新磺酰脲类化合物除草活性的3D-QSAR分析

用比较分子力场分析 (CoMFA) 方法和比较分子相似性指数分析 (CoMSIA) 方法对所合成的新磺酰脲类化合物的除草活性进行了较为系统的3D-QSAR分析.两种方法所建立的模型对化合物的除草活性预测能力均较好,所得三维等值线图为合成高活性的化合物能提供指导作用     

Enantioselectivity of epoxide hydrolase catalysed oxirane ring opening: a 3D QSAR study

A 3D QSAR analysis (quantitative structure activity relationships) of a set of 2,2-disubstituted epoxides, substrates for epoxide hydrolases originating from four different organisms, was conducted by CoMFA (comparative molecular field analysis) and CoMSIA (comparative molecular similarity indices analysis), with respect to the enantioselective ring opening to the corresponding vicinal diol. Structural variations of the substrates include alkyl chains of different lengths, unsaturated moieties ((E)- and (Z)-alkenyl, alkinyl, aryl) and electronegative groups (ether oxygens, halogen atoms) at different locations within the 2-substituent group. Generally, all four organisms, namely Rhodococcus ruber NCIMB 11216, Rhodococcus ruber DSM 43338, Rhodococcus ruber DSM 44540 and Rhodococcus ruber DSM 44539, preferentially react with the (S)-enantiomer of the epoxide. Enantioselectivities (enantiomeric ratio, lnE values) show a rather large variation, ranging from almost no (lnE<1) to nearly complete selectivity (lnE>5.3). In addition, the response of the epoxide hydrolases stemming from the four organisms towards structural modifications of the substrate is different. Models for the enantioselectivity (enantiomeric ratio, ln E values) obtained by CoMFA and CoMSIA are of different but reasonable predictive power, e.g., q² _CV=0.701 and r²=0.937 for the CoMFA model of Rhodococcus ruber DSM 43338. Enantiomeric ratios for the test molecules can be well predicted. Plots of steric and electrostatic CoMFA (CoMSIA) fields allow conclusions to be drawn for the choice of the most suitable organism for a specific type of substrate.     

促生长激素释放素三维定量构效关系及药效团模型

用比较分子场分析方法对促生长激素释放素Ｌ－６９２，４２９的系列物进行了三维定量构效研究，得到具有较强预测能力的模型并确定了母体的活性构象，用距离比较方法将Ｌ－６９２，４２９的活性构象与两个活性多肽进行了迭合，找到了可能的药效团，药效团模型显示Ｌ－６９２，４２９的氨基和四唑是氢键的给体和受体，而Ａ和Ｃ环是主要的疏水核心。     

CoMFA-based comparison of two models of binding site on adenosine A1 receptor

A set of 32 N6-substituted adenosines and 22 8-substituted xanthines with affinity for adenosine A1 receptors was subjected to three-dimensional quantitative structure-affinity relationship analysis using comparative molecular field analysis (CoMFA). The aim was to compare two modes of binding to the receptor – `N6-C8' and `N6-N7'. Good models with high predictive power and stability were obtained. A comparison of these models gives the following results: (a) Inclusion of both steric and electrostatic fields in CoMFA generates better predictive models compared to models based on steric or electrostatic fields alone. (b) The `N6-N7' CoMFA models are slightly better than the `N6-C8' ones. (c) Steric restriction exists around the N6-H in the `N6-N7' steric field map, which is absent in the `N6-C8' steric field map. This report demonstrates that the `N6-N7' mode of binding is a further development of the `N6-C8' model with a slightly better predictive ability and more accurate steric and electrostatic overlaps between agonists and antagonists.     

Development of biologically active compounds by combining 3D QSAR and structure-based design methods

One of the major challenges in computational approaches to drug design is the accurate prediction of the binding affinity of novel biomolecules. In the present study an automated procedure which combines docking and 3D-QSAR methods was applied to several drug targets. The developed receptor-based 3D-QSAR methodology was tested on several sets of ligands for which the three-dimensional structure of the target protein has been solved – namely estrogen receptor, acetylcholine esterase and protein-tyrosine-phosphatase 1B. The molecular alignments of the studied ligands were determined using the docking program AutoDock and were compared with the X-ray structures of the corresponding protein-ligand complexes. The automatically generated protein-based ligand alignment obtained was subsequently taken as basis for a comparative field analysis applying the GRID/GOLPE approach. Using GRID interaction fields and applying variable selection procedures, highly predictive models were obtained. It is expected that concepts from receptor-based 3D QSAR will be valuable tools for the analysis of high-throughput screening as well as virtual screening data     

A CoMFA analysis with conformational propensity: An attempt to analyze the SAR of a set of molecules with different conformational flexibility using a 3D-QSAR method

CoMFA analysis, a widely used 3D-QSAR method, has limitations to handle a set of SAR data containing diverse conformational flexibility since it does not explicitly include the conformational entropic effects into the analysis. Here, we present an attempt to incorporate the conformational entropy effects of a molecule into a 3D-QSAR analysis. Our attempt is based on the assumption that the conformational entropic loss of a ligand upon making a ligand-receptor complex is small if the ligand in an unbound state has a conformational propensity to adopt an active conformation in a complex state. For a QSAR analysis, this assumption was interpreted as follows: a potent ligand should have a higher conformational propensity to adopt an `active-conformation'-like structure in an unbound state than an inactive one. The conformational propensity value was defined as the populational ratio, N<sub>active</sub>/N<sub>stable</sub>, of the number of energetically stable conformers, N<sub>stable</sub>, to the number of `active-conformation'-like structures, N_active. The latter number was calculated by counting the number of conformers that satisfied the structural parameters deduced from the active conformation. A set of SAR data of imidazoleglycerol phosphate dehydratase inhibitors containing 20 molecules with different conformational flexibility was used as a training set for developing a 3D structure-activity relationship by a CoMFA analysis with the conformational propensity value. This resulted in a cross-validated squared correlation coefficient of the CoMFA model with the conformational propensity value (R ² _cross = 0.640) higher than that of the standard CoMFA model (R ² _cross = 0.431). Then we evaluated the quality of the CoMFA models by predicting the inhibitory activity for a new molecule.     

Evaluation of proposed modes of binding of (2S)-2-[4-[[(3S)-1-acetimidoyl-3-pyrrolidinyl]oxy]phenyl]-3-(7-amidino-2-naphthyl)propanoic acid hydrochloride and some analogs to Factor Xa using a comparative molecular field analysis

The binding mode of (2S)-2-[4-[[(3S)-1-acetimidoyl-3-pyrrolidinyl]oxy]phenyl]-3-(7-amidino-2-naphthyl)propanoic acid hydrochloride (DX-9065a, 4) to Factor Xa is examined using inhibition data for a series of analogs that have a hydrophobic group as well as basic or dibasic functionality. Comparative molecular field analysis is utilized on a series of DX-9065a analogs in a series of proposed alternative binding modes. A quantitative measure is provided that distinguishes between the proposed binding modes that describes how well the binding mode explains the structure-activity relationship or the best 3D QSAR agrees with the crystallographically determined binding mode. The best model is in agreement with recently available data [Brandstetter et al., J. Biol. Chem., 271 (1996) 29988]. The highest statistical correlation occurs with the second basic group accommodated in the vicinity of Glu97 and a hydrophobic group accommodated in the pocket defined by Phe174, Tyr99 and Trp215. Also, the best model arises when the conformation of the Glu97 side chain is modified such that an H-bond interaction is maintained with the inhibitor if possible. The model also shows a tightening of the S1 pocket as is shown in the recent data described above.