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AcrAB-TolC is the most important multidrug efflux pump system of Gram-negative bacteria, responsible for their resistance to lipophilic and amphiphilic drugs. In this work, a molecular graphics study of the pump components AcrB and TolC, 16 beta-lactam antibiotics and 7 other substrates, as well as of AcrB-substrate complexes, was performed in order to give a mechanistic proposal for the efflux process at molecular level. AcrAB-TolC is a proton-dependent electromechanical device which opens to extrude drugs from the bacterial periplasm and perhaps cytoplasm, by means of a series of structural changes within the complex and its components AcrA, AcrB and TolC. These changes are initiated by protonation and disruption of salt bridges and certain hydrogen bonds, and are followed by conformational changes in which a number of intra- and interchain interactions are rearranged. Molecular properties of beta-lactams accounting for their lipophilicity, shape/conformation and other sterical features, polar/charge group distribution and other electronic properties, and hydrogen bonding potency determine their interaction with polar headpieces of the inner membrane, recognition and binding to receptors of AcrB and TolC. The orientation of the beta-lactam molecular dipoles with respect the efflux system is maintained during the drug efflux. Elongated cylinder-like beta-lactam antibiotics with lipophylic side chains, a significantly negative component of the dipole moment and low hydrogen bonding capacity seem to be good substrates of AcrAB-TolC.

Molecular graphics and modeling methods illustrated the chemical background of the a priori approach from part I, and visualized steric and electronic enzyme-inhibitor relationships at qualitative and quantitative level for 34 and its derivatives. The enzyme-inhibitor electron density overlap occurs at 1.5-5.5A cut-off distance, beyond van der Waals radii. Derivatives of 34 exhibit linear relationships between biological activity, molecular size and number of intermolecular interactions.

A quantitative structure-activity relationship (QSAR) study on 48 peptidic HIV-1 protease inhibitors was performed. Fourteen a priori molecular descriptors were used to build QSAR models. Hierarchical cluster analysis (HCA), principal component analysis (PCA) and partial least squares (PLS) regression were employed. PLS models with 32/16 (model I) and 48/0 (model II) molecules in the training/external validation set were constructed. The a priori molecular descriptors were related to two energetic variables using PLS. HCA and PCA on data from model II classified the inhibitors as slightly, moderately and highly active; three principal components, the chemical nature of which has been highlighted, are enough to describe the enzyme-inhibitor binding. Model I (r(2)=0.91, q(2)=0.84) is comparable to literature models obtained by various QSAR softwares, which justified the use of a priori descriptors.

Structure-activity relationships (SAR) of the contraceptive progestogens for (I) oral contraceptive activity (OCA), (II) androgenic effect, and (III) binding affinity for sex hormone binding globulin (SHBG) were studied using four different methods: principal component analysis (PCA), hierarchical cluster analysis (HCA), neural networks (NN), and electronic indices method (EIM) employing descriptors calculated by the semi-empirical Austin Model I (AM1) method. An additional set of molecules was used to check the reliability of the results obtained for OCA by PCA. Using PCA, three different sets of descriptors were found to correlate with the three different biological activities, I-III, indicating that the interaction between the receptor and the progestogen must depend on the type of biological activity. The descriptors selected by PCA were also employed for SAR analysis of the contraceptive progestogens using two other methods, HCA and NN. Both HCA and NN correctly classified high activity molecules as different from low activity ones. Thus, those descriptors selected by PCA work well in the other two methods of classification. Using the sign of p, a difference of electron densities of selected molecular orbitals in a specified region in a molecule, it was possible to discriminate high activity molecules from low activity molecules in the three different types of activities studied, I-III, with one exception.