QSAR,Molecular Docking,MD Simulation and MMGBSA Calculations Approaches to Recognize Concealed Pharmacophoric Features Requisite for the Optimization of ALK Tyrosine Kinase Inhibitors as Anticancer Leads

ALK tyrosine kinase ALK TK is an important target in the development of anticancer drugs. In the present work, we have performed a QSAR analysis on a dataset of 224 molecules in order to quickly predict anticancer activity on query compounds. Double cross validation assigns an upward plunge to the genetic algorithm–multi linear regression (GA-MLR) based on robust univariate and multivariate QSAR models with high statistical performance reflected in various parameters like, fitting parameters; R² = 0.69–0.87, F = 403.46–292.11, etc., internal validation parameters; Q²_LOO = 0.69–0.86, Q²_LMO = 0.69–0.86, CCC_cv = 0.82–0.93, etc., or external validation parameters Q²_F1 = 0.64–0.82, Q²_F2 = 0.63–0.82, Q²_F3 = 0.65–0.81, R²_ext = 0.65–0.83 including RMSE_tr < RMSE_cv. The present QSAR evaluation successfully identified certain distinct structural features responsible for ALK TK inhibitory potency, such as planar Nitrogen within four bonds from the Nitrogen atom, Fluorine atom within five bonds beside the non-ring Oxygen atom, lipophilic atoms within two bonds from the ring Carbon atoms. Molecular docking, MD simulation, and MMGBSA computation results are in consensus with and complementary to the QSAR evaluations. As a result, the current study assists medicinal chemists in prioritizing compounds for experimental detection of anticancer activity, as well as their optimization towards more potent ALK tyrosine kinase inhibitor.     

QSAR Evaluations to Unravel the Structural Features in Lysine-Specific Histone Demethylase 1A Inhibitors for Novel Anticancer Lead Development Supported by Molecular Docking,MD Simulation and MMGBSA

Using 84 structurally diverse and experimentally validated LSD1/KDM1A inhibitors, quantitative structure–activity relationship (QSAR) models were built by OECD requirements. In the QSAR analysis, certainly significant and understated pharmacophoric features were identified as critical for LSD1 inhibition, such as a ring Carbon atom with exactly six bonds from a Nitrogen atom, partial charges of lipophilic atoms within eight bonds from a ring Sulphur atom, a non-ring Oxygen atom exactly nine bonds from the amide Nitrogen, etc. The genetic algorithm–multi-linear regression (GA-MLR) and double cross-validation criteria were used to create robust QSAR models with high predictability. In this study, two QSAR models were developed, with fitting parameters like R² = 0.83–0.81, F = 61.22–67.96, internal validation parameters such as Q²_LOO = 0.79–0.77, Q²_LMO = 0.78–0.76, CCC_cv = 0.89–0.88, and external validation parameters such as, R2ext = 0.82 and CCCex = 0.90. In terms of mechanistic interpretation and statistical analysis, both QSAR models are well-balanced. Furthermore, utilizing the pharmacophoric features revealed by QSAR modelling, molecular docking experiments corroborated with the most active compound’s binding to the LSD1 receptor. The docking results are then refined using Molecular dynamic simulation and MMGBSA analysis. As a consequence, the findings of the study can be used to produce LSD1/KDM1A inhibitors as anticancer leads.     

Volatilomic Signatures of AGS and SNU-1 Gastric Cancer Cell Lines

In vitro studies can help reveal the biochemical pathways underlying the origin of volatile indicators of numerous diseases. The key objective of this study is to identify the potential biomarkers of gastric cancer. For this purpose, the volatilomic signatures of two human gastric cancer cell lines, AGS (human gastric adenocarcinoma) and SNU-1 (human gastric carcinoma), and one normal gastric mucosa cell line (GES-1) were investigated. More specifically, gas chromatography mass spectrometry has been applied to pinpoint changes in cell metabolism triggered by cancer. In total, ten volatiles were found to be metabolized, and thirty-five were produced by cells under study. The volatiles consumed were mainly six aldehydes and two heterocyclics, whereas the volatiles released embraced twelve ketones, eight alcohols, six hydrocarbons, three esters, three ethers, and three aromatic compounds. The SNU-1 cell line was found to have significantly altered metabolism in comparison to normal GES-1 cells. This was manifested by the decreased production of alcohols and ketones and the upregulated emission of esters. The AGS cells exhibited the increased production of methyl ketones containing an odd number of carbons, namely 2-tridecanone, 2-pentadecanone, and 2-heptadecanone. This study provides evidence that the cancer state modifies the volatilome of human cells.     

Zwitteration as an alternative to PEGylation

A direct, head-to-head comparison of the efficacy of a zwitterionic versus a poly(ethylene glycol), PEG, coating in preventing protein adsorption to silica and aggregation of silica nanoparticles is presented. The same siloxane coupling chemistry was employed to yield surfaces with similar coverages of both types of ligand. Nanoparticle and planar surfaces were challenged with salt, serum, lysozyme, and serum albumin at 25 and 37 °C. While both types of surface modification are highly effective in preventing protein adsorption and nanoparticle aggregation, the zwitterion provided monolayer-type coverage with minimal thickness, whereas the PEG appeared to yield a more three-dimensional coating. The mechanism for adsorption resistance is thought to be based on preventing ion pairing between protein and surface charges, which releases counterions and water molecules, an entropic driving force enough to overcome a disfavored enthalpy of adsorption.     

Weak and strong convergence of an inertial proximal method for solving Ky Fan minimax inequalities

In this paper we present the relaxed inertial proximal algorithm for Ky Fan minimax inequalities. Based on Opial lemma, we propose a weak convergence result to a solution of the problem by eliminating in the algorithm (RIPAFAN) the Browder–Halpern’s factor of contraction. We present after, a first result of strong convergence by adding a strong monotonicity condition. Secondly, we eliminate the strong monotonicity and add a Browder–Halpern’s contraction factor in the algorithm (RIPAFAN) and then ensure the strong convergence to a selected solution with respect to the contraction factor. Some examples are proposed. The first one concerns the convex minimization where the objective function is only controlled with a provided well conditioning. In the second one, we propose monotone set-valued variational inequalities. The last example deals with the problem of fixed point for a nonexpansive set-valued operator.     

Influence of phosphonation and phosphation on surface acid-base and morphological properties of CaO as investigated by in situ FTIR spectroscopy and electron microscopy

Pure, phosphated, and phosphonated CaO samples were prepared and characterized by X-ray powder diffractometry, FTIR spectroscopy, scanning electron microscopy, and energy-dispersive X-ray microprobing. Surface acid-base properties were probed by in situ FTIR spectroscopy of adsorbed CO (at 85 K), CDCl3 (at RT), CO2 (at RT), and methyl butynol decomposition reactions (at 473 K). Results obtained have shown phosphate and, to a larger extent, phosphonate additives to enhance the strength of Lewis acid sites exposed on CaO surfaces, at the expense of the Lewis base site strength. The phosphonation has been found, moreover, to make CaO particles grow in a preferential direction and be less susceptible to rehydration. These findings may establish surface chemical attributes for the application of the methylene bisphosphonate (MBP) class of drugs to hamper acid-induced resorption of bone materials (osteoporosis).     

Characterization of nano-cerias synthesized in microemulsions by N2 sorptiometry and electron microscopy

A surfactant-stabilized microemulsion method was used to prepare nano-sized particles (<10 nm) of cubic-CeO2 exposing surfaces of not only highest specific areas (142-201 m(2)/g) ever reported for polycrystalline ceria, but also high thermal stability at 800 degrees C. Three different surfactants, a non-ionic, an anionic and a cationic, were used to form the microemulsions. Then, N2 sorptiometry and pore volume distribution calculations, were used to reveal microporous and mesoporous structures of these cerias as a function of surfactant type. Transmission electron microscopy was used to visualize consequent particle behaviors. Suggestions have been made as to the textural attributes of the high surface area and thermal stability. Accordingly, cationic surfactants, in the presence or absence of added non-ionic surfactant, are seen to assist in producing cerias of promising surface textural properties for the chemical makeup of combustion catalysts.