Quantitative Structure-Activity Ranationship And Molecular Design Of Neuraminidase Inhibitors

The negligence of the drug, which used on influenza, caused a global shortage of it. There are only two kinds of major drugs of influenza on the market. At the same time, the fear of avian flu has led to the governments to take corresponding measures of drug storage with a result of the demand of influenza's drug became more and more intense. However, it also has brought about a positive outcome with the research of influenza's drug started to resuscitate. Since the 1983, when the crystal structures of influenza virus neuraminidase and it with its natural substrate of sialic acid have been determined, researches of neuraminidase inhibitors particular its sialic acid analogues for influenza virus has been obtained great progress. Understaning of the crystal structure allows people to do the research of molecular simulations and then to design inhibitors with high efficiency and selectivity. If through further structural optimization increased. Activity is expected to as a new class of highly effective anti-influenza virus drugs. And quantitative structure activity relationship study is an important method of designing drug, so, construction of these compounds between the molecular structure and biological activity quantitative correlation has important significance to design and development of high efficiency anti-influenza drug.In this paper, based on the neuraminidase inhibitors of the mechanism, sum up the results of research on their predecessors, both 2-D QSAR and 3-D-QSAR technology are used to design a new compounds which may have anti-viral activity for biological activity screening. The work carried out mainly in the following aspects.â‘ The molecular electronegativity-distance vector are used to 123 kinds of neuraminidase inhibitors, 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 model with the regression coefficient (R) of 0.705 and the standard deviation (SD) of 3.136 could be achieved. Then the model was evaluated by performing the cross validation with the leave-one-out (LOO) procedure and the results with correlation coefficient(R²_CV) of 0.457and standard deviation (SDCV) of 1.308 could be obtained.The results show that MEDV can not be used to well express the structures of these organic compounds. Because the complexity of the structure which senior become apparent. On the nature of the molecule does not depend on the elements but also within the power of the atomic size and the distance between each other, including atomic seen from space, the space between each other, and so on. So MEDV is no longer able to accurately describe the elements. The results are not very satisfactory. The MEDV is not applicable to characterizing of the structure of neuraminidase inhibitors.â‘¡In the model of MEDV discussed above, the results obtained in both the predictive ability and evaluate the predictive abilities are not very satisfactory. And anther molecular descriptor called the MEIV was used to describe the structures of 123 kinds of neuraminidase inhibitors, and the anther QSAR model of three variables could be obtained.Modeling results are R = 0.715, SD = 1.308, R²_CV = 0.475, SDCV = 1.286.The method used in this 123 kinds of neuraminidase inhibitors MEIV description of the model calculation results, The results show that MEIV is also unsatisfactory.And the ability to estimate and forecast capacity are not very satisfactory. From the above we can see the results of cross-examination (R²_CV) has increased from 0.457 to 0.475, SDCV fell to 1.286 from 1.308, R has increased from 0.705 to 0.715, SD fell to 1.293 from 1.298, but to the overall results that is not very satisfactory. MEIV descriptors so that the same as MEDV is not applicable to characterizaing of the structures of the neuraminidase inhibitors. So, there are some shortcomings with 2D-QSAR technique.â‘¢Because the results of modles of MEDV and MEIV were not very good, so a nother method based on three non-bonded (electrostatic, van der waals and hydrophobic) factors, directly related to bio-activities, called three dimensional holographic vector of atomic interaction field (3D-HoVAIF) was proposed to study the QSAR model of 123 compounds of neuraminidase inhibitors too. The descriptors were selected by stepwise multiple regression (SMR). The model have been constructed by using multiple linear regression technique.The model with the regression coefficient (R) of 0.885 and the standard deviation (SD) of 0.848 could be achieved. Then the model was evaluated by performing the cross validation with the leave-one-out (LOO) procedure and the results with correlation coefficient(R²_CV) of 0.736 and standard deviation (SDCV) of 0.935 could be obtained Obviously, the statistical results indicated that 3D-HoVAIF descriptors were proved to be potent in characterizing neuraminidase inhibitor activity. And the model has a good ability to estimate the internal and external predictive ability.The applicable fields of 3-D HoVAIF are extended. 3-D HoVAIF has been related to neuraminidase inhibitors which divided into two parts, namely, training set and test set for the 100 and 23 samples. And the quantitative relationship models have been constructed by using multiple linear regression and partial least squares technique build. Results:The correlation coefficient (R), cross-validation of the correlation coefficient (Q2) and the standard deviation model for R² = 0.805, Q² = 0.657, SD = 0.936, respectively. The model has a good stability and predictability, The 23 drugs in the literature and design 10 series compounds were predicted. That three-dimensional holographic atomic field vector can better characterizing of the molecular structure , It should be further popularized.â‘£Based on the study of quantitive structure-activity relationship of 2D( MEDV and MEIV) and 3D (3D-HoVAIF) on neuraminidase inhibitors, and then according to the active spot of NA, linking activity of NAI and the reference of reported result, we focus on transformation of neuraminidase inhibitors (NAI) particularly their mother central have been listed of the structures. We designed 10 series of new compounds, and their activity was predicted. From the results, we found some of the compounds with high value of activity. These compounds may become the synthetic object of the next step. It may provide useful refrence for new development of neuraminidase inhibitors.