QSPR modelling for investigation of different properties of aminoglycoside-derived polymers using 2D descriptors

The quantitative structure-property relationship (QSPR) method is commonly used to predict different physicochemical characteristics of interest of chemical compounds with an objective to accelerate the process of design and development of novel chemical compounds in the biotechnology and healthcare industries. In the present report, we have employed a QSPR approach to predict the different properties of the aminoglycoside-derived polymers (i.e. polymer DNA binding and aminoglycoside-derived polymers mediated transgene expression). The final QSPR models were obtained using the partial least squares (PLS) regression approach using only specific categories of two-dimensional descriptors and subsequently evaluated considering different internationally accepted validation metrics. The proposed models are robust and non-random, demonstrating excellent predictive ability using test set compounds. We have also developed different kinds of consensus models using several validated individual models to improve the prediction quality for external set compounds. The present findings provide new insight for exploring the design of an aminoglycoside-derived polymer library based on different identified physicochemical properties as well as predict their property before their synthesis.

Predicting the rate constants of volatile organic compounds (VOCs) with ozone reaction at different temperatures

Based on the bond order, fukui indices and other related descriptors, as well as temperature, a new QSAR model was established to predict the rate constant (kO3) of VOCs degradation by O3. 302 logkO3 values (178-409 K) of 149 VOCs were divided into training set (242 logkO3) and test set (60 logkO3), respectively, which were used to construct and verify the QSAR model. The optimal model (R2 = 0.83, q2 = 0.82, Qext2 = 0.72) shows that EHOMO, BOx and q(C-)n have a greater influence on the value of logkO3. In addition, fukui indices and logkO3 are well correlated. The applicability domains of the current models can be used to predict kO3 of a wide range of VOCs at different temperatures.

Modeling the pH and temperature dependence of aqueousphase hydroxyl radical reaction rate constants of organic micropollutants using QSPR approach

Designing of advanced oxidation process (AOP) requires knowledge of the aqueous phase hydroxyl radical (^●OH) reactions rate constants (k _OH), which are strictly dependent upon the pH and temperature of the medium. In this study, pH- and temperature-dependent quantitative structure-property relationship (QSPR) models based on the decision tree boost (DTB) approach were developed for the prediction of k _OH of diverse organic contaminants following the OECD guidelines. Experimental datasets (n = 958) pertaining to the k _OH values of aqueous phase reactions at different pH (n = 470; 1.4 × 10⁶ to 3.8 × 10¹⁰ M^-1 s^-1) and temperature (n = 171; 1.0 × 10⁷ to 2.6 × 10¹⁰ M^-1 s^-1) were considered and molecular descriptors of the compounds were derived. The Sanderson scale electronegativity, topological polar surface area, number of double bonds, and halogen atoms in the molecule, in addition to the pH and temperature, were found to be the relevant predictors. The models were validated and their external predictivity was evaluated in terms of most stringent criteria parameters derived on the test data. High values of the coefficient of determination (R ²) and small root mean squared error (RMSE) in respective training (> 0.972, ≤ 0.12) and test (≥ 0.936, ≤ 0.16) sets indicated high generalization and predictivity of the developed QSPR model. Other statistical parameters derived from the training and test data also supported the robustness of the models and their suitability for screening new chemicals within the defined chemical space. The developed QSPR models provide a valuable tool for predicting the ^●OH reaction rate constants of emerging new water contaminants for their susceptibility to AOPs.

QSAR modeling for predicting mutagenic toxicity of diverse chemicals for regulatory purposes

The safety assessment process of chemicals requires information on their mutagenic potential. The experimental determination of mutagenicity of a large number of chemicals is tedious and time and cost intensive, thus compelling for alternative methods. We have established local and global QSAR models for discriminating low and high mutagenic compounds and predicting their mutagenic activity in a quantitative manner in Salmonella typhimurium (TA) bacterial strains (TA98 and TA100). The decision treeboost (DTB)-based classification QSAR models discriminated among two categories with accuracies of >96% and the regression QSAR models precisely predicted the mutagenic activity of diverse chemicals yielding high correlations (R ²) between the experimental and model-predicted values in the respective training (>0.96) and test (>0.94) sets. The test set root mean squared error (RMSE) and mean absolute error (MAE) values emphasized the usefulness of the developed models for predicting new compounds. Relevant structural features of diverse chemicals that were responsible and influence the mutagenic activity were identified. The applicability domains of the developed models were defined. The developed models can be used as tools for screening new chemicals for their mutagenicity assessment for regulatory purpose.

Atmospheric oxidation of halogenated aromatics: comparative analysis of reaction mechanisms and reaction kinetics

Atmospheric transport is the major route for global distribution of semi-volatile compounds such as halogenated aromatics as well as their major exposure route for humans. Their major atmospheric removal process is oxidation by hydroxyl radicals. There is very little information on the reaction mechanism or reaction-path dynamics of atmospheric degradation of halogenated benzenes. Furthermore, the measured reaction rate constants are missing for the range of environmentally relevant temperatures, i.e. 230-330 K. A series of recent theoretical studies have provided those valuable missing information for fluorobenzene, chlorobenzene, hexafluorobenzene and hexachlorobenzene. Their comparative analysis has provided additional and more general insight into the mechanism of those important tropospheric degradation processes as well as into the mobility, transport and atmospheric fate of halogenated aromatic systems. It was demonstrated for the first time that the addition of hydroxyl radicals to monohalogenated as well as to perhalogenated benzenes proceeds indirectly, via a prereaction complex and its formation and dynamics have been characterized including the respective transition-state. However, in fluorobenzene and chlorobenzene reactions hydroxyl radical hydrogen is pointing approximately to the center of the aromatic ring while in the case of hexafluorobenzene and hexachlorobenzene, unexpectedly, the oxygen is directed towards the center of the aromatic ring. The reliable rate constants are now available for all environmentally relevant temperatures for the tropospheric oxidation of fluorobenzene, chlorobenzene, hexafluorobenzene and hexachlorobenzene while pentachlorophenol, a well-known organic micropollutant, seems to be a major stable product of tropospheric oxidation of hexachlorobenzene. Their calculated tropospheric lifetimes show that fluorobenzene and chlorobenzene are easily removed from the atmosphere and do not have long-range transport potential while hexafluorobenzene seems to be a potential POP chemical and hexachlorobenzene is clearly a typical persistent organic pollutant.