Chemical similarity of molecules with physiological response.

Measuring the similarity among molecules is an important task in various chemically oriented problems. This elusive concept is hard to define and quantify. Moreover, the complexity of the problem is elevated by bifurcating the notion of molecular similarity to structural and chemical similarity. While the structural similarity of molecules is being extensively researched, the so-called chemical similarity is being mentioned scarcely. Here, we propose a way of converting the physico-chemical properties into molecular fingerprints. Then, using the apparatus of measuring the structural similarity, the chemical similarity can be assessed. The proof of a concept is demonstrated on a set of molecules that induce diverse physiological responses.

Predictive potential of eigenvalue-based topological molecular descriptors.

This study is directed toward assessing the predictive potential of eigenvalue-based topological molecular descriptors. The graph energy, Estrada index, resolvent energy, and the Laplacian energy were tested as parameters for the prediction of boiling points, heats of formation, and octanol/water partition coefficients of alkanes. It was shown that an eigenvalue-based molecular descriptor cannot be individually used for successful prediction of these physico-chemical properties, but the first Zagreb index, the number of zeros in the spectrum and the number of methyl groups must be also involved in the models. Performed statistics show that the models constructed using the Estrada index and resolvent energy are significantly better than ones with the energy of a graph and the Laplacian energy. Such a trend is even more noticeable in the case of octanol/water partition coefficients of alkanes.

On Relationships of Eigenvalue-Based Topological Molecular Descriptors.

Three eigenvalue-based topological molecular descriptors are compared using several datasets of alkanes. Two of them are well-known and frequently employed in various QSPR/QSAR investigations, and third-one is a newly derived whose predictive potential is yet to be proven. The relations among them are found and discussed. Structural parameters that govern these relations are identified and the corresponding formulas based on multiple linear regression have been obtained. It has been shown that all three investigated indices are encoding almost the same structural information of a molecule. They differ only by the extent of the sensitivity on a structural branching of a molecule and on the number of non-bonding molecular orbitals.

Magnetically Induced Current Density in Nonplanar Fully Benzenoid Hydrocarbons.

In our recent paper, the effects of molecular planarity on the local aromaticity in several series of increasingly planar fully benzenoid hydrocarbons were examined. It was found that the Clar formulas can provide correct information on the local aromaticity distribution even in nonplanar fully benzenoid systems. In the present work, the influence of molecular planarity on the ab initio magnetically induced current densities was examined for the same sets of molecules. The planarity effects were rationalized by examining the origins of the induced current density through the virtual transitions between occupied and unoccupied molecular orbitals.

Aromaticity of Nonplanar Fully Benzenoid Hydrocarbons.

The Clar aromatic sextet theory can provide a qualitative description of the dominant modes of cyclic π-electron conjugation in benzenoid molecules and of the relative stability among a series of isomeric benzenoid systems. In a series of nonplanar fully benzenoid hydrocarbons, the predictions of the Clar theory were tested by means of several different theoretical approaches: topological resonance energy (TRE), energy effect (ef), harmonic oscillator model of aromaticity (HOMA) index, six center delocalization index (SCI), and nucleus-independent chemical shifts (NICS). To assess deviations from planarity in the examined molecules, four different planarity descriptors were employed. It was shown how the planarity indices can be used to quantify the effect of nonplanarity on the local and global aromaticity of the studied systems.

Structural discrimination of networks by using distance, degree and eigenvalue-based measures.

In chemistry and computational biology, structural graph descriptors have been proven essential for characterizing the structure of chemical and biological networks. It has also been demonstrated that they are useful to derive empirical models for structure-oriented drug design. However, from a more general (complex network-oriented) point of view, investigating mathematical properties of structural descriptors, such as their uniqueness and structural interpretation, is also important for an in-depth understanding of the underlying methods. In this paper, we emphasize the evaluation of the uniqueness of distance, degree and eigenvalue-based measures. Among these are measures that have been recently investigated extensively. We report numerical results using chemical and exhaustively generated graphs and also investigate correlations between the measures.

On the cycle-dependence of topological resonance energy.

The topological resonance energy (TRE) was conceived in the 1970s. From the very beginning, it was known that TRE is equal to the collective energy-effect of all cycles present in a conjugated molecule. Also in the 1970s a theory of cyclic conjugation was elaborated, by means of which it was possible to compute the energy-effect ef(Z) of each individual cycle Z present in a conjugated molecule. Yet, the connection between TRE and the ef(Z)-values was, until now, not studied. We now show that TRE and the sum of the ef(Z)-values are closely correlated but that a certain correction needs to be made by taking into account the energy-effects of pairs, triplets, quartets, etc. of cycles.