Simulating relaxation channels of CO2 in clathrate canocages

The energy levels of CO2 in the small (s) and large (l) nano-cages of cubic sI clathrates are calculated in the Born-Oppenheimer approximation using pairwise atom-atom interaction potentials. In the s cage, the centre of mass of CO2 oscillates with small amplitudes, asymmetrically about the cage center with harmonic frequencies around 100 cm-1. In the l cage, oscillations are anharmonic with large amplitude motions in a plane parallel to the hexagonal faces of the cage and the corresponding frequencies are calculated to be 55 cm-1 and 30 cm-1. Librational harmonic frequencies are calculated at 101.7 cm-1 and 56.0 cm-1 in the 5 cage and at 27.9 cm-1 and 46.4 cm-1 in the l cage. Results show that the coupling between the CO2 molecule and the nano-cage is quite different for the low frequency translational, rotational or librational modes and the high frequency vibrational modes, which consequently leads to different relaxation channels

Interactions between (4Z)-hex-4-en-1-ol and 2-methylbutyl 2-methylbutanoate with olfactory receptors using computational methods

The first step in the perception of an odor is the activation of one or more olfactory receptors (ORs) following binding of the odorant molecule to the OR. The compounds (4Z)-hex-4-en-1-ol and 2-methylbutyl 2-methylbutanoate are two important odorants molecules known as food flavor. In this research, we investigate the potential targets for this two molecules and try to interpret the type of binding with different ORs models and their relationship with the retention/release property. We used the SWISS-MODEL modelling server to predict the three-dimensional (3D) structure of the ORs. We then used the Autodock vina and Autodock tools to predict the binding site and binding energy for the ligands to these receptors. The results indicate that the molecule (4Z)-hex-4-en-1-ol has given more hydrogen bonds with the majority of these receptors and the 2-methylbutyl 2-methylbutanoate molecule mainly has given Pi bonds interaction type

Structure-toxicity relationships for phenols and anilines towards Chlorella vulgaris using quantum chemical descriptors and statistical methods.

Quantitative structure–toxicity relationship (QSTR) models are useful to understand how chemical structure relates to the toxicity of natural and synthetic chemicals. The chemical structures of 67 phenols and anilines have been characterized by electronic and physic-chemical descriptors. Density functional theory (DFT) with Beck’s three parameter hybrid functional using the LYP correlation functional (B3LYP/6-31G(d)) calculations have been carried out in order to get insights into the structure chemical and property information for the study compounds. The statistical quality of the MLR and MNLR models was found to be efficient for the predicting of the toxicity, but when compared to the obtained results by ANN model, we realized that the predictions achieved by this latter one were more effective. The results indicated that the developed models could produce satisfactory predictive results for the four different toxicity endpoints with high squared correlation coefficients (R2 ). Leave-one-out cross validation, external validation, Y-randomized validation and application domain analysis demonstrated the accuracy, robustness and reliability of these models. Accordingly.the obtained results suggested that the proposed descriptors could be useful to predict the toxicity of phenols and anilines towards Chlorella vulgaris.

Quantitative Structure–Activity Relationship (QSAR) Studies of Some Glutamine Analogues for Possible Anticancer Activity

A Quantitative Structure–Activity Relationship (QSAR) study was performed to predict an anticancer activity in tumor cells of thirty-six 5-N-substituted-2-(substituted benzenesulphonyl) glutamines compounds using the electronic and topologic descriptors computed respectively, with ACD/ChemSketch and Gaussian 03W programs. The structures of all 36 compounds were optimized using the hybrid Density Functional Theory (DFT) at the B3LYP/6-31G(d) level of theory. In both approaches, 30 compounds were assigned as the training set and the rest as the test set. These compounds were analyzed by the Principal Components Analysis (PCA) method, a descendant Multiple Linear Regression (MLR), Multiple Nonlinear Regression (MNLR) analyses and an Artificial Neural Network (ANN). The robustness of the obtained models was assessed by leave-many-out cross-validation, and external validation through a test set.This study shows that the ANN has served marginally better to predict antitumor activity when compared with the results given by predictions made with MLR and MNL

The photophysical properties and electronic structures of ((2E, 2’E)-1, 1’-[chalcogen bis (4, 1-phenylene)] bis [3-(4-chlorophenyl) prop-2-en-1-one] derivatives as hole-transporting materials for organic light-emitting diodes (OLEDs). Quantum chemical investigations

In order to propose new organic materials for organic light-emitting diodes (OLEDs) applications, The quantum chemical calculations have been performed on four molecules M0 ((2E, 2’E)-1, 1’ (selenobis (4, 1phenylene)) bis (bis (3-(4-chlorophenyl) prop-2en-1-one)), M1 ((2E, 2’E)-1, 1’ (thiobis (4, 1phenylene)) bis (bis (3-(4-chlorophenyl) prop-2en-1-one)), M2 ((2E, 2’E)-1, 1’ (oxybis (4, 1phenylene)) bis (bis (3-(4-chlorophenyl) prop-2en-1-one)), M3 ((2E, 2’E)-1, 1’ (azanediylbis (4, 1phenylene)) bis (bis (3-(4-chlorophenyl) prop-2en-1-one)).The principal objective of this work is to study the effect of Chalcogen (O, S, and Se) and nitrogen (N) on geometrical, electronic, optical, and charge transfer properties of these compounds by setting their ionization potentials (IP), their electron affinities (EA), their chemical reactivity indices, their reorganization energies, their electrostatic potential as well as the nonlinear optical (NLO) properties. The geometry of these studied compounds was obtained after optimization in their fundamental states by using the functional density theory (DFT) with the B3LYP method and the basis set 6-311G (d, p).  The studied parameters determined from the most stable conformation of each studied molecule. The time-dependent density theory method TD-DFT-B3LYP 6-311G (d, p) was used for the study of absorption. The results of the theoretical calculations show that the mentioned parameters above are affected by the change of atoms O, S, Se, and NH. The smaller hole and electron reorganization energies of these molecules suggest possible use in OLEDs.

In silico design of new α-glucosidase inhibitors through 3D-QSAR study, molecular docking modeling and ADMET analysis

α-Glucosidase enzyme is a therapeutic target for diabetes mellitus and its inhibitors shown a crucial importance in the treatment of this disease. Twenty oxindole based oxadiazole molecules were studied based on the combination between 3D-QSAR and molecular docking approaches in order to develop new α-glucosidase inhibitors with high predicted activities. The proposed CoMFA and CoMSIA models exhibited important Q2 values (0.544 and 0.605 respectively) and significant R2 values (0.977 and 0.935 respectively). The CoMFA and CoMSIA models were undergone to an external validation to test their proficiency; the produced R2test values are 0.950 and 0.804, respectively. Moreover, the contour maps produced by CoMFA and CoMSIA models have been exploited to determine the main groups influencing (decreasing or increasing) the α-glucosidase inhibitory activity. Therefore, two new oxindole based oxadiazole molecules with significant activities were proposed and designed. In a similar vein, molecular docking simulation was conducted to scrutinize the binding interactions between oxindole based oxadiazole molecules and α-glucosidase receptor (PDB code: 3A4A). Finally yet importantly, ADMET properties were predicted to assess the oral bioavailability of the proposed new compounds and examine their toxicity

Combined 3D-QSAR Modeling and Molecular Docking Study on metronidazole-triazole-styryl hybrids as antiamoebic activity

A series of twenty-two metronidazole-triazole-styryl hybrids as antiamoebic agents were studied based on the combination of 3D-QSAR and surflex-docking. The CoMFA and CoMSIA models were carried out using eighteen compounds in the training set and four compounds in the test set gives Q2 values of 0.684 and 0.664 respectively, and R2 values of 0.882 and 0.894 respectively. The adapted alignment method with the suitable parameters resulted in reliable models. Based on contour maps produced by the CoMFA and CoMSIA, we suggested new compounds with high predicted activities, Surflex-docking revealed the important interactions between the ligand and receptor. Therefore, it confirmed the stability of predicted molecules in the receptor with PDB: 4CCQ

New compounds based on 1H-pyrrolo[2,3-b] pyridine as potent TNIK inhibitors against colorectal cancer cells. Molecular modeling studies

Cancer is a disease caused by the incorrect transformation of cells that proliferate abnormally, and it is one of the leading causes of mortality worldwide. As a result, new compounds with potential anticancer activity must be designed. In this article, three – dimensional Quantitative Structure-Activity Relationship is used to study thirty-one compounds of 1H-pyrrolo[2,3-b]pyridine derivatives as potent TNIK inhibitors against colorectal cancer cells. Their pIC50 varied from 7.37 to 9.92. The two contours, Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices (CoMSIA) are critical in determining the nature of the groups that enhance or reduce activity. The models CoMFA and CoMSIA indicate strong reliability with (Q2 = 0.65; R2 = 0.86; rtest2 = 0.97) and (Q2= 0.74; R2 = 0. 96; rtest2 = 0. 95), respectively. Based on the good findings produced by the contour maps generated by the approach model, we have suggested five drugs with strong activity against colorectal cancer cells. In addition, the ADMET characteristics of these newly designed compounds were examined in silico. These compounds were further evaluated by molecular docking, showing that two molecules, Y4 and Y5, exhibit favorable interactions with the targeted receptor and a high total score. Our vision is to develop new medicines with strong TNIK inhibitory activities that target Traf2 and Nck-interacting kinase TNIK as a therapeutic target