were not exploited by first generation RET inhibitors. We identify a cryptic pocket adjacent to the catalytic lysine formed by K758, L760, E768 and L772, that we name the post-lysine pocket, with higher druggability potential than the adenine-binding site and with important implications in the regulation of the phospho-tyrosine kinase activity. Crystal structure and simulation data show that the binding mode of highly-selective RET kinase inhibitors LOXO-292 and BLU-667 is controlled by a synchronous open P-loop and αC-in configuration that allows accessibility to the post-lysine pocket. Molecular dynamics simulations show that these inhibitors efficiently occupy the post-lysine pocket with high stability through the simulation time-scale (300 ns), with both inhibitors forming hydrophobic contacts further stabilized by pi-cation interactions with the catalytic K758. Engineered mutants targeting the post-lysine pocket impact on inhibitor binding and sensitivity, as well as RET tyrosine kinase activity. CONCLUSIONS: The identification of the post-lysine pocket as a new druggable vulnerability in the RET kinase and its exploitation by second generation RET inhibitors have important implications for future drug design and the development of personalized therapies for patients with RET-driven cancers.

In-Silico targeting of SARS-CoV-2 NSP6 for drug and natural products repurposing.

Non-Structural Protein 6 (NSP6) has a protecting role for SARS-CoV-2 replication by inhibiting the expansion of autophagosomes inside the cell. NSP6 is involved in the endoplasmic reticulum stress response by binding to Sigma receptor 1 (SR1). Nevertheless, NSP6 crystal structure is not solved yet. Therefore, NSP6 is considered a challenging target in Structure-Based Drug Discovery. Herein, we utilized the high quality NSP6 model built by AlphaFold in our study. Targeting a putative NSP6 binding site is believed to inhibit the SR1-NSP6 protein-protein interactions. Three databases were virtually screened, namely FDA-approved drugs (DrugBank), Northern African Natural Products Database (NANPDB) and South African Natural Compounds Database (SANCDB) with a total of 8158 compounds. Further validation for 9 candidates via molecular dynamics simulations for 100 ns recommended potential binders to the NSP6 binding site. The proposed candidates are recommended for biological testing to cease the rapidly growing pandemic.