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1.
A panel of 92 catechol-O-methyltransferase (COMT) inhibitors was used to examine the molecular interactions affecting their biological activity. COMT inhibitors are used as therapeutic agents in the treatment of Parkinson's disease, but there are limitations in the currently marketed compounds due to adverse side effects. This study combined molecular docking methods with three-dimensional structure-activity relationships (3D QSAR) to analyse possible interactions between COMT and its inhibitors, and to incite the design of new inhibitors. Comparative molecular field analysis (CoMFA) and GRID/GOLPE models were made by using bioactive conformations from docking experiments, which yielded q2 values of 0.594 and 0.636, respectively. The docking results, the COMT X-ray structure, and the 3D QSAR models are in agreement with each other. The models suggest that an interaction between the inhibitor's catechol oxygens and the Mg2+ ion in the COMT active site is important. Both hydrogen bonding with Lys144, Asn170 and Glu199, and hydrophobic contacts with Trp38, Pro174 and Leu198 influence inhibitor binding. Docking suggests that a large R1 substituent of the catechol ring can form hydrophobic contacts with side chains of Val173, Leu198, Met201 and Val203 on the COMT surface. Our models propose that increasing steric volume of e.g. the diethylamine tail of entacapone is favourable for COMT inhibitory activity. 相似文献
2.
Three-dimensional quantitative structure-activity relationship (3D QSAR) using comparative molecular field analysis (CoMFA)
was performed on a series of substituted tetrahydropyran (THP) derivatives possessing serotonin (SERT) and norepinephrine
(NET) transporter inhibitory activities. The study aimed to rationalize the potency of these inhibitors for SERT and NET as
well as the observed selectivity differences for NET over SERT. The dataset consisted of 29 molecules, of which 23 molecules
were used as the training set for deriving CoMFA models for SERT and NET uptake inhibitory activities. Superimpositions were
performed using atom-based fitting and 3-point pharmacophore-based alignment. Two charge calculation methods, Gasteiger-Hückel
and semiempirical PM3, were tried. Both alignment methods were analyzed in terms of their predictive abilities and produced
comparable results with high internal and external predictivities. The models obtained using the 3-point pharmacophore-based
alignment outperformed the models with atom-based fitting in terms of relevant statistics and interpretability of the generated
contour maps. Steric fields dominated electrostatic fields in terms of contribution. The selectivity analysis (NET over SERT),
though yielded models with good internal predictivity, showed very poor external test set predictions. The analysis was repeated
with 24 molecules after systematically excluding so-called outliers (5 out of 29) from the model derivation process. The resulting
CoMFA model using the atom-based fitting exhibited good statistics and was able to explain most of the selectivity (NET over
SERT)-discriminating factors. The presence of −OH substituent on the THP ring was found to be one of the most important factors
governing the NET selectivity over SERT. Thus, a 4-point NET-selective pharmacophore, after introducing this newly found H-bond
donor/acceptor feature in addition to the initial 3-point pharmacophore, was proposed. 相似文献
3.
Sippl W Contreras JM Parrot I Rival YM Wermuth CG 《Journal of computer-aided molecular design》2001,15(5):395-410
The paper describes the construction, validation and application of a structure-based 3D QSAR model of novel acetylcholinesterase (AChE) inhibitors. Initial use was made of four X-ray structures of AChE complexed with small, non-specific inhibitors to create a model of the binding of recently developed aminopyridazine derivatives. Combined automated and manual docking methods were applied to dock the co-crystallized inhibitors into the binding pocket. Validation of the modelling process was achieved by comparing the predicted enzyme-bound conformation with the known conformation in the X-ray structure. The successful prediction of the binding conformation of the known inhibitors gave confidence that we could use our model to evaluate the binding conformation of the aminopyridazine compounds. The alignment of 42 aminopyridazine compounds derived by the docking procedure was taken as the basis for a 3D QSAR analysis applying the GRID/GOLPE method. A model of high quality was obtained using the GRID water probe, as confirmed by the cross-validation method (q2
LOO=0.937, q2
L50% O=0.910). The validated model, together with the information obtained from the calculated AChE-inhibitor complexes, were considered for the design of novel compounds. Seven designed inhibitors which were synthesized and tested were shown to be highly active. After performing our modelling study the X-ray structure of AChE complexed with donepezil, an inhibitor structurally related to the developed aminopyirdazines, has been made available. The good agreement found between the predicted binding conformation of the aminopyridazines and the one observed for donepezil in the crystal structure further supports our developed model. 相似文献
4.
新型2-杂环芳基苯并二氢吡喃-4-酮衍生物的三维定量构效关系研究 总被引:1,自引:0,他引:1
为开发新型环境友好杀菌剂,选择了黄烷酮类植物抗毒素为先导,利用生物等排取代原理对其结构进行修饰,设计合成了23个未见文献报道的2-杂环芳基苯并二氢吡喃-4-酮类化合物,并系统测定了所有化合物对水稻稻瘟病抑制活性的IC~5~0值。在此基础上,采用CoMFA方法对它们进行了三维定量结构活性关系研究,系统考查了网格结构、探针以及场类型对CoMFA结果的影响。研究结果表明,苯并二氢吡喃-4-酮苯环5,6,7位上应该引入一些体积较小且具有强供电子能力的取代基有利于提高化合物的杀菌活性。CoMFA分析对7位氧原子和19位氧原子的电性要求与前文采用Hansch-Fujita方法的分析结果是相一致的。 相似文献
5.
Three-dimensional quantitative structure-activity relationship (3D-QSAR) modelling using comparative molecular similarity indices analysis (CoMSIA) was applied to a series of 406 structurally diverse dihydrofolate reductase (DHFR) inhibitors from Pneumocystis carinii (pc) and rat liver (rl). X-ray crystal structures of three inhibitors bound to pcDHFR were used for defining the alignment rule. For pcDHFR, a QSAR model containing 6 components was selected using leave-10%-out cross-validation (n= 240, q2 = 0.65), while a 4-component model was selected for rlDHFR (n= 237, q2 = 0.63); both include steric, electrostatic and hydrophobic contributions. The models were validated using a large test set, designed to maximise its diversity and to verify the predictive accuracy of models for extrapolation. The pcDHFR model has r2 = 0.60 and mean absolute error (MAE) = 0.57 for the test set after removing 4 outliers, and the rlDHFR model has r2 = 0.60 and MAE = 0.69 after removing 4 test set outliers. In addition, classification models predicting selectivity for pcDHFR over rlDHFR were developed using soft independent modelling by class analogy (SIMCA), with a selectivity ratio of 2 (IC50,rlDHFR/ IC50,pcDHFR) used for delimiting classes. A 5-component model including steric and electrostatic contributions has cross-validated and test set classification rates of 0.67 and 0.68 for selective inhibitors, and 0.85 and 0.72 for unselective inhibitors. The predictive accuracy of models, together with the identification of important contributions in QSAR and classification models, offer the possibility of designing potent selective inhibitors and estimating their activity prior to synthesis. 相似文献
6.
Maurizio Recanatini 《Journal of computer-aided molecular design》1996,10(1):74-82
Summary A series of non-steroidal inhibitors of aromatase, structurally related to fadrozole (2), was investigated with the aim of developing a 3D QSAR model using the Comparative Molecular Field Analysis (CoMFA) technique. The alignment of the molecules was performed following two approaches (atom-by-atom and field fit), both starting from an initial hypothesis of superimposition of fadrozole to a steroidal inhibitor (3). From a number of CoMFA models built with different characteristics, one was recognized as the most statistically relevant; this one is discussed in detail. The features of the 3D QSAR model are consistent with those of other 3D and QSAR models of aromatase and its inhibitors. 相似文献
7.
Development of biologically active compounds by combining 3D QSAR and structure-based design methods
Sippl W 《Journal of computer-aided molecular design》2002,16(11):825-830
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 相似文献
8.
Phosphoinositide-dependent protein kinase-1 (PDK1) is a Ser/Thr kinase which phosphorylates and activates members of the AGC
kinase group known to control processes such as tumor cell growth, protection from apoptosis, and tumor angiogenesis. In this
paper, CoMFA and CoMSIA studies were carried out on a training set of 56 conformationally rigid indolinone inhibitors of PDK1.
Predictive 3D QSAR models, established using atom fit alignment rule based on crystallographic-bound conformation, had cross-validated
(r
cv2) values of 0.738 and 0.816 and non-cross-validated (r
ncv2) values of 0.912 and 0.949 for CoMFA and CoMSIA models, respectively. The predictive ability of the CoMFA and CoMSIA models
was determined using a test set of 14 compounds, which gave predictive correlation coefficients (r
pred2) of 0.865 and 0.837, respectively. Structure-based interpretation of the CoMFA and CoMSIA field properties provided further
insights for the rational design of new PDK1 inhibitors.
Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users. 相似文献
9.
Kailin Tang 《Analytica chimica acta》2003,476(1):85-92
In this paper, the partial least-squares (PLS) is discussed. A new hybrid method combining PLS with GAGP, in which selection of variables, selection of functions and optimization of parameters were carried at the same time without any foreknowledge, was studied. A number of PLS algorithms (linear PLS, QPLS, SPL-PLS, NPLSNGA) that have appeared were compared from a theoretical viewpoint. Eight practical results with all the compared methods indicated that nonlinear models are better than linear model. In nonlinear methods, GAGP-PLS is significant. 相似文献
10.
类吗啡类拮抗物的结构与抑食活性的3D-QSAR研究 总被引:1,自引:0,他引:1
用比较力场分析研究了3,4-二甲基-4-(3-羟基苯基)哌啶及其衍生物类吗啡拮抗物的结构与抑食活性的关系,考察了网格结构和探针原子的影响.结果表明,立体效应和静电作用场是描述其抑食活性和进行结构性能关系研究的最重要的结构参数. 相似文献
11.
Giovanni Greco Ettore Novellino Maurizio Pellecchia Carlo Silipo Antonio Vittoria 《Journal of computer-aided molecular design》1994,8(2):97-112
Summary An example of a CoMFA study is described with the aim to discuss one of the major problems of this 3D QSAR method: lack of variable selection. It is shown that the use of nonrelevant energy parameters might produce CoMFA contour maps which poorly reflect the actual nature of the binding site and are in part statistical artefacts. The data set employed in our analysis comparises triazine inhibitors of dihydrofolate reductase (DHFR), isolated from chicken liver, which have already been the object of a QSAR study by other authors. Since three-dimensional structures of triazine-DHFR complexes are known, it was possible not only to reduce ambiguities in the superimposition of the ligands, but also to compare the resulting CoMFA contour maps with the enzyme active site.Supplementary material available: The Cartesian coordinates and the atomic charges of the PM3-optimized structures used in the CoMFA study are available as MOL2 files upon request.To whose memory this paper is dedicated. 相似文献
12.
Sippl W 《Journal of computer-aided molecular design》2000,14(6):559-572
One of the major challenges in computational approaches to drug design is the accurate prediction of binding affinity of biomolecules. In the present study several prediction methods for a published set of estrogen receptor ligands are investigated and compared. The binding modes of 30 ligands were determined using the docking program AutoDock and were compared with available X-ray structures of estrogen receptor-ligand complexes. On the basis of the docking results an interaction energy-based model, which uses the information of the whole ligand-receptor complex, was generated. Several parameters were modified in order to analyze their influence onto the correlation between binding affinities and calculated ligand-receptor interaction energies. The highest correlation coefficient (r
2 = 0.617, q
2
LOO = 0.570) was obtained considering protein flexibility during the interaction energy evaluation. The second prediction method uses a combination of receptor-based and 3D quantitative structure-activity relationships (3D QSAR) methods. The ligand alignment obtained from the docking simulations was taken as basis for a comparative field analysis applying the GRID/GOLPE program. Using the interaction field derived with a water probe and applying the smart region definition (SRD) variable selection, a significant and robust model was obtained (r
2 = 0.991, q
2
LOO = 0.921). The predictive ability of the established model was further evaluated by using a test set of six additional compounds. The comparison with the generated interaction energy-based model and with a traditional CoMFA model obtained using a ligand-based alignment (r
2 = 0.951, q
2
LOO = 0.796) indicates that the combination of receptor-based and 3D QSAR methods is able to improve the quality of the underlying model. 相似文献
13.
Summary Recently, methods have been developed in the field of Artificial Intelligence (AI), specifically in the expert systems area using rule-induction, designed to extract rules from data. We have applied these methods to the analysis of molecular series with the objective of generating rules which are predictive and reliable.The input to rule-induction consists of a number of examples with known outcomes (a training set) and the output is a tree-structured series of rules. Unlike most other analysis methods, the results of the analysis are in the form of simple statements which can be easily interpreted. These are readily applied to new data giving both a classification and a probability of correctness.Rule-induction has been applied to in-house generated and published QSAR datasets and the methodology, application and results of these analyses are discussed.The results imply that in some cases it would be advantageous to use rule-induction as a complementary technique in addition to conventional statistical and pattern-recognition methods. 相似文献
14.
In this paper, two 3‐dimensional quantitative structure‐activity relationship models for 60 human immunodeficiency virus (HIV)‐1 protease inhibitors were established using random sampling analysis on molecular surface and translocation comparative molecular field vector analysis (Topomer CoMFA). The non–cross‐validation (r2), cross‐validation (q2), correlation coefficient of external validation (Q2ext), and F of 2 models were 0.94, 0.80, 0.79, and 198.84 and 0.94, 0.72, 0.75, and 208.53, respectively. The results indicated that 2 models were reasonable and had good prediction ability. Topomer Search was used to search R groups in the ZINC database, 20 new compounds were designed, and the Topomer CoMFA model was used to predicate the biological activity. The results showed that 18 new compounds were more active than the template molecule. So the Topomer Search is effective in screening and can guide the design of new HIV/AIDS drugs. The mechanism of action was studied by molecular docking, and it showed that the protease inhibitors and Ile50, Asp25, and Arg8 sites of HIV‐1 protease have interactions. These results have provided an insight for the design of new potent inhibitors of HIV‐1 protease. 相似文献
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Summary An analysis of five different datasets of inhibitors of serotonin uptake has yielded quantitative structure/ activity relationships (QSARs) which delineate the role of steric and hydrophobic properties essential for inhibition by phenylethylamine-type analogues. 相似文献