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This is the first observation of inhibitory activity of isostrychnine against β-tubulin and warrants further experimental investigation. Copyright © 2016 John Wiley & Sons, Ltd.

Neuraminidase (NA), a surface protein, facilitates the release of nascent virus and thus spreads infection. It has been renowned as a potential drug target for influenza A virus infection. The drugs such as oseltamivir, zanamivir, peramivir, and laninamivir are approved for the treatment of influenza infection. Additionally, investigational drugs namely MK2206, tamiphosphor, crenatoside, and dehydroepiandrosterone (DHEA) are also available for the treatment. However, recent outbreaks of highly pathogenic and drug-resistant influenza A strains highlighted the need to discover novel NA inhibitor. Keeping this in mind, in the current investigation, an effort was made to ascertain potent inhibitors using pharmacophore-based virtual screening and docking approach. A 3D pharmacophore model was generated based on the chemical features of approved and investigational NA inhibitors using PHASE module of Schrödinger suite. The model consists of two hydrogen bond acceptors (A), one hydrogen bond donor (D), and one positively charged group (P), AADP. Subsequently, molecules with same pharmacophoric features were screened from among the two million compounds available in the ZINC database using the generated pharmacophore hypothesis. Ligand filtration was also done to obtain an efficient collection of hit molecules by employing Lipinski "rule of five" using Qikprop module. Finally, the screened molecule was subjected to docking and molecular dynamic simulations to examine the inhibiting activity of the compounds. The results of our analysis suggest that "acebutolol hydrochloride" (156792) could be the promising candidates for the treatment of influenza A virus infection.

The emergence and rapid spreading of novel SARS-CoV-2 across the globe represent an imminent threat to public health. Novel antiviral therapies are urgently needed to overcome this pandemic. Given the significant role of the main protease of Covid-19 for virus replication, we performed a drug-repurposing study using the recently deposited main protease structure, 6LU7. For instance, pharmacophore-and e-pharmacophore-based hypotheses such as AARRH and AARR, respectively, were developed using available small molecule inhibitors and utilized in the screening of the DrugBank repository. Further, a hierarchical docking protocol was implemented with the support of the Glide algorithm. The resultant compounds were then examined for their binding free energy against the main protease of Covid-19 by means of the Prime-MM/GBSA algorithm. Most importantly, the machine learning-based AutoQSAR algorithm was used to predict the antiviral activities of resultant compounds. The hit molecules were also examined for their drug-likeness and toxicity parameters through the QikProp algorithm. Finally, the hit compounds activity against the main protease was validated using molecular dynamics simulation studies. Overall, the present analysis yielded two potential inhibitors (DB02986 and DB08573) that are predicted to bind with the main protease of Covid-19 better than currently used drug molecules such as N3 (cocrystallized native ligand), lopinavir, and ritonavir.

Objective: Drug resistance is an imperative issue in the treatment of patients with lung cancer. In this work, investigation of the drug resistance mechanism of G2032R mutation in ROS1 is carried out using computational simulation techniques.Methods: Molecular docking and molecular dynamics (MD) simulation approach have been utilized to uncover the mechanism behind crizotinib resistance in ROS1 at a molecular level. Normal mode analysis was carried out using ElNemo server which examines the movements and conformational changes in the protein structure. ArgusLab, PEARLS, and Autodock were employed for the docking analysis, whereas GROMACS package 4.5.3 was used for MD simulation approach. Results:The results from our analysis indicates that wild-type ROS1 (Protein Data Bank Code 3ZBF) could be more crucial for the crizotinib binding as it indicates largest binding affinity, minimum number of H-bonds, and higher flexibility than mutant-type ROS1. Moreover, the theoretical basis for the cause of drug insensitivity is the differences in the electrostatic properties of binding site residues between the wild and mutant ROS1 structures. Our analysis theoretically suggests that E-2027 is a key residue responsible for the ROS1 drug selectivity.Conclusion: Molecular docking and MD simulation results provide an explanation of the resistance caused by G2032R and may give a key clue for the drug design to encounter drug resistance.