By introducing an electron bath that represents the chemical environment in which a chemical species is immersed, and by making use of the second-order Taylor series expansions of the energy as a function of the number of electrons in the intervals between N - 1 and N, and N and N + 1, we show that the electrodonating (omega-) and the electroaccepting (omega+) powers may be defined as omega-/+ = (mu-/+)2/2eta-/+, where mu-/+ are the chemical potentials and eta-/+ are the chemical hardnesses, in their corresponding intervals. Approximate expressions for omega- and omega+ in terms of the ionization potential I and the electron affinity A are established by assuming that eta- = eta+ = eta = mu+ - mu-. The functions omega-/+(r) = omega-/+f -/+(r), where f -/+(r) are the directional Fukui functions, derived from a functional Taylor series for the energy functional truncated at second order, represent the local electrodonating and electroaccepting powers.

Electrodonating and electroaccepting powers.

The substitution of isoelectronic B–N units for C–C units in aromatic hydrocarbons produces novel heterocycles with structural similarities to the all-carbon frameworks, but with fundamentally alte...

B-N as a C-C substitute in aromatic systems

The nucleophilicity N index (J. Org. Chem.2008, 73, 4615), the inverse of the electrophilicity, , and the recently proposed inverse of the electrodonating power, , (J. Org. Chem.2010, 75, 4957) have been checked toward (i) a series of single 5-substituted indoles for which rate constants are available, (ii) a series of para-substituted phenols, and for (iii) a series of 2,5-disubstituted bicyclic[2.2.1]hepta-2,5-dienes which display concurrently electrophilic and nucleophilic behaviors. While all considered indices account well for the nucleophilic behavior of organic molecules having a single substitution, the nucleophilicity N index works better for more complex molecules. Unlike, the inverse of the electrophilicity, , (R2 = 0.71), and the inverse of the electrodonating power, (R2 = 0.83), a very good correlation of the nucleophilicity N index of twelve 2-substituted-6-methoxy-bicyclic[2.2.1]hepta-2,5-dienes versus the activation energy associated with the nucleophilic attack on 1,1-dicyanoethylene is found (R2 = 0.99). This comparative study allows to assert that the nucleophilicity N index is a measure of the nucleophilicity of complex organic molecules displaying concurrently electrophilic and nucleophilic behaviors.

The nucleophilicity N index in organic chemistry

Although thousands of quantitative structure–activity and structure–property relationships (QSARs/QSPRs) have been published, as well as numerous papers on the correct procedures for QSAR/QSPR analysis, many analyses are still carried out incorrectly, or in a less than satisfactory manner. We have identified 21 types of error that continue to be perpetrated in the QSAR/QSPR literature, and each of these is discussed, with examples (including some of our own). Where appropriate, we make recommendations for avoiding errors and for improving and enhancing QSAR/QSPR analyses.

How not to develop a quantitative structure–activity or structure–property relationship (QSAR/QSPR)

Atomic clusters, consisting of a few to a few thousand atoms, have emerged over the past 40 years as the ultimate nanoparticles, whose structure and properties can be controlled one atom at a time. One of the early motivations in studying clusters was to understand how the properties of matter evolve as a function of size, shape, and composition. Over the past few decades, more than 200 000 papers have been published in this field. These studies have not only led to a considerable understanding of this evolution from clusters to crystals, but also have revealed many unusual size-specific properties that make cluster science an interdisciplinary field on its own, bridging physics, chemistry, materials science, biology, and medicine. More importantly, the possibility of creating a new class of materials, composed of clusters instead of atoms as building blocks, has fueled the hope that one can synthesize materials from the bottom-up with unique and tailored properties. This Review focuses on the properties ...

Super Atomic Clusters: Design Rules and Potential for Building Blocks of Materials

Update 1 of: Electrophilicity Index

Electrophilicity index as a possible descriptor of biological activity.

Electrophilicity as a possible descriptor for toxicity prediction.

In line with the local philicity concept proposed by Chattaraj et al. (Chattaraj, P. K.; Maiti, B.; Sarkar, U. J. Phys. Chem. A. 2003, 107, 4973) and a dual descriptor derived by Morell, Grand and Toro-Labbe, (J. Phys. Chem. A 2005, 109, 205), we propose a multiphilic descriptor. It is defined as the difference between nucleophilic (omega(k)+) and electrophilic (omega(k)-) condensed philicity functions. This descriptor is capable of simultaneously explaining the nucleophilicity and electrophilicity of the given atomic sites in the molecule. Variation of these quantities along the path of a soft reaction is also analyzed. Predictive ability of this descriptor has been successfully tested on the selected systems and reactions. Corresponding force profiles are also analyzed in some representative cases. Also, to study the intra- and intermolecular reactivities another related descriptor, namely, the nucleophilicity excess (Deltaomega(g)-/+) for a nucleophile over the electrophilicity in it, has been defined and tested on all-metal aromatic compounds.

Multiphilic descriptor for chemical reactivity and selectivity.

The toxicological structure-activity relationships are investigated using conceptual DFT based descriptors like global and local electrophilicities. In the present work the usefulness of electrophilicity in predicting toxicity of several polyaromatic hydrocarbons (PAH) is assessed. The toxicity is expressed through biological activity data (pIC50) defined as molar concentration of those chemicals necessary to displace 50% of radiolabeled tetrachlorodibenzo-p-dioxin (TCDD) from the arylhydrocarbon (Ah) receptor. The experimental toxicity values (pIC50) for the electron acceptor toxin like polychlorinated dibenzofurans (PCDF) are taken as dependent variables and the DFT based global descriptor electrophilicity index (omega) is taken as independent variable in the training set. The same model is then tested on a test set of polychlorinated biphenyls (PCB). A good correlation is obtained which vindicates the importance of these descriptors in the QSAR studies on toxins. These toxins act as electron acceptors in the presence of biomolecules whereas aliphatic amines behave as electron donors some of which are also taken into account for the present work. The toxicity values of the aliphatic amines in terms of the 50% inhibitory growth concentration (IGC50) towards ciliate fresh-water protozoa Tetrahymena pyriformis are considered. Since there is no global nucleophilicity we apply local nucleophilicity (omegamax+) as the descriptor in this case of training set. The same regression model is then applied to a test set of amino alcohols. Although the correlation is very good the statistical analysis reflects some cross validation problem. As a further check the amines and amino alcohols are used together to form both the training and the test sets to provide good correlation. It is demonstrated that the toxicity of several toxins (both electron donors and acceptors) in the gas and solution phases can be adequately explained in terms of global and local electrophilicities. Amount of charge transfer between the toxin and the biosystem, simulated as nucleic acid bases and DNA base pairs, indicates the importance of charge transfer in the observed toxicity. The major strength of the present analysis vis-a-vis the existing ones rests on the fact that it requires only one descriptor having a direct relationship with toxicity to provide a better correlation. Importance of using the information from both the toxin and the biosystem is also analyzed.

Debesh R. Roy

Papers

Update 1 of: Electrophilicity Index

Electrophilicity index as a possible descriptor of biological activity.

Electrophilicity as a possible descriptor for toxicity prediction.

Multiphilic descriptor for chemical reactivity and selectivity.

Analyzing Toxicity Through Electrophilicity