Gas-to-ionic liquid partition: QSPR modeling and mechanistic interpretation.

The present work was devoted to explore the quantitative structure-property relationships for gas-to-ionic liquid partition coefficients (log KILA ). A series of linear models were first established for the representative dataset (IL01). The optimal model was a four-parameter equation (1Ed) consisting of two electrostatic potential-based descriptors ( Σ V s , i n d - ${{\rm { \Sigma }}{V}_{s,ind}^{-}}$ and Vs,max ), one 2D matrix-based descriptor (J_D/Dt) and dipole moment (µ). All of the four descriptors introduced in the model can find the corresponding parameters, directly or indirectly, from Abraham's linear solvation energy relationship (LSER) or its theoretical alternatives, which endows the model good interpretability. Gaussian process was utilized to build the nonlinear model. Systematical validations, including 5-fold cross-validation for the training set, the validation for test set, as well as a more rigorous Monte Carlo cross-validation were performed to verify the reliability of the constructed models. Applicability domain of the model was evaluated, and the Williams plot revealed that the model can be used to predict the log KILA values of structurally diverse solutes. The other 13 datasets were also processed in the same way, and all of the linear models with expressions similar to equation 1Ed were obtained. These models, whether linear of nonlinear, represent satisfactory statistical results, which confirms the universality of the method adopted in this study in QSPR modeling of gas-to-IL partition.

QSPR study on Hydrophobicity of Pt(II) complexes with surface electrostatic potential-based descriptors.

Pt(II) complexes play an important role in bioinorganic chemistry due to their antitumor activities. In the present study, we focused on building predictive models for the hydrophobicity of Pt(II) complexes. A five-parameter model, integrating frontier orbital energies (EHOMO, ELUMO) and descriptors derived from electrostatic potentials on molecular surface, was firstly constructed by using multiple linear regression (MLR) method. Mechanistic interpretations of the introduced descriptors were elucidated in terms of intermolecular interactions in the n-octanol/water partition system. Then, four up-to-date modeling methods, including support vector machine (SVM), least-squares support vector machine (LSSVM), random forest (RF) and Gaussian process (GP), were utilized to build the nonlinear models. Systematical validations including leave-one-out cross-validation, the validation for test set, as well as a very rigorous Monte Carlo cross-validation (MCCV) were performed to verify the reliability of the constructed models. The peak, median and integralRext2 values of the best GP model are 0.88, 0.86 and 0.84, respectively. The root mean squared errors for the test set (RMSEP) of the MLR, SVM, LSSVM and GP models fall in the range of 0.62-0.71. Although they are not superior to prior models built with the use of a number of descriptors, the results are satisfactory. Applicability domain of the model was evaluated.

Prediction of the hydrophobicity of platinum(IV) complexes based on molecular surface properties.

A quantitative structure-property relationship (QSPR) study was performed for predicting the hydrophobicity of Pt(IV) complexes. Two four-parameter equations, one based solely on structural descriptors derived from electrostatic potentials (ESPs) on molecular surface, and the other integrated ESP descriptors with molecular surface area (AS), were firstly constructed. Mechanistic interpretations of the structural descriptors introduced were elucidated in terms of solute-solvent intermolecular interactions. Subsequently, several up-to-date modeling techniques, including support vector machine (SVM), least-squares support vector machine (LSSVM), random forest (RF) and Gaussian process (GP), were utilized to build the nonlinear models. Systematical validations including leave-one-out cross-validation, the validation for test set, as well as a more rigorous Monte Carlo cross-validation were performed to verify the reliability of the constructed models. The predictive performances of the four different nonlinear modeling methods follow the order of LSSVM≈GP > RF > SVM. The pure-ESP-based models are generally inferior to the AS-integrated ones. Comparisons with previous results were made.

Phosphorylation Mechanism of N-Acetyl-l-glutamate Kinase, a QM/MM Study.

In microorganisms and plants, N-acetyl-l-glutamate kinase (NAGK) catalyzes the second step in l-arginine synthesis, the phosphorylation of N-Acetyl-l-glutamate (NAG) to give N-acetyl-l-glutamate-5-phosphate. NAGK is only present in microorganisms and plants but absent in mammals, which makes it an attractive target for antimicrobial or biocidal development. Understanding the substrate binding mode and reaction mechanism of NAGK is crucial for targeting the kinase to develop potential therapies. Here, the substrate binding mode was studied by comparing the conformational change of NAGK in the presence and in the absence of the NAG substrate based on molecular dynamics simulations. We revealed that with substrate binding, the catalytic site of the kinase involving three loops in NAGK exhibits a closed conformation, which is predominantly controlled by an interaction between Arg98 and the α-COO- of NAG. Lys41 is found to guide phosphate transfer through the interactions with the ß-,γ-, and γ-phosphate oxygen atoms of adenosine 5'-triphosphate surrounded by two highly conserved glycine residues (Gly44 and Gly76), while Arg98 helps to position the NAG substrate in the catalytic site, which facilitates the phosphate transfer. Furthermore, we elucidated phosphate-transfer reaction mechanism using hybrid density functional theory-based quantum mechanics/molecular mechanics calculations (B97D/AMBER99) and found that the catalysis follows a dissociative mechanism.

Quantitative structure-hydrophobicity relationships of molecular fragments and beyond.

Quantitative structure-property relationship (QSPR) models were firstly established for the hydrophobic substituent constant (πX) using the theoretical descriptors derived solely from electrostatic potentials (EPSs) at the substituent atoms. The descriptors introduced are found to be related to hydrogen-bond basicity, hydrogen-bond acidity, cavity, or dipolarity/polarizability terms in linear solvation energy relationship, which endows the models good interpretability. The predictive capabilities of the models constructed were also verified by rigorous Monte Carlo cross-validation. Then, eight groups of meta- or para-disubstituted benzenes and one group of substituted pyridines were investigated. QSPR models for individual systems were achieved with the ESP-derived descriptors. Additionally, two QSPR models were also established for Rekker's fragment constants (foct), which is a secondary-treatment quantity and reflects average contribution of the fragment to logP. It has been demonstrated that the descriptors derived from ESPs at the fragments, can be well used to quantitatively express the relationship between fragment structures and their hydrophobic properties, regardless of the attached parent structure or the valence state. Finally, the relations of Hammett σ constant and ESP quantities were explored. It implies that σ and π, which are essential in classic QSAR and represent different type of contributions to biological activities, are also complementary in interaction site.

3D-QSAR and 3D-QSSR studies of thieno[2,3-d]pyrimidin-4-yl hydrazone analogues as CDK4 inhibitors by CoMFA analysis.

AIM: To investigate the structural basis underlying potency and selectivity of a series of novel analogues of thieno[2,3-d]pyrimidin-4-yl hydrazones as cyclin-dependent kinase 4 (CDK4) inhibitors and to use this information for drug design strategies. METHODS: Three-dimensional quantitative structure-activity relationship (3D-QSAR) and three-dimensional quantitative structure-selectivity relationship (3D-QSSR) models using comparative molecular field analysis (CoMFA) were conducted on a training set of 48 compounds. Partial least squares (PLS) analysis was employed. External validation was performed with a test set of 9 compounds. RESULTS: The obtained 3D-QSAR model (q(2)=0.724, r(2)=0.965, r(2)pred=0.945) and 3D-QSSR model (q(2)=0.742, r(2)=0.923, r(2)pred=0.863) were robust and predictive. Contour maps with good compatibility to active binding sites provided insight into the potentially important structural features required to enhance activity and selectivity. The contour maps indicated that bulky groups at R1 position could potentially enhance CDK4 inhibitory activity, whereas bulky groups at R3 position have the opposite effect. Appropriate incorporation of bulky electropositive groups at R4 position is favorable and could improve both potency and selectivity to CDK4. CONCLUSION: These two models provide useful information to guide drug design strategies aimed at obtaining potent and selective CDK4 inhibitors.

Quantitative structure-chromatographic retention relationship for polycyclic aromatic sulfur heterocycles.

Polycyclic aromatic sulfur heterocycles (PASHs) are of concern in petroleum geochemistry and environmental chemistry. In the present study, geometrical optimization and electrostatic potential calculations have been performed for 114 PASHs reported previously at the HF/6-31G* level of theory. A group of 25 statistically based parameters have been extracted. Linear relationships between gas-chromatographic retention index (RI) and the structural descriptors have been established by stepwise linear regression analysis. The result shows that two quantities derived from positive electrostatic potential on molecular surface, V(s)(+) (the average value of the positive electrostatic potentials on molecular surface) and sigma(+)(2) (a measure of dispersion tendency of positive electrostatic potential), together with V(mc) (the molecular volume) and E(HOMO) (the energy of the highest occupied molecular orbital) can be well used to express the quantitative structure-retention relationship (QSRR) of PASHs. Predictive capability of the model has been demonstrated by leave-one-out cross-validation with the cross-validated correlation coefficient (R(CV)) of 0.992. Furthermore, when splitting the 114 PASH samples into calibration and test sets in the ratio of 2:1, a similar treatment yields an equation of almost equal statistical quality and very similar regression coefficients, validating the robustness of our model. Predictions for six PASHs from other source have also been made. The QSRR model established may provide a new powerful method for predicting chromatographic properties of aromatic organosulfur compounds.

Ab initio study of the complexes of halogen-containing molecules RX (X=Cl, Br, and I) and NH3: towards understanding the nature of halogen bonding and the electron-accepting propensities of covalently bonded halogen atoms.

Ab initio calculations have been performed on a series of complexes formed between halogen-containing molecules and ammonia to gain a deeper insight into the nature of halogen bonding. It appears that the dihalogen molecules form the strongest halogen-bonded complexes with ammonia, followed by HOX; the charge-transfer-type contribution has been demonstrated to dominate the halogen bonding in these complexes. For the complexes involving carbon-bound halogen molecules, our calculations clearly indicate that electrostatic interactions are mainly responsible for their binding energies. Whereas the halogen-bond strength is significantly enhanced by progressive fluorine substitution, the substitution of a hydrogen atom by a methyl group in the CH(3)X...NH(3) complex weakened the halogen bonding. Moreover, remote substituent effects have also been noted in the complexes of halobenzenes with different para substituents. The influence of the hybridization state of the carbon atom bonded to the halogen atom has also been examined and the results reveal that halogen-bond strengths decrease in the order HC triple bond CX > H(2)C=CHX approximately O=CHX approximately C(6)H(5)X > CH(3)X. In addition, several excellent linear correlations have been established between the interaction energies and both the amount of charge transfer and the electrostatic potentials corresponding to an electron density of 0.002 au along the R-X axis; these correlations provide good models with which to evaluate the electron-accepting abilities of the covalently bonded halogen atoms. Finally, some positively charged halogen-bonded systems have been investigated and the effect of the charge has been discussed.

Binding interaction of gatifloxacin with bovine serum albumin.

The binding of gatifloxacin to bovine serum albumin (BSA) in aqueous solution was studied using fluorescence spectroscopy and absorbance spectra, Further, the interactions influenced by Fe3+ and Cu2+ were also explored in this work. Based on Scatchard's site-binding model and florescence quenching, practical formulas for small molecule ligands to bio-macromolecules have been proposed. The binding parameters were measured according to suggested models, and the binding distance and the transfer efficiency of energy between gatifloxacin and BSA were also obtained in view of the Förster theory of non-radiation energy transfer. The effect of gatifloxacin on the conformation of BSA has also been analyzed using synchronous fluorescence spectroscopy.