3-羧基香豆素类乳酸转运抑制剂的三维定量构效关系研究

目的 建立3-羧基香豆素类乳酸转运抑制剂三维定量构效关系(3D-QSAR)模型.方法 采用分子力场分析法(CoMFA)和比较分子相似性指数分析法(CoMSIA)来研究3-羧基香豆素类乳酸转运抑制剂的构效关系.结果 建立了合理、可靠的3-羧基香豆素类乳酸转运抑制剂CoMFA(q2=0.630,r2 =0.994,rpred2=0.909)和CoMSIA(q2=0.676,r2=0.972,rpred2 =0.574)模型.结论 构建的3D-QSAR模型揭示了3-羧基香豆素类化合物的结构和生物活性间的关系,可为该类乳酸转运抑制剂的进一步优化设计提供科学依据.     

Anticarcinogenic and antioxidant activity of diindolylmethane derivatives

To investigate the synthesis methods and the bioactivity of diindolylmethane (DIM) derivatives. METHODS:1) A 3D-Quantitative Structure-Active Relationships (QSAR) Comparative Molecular Field Analysis (CoMFA) study of 14 DIM derivatives was investigated to predict their anticarcinogenic activity. 2) Based on CoMFA model, a series of new derivatives of DIM were designed and synthesized. 3) Their free radical scavenging and antioxidant potentials were tested using in-vitro DPPH radical scavenging and ~-carotene antioxidant models. 4) The anticarcinogenic activities of some compounds were tested by using microculture tetrazolium assay (MTT) and sulforhodamine B (SRB) proteochromosomic assays. RESULTS: 1) The CoMFA model derived from DIM analogues proved a good predictive ability with q2 value of 0.827. 2) New designed compounds 3c and 4c exhibited 3-fold more potent radical scavenging activity than reference substance Vitamin E in DPPH model expressed by IC50 values. 3) The primary antitumor screening essay showed that some DIM derivatives designed exhibited the inhibitory activities to some tumor cell growth at relatively high concentration, and DIM was the most effective among them. CONCLUSION: DIM‘s 3D-QSAR model is reliable. According to it, eleven DIM derivatives weresynthesized, and two derivatives of them possess potent radical scavenging activities and some showed the inhibitory activities in primary anticancer assay in vitro.     

Antitumor agents. 199. Three-dimensional quantitative structure-activity relationship study of the colchicine binding site ligands using comparative molecular field analysis

Inhibitors of tubulin polymerization interacting at the colchicine binding site are potential anticancer agents. We have been involved in the synthesis of a number of colchicine site agents, such as thiocolchicinoids and allocolchicinoids, which are colchicine analogues, and 2-phenyl-quinolones and 2-aryl-naphthyridinones, which are the amino analogues of cytotoxic antimitotic flavonoids. The most cytotoxic of the latter compounds strongly inhibit binding of radiolabeled colchicine to tubulin, and these agents therefore probably bind in the colchicine site of tubulin. We have applied conventional CoMFA and q(2)-GRS CoMFA to identify the essential structural requirements for increasing the ability of these compounds to form tubulin complexes. The CoMFA model for the training set of 51 compounds yielded cross-validated R(2) (q(2)) values of 0.637 for conventional CoMFA and 0.692 for q(2)-GRS CoMFA. The predictive power of this model was confirmed by successful activity prediction for a test set of 53 compounds with known potencies as inhibitors of tubulin polymerization. The activities of 88% of the compounds were predicted with absolute value of residuals of less than 0.5. The predictive q(2) values were 0.546 for conventional CoMFA and 0.426 for q(2)-GRS CoMFA. The conventional CoMFA model with the highest predictive q(2) (0.546) was analyzed in detail in terms of underlying structure-activity relationships.     

3D QSAR studies on cinnamaldehyde analogues as farnesyl protein transferase inhibitors

Three-dimensional quantitative structure-activity relationship (3D-QSAR) studies on 59 cinnamaldehyde analogues as Farnesyl Protein Transferase (FPTase) inhibitors were investigated using comparative molecular field analysis (CoMFA) with the PLS region-focusing method. Forty-nine training set inhibitors were used for CoMFA with two different grid spacings, 2A and 1A. Ten compounds, which were not used in model generation, were used to validate the CoMFA models. After the PLS analysis, the best predictive CoMFA model showed that the cross-validated value (r2cv) and the non-cross validated conventional value (r2ncv) are 0.557 and 0.950, respectively. From the CoMFA contour maps, the steric and electrostatic properties of cinnamaldehyde analogues can be identified and verified.     

Molecular docking and 3D-QSAR studies of 2-substituted 1-indanone derivatives as acetylcholinesterase inhibitors

Aim： To explore the binding mode of 2-substituted 1-indanone derivatives with acetylcholinesterase （ACHE） and provide hints for the future design of new de- rivatives with higher potency and specificity. Methods： The GOLD-docking con- formations of the compounds in the active site of the enzyme were used in subse- quent studies. The highly reliable and predictive three-dimensional quantitative structure-activity relationship （3D-QSAR） models were achieved by comparative molecular field analysis （CoMFA） and comparative molecular similarity analysis （CoMSIA） methods. The predictive capabilities of the models were validated by an external test set. Moreover, the stabilities of the 3D-QSAR models were veri- fied by the leave-4-out cross-validation method. Results： The CoMFA and CoMSIA models were constructed successfully with a good cross-validated coef- ficient （q2） and a non-cross-validated coefficient （r2）. The q2 and r2 obtained from the leave- 1-out cross validation method were 0.784 and 0.974 in the CoMFA model and 0.736 and 0.947 in the CoMSIA model, respectively. The coefficient isocontour maps obtained from these models were compatible with the geometrical and physi- cochemical properties of ACHE. Conclusion： The contour map demonstrated that the binding affinity could be enhanced when the small protonated nitrogen moi- ety was replaced by a more hydrophobic and bulky group with a highly partial positive charge. The present study provides a better understanding of the inter- action between the inhibitors and ACHE, which is helpful for the discovery of new compounds with more potency and selective activity.     

3D-QSAR CoMFA on cyclin-dependent kinase inhibitors

Several series of cyclin-dependent kinase inhibitors previously prepared in our laboratory were compared using 3D-QSAR (CDK1) and docking (CDK2) techniques. Evaluation of our own library of 93 purine derivatives served to establish the model which was validated by evaluation of an external library of 71 compounds. The best predictions were obtained with the CoMFA standard model (q(2) = 0.68, r(2) = 0.90) and with the CoMSIA combined steric, electrostatic, and lipophilic fields (q(2) = 0.74, r(2) = 0.90). The CDK1 3D-QSAR model was then superimposed to the ATP/CDK2 binding site, giving direct contour maps of the different fields. Although too few compounds were evaluated on CDK5 to derive a 3D-QSAR model, some interesting SARs have been deduced. Comparison of the results obtained from both methods helped with understanding the specific activity of some compounds and designing new specific CDK inhibitors.     

3D-QSAR studies of JNK1 inhibitors utilizing various alignment methods

We report our three-dimensional quantitative structure activity relationship (3D-QSAR) studies of the series of anilinopyrimidine derivatives of JNK1 inhibitors. The comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were applied using different alignment methods. The ligand-based atom-by-atom matching alignment has produced better values for CoMFA (q(2) = 0.646 and r(2) = 0.983), while in CoMSIA it has achieved only lower statistical values. The pharmacophore-based model has produced (q(2) = 0.568, r(2) = 0.938) and (q(2) = 0.670, r(2) = 0.982) for CoMFA and CoMSIA models, respectively. As the model was based on the receptor-guided alignment, all the compounds were optimized within the receptor, resulting in q(2) = 0.605 and r(2) = 0.944 for CoMFA, and q(2) = 0.587 and r(2) = 0.863 for CoMSIA. Molecular Dynamic simulation studies suggested that the generated models were consistent with the low-energy protein ligand conformation. The CoMFA and CoMSIA contour maps indicated that the substitutions of the electropositive groups in the phenyl ring, and an addition of hydrophobic groups in the pyrimidine ring, are important to enhance the activity of this series. Moreover, the virtual screening analysis against NCI database yields potentials hits, and the results obtained would be useful to synthesize selective and highly potent c-Jun N-terminal kinase 1 analogs.     

Ligand-based 3D-QSAR studies of diaryl acyl-sulfonamide analogues as human umbilical vein endothelial cells inhibitors stimulated by VEGF

Diaryl acylsulfonamide derivatives were reported as Human Umbilical Vein Endothelial cell (HUVEC) inhibitors, stimulated by Vascular Endothelial Growth Factor (VEGF). VEGF has angiogenic property to cause colorectal cancer. A ligand-based 3D-QSAR technique was carried out on diaryl acylsulfonamide derivatives by using Comparative Molecular Field Analysis (CoMFA) studies to find relations between biological activities of inhibitors and their structures. In absence of binding mechanism for the ligand with VEGF receptor, current study hopes to shed some light on the inhibition mechanism of the ligands with HUVEC. 3D-QSAR technique was applied to a set of fifty ligands in order to facilitate the design of more potent inhibitors. However, the maximum cross-validated correlation coefficient value was found to be 0.417. The value is relatively low when compared to the usual acceptable cross-validated correlation coefficient, but no further improvements were observed by applying different available options. Therefore, the final model was used for further analysis. Additionally, the resulted CoMFA model was validated by an external set of 10 compounds yielding surprisingly, a satisfactory correlation coefficient value (r(2) (pred) ) 0.80. Moreover, the analysis of the individual generated 3D contours helped in understanding the possible structural modifications of molecules to improve the inhibitory potency.     

Three-dimensional quantitative structure-activity relationships of cyclo-oxygenase-2 (COX-2) inhibitors: a comparative molecular field analysis

The three-dimensional quantitative structure-activity relationship (3D-QSAR) approach using comparative molecular field analysis (CoMFA) was applied to an extensive series of 305 varied diarylheterocyclic derivatives known as COX-2 selective inhibitors. X-ray crystal structure of COX-2 bound with SC-558, a selective COX-2 inhibitor, was used to derive the putative bioactive conformation of these inhibitors. Five statistically significant models were obtained from the randomly constituted training sets (229 compounds) and subsequently validated with the corresponding test sets (76 compounds). The best predictive model (n = 229, q(2) = 0.714, N = 8, r(2) = 0.905, s = 0.291, F = 261.545) was selected for further comparison of the CoMFA contour maps obtained for steric, electrostatic, and lipophilic fields with the enzyme structure. The high level of compatibility with the COX-2 enzyme topology shows the great accuracy of this model that can predict inhibitory activities for a wide range of compounds and offers important structural insight into designing novel antiinflammatory drugs prior to their synthesis.     

Comparative molecular field analysis of substrates for an aryl sulfotransferase based on catalytic mechanism and protein homology modeling

Comparative Molecular Field Analysis (CoMFA) methods were used to produce a 3D-QSAR model that correlated the catalytic efficiency of rat hepatic aryl sulfotransferase (AST) IV, expressed as log(k(cat)/K(m)), with the molecular structures of its substrates. A total of 35 substrate molecules were used to construct a CoMFA model that was evaluated on the basis of its leave-one-out cross-validated partial least-squares value (q(2)) and its ability to predict the activity of six additional substrates not used in the training set. The model was constructed using substrate conformations that favored (1) proton abstraction by the catalytic histidine residue, (2) an in-line sulfuryl-group transfer mechanism, and (3) constraints imposed by the residues lining the substrate binding pocket of a homology model of AST IV. This CoMFA model had a q(2) value of 0.691, and it successfully predicted the activities of the six molecules not used in the training set. A final CoMFA model was constructed using the same methodology but with molecules from both the training set and the test set. Its q(2) value was 0.701, and it had a non-cross-validated r(2) value of 0.922. The contour coefficient map generated by this CoMFA was overlaid on the amino acids in the substrate-binding pocket of the homology model of AST IV and found to show a good fit. Additionally external validation was obtained by using the CoMFA model to design substrates that show high activities. These results establish a methodology for prediction of the substrate specificity of this sulfotransferase based on CoMFA methods that are guided by both the homology model and the catalytic mechanism of the enzyme.     

3D QSAR CoMFA/CoMSIA and docking studies on azole dione derivatives, as anti-cancer inhibitors

Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) were performed on a series of 103 azole dione derivatives, as selective anti-cancer inhibitors. The atom and shape based root mean square alignment yielded the best predictive CoMFA model q2 = 0.923, r2 = 0.980, when compared with the CoMSIA model. Docking studies were employed to position the inhibitors into active site of Crystal Structure of Delta (4)-3-ketosteroid 5-beta-reductase (PDB id: 3BUR). Results that indicate steric, electrostatic, hydrophobic, hydrogen bond donor and acceptor substituents play a significant role in design novel, potent and selective anti-cancer activity of the compounds.     

3-哌啶甲酸和四氢烟酸的4,4-二芳基-3-丁烯衍生物的三维定量构效关系(比较分子力场分析)研究

目的研究3-哌啶甲酸和四氢烟酸的4,4-二芳基-3-丁烯衍生物结构和对γ-氨基丁酸摄取抑制活性之间的关系.方法使用三维定量构效关系(3D-QSAR)--比较分子场分析(CoMFA)方法进行构效关系研究.结果交叉验证系数q2和非交叉验证系数r2分别为0.726和0.986,方差比F为117.562,标准估计误差(SEE)为0.062.结论这些数值表明所得的CoMFA模型有实际意义,并且对3-哌啶甲酸和四氢烟酸的4,4-二芳基-3-丁烯衍生物抑制活性具有较好的预测能力.     

Inhibitory mode of 1,5-diarylpyrazole derivatives against cyclooxygenase-2 and cyclooxygenase-1: molecular docking and 3D QSAR analyses

The Lamarckian genetic algorithm of AutoDock 3.0 has been employed to dock 40 1,5-diarylpyrazole class compounds into the active sites of cyclooxygenase-2 (COX-2) and cyclooxygenase-1 (COX-1). The binding models were demonstrated in the aspects of inhibitor's conformation, subsite interaction, and hydrogen bonding. The data of geometrical parameters and RMSD values compared with the known inhibitor, SC-558 (43), show that these inhibitors interact respectively with COX-2 and COX-1 in a very similar way. The r(2) values of 0.648 for COX-2 and 0.752 for COX-1 indicate that the calculated binding free energies correlate well with the inhibitory activities. The structural and energetic differences in inhibitory potencies of 1,5-diarylpyrazoles were reasonably explored, and the COX-2/COX-1 selectivity was demonstrated by the three-dimensional (3D) interaction models of inhibitors complexing with these two enzymes. Using the binding conformations of 1,5-diarylpyrazoles, consistent and highly predictive 3D quantitative structure-activity relationship (QSAR) models were developed by performing comparative molecular field analyses (CoMFA) and comparative molecular similarity analyses (CoMSIA). The q(2) values are 0.635 and 0.641 for CoMFA and CoMSIA models, respectively. The predictive ability of these models was validated by SC-558 (43) and a set of 10 other compounds that were not included in the training set. Mapping these models back to the topology of the active site of COX-2 leads to a better understanding of vital diarylpyrazole compounds and COX-2 interactions. Structure-based investigations and the final 3D QSAR results provided possible guidelines and accurate activity predictions for novel inhibitor design.     

A refined 3-dimensional QSAR of cytochrome P450 2C9: computational predictions of drug interactions

A ligand-based model is reported that predicts the Ki values for cytochrome P450 2C9 (CYP2C9) inhibitors. This CoMFA model was used to predict the affinity of 14 structurally diverse compounds not in the training set and appears to be robust. The mean error of the predictions is 6 microM. The experimentally measured Ki values of the 14 compounds range from 0.1 to 48 microM. Leave-one-out cross-validated partial least-squares gives a q2 value of between 0.6 and 0.8 for the various models which indicates internal consistency. Random assignment of biological data to structure leads to negative q2 values. These models are useful in that they establish a pharmacophore for binding to CYP2C9 that can be tested with site-directed mutagenesis. These models can also be used to screen for potential drug interactions and to design compounds that will not bind to this enzyme with high affinity.     

Predictive three-dimensional quantitative structure-activity relationship of cytochrome P450 1A2 inhibitors

The purpose of this study was to determine the cytochrome P450 1A2 (CYP1A2) inhibition potencies of structurally diverse compounds to create a comprehensive three-dimensional quantitative structure-activity relationship (3D-QSAR) model of CYP1A2 inhibitors and to use this model to predict the inhibition potencies of an external set of compounds. Fifty-two compounds including naphthalene, lactone and quinoline derivatives were assayed in a 96-well plate format for CYP1A2 inhibition activity using 7-ethoxyresorufin O-dealkylation as the probe reaction. The IC50 values of the tested compounds varied from 2.3 microM to over 40,000 microM. On the basis of this data set, a comparative molecular field analysis (CoMFA) and GRID/GOLPE models were created that yielded novel structural information about the interaction between inhibitory molecules and the CYP1A2 active site. The created CoMFA model was able to accurately predict inhibitory potencies of several structurally unrelated compounds, including selective inhibitors of other cytochrome P450 forms.     

A ligand-based approach to identify quantitative structure-activity relationships for the androgen receptor

We examined the three-dimensional quantitative structure-activity relationship (QSAR) of a group of endogenous and synthetic compounds for the androgen receptor (AR) using comparative molecular field analysis (CoMFA). The goal of these studies was to identify structural features necessary for high binding affinity and optimization of selective androgen receptor modulators (SARMs). A homology model of the AR was used as a scaffold to align six lead compounds that served as templates for alignment of the remaining 116 structures prior to CoMFA modeling. The conventional r(2) and cross-validated q(2) relating observed and predicted relative binding affinity (RBA) were 0.949 and 0.593, respectively. Comparison of predicted and observed RBA for a test set of 10 compounds resulted in an r(2) of 0.954, demonstrating the excellent predictive ability of the model. These integrated homology modeling and CoMFA studies identified critical amino acids for SARM interactions and provided QSAR data as the basis for mechanistic studies of AR structure, function, and design of optimized SARMs.