Binary azeotropes, which contain two chemicals with a relative volatility of 1, are very common in the chemical industry. Understanding azeotropes is essential for effectively separating binary azeotropes containing l...Binary azeotropes, which contain two chemicals with a relative volatility of 1, are very common in the chemical industry. Understanding azeotropes is essential for effectively separating binary azeotropes containing lower alcohols. Experimental techniques and ab initio approaches can produce accurate results;however, these two processes are time consuming and labor intensive. Although thermodynamic equations such as UNIFAC are widely used, experimental values are required, and it is difficult to choose the best groups to represent a complex system. Because of their high efficiency and fast calculation speed, quantitative structure–property relationship(QSPR) tools were used in this work to predict the azeotropic temperatures and compositions of binary azeotropes containing lower alcohols. The QSPR models for 64 binary azeotropes based on centroid approximation and weighted-contribution-factor approximation were established using the genetic function approximation(GFA) procedure in Materials Studio software, and a leave-one-out cross-validation procedure was conducted.External tests of an additional 16 azeotropes were also investigated, and high determination coefficient values were obtained. The best QSPR models were explained in terms of the molecular structure of the azeotropes,and good predictive ability was obtained within acceptable prediction error levels.展开更多
HIV-1整合酶(integrase,IN)是病毒复制过程的关键酶,已被证实是开发抗HIV-1药物的一个理想靶标。针对48个喹诺酮酸类整合酶链转移抑制剂(integrasestrandtransfer inhibitors, INSTIs),利用遗传函数逼近法(genetic function approximati...HIV-1整合酶(integrase,IN)是病毒复制过程的关键酶,已被证实是开发抗HIV-1药物的一个理想靶标。针对48个喹诺酮酸类整合酶链转移抑制剂(integrasestrandtransfer inhibitors, INSTIs),利用遗传函数逼近法(genetic function approximation, GFA)构建10个抑制活性与优选的分子结构描述符之间的二维定量构效关系(2D-QSAR)模型,从中优选出最佳的模型并对其进行验证,据此探究影响抑制剂生物活性的主要分子微观结构因素,希冀为其进一步结构优化提供理论指导。所建立的最优2D-QSAR模型的非交叉验证相关系数R^2为0.8903,交叉验证相关系数Q^2为0.8213,表明该模型具有较高的预测能力和明显的统计学意义。该研究表明,喹诺酮酸类INSTIs的生物活性主要受Jurs_RPCG、Shadow_nu、BIC、ALogP、Dipole_X以及Dipole_Y描述符的影响,为其进一步结构修饰,开发高效抗HIV-1药物奠定了理论基础。展开更多
Quantitative structure activity relationship （QSAR） studies were performed on 45 anthranilic acid derivatives for their potent allosteric inhibition activities of HCV NSSB polymerase. Genetic algorithm based genetic...Quantitative structure activity relationship （QSAR） studies were performed on 45 anthranilic acid derivatives for their potent allosteric inhibition activities of HCV NSSB polymerase. Genetic algorithm based genetic function approximation （GFA） method of variable selection was used to generate the model. Highly statistically significant model with r^2 = 0.966 and r^2cv = 0.951 was obtained when the number of descriptors in the equation was set to 5. High r^2pred value of 0.884 indicates the good predictive power of the best model. Spatial descriptors of radius of gyration （RadOfGration）, molecular volume （Vm）, length of molecule in the z dimension （Shadow-Zlength）, thermodynamic descriptors of the octanol/water partition coefficient （LogP） and molecular refractivity index （MR） showed enormous contributions to HCV NS5B polymerase inhibition. The validation of the model was done by leave-one-out （LOO） test, randomization tests and external test set prediction. The model gives insight on indispensable structural requirements for the activity and can be used to design more potent analogs against HCV NSSB polymerase.展开更多
The extensive utilization of the low-energy dipeptide sweetener aspartame in foods leads to various studies on searching for new sweeteners in series. However, the real mechanistic cause of their sweetness power is st...The extensive utilization of the low-energy dipeptide sweetener aspartame in foods leads to various studies on searching for new sweeteners in series. However, the real mechanistic cause of their sweetness power is still not completely known owing to their complex interactions with human sweet receptor, which may be different from that of other sweeteners to some extent. In this contribution, predictive quantitative structure-property relationship(QSPR) models have been developed for diverse aspartame analogues using Materials Studio 5.0 software. The optimal QSPR model(r2 = 0.913, r2 CV = 0.881 and r2 pred = 0.730) constructed by the genetic function approximation method has been validated by the tests of cross validation, randomization, external prediction and other statistical criteria, which shows that their sweetness power is mainly governed by their electrotopological-state indices(SssCH and SsNH), spatial descriptors(Shadow length: LX, ellipsoidal volume and Connolly surface occupied volume) and topological descriptors(Chi(3): cluster and Chi(0)(valence modified)), which partially supports both multipoint attachment theory proposed by Nofre and Tinti et al. and B-X theory proposed by Kier et al.. Present exploited results provide the key structural features for the sweetness power of aspartame analogues, supplement the mechanistic understanding of the sweet perception, and would be also helpful for the design of potent sweetener analogs prior to their synthesis.展开更多
目的:探究影响人类免疫缺陷病毒Ⅰ型(human immunodeficiency virus type 1,HIV-1)非核苷类逆转录酶抑制剂6-苄基-1-乙氧甲基-5-异丙基尿嘧啶[6-benzyl-1-(ethoxymethyl)-5-isopropyluracil,MKC-442]及其类似物抗病毒活性的主要分子微...目的:探究影响人类免疫缺陷病毒Ⅰ型(human immunodeficiency virus type 1,HIV-1)非核苷类逆转录酶抑制剂6-苄基-1-乙氧甲基-5-异丙基尿嘧啶[6-benzyl-1-(ethoxymethyl)-5-isopropyluracil,MKC-442]及其类似物抗病毒活性的主要分子微观结构因素。方法:针对45个MKC-442及其类似物,利用遗传函数逼近法(genetic function approximation,GFA)构建10个抗HIV-1活性与优选的分子结构描述符之间的二维定量构效关系(2-dimensional quantitative structure-activity relationship,2D-QSAR)模型,从中挑选出最优模型并对其进行验证,据此阐明影响MKC-442及其类似物抗HIV-1活性的主要微观结构因素。结果:最优2D-QSAR模型的非交叉验证相关系数r2为0.7845,交叉验证相关系数q2为0.6958,预测验证相关系数r2pred为0.8415,表明其具有较高的预测能力和稳定性。结论:研究表明,MKC-442及其类似物抗HIV-1活性主要与描述符JursFNSA2,ShadowYZ,DipoleX,Kappa3AM和CHIV3P相关,为MKC-442及其类似物的进一步结构修饰打下了一定的理论基础。展开更多
评述了4种炸药感度判据,包括最易跃迁法(最小能隙)、最小键级、最弱键离解能、X—NO2(XC,N or O)中硝基的Mulliken电荷。首次提出了基于炸药分子整体稳定性的名为"键&非键耦合分子刚柔度"的新的感度判据。比较了11种典...评述了4种炸药感度判据,包括最易跃迁法(最小能隙)、最小键级、最弱键离解能、X—NO2(XC,N or O)中硝基的Mulliken电荷。首次提出了基于炸药分子整体稳定性的名为"键&非键耦合分子刚柔度"的新的感度判据。比较了11种典型炸药[1,3,5-三硝基苯(TNB)、2,4,6-三硝基甲苯(TNT)、1,3,3-三硝基氮杂环丁烷(TNAZ)、1,3,5-三硝基-1,3,5-三氮杂环己烷(RDX)、1,3,5-三硝基-2-氧-1,3,5-三氮杂环己烷(K6)、2,4,6,8,10,12-六硝基-2,4,6,8,10,12-六氮杂异伍兹烷(CL-20)、2-苦基-1,2,3-三唑(P CTA)、4-硝基-2-苦基-1,2,3-三唑(NPCTA)、2,6-二氨基-3,5-二硝基吡啶-1-氧化物(LLM-105)、4,6-二硝基苯并氧化呋咱(DNBF)、5,7-二氨基-4,6-二硝基苯并氧化呋咱(DADNBF)]的撞击感度与判据之间的相关性。结果表明,在这5种感度判据中,"键!非键耦合分子刚柔度"评价方法的相关性最高。判据组合能提高预测感度的能力。张力能是炸药分子中键!非键耦合能的一种形式,它不仅能够用于衡量炸药的感度,尤其是不含硝基炸药的感度,同时还能用来量度炸药的储能水平,这对新型炸药的设计和评价具有重要意义。展开更多
A series of pyrazoline-based new heterocycles have recently been synthesized from our group where some of the compounds display potent anti-tubercular activity against Mycobacterium tuberculosis H37Rv. In order to fur...A series of pyrazoline-based new heterocycles have recently been synthesized from our group where some of the compounds display potent anti-tubercular activity against Mycobacterium tuberculosis H37Rv. In order to further explore the potency of the compounds, quantitative structure activity relationship study is carried out using genetic function approximation. Statistically significant (r2 = 0.85) and predictive (r2pred=0.89 and r2m=0.74)?QSAR models are developed. It is evident from the QSAR study that majority of the anti-tubercular activity is found to be driven by lipophilicity. Also, molecular solubility, Jurs and shadow descriptors influence the biological activity significantly. Also, positive contribution of molecular shadow descriptors suggests that molecules with bulkier substituents are more likely to enhance anti-tubercular activity. Since the developed QSAR models are found to be statistically significant and predictive, they potentially can be applied for predicting anti-tubercular activity of new molecules for prioritization of molecules for synthesis.展开更多
应用Materials Studio4.2计算38个含氮化合物的结构参数,对其碱性做QSAR研究。使用遗传函数算法(genetic function approximation,GFA),从前线分子轨道能量、偶极矩、部分电荷、分子表面积、分子体积等30个反映分子微观特征和溶剂化效...应用Materials Studio4.2计算38个含氮化合物的结构参数,对其碱性做QSAR研究。使用遗传函数算法(genetic function approximation,GFA),从前线分子轨道能量、偶极矩、部分电荷、分子表面积、分子体积等30个反映分子微观特征和溶剂化效应的结构参数中,筛选出主要的结构参数,建立出含氮化合物碱性-结构参数定量关系方程。所建方程的关联系数r^2=0.951,交叉相关系数CV-r^2=0.930,并且应用方程估算测试样本的碱性,其预测值与实验值基本一致,表明建立的QSAR方程具有较好的拟合度和较强的预测能力。分析QSAR方程各参数对含氮化合碱性影响表明,分子的最高占据轨道能量(HOMO)、偶极矩、氮原子上的电荷以及表示溶剂化效应的参数,是影响碱性的主要结构因素。HOMO能量反映分子供电子能力,能量越高,越易供给电子,碱性越强。分子偶极矩越大、氮原子上的负电荷越多,都使碱性增强。方程中引入电介质能量,说明溶剂化效应对含氮化合物碱性有一定的影响;电介质能量越大,溶质一溶剂的相互作用可能降低溶质分子的稳定性,使含氮化合物的碱性增强。展开更多
基金Supported by the National Natural Science Foundation of China(21776145,21676152)Key Research Project of Shandong Province(2016GSF116004)
文摘Binary azeotropes, which contain two chemicals with a relative volatility of 1, are very common in the chemical industry. Understanding azeotropes is essential for effectively separating binary azeotropes containing lower alcohols. Experimental techniques and ab initio approaches can produce accurate results;however, these two processes are time consuming and labor intensive. Although thermodynamic equations such as UNIFAC are widely used, experimental values are required, and it is difficult to choose the best groups to represent a complex system. Because of their high efficiency and fast calculation speed, quantitative structure–property relationship(QSPR) tools were used in this work to predict the azeotropic temperatures and compositions of binary azeotropes containing lower alcohols. The QSPR models for 64 binary azeotropes based on centroid approximation and weighted-contribution-factor approximation were established using the genetic function approximation(GFA) procedure in Materials Studio software, and a leave-one-out cross-validation procedure was conducted.External tests of an additional 16 azeotropes were also investigated, and high determination coefficient values were obtained. The best QSPR models were explained in terms of the molecular structure of the azeotropes,and good predictive ability was obtained within acceptable prediction error levels.
基金supported by the National Natural Science Foundation of China (No. 30500339)Natural Science Foundation of Zhejiang Province (NO.Y407308)the Sprout Talented Project Program of Zhejiang Province (No. 2008R40G2020019)
文摘Quantitative structure activity relationship （QSAR） studies were performed on 45 anthranilic acid derivatives for their potent allosteric inhibition activities of HCV NSSB polymerase. Genetic algorithm based genetic function approximation （GFA） method of variable selection was used to generate the model. Highly statistically significant model with r^2 = 0.966 and r^2cv = 0.951 was obtained when the number of descriptors in the equation was set to 5. High r^2pred value of 0.884 indicates the good predictive power of the best model. Spatial descriptors of radius of gyration （RadOfGration）, molecular volume （Vm）, length of molecule in the z dimension （Shadow-Zlength）, thermodynamic descriptors of the octanol/water partition coefficient （LogP） and molecular refractivity index （MR） showed enormous contributions to HCV NS5B polymerase inhibition. The validation of the model was done by leave-one-out （LOO） test, randomization tests and external test set prediction. The model gives insight on indispensable structural requirements for the activity and can be used to design more potent analogs against HCV NSSB polymerase.
基金Supported by the National Natural Science Foundation of China(No.21673207)Special Fundamental Research Fund for the Central Public Scientific Research Institutes(No.562018Y-5983)Zhejiang Provincial Collaborative Innovation Center of Food Safety and Nutrition(No.2017SICR115,2017SICR101)
文摘The extensive utilization of the low-energy dipeptide sweetener aspartame in foods leads to various studies on searching for new sweeteners in series. However, the real mechanistic cause of their sweetness power is still not completely known owing to their complex interactions with human sweet receptor, which may be different from that of other sweeteners to some extent. In this contribution, predictive quantitative structure-property relationship(QSPR) models have been developed for diverse aspartame analogues using Materials Studio 5.0 software. The optimal QSPR model(r2 = 0.913, r2 CV = 0.881 and r2 pred = 0.730) constructed by the genetic function approximation method has been validated by the tests of cross validation, randomization, external prediction and other statistical criteria, which shows that their sweetness power is mainly governed by their electrotopological-state indices(SssCH and SsNH), spatial descriptors(Shadow length: LX, ellipsoidal volume and Connolly surface occupied volume) and topological descriptors(Chi(3): cluster and Chi(0)(valence modified)), which partially supports both multipoint attachment theory proposed by Nofre and Tinti et al. and B-X theory proposed by Kier et al.. Present exploited results provide the key structural features for the sweetness power of aspartame analogues, supplement the mechanistic understanding of the sweet perception, and would be also helpful for the design of potent sweetener analogs prior to their synthesis.
文摘目的:探究影响人类免疫缺陷病毒Ⅰ型(human immunodeficiency virus type 1,HIV-1)非核苷类逆转录酶抑制剂6-苄基-1-乙氧甲基-5-异丙基尿嘧啶[6-benzyl-1-(ethoxymethyl)-5-isopropyluracil,MKC-442]及其类似物抗病毒活性的主要分子微观结构因素。方法:针对45个MKC-442及其类似物,利用遗传函数逼近法(genetic function approximation,GFA)构建10个抗HIV-1活性与优选的分子结构描述符之间的二维定量构效关系(2-dimensional quantitative structure-activity relationship,2D-QSAR)模型,从中挑选出最优模型并对其进行验证,据此阐明影响MKC-442及其类似物抗HIV-1活性的主要微观结构因素。结果:最优2D-QSAR模型的非交叉验证相关系数r2为0.7845,交叉验证相关系数q2为0.6958,预测验证相关系数r2pred为0.8415,表明其具有较高的预测能力和稳定性。结论:研究表明,MKC-442及其类似物抗HIV-1活性主要与描述符JursFNSA2,ShadowYZ,DipoleX,Kappa3AM和CHIV3P相关,为MKC-442及其类似物的进一步结构修饰打下了一定的理论基础。
文摘评述了4种炸药感度判据,包括最易跃迁法(最小能隙)、最小键级、最弱键离解能、X—NO2(XC,N or O)中硝基的Mulliken电荷。首次提出了基于炸药分子整体稳定性的名为"键&非键耦合分子刚柔度"的新的感度判据。比较了11种典型炸药[1,3,5-三硝基苯(TNB)、2,4,6-三硝基甲苯(TNT)、1,3,3-三硝基氮杂环丁烷(TNAZ)、1,3,5-三硝基-1,3,5-三氮杂环己烷(RDX)、1,3,5-三硝基-2-氧-1,3,5-三氮杂环己烷(K6)、2,4,6,8,10,12-六硝基-2,4,6,8,10,12-六氮杂异伍兹烷(CL-20)、2-苦基-1,2,3-三唑(P CTA)、4-硝基-2-苦基-1,2,3-三唑(NPCTA)、2,6-二氨基-3,5-二硝基吡啶-1-氧化物(LLM-105)、4,6-二硝基苯并氧化呋咱(DNBF)、5,7-二氨基-4,6-二硝基苯并氧化呋咱(DADNBF)]的撞击感度与判据之间的相关性。结果表明,在这5种感度判据中,"键!非键耦合分子刚柔度"评价方法的相关性最高。判据组合能提高预测感度的能力。张力能是炸药分子中键!非键耦合能的一种形式,它不仅能够用于衡量炸药的感度,尤其是不含硝基炸药的感度,同时还能用来量度炸药的储能水平,这对新型炸药的设计和评价具有重要意义。
文摘A series of pyrazoline-based new heterocycles have recently been synthesized from our group where some of the compounds display potent anti-tubercular activity against Mycobacterium tuberculosis H37Rv. In order to further explore the potency of the compounds, quantitative structure activity relationship study is carried out using genetic function approximation. Statistically significant (r2 = 0.85) and predictive (r2pred=0.89 and r2m=0.74)?QSAR models are developed. It is evident from the QSAR study that majority of the anti-tubercular activity is found to be driven by lipophilicity. Also, molecular solubility, Jurs and shadow descriptors influence the biological activity significantly. Also, positive contribution of molecular shadow descriptors suggests that molecules with bulkier substituents are more likely to enhance anti-tubercular activity. Since the developed QSAR models are found to be statistically significant and predictive, they potentially can be applied for predicting anti-tubercular activity of new molecules for prioritization of molecules for synthesis.
文摘应用Materials Studio4.2计算38个含氮化合物的结构参数,对其碱性做QSAR研究。使用遗传函数算法(genetic function approximation,GFA),从前线分子轨道能量、偶极矩、部分电荷、分子表面积、分子体积等30个反映分子微观特征和溶剂化效应的结构参数中,筛选出主要的结构参数,建立出含氮化合物碱性-结构参数定量关系方程。所建方程的关联系数r^2=0.951,交叉相关系数CV-r^2=0.930,并且应用方程估算测试样本的碱性,其预测值与实验值基本一致,表明建立的QSAR方程具有较好的拟合度和较强的预测能力。分析QSAR方程各参数对含氮化合碱性影响表明,分子的最高占据轨道能量(HOMO)、偶极矩、氮原子上的电荷以及表示溶剂化效应的参数,是影响碱性的主要结构因素。HOMO能量反映分子供电子能力,能量越高,越易供给电子,碱性越强。分子偶极矩越大、氮原子上的负电荷越多,都使碱性增强。方程中引入电介质能量,说明溶剂化效应对含氮化合物碱性有一定的影响;电介质能量越大,溶质一溶剂的相互作用可能降低溶质分子的稳定性,使含氮化合物的碱性增强。
