Textbooks show that in cis-1,3-disubstituted cyclohexane molecule, the conformer with the substituents in the diaxial positions is higher in energy and hence, it presents a low population in the conformational equilibrium. The diaxial conformer is destabilized by the repulsion between the substituent groups and the axial hydrogen atoms on the same side of the ring. This interaction is known as the 1,3-diaxial interaction. In this study, the solvent effect on the conformational equilibria of cis-3-N-ethylaminocyclohexanol (cis-3-EACOL) and cis-3-N,N-diethylaminocyclohexanol (cis-3-DEACOL) has been assessed through the spin-spin coupling constant (3JHH). The results show that the diaxial conformation of cis-3-EACOL decreases from 92% in CCl4 (∆Gee−aa = 1.48 kcal mol−1) to 10% in DMSO-d6 (∆Gee−aa = −1.31 kcal mol−1). For cis-3-DEACOL the diaxial conformer decreased from 36% in CCl4 (∆Gee−aa = −0.33 kcal mol−1) to 7% in Pyridine-d5 (∆Gee−aa = −1.55 kcal mol−1). The stabilization of the diaxial conformer in nonpolar solvents takes place due to the O-H···N intramolecular hydrogen bond, which overcomes the 1,3-diaxial steric interactions.

The influence of electrostatic and dispersion components of intermolecular interactions on the recognition of carbohydrates by aromatic protein residues is important for many biological processes. Interactions between glucose and galactose and aromatic moieties of tryptophan, phenylalanine and histidine were investigated through 1H nuclear magnetic resonance (NMR) chemical shift perturbation and fully explained by molecular modelling at the density functional theory (DFT) level. According to NMR experiments, aromatic amino acids interact preferably with one face of the carbohydrate and the calculations showed how intermolecular interactions were determinant in explaining the selectivity. Non-covalent interaction surfaces revealed that a CH bond oriented toward the center of the aromatic ring maximized the attractive interaction while minimizing the steric repulsion. Energy decomposition analyses showed that the dispersion component was stronger than the electrostatic component and contributes more when hydrogen bonds are not present in the studied complexes. However, it was the electrostatic component that correlated with the facial preference, especially for the complexes with tryptophan.

Estruturas químicas bidimensionais de uma série de derivados da 2,5-diaminobenzofenona, alguns inibidores de farnesiltransferase, correlacionam-se com as respectivas atividades antimaláricas. Os descritores nessa análise QSAR são pixels das estruturas químicas (imagens bidimensionais) transformados em binários e, portanto, a variação dos dados que explica a variância no bloco das bioatividades corresponde às coordenadas de cada pixel do desenho das moléculas. Este método, chamado análise multivariada de imagens aplicada ao estudo da relação quantitativa entre estrutura e atividade (MIA-QSAR), foi aplicado para modelar as atividades antimaláricas dos compostos acima e os resultados foram comparados com técnicas de QSAR 3D bastante conhecidas. Além da simplicidade e alto poder de predição do modelo MIA-QSAR, este método baseado em imagens 2D tem potencial para funcionar bem quando análises clássicas igualmente simples falham. Enfim, a presente análise QSAR baseada em desenhos de estruturas químicas bidimensionais dispensa uma varredura conformacional e alinhamento tridimensional das moléculas para fornecer um modelo QSAR robusto; a descrição físico-química de efeitos estéricos e centros estereogênicos, por exemplo, está toda incorporada na maneira com que substituintes são representados, e o método serve como uma ferramenta para aqueles que interessem em trabalhar com modelagem de fármacos.

Two-dimensional chemical structures of a series of 2,5-diaminobenzophenone derivatives, some farnesyltransferase inhibitors, have shown to correlate with the corresponding antimalarial activities. The descriptors in this QSAR analysis are pixels of the chemical structures (two dimensional images) transformed into binaries and, therefore, the data variance explaining the variance in the activities block corresponds to the coordinates of each pixel in each molecule. This method, named multivariate image analysis applied to quantitative structure-activity relationship (MIA-QSAR), was applied to model the antimalarial activities of the titled compounds and the results were compared to well known three-dimensional QSAR techniques for the same class of compounds. In addition to the simplicity and high predictive performance of the MIA-QSAR modelling, this 2D image-based method has the potential of working well when equally simple, classical analysis fails. Overall, the present QSAR analysis based on 2D chemical drawings (constrained structures) dispensed conformational screening and 3D alignment to provide a reliable QSAR model; the physicochemical description about e.g. steric effects and chiral centers is all contained in the way in which substituents in a congeneric series are drawn, and the method can serve as a tool to introduce those who are planning to deal with drug design.

The objective of this work was to determine the influence of hyperconjugative interactions on the ¹J CH coupling constant for hexamethylenetetramine (1) and adamantane (2). For this end, theoretical and experimental ¹J CH were obtained and hyperconjugative interactions were investigated using NBO. It was observed, theoretically and experimentally, that ¹J CH in 1 is 20 Hz larger than in 2, mainly due to the nN<FONT FACE=Symbol>®s</FONT>*C-H hyperconjugative interaction. This interaction occurs only in 1, with an energy of 9.30 kcal mol-1. It increases the s-character of the carbon atom in the C-H bond and the occupancy of the sigma*C-H orbital in (1).