Binary-QSAR guided virtual screening of FDA approved drugs and compounds in clinical investigation against SARS-CoV-2 main protease

Covalent docking-driven virtual screening of extensive small-molecule libraries against Bruton tyrosine kinase for the identification of highly selective and potent novel therapeutic candidates

Bruton tyrosine kinases (BTKs) play critical roles in various diseases, including chronic lymphatic leukemia (CLL), Waldenström Macroglobulinemia, Marginal Zone Lymphoma, Mantle Cell Lymphoma (MCL), and Graft Versus Host diseases. BTKs are a family of tyrosine kinases involved in B lymphocyte signal transduction, development, and maturation. Their overexpression can lead to cancer as they are essential for the activation of the B Cell Receptor (BCR) signaling pathway. Blocking the activation of BTKs presents a promising approach for treating CLL. This study was centered around the identification of small-molecule therapeutics that have an impact on human BTK. The covalently bound Ibrutinib molecule, recognized for its ability to inhibit BTK, was used as the query molecule. IUPAC text files containing molecular fragments of Ibrutinib were employed to virtually screen five different libraries comprising small-molecules, resulting in the screening of over 2.4 million synthesized compounds. Covalent docking simulations were applied to the selected small-molecules obtained through text mining from databases. Potent hit molecules capable of inhibiting BTKs through virtual screening algorithms were identified, paving the way for novel therapeutic strategies in the treatment of CLL.

Scope of repurposed drugs against the potential targets of the latest variants of SARS-CoV-2

The unprecedented outbreak of the severe acute respiratory syndrome (SARS) Coronavirus-2, across the globe, triggered a worldwide uproar in the search for immediate treatment strategies. With no specific drug and not much data available, alternative approaches such as drug repurposing came to the limelight. To date, extensive research on the repositioning of drugs has led to the identification of numerous drugs against various important protein targets of the coronavirus strains, with hopes of the drugs working against the major variants of concerns (alpha, beta, gamma, delta, omicron) of the virus. Advancements in computational sciences have led to improved scope of repurposing via techniques such as structure-based approaches including molecular docking, molecular dynamic simulations and quantitative structure activity relationships, network-based approaches, and artificial intelligence-based approaches with other core machine and deep learning algorithms. This review highlights the various approaches to repurposing drugs from a computational biological perspective, with various mechanisms of action of the drugs against some of the major protein targets of SARS-CoV-2. Additionally, clinical trials data on potential COVID-19 repurposed drugs are also highlighted with stress on the major SARS-CoV-2 targets and the structural effect of variants on these targets. The interaction modelling of some important repurposed drugs has also been elucidated. Furthermore, the merits and demerits of drug repurposing are also discussed, with a focus on the scope and applications of the latest advancements in repurposing.