Preface

Cyclohexane-1,3-dione Derivatives as Future Therapeutic Agents for NSCLC: QSAR Modeling, In Silico ADME-Tox Properties, and Structure-Based Drug Designing Approach

The abnormal expression of the c-Met tyrosine kinase has been linked to the proliferation of several human cancer cell lines, including non-small-cell lung cancer (NSCLC). In this context, the identification of new c-Met inhibitors based on heterocyclic small molecules could pave the way for the development of a new cancer therapeutic pathway. Using multiple linear regression (MLR)-quantitative structure-activity relationship (QSAR) and artificial neural network (ANN)-QSAR modeling techniques, we look at the quantitative relationship between the biological inhibitory activity of 40 small molecules derived from cyclohexane-1,3-dione and their topological, physicochemical, and electronic properties against NSCLC cells. In this regard, screening methods based on QSAR modeling with density-functional theory (DFT) computations, in silico pharmacokinetic/pharmacodynamic (ADME-Tox) modeling, and molecular docking with molecular electrostatic potential (MEP) and molecular mechanics-generalized Born surface area (MM-GBSA) computations were used. Using physicochemical (stretch-bend, hydrogen bond acceptor, Connolly molecular area, polar surface area, total connectivity) and electronic (total energy, highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energy levels) molecular descriptors, compound 6d is identified as the optimal scaffold for drug design based on in silico screening tests. The computer-aided modeling developed in this study allowed us to design, optimize, and screen a new class of 36 small molecules based on cyclohexane-1,3-dione as potential c-Met inhibitors against NSCLC cell growth. The in silico rational drug design approach used in this study led to the identification of nine lead compounds for NSCLC therapy via c-Met protein targeting. Finally, the findings are validated using a 100 ns series of molecular dynamics simulations in an aqueous environment on c-Met free and complexed with samples of the proposed lead compounds and Foretinib drug.

Density functional modeling, and molecular docking with SARS-CoV-2 spike protein (Wuhan) and omicron S protein (variant) studies of new heterocyclic compounds including a pyrazoline nucleus

Nowadays, different vaccines and antiviral drugs have been developed and their effectiveness has been proven against SARS-CoV-2. Pyrazoline derivatives are biologically active molecules and exhibit broad-spectrum biological activity properties. In this scope, four new molecules (4a-d) including a pyrazoline core were synthesized in order to predict their antiviral properties theoretically. Compounds 4a-d were purified by the crystallization method. The structures of 4a-d were completely characterized by NMR, IR, and elemental analysis. The molecular structures of the compounds in the ground state have been optimized using density functional theory with the B3LYP/6-31++G(d,p) level. The quantum chemical parameters were predicted by density functional theory calculations. Moreover, the molecular docking studies of 4a-d with SARS-CoV-2 Spike protein (Wuhan) and omicron S protein (variant) were presented to investigate and predict potential interactions. The binding sites, binding types and energies, bond distances of the non-covalent interactions and calculated inhibition constants (calc. Ki) as a consequence of molecular docking for 4a-d were presented in this study. Furthermore, the stability of the protein-4a complex obtained from the docking was investigated through molecular dynamics simulation.Communicated by Ramaswamy H. Sarma.

Intranasal drug delivery of sumatriptan succinate-loaded polymeric solid lipid nanoparticles for brain targeting

Migraine is a frequent neurological condition characterized by throbbing headaches, nausea, photophobia, and phonophobia, among other symptoms. Sumatriptan belongs to a BCS class III, which exhibits poor oral bioavailability and several side-effects. The objective of the present study was to develop solid lipid nanoparticles (SLNPs) of sumatriptan succinate for brain targeting by nasal route. Solvent injection method was used to increase the entrapment efficiency of hydrophilic drug. Thus, formulation was optimized by central composite design with minimum particle size, optimized zeta potential, and maximum entrapment efficiency, which was found to be 133.4 nm, -17.7 mV, and 75.5%, respectively. Optimized batch was further evaluated for surface morphology, Fourier-transform infrared spectroscopy, in vitro release, permeation across nasal mucosa, and histopathology. It was seen that most of the particles were spherical in shape as confirmed by scanning electron microscopy and transmission electron microscopy. The release of drug through the lipid showed initial burst release followed by sustained release up to 12 h. The ex vivo diffusion study using goat nasal mucosa at pH 6.8 revealed that SLNPs permeation across nasal mucosa was quick, which was sufficient for brain targeting. Histopathology studies further revealed integrity of nasal mucosa after treatment with SLNPs. The investigation indicated that hydrophilic drug, sumatriptan succinate can be successfully entrapped in SLNPs to target brain via nasal delivery, and thus it could be an effective approach for nose-to-brain delivery.