Three-Component Liquid Parallel Combinatorial Synthesis And Quantitative Structure-Activity Relationship Studies

Combinatorial synthesis is one of combinatorial chemical techniques based on high efficient, fast and parallel synthetic methodology, which has less experimental steps, however, owe to all sorts of reactants, enormous compounds library can be gotten by one experimental trial. Therefore, combinatorial chemistry has a great superiority on synthetic biology and chemistry, especially in the study and development of novel drugs. A multiple-component reaction is a considerably useful tool for important instrumentality of module synthesis strategy in combinatorial synthesis; while higher target product can be obtained by a single reaction process than other chemical reaction. One can save time, labor, money, resource, and so on by using a multiple-component reaction skill, which is an important and perfect tool to search and find novel drugs.In this thesis, the research and application of multiple component reaction in modern combinatorial chemical is taken the mainline, the realization of general parallel solution combinatorial synthesis is explored in the three components reaction (3CR) preliminarily. Some aspects are discussed in details on Mannich reactions for organic syntheses and quantitative structure activity relationships (QSAR). Based on some good studies fulfilled on our laboratory, all chemometrics research in the paper are based on the two dimensional information of molecular structure, multiple linear regression (MLR) and stepwise multiple regression (SMR) are used to correlate the two dimension vector of molecules with their data. Beginning with the two dimensional structure of molecular, a quantitative structure-spectroscopy relationship (QSSR) method based on both novel atomic electronegativity interaction vector (AEIV) and atomic hybridation state index (AHSI) is developed for expression of local chemical microenvironment and atomic hybridation state. In the prediction to yields of compounds, novel molecular electronegativity interaction vector (MEIV) and heuristic method (HM) are applied and extended, respectively, most obtained models are favorable. The main contents are as follows:(1) General parallel solution combinatorial synthesis method is used to synthesize Mannich bases. Three components reaction Mannich condensation system is taken as the templet, a small amount of structurally similar target molecules, considered as a mini-size combinatorial compound library, were synthesized under almost coincident reaction conditions through varying the three substrates or reagents. The reaction is studied by classifying chain ketone, cycle ketone and aroma ketone, which is realized in the 95% ethanol medium. In this way, the combinatorial synthesis might be simulated. Meanwhile, the effect of reaction conditions, catalyst and reagent structure on the synthetic reaction were discussed in detail. About 50 new compounds were synthesized with yields from 13.25 to 80.48%, solid compounds are mensurated melting points, and some molecule structures of compounds are analysed by spectroscopy methods.(2) Quantitative structure-spectroscopy relationship (QSSR) research of 13C Nuclear Magnetic Resonance of aldehyde, ketone and amine. Beginning with the topologic indexes of two dimensional structure of molecular, which are bond length and electronegativity, a quantitative structure-spectroscopy relationship method based on both novel atomic electronegativity interaction vector (AEIV) and atomic hybridation state index (AHSI) is developed for expression of local chemical microenvironment and atomic hybridation state. By using these ways, we successfully model carton atoms 13C NMR chemical shift from aldehyde, amine and ketone. The correlation coefficient(R) values of QSSR model estimation with 6 variables based on multiple linear regression analysis (MLR) are 0.965, 0.981 and 0.949, the leave-one-out (LOO) cross-validation (CV) RCV are 0.830, 0.978, 0.944, respectively. Afterwards, these models are tested by 13C NMR chemical shifts of aldehyde, ketone and amine at random with the prediction correlation coefficients being 0.965, 0.982, 0.946, the leave-one-out cross-validation RCV are 0.835, 0.978, 0.927. The results show that the novel vector AEIV is an excellent structural index with satisfactory estimation stability and favorable generalization.(3) Prediction of yields of synthesis based on novel molecular electronegativity interaction vector (MEIV). Quantitative structure-produce relationship (QSPR) research are carried out for 2 different groups of Wittig and Mannich bases. Multiple linear regression analysis (MLR) is used to built model, and some variables are selected by stepwise multiple regression (SMR). A 7 variables which are selected by SMR model is obtained, The correlation coefficient(R) values of QSPR model estimation based on multiple linear regression analysis is 0.985, the leave-one-out cross-validation correlation coefficient(RCV) is 0.973. Besides, to test the prediction ability and the stability of the model, an exterior set is built at random, the prediction correlation coefficients being RMM=0.984 and RCV=0.965. The results show the QSPR model is favorable. The same way is used to predict produce of 67 Mannich bases, which model is made of 4 variables by SMR. The correlation coefficient(R) values is 0.578, RCV is 0.470, exterior set estimation results are R=0.565, RCV=0.428, the model is stability. Above discussions indicate MEIV method is a good way to predict produce of Wittig and Mannich bases ultimately, and the development of MEIV will be applied to predict produce of other compounds.(4) Prediction of yields of Mannich bases based on Heuristic method (HM). Heuristic method is a novel way to predict compounds yield, which is utilized to construct the line prediction model of Mannich bases, leading to a correlation coefficient R and cross-validation RCV of 0.735 and 0.520 by 10 variables model. 2 abnormal compounds are eliminated after analysis, new model results are: R=0.860, RCV=0.770. 2 exterior sets are constructed to test the prediction ability and stability.â‘ The exterior sets is used to test the model, datum of 42 compounds are obtained form references, 10 compounds which are from the above 42 compounds at random, are made of the test set, which R and RCV are 0.926, 0.820, and the results are favorable.â‘¡In the second predicted model, 5 Mannich bases are designed, then, which yields are predicted by the model constructed by 42 compounds above. afterwards, we synthesize them in the lab, and get experimented yields, which are compared with the predicted results. The results indicate the model are favorable, and has good prediction ability and stability. The results show that the novel heuristic method can be applied to predict the yields of compounds in the organic synthesis reaction, and HM is an excellent method with satisfactory estimation stability and favorable generalization.In the paper, molecular structure is described by 2D-QSAR skill, and the results of the models show that all ways are favorable to characterized molecular structure, which are used in the thesis. Predicting the yields of compounds provides a guide tool in the experiments of synthesis in reality.