The Method Of Three Dimensional Holographic Vector Of Atomic Interaction Field (3D-HoVAIF) And Its Applications In Quantitative Structure-Activity Relationship (QSAR) Studies

A novel molecular structural characterization (MSC) method, three dimensional holographic vector of atomic interaction field (3D-HoVAIF), is proposed in our laboratory, focusing its idea on three points: (a) Atoms are typed for 10 kinds according to their families in periodic table of elements and self hybridization states; (b) Three non-bonded (electrostatic, van der Waals and hydrophobic) factors, directly related to bioactivities, are utilized to express intramolecular potential energies; (c) Based on molecular steric structures, 165 non-bond interaction items calculated are taken as the three-dimensional (3D) structural descriptors of the molecule. Original spatial structures of the target compounds are autogenerated by software Chemoffice 8.0, then implementing a molecular mechanic (MM) conformation optimization (adopting MM+force field) with molecular simulation software HyperChem 7.5, and the end semi-experimental quantum chemistry software MOPAC 6.0 is further utilized to generate the ultimate 3D structures at AM1 levels. Simultaneously, atomic partial charges are calculated by Mülliken population analysis. Taking forms of Cartesian coordinates and partial charges respectively, spatial position for each atom in a molecule and the atomic charges are input into C-edited program Super-3D.EXE, giving rise to 3D-HoVAIF descriptors of the molecules. In the modeling process, stepwise multiple linear regression (SMR), multiple linear regression (MLR), partial least squares (PLS) regression, are used to correlate the 3D vector of molecules with their dissolved data, most obtained models have superior quality compared with literatures.(1) The developed three-dimensional holographic vector of atomic interaction field (3D-HoVAIF) was used to describe the chemical structures of 19 antitumor quinolone agents. After the structural characterization, the descriptors obtained were screened by stepwise multiple regression (SMR) then a model of 3D-HoVAIF descriptors and antitumor quinolone agents'activity was built with partial least square regression ( PLS). The obtained model with the cumulative multiple correlation coefficient (R²) , cumulative cross-validated (Q²) and the Root Mean Square Error of Estimation (RMSEE) were R²=0.912, Q_cum²=0.811, RMSEE=0.284 respectively. The result confirmed that 3D-HoVAIF is able to extract molecular steric potential information efficiently,and well to relate with the bioactivities.(2) And the developed descriptor, three dimensional holographic vector of atomic inter-action field(3D-HoVAIF), was also used to describe the chemical structures of 26 thienopyrimidones. After variable screening by stepwise multiple regression (SMR) technique, a partial least square (PLS) regression model was built with 3D-HoVAIF. The model is satisfactory comparing to reference since correlation coefficients of molecular modeling(R²), cross-validation(Q_cum²) and root-mean-square error of estimations(RMSEE) are≥0.891,≥0.85 and≤0.174, respectively, showing that the model has favorable estimation and prediction capabilities.(3) To study the relationships between the chemical structures of Thyroid receptors ligands with activities, the developed three-dimensional holographic vector of atomic interaction field (3D-HoVAIF) was used, 55 samples for the training set and 13 samples for the test set. After the structural characterization, the descriptors obtained were screened by stepwise multiple regression (SMR), correlation coefficients and crossvalidated correlation coefficients were obtained , R²=0.766,Q2=0.586, RMS=0.641 (TRα) and R²=0.754, Q²=0.593, RMS=0.672 (TRβ) respectively. These results show that the model have favorable stability and good prediction capability and the 3D-HoVAIF is applicable to the molecular structural characterization and biological activity prediction, suggesting that the models could be useful in the design of novel, more potent TR ligands.(4) To study the quantitative structure-activity relationship QSAR of 100 influenza neuraminidase inhibitors, three-dimensional holographicvector of atomic interaction field (3D-HoVAIF) method was used to describe the chemical structure of influenza neuraminidase inhibitors. After the structural characterization, the descriptors obtained were screened by least square regression ( PLS). The obtained model with the cumulative multiple correlation coefficient (R_cum² ) , cumulative cross-validated (Qcum2 ) , and standard error of estimation ( SD) were R_cum² = 0.805, Q_cum² = 0.657 and SD = 0.936, respectively. The result shows that the model has favorable stability and good prediction capability and predicted the literature 23 drugs as well as design of 32 compounds. The 3D-HoVAIF is applicable to the molecular structural characterization and biologicalactivity prediction.(5) Finally, using 3D-HoVAIF method, 11 series of the designed neuraminidase inhibitors were predicted , according to the active sites of influenza neuraminidase. Some of them may be higher activities than oseltamivir, an approved neuraminidase inhibitor recently. This designed compounds will be studied in the future in our laboratory.