典型抗結(jié)核病藥物的QSAR研究
發(fā)布時(shí)間：2018-08-23 09:35
【摘要】：結(jié)核病是由結(jié)核桿菌感染引起的慢性傳染病。解放后人民的生活水平不斷提高，結(jié)核病已基本控制，但是近年來隨著環(huán)境污染和艾滋病(HIV)的傳播以及藥物耐受，結(jié)核病發(fā)病率急劇增加。目前臨床上使用治療方案雖然可使85%以上的初治肺結(jié)核患者痊愈，但多存在不良反應(yīng)、藥物間相互作用、療程長(zhǎng)、對(duì)耐多藥結(jié)核病無效和對(duì)潛伏態(tài)的結(jié)核桿菌作用不強(qiáng)等缺點(diǎn)。因此，需要深入了解目前抗結(jié)核藥物的作用機(jī)制及耐藥機(jī)制，以指導(dǎo)研發(fā)對(duì)持留菌和耐藥菌更加有效的新型藥物，實(shí)現(xiàn)對(duì)結(jié)核病的有效治療與控制。 新藥的研發(fā)是一項(xiàng)周期長(zhǎng)，耗資大，技術(shù)要求高，風(fēng)險(xiǎn)大的系統(tǒng)工程。從定量構(gòu)效關(guān)系(QSAR)這一角度出發(fā)，首先從理論上預(yù)測(cè)其藥理活性，再用于臨床使用，有效地降低開發(fā)成本，并且能夠有目的的設(shè)計(jì)合成新藥。本文采用新型3D分子結(jié)構(gòu)描述子——三維全息原子場(chǎng)作用矢量(3D-HoVAIF)，在不借助任何實(shí)驗(yàn)手段及無需樣本構(gòu)想重疊的前提下建立了結(jié)核病藥物活性與其結(jié)構(gòu)的定量關(guān)系，，取得了相當(dāng)滿意的結(jié)果。為新型抗結(jié)核病藥物的研發(fā)提供了理論依據(jù)。 本文的研究?jī)?nèi)容有以下幾個(gè)方面： （1）采用3D-HoVAIF對(duì)25個(gè)香豆素-4乙酰芐肼類抗結(jié)核病藥物分子進(jìn)行結(jié)構(gòu)參數(shù)化表征，同時(shí)結(jié)合逐步回歸的方法對(duì)眾多變量進(jìn)行篩選，以得出相關(guān)性高的變量用于建立與其活性相關(guān)的QSAR模型。分別采用偏最小二乘回歸(PLS)和多元線性回歸(MLR)建模，為考慮模型穩(wěn)定性同時(shí)對(duì)訓(xùn)練集和測(cè)試集進(jìn)行雙重驗(yàn)證。PLS建模和MLR建模的復(fù)相關(guān)系數(shù)(R_(cum))、留一法交互校驗(yàn)復(fù)相關(guān)系數(shù)(Q_(LOO))以及外部樣本校驗(yàn)復(fù)相關(guān)系數(shù)(Q_(ext))分別為0.919、0.828、0.836和0.926、0.819、0.805。結(jié)果表明，3D-HoVAIF描述子能較好表征抗結(jié)核藥物分子結(jié)構(gòu)信息，為抗結(jié)核病藥物的研發(fā)提供一定的理論基礎(chǔ)。 （2）采用3D-HoVAIF對(duì)115個(gè)酰肼類抗結(jié)核病藥物分子進(jìn)行結(jié)構(gòu)參數(shù)化表征，同時(shí)結(jié)合逐步回歸的方法對(duì)眾多變量進(jìn)行篩選，以得出相關(guān)性高的變量用于建立與其活性相關(guān)的QSAR模型。分別采用PLS和MLR建模，為考慮模型穩(wěn)定性同時(shí)對(duì)訓(xùn)練集和測(cè)試集進(jìn)行雙重驗(yàn)證。PLS建模和MLR建模的三個(gè)相關(guān)系數(shù)R_(cum)~2、Q_(LOO)~2以及Q_(ext)~2分別為0.733、0.614、0.715和0.766、0.663、0.748。結(jié)果表明，3D-HoVAIF描述子能較好表征抗結(jié)核藥物分子結(jié)構(gòu)信息，所建QSAR模型具有良好穩(wěn)定性和預(yù)測(cè)能力。 （3）采用3D-HoVAIF對(duì)28個(gè)芳基酰胺類抗結(jié)核病藥物分子進(jìn)行結(jié)構(gòu)參數(shù)化表征。該體系進(jìn)行了三次訓(xùn)練集和測(cè)試集的劃分，同時(shí)結(jié)合逐步回歸的方法對(duì)眾多變量進(jìn)行篩選，以得出相關(guān)性高的變量用于建立與其活性相關(guān)的QSAR模型。三個(gè)體系均得到了良好的效果。 （4）用3D-HoVAIF對(duì)另一芳基酰胺類抗結(jié)核病藥物分子進(jìn)行結(jié)構(gòu)參數(shù)化表征，該體系有37個(gè)藥物分子。該體系進(jìn)行了兩次次訓(xùn)練集和測(cè)試集的劃分，同時(shí)結(jié)合逐步回歸的方法對(duì)眾多變量進(jìn)行篩選，以得出相關(guān)性高的變量用于建立與其活性相關(guān)的QSAR模型。分別采用PLS和MLR建模，為考慮模型穩(wěn)定性同時(shí)對(duì)訓(xùn)練集和測(cè)試集進(jìn)行雙重驗(yàn)證。結(jié)果表明，3D-HoVAIF描述子建立的模型取得了優(yōu)于文獻(xiàn)結(jié)果。該方法能較好地表征該類分子結(jié)構(gòu)信息，有物化意義明確及結(jié)果易于解釋等特點(diǎn)，值得進(jìn)一步推廣應(yīng)用。
[Abstract]:Tuberculosis is a chronic infectious disease caused by the infection of Mycobacterium tuberculosis. After liberation, people's living standards have been improved and tuberculosis has been basically controlled. However, in recent years, with the spread of environmental pollution, HIV and drug tolerance, the incidence of tuberculosis has increased dramatically. TB patients recover, but there are many disadvantages, such as adverse reactions, drug interactions, long course of treatment, ineffective against MDR-TB and weak effect on latent TB. Therefore, it is necessary to understand the mechanism of action and drug resistance of anti-TB drugs in depth, so as to guide the development of new drugs which are more effective against retaining bacteria and drug-resistant bacteria. To achieve effective treatment and control of tuberculosis.
The research and development of new drugs is a systematic engineering with long period, high cost, high technical requirement and high risk. From the perspective of quantitative structure-activity relationship (QSAR), the pharmacological activity of new drugs is predicted theoretically, and then used in clinic. The new drugs can be designed and synthesized effectively and purposefully. The relationship between the activity and structure of tuberculosis drugs has been established without any experimental means and overlapping of sample concepts. The satisfactory results have been obtained, which provide a theoretical basis for the development of new anti-tuberculosis drugs.
The research contents of this paper are as follows:
(1) Twenty-five coumarin-4-acetylbenzylhydrazine antituberculosis drugs were characterized by 3D-HoVAIF, and many variables were screened by stepwise regression method to obtain high correlation variables for establishing QSAR model related to their activities. Partial least squares regression (PLS) and multiple linear regression (MLR) were used respectively. MLR modeling, in order to consider the stability of the model, both the training set and the test set are validated. The complex correlation coefficients (R_ (cum)) of PLS modeling and MLR modeling, the interactive check complex correlation coefficients (Q_ (LOO)) and the external sample check complex correlation coefficients (Q_ (ext)) are 0.919, 0.828, 0.836 and 0.926, 0.819, 0.805, respectively. The narrator can better characterize the molecular structure information of anti-tuberculosis drugs and provide a theoretical basis for the research and development of anti-tuberculosis drugs.
(2) 115 hydrazide anti-tuberculosis drugs were characterized by 3D-HoVAIF, and many variables were selected by stepwise regression method to obtain high correlation variables for establishing QSAR model related to their activities. PLS and MLR were used to model the QSAR model respectively, and the training set and measurement were carried out simultaneously to consider the stability of the model. The three correlation coefficients R_ (cum) ~2, Q_ (LOO) ~2 and Q_ (ext) ~2 of PLS and MLR were 0.733, 0.614, 0.715 and 0.766, 0.663 and 0.748, respectively. The results showed that the 3D-HoVAIF descriptor could well characterize the molecular structure information of anti-tuberculosis drugs, and the QSAR model had good stability and predictive ability.
(3) Twenty-eight arylamide antituberculosis drugs were characterized by 3D-HoVAIF. The system was divided into three training sets and test sets, and many variables were selected by stepwise regression method to obtain high correlation variables for establishing QSAR model related to their activities. Good results have been achieved.
(4) Structural parameterization of another aryl amide antituberculosis drug molecule was carried out by 3D-HoVAIF. There were 37 drug molecules in the system. The system was divided into two training sets and test sets. At the same time, many variables were screened by stepwise regression method to obtain high correlation variables for the establishment of its active phase. The results show that the model established by 3D-HoVAIF descriptor is superior to the results of literature. The method can well characterize the molecular structure information of this kind, and has the characteristics of clear physical and chemical meaning and easy interpretation of the results. Further popularization and application.
【學(xué)位授予單位】：陜西科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：R52;R91
本文編號(hào)：2198646
[Abstract]:Tuberculosis is a chronic infectious disease caused by the infection of Mycobacterium tuberculosis. After liberation, people's living standards have been improved and tuberculosis has been basically controlled. However, in recent years, with the spread of environmental pollution, HIV and drug tolerance, the incidence of tuberculosis has increased dramatically. TB patients recover, but there are many disadvantages, such as adverse reactions, drug interactions, long course of treatment, ineffective against MDR-TB and weak effect on latent TB. Therefore, it is necessary to understand the mechanism of action and drug resistance of anti-TB drugs in depth, so as to guide the development of new drugs which are more effective against retaining bacteria and drug-resistant bacteria. To achieve effective treatment and control of tuberculosis.
The research and development of new drugs is a systematic engineering with long period, high cost, high technical requirement and high risk. From the perspective of quantitative structure-activity relationship (QSAR), the pharmacological activity of new drugs is predicted theoretically, and then used in clinic. The new drugs can be designed and synthesized effectively and purposefully. The relationship between the activity and structure of tuberculosis drugs has been established without any experimental means and overlapping of sample concepts. The satisfactory results have been obtained, which provide a theoretical basis for the development of new anti-tuberculosis drugs.
The research contents of this paper are as follows:
(1) Twenty-five coumarin-4-acetylbenzylhydrazine antituberculosis drugs were characterized by 3D-HoVAIF, and many variables were screened by stepwise regression method to obtain high correlation variables for establishing QSAR model related to their activities. Partial least squares regression (PLS) and multiple linear regression (MLR) were used respectively. MLR modeling, in order to consider the stability of the model, both the training set and the test set are validated. The complex correlation coefficients (R_ (cum)) of PLS modeling and MLR modeling, the interactive check complex correlation coefficients (Q_ (LOO)) and the external sample check complex correlation coefficients (Q_ (ext)) are 0.919, 0.828, 0.836 and 0.926, 0.819, 0.805, respectively. The narrator can better characterize the molecular structure information of anti-tuberculosis drugs and provide a theoretical basis for the research and development of anti-tuberculosis drugs.
(2) 115 hydrazide anti-tuberculosis drugs were characterized by 3D-HoVAIF, and many variables were selected by stepwise regression method to obtain high correlation variables for establishing QSAR model related to their activities. PLS and MLR were used to model the QSAR model respectively, and the training set and measurement were carried out simultaneously to consider the stability of the model. The three correlation coefficients R_ (cum) ~2, Q_ (LOO) ~2 and Q_ (ext) ~2 of PLS and MLR were 0.733, 0.614, 0.715 and 0.766, 0.663 and 0.748, respectively. The results showed that the 3D-HoVAIF descriptor could well characterize the molecular structure information of anti-tuberculosis drugs, and the QSAR model had good stability and predictive ability.
(3) Twenty-eight arylamide antituberculosis drugs were characterized by 3D-HoVAIF. The system was divided into three training sets and test sets, and many variables were selected by stepwise regression method to obtain high correlation variables for establishing QSAR model related to their activities. Good results have been achieved.
(4) Structural parameterization of another aryl amide antituberculosis drug molecule was carried out by 3D-HoVAIF. There were 37 drug molecules in the system. The system was divided into two training sets and test sets. At the same time, many variables were screened by stepwise regression method to obtain high correlation variables for the establishment of its active phase. The results show that the model established by 3D-HoVAIF descriptor is superior to the results of literature. The method can well characterize the molecular structure information of this kind, and has the characteristics of clear physical and chemical meaning and easy interpretation of the results. Further popularization and application.
【學(xué)位授予單位】：陜西科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：R52;R91
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