On the Validity of Minimum Magnetizability Principle in Chemical Reactions.

A new principle known as Minimum Magnetizability Principle has recently been introduced in the context of Density Functional Theory. In order to validate this principle, changes in the magnetizability (Δξ) and its cube-root (Δξ1/3) are computed at B3LYP/LanL2DZ level of theory for some elementary chemical reactions. The principle is found to be valid for 77% of reactions under study. It is observed that the molecules with the lowest sum of ξ or ξ1/3 are generally the most stable. The principle fails to work in the presence of hard species. A comparative study is also made with change in hardness (Δη), electrophilicity index (Δω), polarizability (Δα) and their cube-roots (Δη1/3, Δω1/3, Δα1/3). It is observed that the Minimum Magnetizability Principle is nearly as reliable as Minimum Electrophilicity Principle. It appears that this principle could be helpful in predicting the direction of diverse reactions as well as stable geometrical arrangements.

Polarizability: a promising descriptor to study chemical-biological interactions.

Recently, we have defined atomic polarizability, a Conceptual Density Functional Theory (CDFT)-based reactivity descriptor, through an empirical method. Though the method is empirical, it is competent enough to meet the criteria of periodic descriptors and exhibit relativistic effect. Since the atomic data are very accurate, we have applied them to determine molecular polarizability. Molecular polarizability is an electronic parameter and has an impact on chemical-biological interactions. Thus, it plays a pivotal role in explaining such interactions through Structure Activity Relationships (SAR). In the present work, we have explored the application of polarizability in the real field through investigation of chemical-biological interactions in terms of molecular polarizability. A Quantitative Structure-Activity Relationship (QSAR) model is constructed to account for electronic effects owing to polarizability in ligand-substrate interactions. The study involves the prediction of various biological activities in terms of minimum block concentration, relative biological response, inhibitory growth concentration or binding affinity. Superior results are presented for the predicted and observed activities which support the accuracy of the proposed polarizability-QSAR model. Further, the results are considered from a biological viewpoint in order to understand the mechanism of interactions. The study is performed to explore the efficacy of the computational model based on newly proposed polarizability and not to establish the finest QSAR. For future studies, it is suggested that the descriptor polarizability should be contrasted with the use of other drug-like descriptors.

A model of atomic compressibility and its application in QSAR domain for toxicological property prediction.

A model for computing the atomic compressibility (ß) based on two periodic descriptors, namely, absolute radius (r) and atomic electrophilicity index (ω), is proposed as[Formula: see text]The ansatz is invoked to compute compressibilities of atoms of 57 elements of the periodic table. The computed atomic data exhibits all sine qua non of periodic properties. Further, the concept group compressibility (Gß) is also established invoking additivity property using some molecules with different functional groups and consequently utilized in correlating with molecular polarizability. Since toxicity prediction is an imperative need of the hour, chemical reactivity descriptors are of paramount importance in the study of toxicological behaviour along with a lot of other molecular reactivity studies within a Quantitative Structure-Activity Relationship (QSAR) context. Hence, this quantity is applied in the modelling of toxicological property through QSAR and a comprehensive study is performed in an effort to investigate and validate the application of compressibility in determining its toxicological power. Consequently, varied 209 organic molecules are selected for studying the toxic effect on Tetrahymena pyriformis. A QSAR model is constructed in terms of compressibility which offers a superior prediction of toxicity independently without adopting additional descriptors or properties as in some other QSAR studies. Graphical abstract.