A Structure-activity Relationship （SAR） Study of Fluoroquinolones with Biological Activity against Anti-S.pneumoniae

1INTRODUCTION Streptococcus pneumoniae is a key pathogen in many respiratory tract infections.In a Canada-wide surveillance study published in1999,it was reported that21.2%of pneumococcal tested were interme-diately susceptible or resistant to penicillin.As the newer respiratory fluoroquinolones are active aga-inst both penicillin-susceptible and penicillin-resis-tant isolates of S.pneumoniae,they will be increa-singly important in the future treatment of infections caused by this pathoge…     

胆固醇酯转运蛋白抑制剂的3D-QSAR模型

利用VolSurf参数和比较分子场分析(CoMFA)方法对N,N-二取代三氟-3-氨基-2-丙醇衍生物类胆固醇酯转运蛋白抑制剂进行了三维定量构效关系(3D-QSAR)模型研究, 均得到较好的结果, 训练集模型具有良好的预测能力. VolSurf参数分析表明抑制活性高的分子必须具有合适的亲水性、多的氢键给体和少的氢键受体; 在一定范围内, 分子量大、表面光滑且非球性高的分子抑制活性高; 高疏水性以及质量中心与疏水区中心的高不平衡性对活性是不利因素. CoMFA结果表明, 立体作用对活性的影响较静电作用稍强, N-苯基取代基苯氧基的间位体积大且正电性强的基团对活性有利, N-苄基取代基的间位体积大且合适的电负性对活性有利, 而苄基的对位立体位阻的增加则对活性不利. VolSurf参数提供了分子整体性质信息, CoMFA提供了取代基信息, 两者互为补充, 对该类抑制剂新化合物的设计具有指导意义.     

3-氨磺酰苯甲酸类AKR1C3抑制剂的3D-QSAR和分子对接研究

醛酮还原酶1C3(AKR1C3)作为治疗前列腺癌的新靶点已成为研究热点,3-氨磺酰苯甲酸衍生物对其具有高效的选择性和抑制活性。本文采用比较分子场分析(COMFA)和比较分子相似性指数分析(COMSIA)方法,将经分子对接后的34个优势构象组成训练集和11个优势构象组成测试集,构建三维定量构效关系(3D-QSAR)模型。COMFA模型的交叉验证系数(q2),非交叉验证系数(R2),标准偏差(SEE)和F值分别为0.761,0.973,0.122,185.963;自举法回归系数为R2bs=0.98。最佳组合COMSIA模型的q2,R2,SEE,F和R2bs分别为0.734,0.984,0.097,147.850,0.994。COMFA和COMSIA模型的系统外部测试R2pred分别为0.864和0.756,r2m分别为0.8127和0.5377。这些结果表明,所建立的QSAR模型具有较高的可靠性和较强预测能力。经三维等势图分析可知,在2、5或6位适当增加取代基体积,或在5位引入氢键受体,或在7位引入负电性取代基则能提高化合物的生物活性。该模型为进一步设计具有更优选择性和活性的化合物提供了理论依据。     

A study on the antipicornavirus activity of flavonoid compounds (flavones) by using quantum chemical and chemometric methods

The AM1 semiempirical method is employed to calculate a set of molecular properties (variables) of 45 flavone compounds with antipicornavirus activity, and 9 new flavone molecules are used for an activity prediction study. Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA), Stepwise Discriminant Analysis (SDA), and K-Nearest Neighbor (KNN) are employed in order to reduce dimensionality and investigate which subset of variables should be more effective for classifying the flavone compounds according to their degree of antipicornavirus activity. The PCA, HCA, SDA, and KNN methods showed that the variables MR (molar refractivity), B(9) (bond order between C(9) and C(10) atoms), and B(25) (bond order between C(11) and R(7) atoms) are important properties for the separation between active and inactive flavone compounds, and this fact reveals that electronic and steric effects are relevant when one is trying to understand the interaction between flavone compounds with antipicornavirus activity and the biological receptor. In the activity prediction study, using the PCA, HCA, SDA, and KNN methodologies, three of the 9 new flavone compounds studied were classified as potentially active against picornaviruses.     

Application of PCA and HCA to the Structure-activity Relationship （SAR） Study of Fluoroquinolones

1 INTRODUCTION The earliest antibacterial agents used as chemo- therapeutic drugs in the 1920s were synthetic agents, such as sulponamides. Since the discovery of peni- cillin and its entry into clinical use in the 1940s, the field has been dominated over the past 50 years by natural products or their semi-synthetic derivatives. The fluoroquinolones are the only synthetic anti- bacterial agents to rival β-lactams for impact in clinical usage in the antibacterial field. In recent years, …