Molecular Electronegativity-Distance Vector As Applied In Quantitative Structure-Activity Relationship (QSAR) For Pharmacy

Quantitative Structure-Activity Relationship (QSAR), which investigates the quantitative relationship between the molecular structural parameters and biological activities or dependent functions, is one of the most important fundamental fields in pure and applied chemistry and pharmacy. Molecular structural characterization is an important technique in QSAR studies. With development and application of graphic theory, more and more topological indices have been developed rapidly and widely. One of merits for topological indices is that they can be derived directly from molecular structure without experiments, and so they have been applied in QSAR as simple, direct and effective molecular structure parameterization methods. Both molecular and atomic electronegativity distance vector (MEDV/AEDV), which have been developed in our laboratory to describe two-dimensional (2D) molecular topology and local microenvironment around various chemically equivalent carbon atoms, are applicable to various molecular global and local structures which contain the multiple bonds and/or heteroatoms by introducing the concepts of relative electronegative (REN) and relative bond length (RBL). In this dissertation, investigation on applicability of MEDV-4/AEDV as the extended and improved 2D descriptors are performed as viewed from the molecular microenvironment, relative distance and electronegativity effect.The main contents are as follows:Taking the effects of various hybridization on atomic electronegativities into account, a set of novel structural descriptors, called molecular electronegativity- distance vector with hybridization (MEDVh), has been developed. MEDV-4 and MEDVh have been used to express the structures of several groups of estrogens. The correlation coefficients R of the QSAR models that related MEDV-4 to biological activities of two sets of estradiols and a set of 2-phenylindoles are higher than 0.92, and the RCV are higher than 0.85. The QSAR models related MEDVh to 21 progesterones has R=0.9546 and RCV=0.8826.Hydrogen-association classified molecular electronegativity-distance vector (H-MEDV) can be used express molecular structures of two sets of anti-HIV HEPT agents and one set of dihydrofolate reductase inhibitors and the results are better than that of MEDV-4. The R and RCV for QSAR models for HEPT are higher than 0.90 and 0.85, respectively. Both the R and RCV of the QSAR models for activities of dihydrofolate reductase inhibitors are higher than 0.80.The applicable fields of MEDV-4 are extended. MEDV-4 has been related to various of physicochemical properties of alcohols, aldehydes, ketones and polychlorinated diphenyl ethers, and the quantitative relationship models have been constructed by using multiple linear regression technique. The correlation coefficient R and standard deviation SD between the estimated properties and observed experimentally properties have been used to evaluate the estimation abilities for internal samples. The correlation coefficient RCV and standard deviation SDCV between the properties observed experimentally and the properties predicted by leave-one-out crossvalidation technique have been used to evaluate the predictive abilities of models. The R of the models for boiling points, water solubility, octane/water partition, molecular total surface area, molecular volumes and molecular refractions are higher than 0.99, and RCV are higher than 0.98. The models which related MEDV-4 to boiling point of aldehydes and ketones has R=0.9911 and RCV=0.9881. The R and RCV of models for liquid vapor pressures, n-octanol/water partition coefficients and liquid water solubilities of polychlorinated diphenyl ethers are higher than 0.98 and 0.97, respectively. The results show that MEDV-4 can be used to well express the structures of these organic compounds.The descriptors, AEDV, are used to express the local microenvironment of various chemically equivalent carbon atoms in 88 aromatic aldehydes and ketones and the quantitative relationship model exhibits good estimation ability fo...