NMDA受体甘氨酸位点拮抗剂的三维构效关系研究

目的　建立NMDA受体甘氨酸位点拮抗剂的三维构效关系(3D-QSAR)模型。方法和结果　使用比较分子场分析法(CoMFA)建立的3D-QSAR模型,交叉验证回归系数R²cv、非交叉验证回归系数R²和标准偏差SEE分别为0.650,0.940和0.330,说明系列化合物分子周围立体场和静电场的分布与生物活性间存在良好的相关性。结论　所得模型较好的模拟了受体结合腔穴的立体和静电性质,可用于综合解释已报道的甘氨酸位点拮抗剂构效关系研究结果,并对文献中较少或较模糊的一些区域作了新的探讨,可用来指导设计新的先导物分子。     

Combined target-based and ligand-based drug design approach as a tool to define a novel 3D-pharmacophore model of human A3 adenosine receptor antagonists: pyrazolo[4,3-e]1,2,4-triazolo[1,5-c]pyrimidine derivatives as a key study

A combined target-based and ligand-based drug design approach has been carried out to define a novel pharmacophore model of the human A(3) receptor antagonists. High throughput molecular docking and comparative molecular field analysis (CoMFA) have been used in tandem to assemble a new target based pharmacophore model. In parallel, to provide more accurate information about the putative binding site of these A(3) inhibitors, a rhodopsin-based model of the human A(3) receptor was built and a novel Y-shape binding motif has been proposed. Docking-based structure superimposition has been used to perform a quantitative study of the structure-activity relationships for binding of these pyrazolo-triazolo-pyrimidines to adenosine A(3) receptor using CoMFA. Both steric and the electrostatic contour plots obtained from the CoMFA analysis nicely fit on the hypothetical binding site obtained by molecular docking. On the basis of the combined hypothesis, we have designed, synthesized, and tested 17 new derivatives. Consistently, the predicted K(i) values were very close to the experimental values.     

3D-QSAR studies on cannabinoid CB1 receptor agonists: G-protein activation as biological data

G-protein activation via the CB1 receptor was determined for a group of various CB1 ligands and utilized as biological activity data in subsequent CoMFA and CoMSIA studies. Both manual techniques and automated docking at CB1 receptor models were used to obtain a common alignment of endocannabinoid and classical cannabinoid derivatives. In the final alignment models, the endocannabinoid headgroup occupies a unique region distinct from the classical cannabinoid structures, supporting the hypothesis that these structurally diverse molecules overlap only partially within the receptor binding site. Both CoMFA and CoMSIA produce statistically significant models based on the manual alignment and a docking alignment at one receptor conformer. Leave-half-out cross-validation and progressive scrambling were successfully used in assessing the predictivity of the QSAR models.     

Effects of variable docking conditions and scoring functions on corresponding protein-aligned comparative molecular field analysis models constructed from diverse human protein tyrosine phosphatase 1B inhibitors

The effects of variable docking conditions and scoring functions on corresponding protein-aligned comparative molecular field analysis (CoMFA) models have been assessed. To this end, a group of diverse inhibitors were docked into the active site of human protein tyrosine phosphatase 1B (h-PTP 1B). The docked structures were utilized to construct corresponding protein-aligned CoMFA models by employing probe-based (H+, OH, CH3) energy grids and genetic partial least squares (G/PLS) statistical analysis. A total of 48 different docking configurations were evaluated, of which some succeeded in producing self-consistent and predictive CoMFA models. However, the best CoMFA model coincided with docking the un-ionized ligands into the hydrated form of the binding site via the PLP1 scoring function and restricted docking settings (r2(LOO) = 0.647, r2(PRESS) against 27 test compounds = 0.617). Interestingly, the most significant CoMFA models were orthogonal and corresponded to significantly different docked conformers/poses. To utilize the predictive potentials of the best CoMFA models collectively, it was decided to combine them in a single quantitative structure-activity relationship (QSAR) model. The combination model illustrated excellent statistical properties (r2(LOO) = 0.890, r2(PRESS) against 27 test compounds = 0.750).     

A molecular basis for agonist and antagonist actions at GABA(C) receptors

We modelled the N-terminal ligand-binding domain of the rho1 GABA(C) receptor based on the Lymnaea stagnalis acetylcholine-binding protein (L-AChBP) crystal structure using comparative modelling and validated using flexible docking guided by known mutagenesis studies. A range of known rho1 GABA(C) receptor ligands comprising seven full agonists, 10 partial agonists, 43 antagonists and 12 inactive molecules were used to evaluate and validate the models. Of the 50 models identified, six models that allowed flexible ligand docking in accordance with the experimental data were selected and used to study detailed receptor-ligand interactions. The most refined model to accommodate all known active ligands featured a cavity comprising of a volume of 488 A(3). A detailed analysis of the interaction between the rho1 GABA(C) receptor model and the docked ligands revealed possible H-bonds and cation-pi interactions between the different ligands and binding site residues. Based on quantum mechanical/molecular mechanical (QM/MM) calculations, the model showed distinctive conformations of loop C that provided a molecular basis for agonist and antagonist actions. Agonists elicit loop C closure, while a more open loop C was observed upon antagonist binding. The model differentiates the role for key residues known to be involved in either binding and/or gating.     

3D-QSAR comparative molecular field analysis on opioid receptor antagonists: pooling data from different studies

Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were constructed using comparative molecular field analysis (CoMFA) on a series of opioid receptor antagonists. To obtain statistically significant and robust CoMFA models, a sizable data set of naltrindole and naltrexone analogues was assembled by pooling biological and structural data from independent studies. A process of "leave one data set out", similar to the traditional "leave one out" cross-validation procedure employed in partial least squares (PLS) analysis, was utilized to study the feasibility of pooling data in the present case. These studies indicate that our approach yields statistically significant and highly predictive CoMFA models from the pooled data set of delta, mu, and kappa opioid receptor antagonists. All models showed excellent internal predictability and self-consistency: q(2) = 0.69/r(2) = 0.91 (delta), q(2) = 0.67/r(2) = 0.92 (mu), and q(2) = 0.60/r(2) = 0.96 (kappa). The CoMFA models were further validated using two separate test sets: one test set was selected randomly from the pooled data set, while the other test set was retrieved from other published sources. The overall excellent agreement between CoMFA-predicted and experimental binding affinities for a structurally diverse array of ligands across all three opioid receptor subtypes gives testimony to the superb predictive power of these models. CoMFA field analysis demonstrated that the variations in binding affinity of opioid antagonists are dominated by steric rather than electrostatic interactions with the three opioid receptor binding sites. The CoMFA steric-electrostatic contour maps corresponding to the delta, mu, and kappa opioid receptor subtypes reflected the characteristic similarities and differences in the familiar "message-address" concept of opioid receptor ligands. Structural modifications to increase selectivity for the delta over mu and kappa opioid receptors have been predicted on the basis of the CoMFA contour maps. The structure-activity relationships (SARs) together with the CoMFA models should find utility for the rational design of subtype-selective opioid receptor antagonists.     

3D-QSAR and docking studies on pyridopyrazinones as BRAF inhibitors

BRAF has become an important and exciting therapeutic target toward human cancer. 3D-QSAR and docking studies were performed to explore the interaction of the BRAF with a series of pyridopyrazinones. The comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods were carried out in terms of their potential for predictability. The CoMFA and CoMSIA models using 71 compounds in the training set gave r _cv² values of 0.567 and 0.662, r ² values of 0.900 and 0.907, respectively. The 3D contour maps generated by the CoMFA and CoMSIA models were used to identify the key structural requirements responsible for the biological activity. Molecular docking was applied to explore the binding mode between the ligands and the receptor. The information obtained by 3D-QSAR models may be useful to design novel potential BRAF inhibitors.     

Pharmacophore based receptor modeling: the case of adenosine A3 receptor antagonists. An approach to the optimization of protein models

To design and synthesize new potent and selective antagonists of the human A(3) adenosine receptor, pharmacophoric hypotheses were generated with the software Catalyst for a comprehensive set of compounds retrieved from previous literature. Three of these pharmacophores were used to drive the optimization of a molecular model of the receptor built by homology modeling. The alignment of the ligands proposed by Catalyst was then used to manually dock a set of known A(3) antagonists into the binding site, and as a result, the model was able to explain the different binding mode of very active compounds with respect to less active ones and to reproduce, with good accuracy, free energies of binding. The docking highlighted that the nonconserved residue Tyr254 could play an important role for A(3) selectivity, suggesting that a mutagenesis study on this residue could be of interest in this respect. The reliability of the whole approach was successfully tested by rational design and synthesis of new compounds.     

维A类化合物的构效关系研究.I.维A类与受体结合作用的三维构效关系

准确地预测配体 受体的结合常数是基于受体结构设计(structure-based design)的一个重要方面。目前几乎所有的全新设计(de novo design)或3D数据库搜寻的方法都侧重于结构的生成而忽视了对结构的定量评价。本文以副睾维A酸结合蛋白(ERABP)为模板,用DOCK程序研究了一组维A类化合物与受体的相互作用,得到一个预测受体结合常数的方程。另外,对DOCK后的分子构象进行了CoMFA分析,得到这类化合物的作用模型。     

Docking and CoMFA study on novel human CCR5 receptor antagonists

The CC-chemokine receptor 5 (CCR5), a membrane protein belonging to the G protein-coupled receptor super-family, has been identified as an essential co-receptor for HIV entry into the cells. Small molecules were used to inhibit HIV entry by targeting CCR5. In this study, comparative molecular field analysis (CoMFA) was carried out on 70 novel phenoxybenzyl derivatives as antagonists of CCR5 HIV co receptor. This CoMFA model yielded satisfactory statistical data with the cross-validated q ² of 0.611 and non-cross-validated r ² of 0.903. Mapping this model according to the topology of the active site of CCR5 end to a better understanding of antagonist-CCR5 interactions. Because of lacking crystallography structure of CCR5, the 3D structure from threading assembly refinement (TASSER) method was used. These antagonists were docked into the binding site of the 3D model of CCR5 using ligandfit, and the probable interaction model between CCR5 and the antagonists were obtained. The correlation of predicted binding affinities between antagonists and CCR5 has good statistical quality.     

维A类化合物的构效关系研究.I.维A类与受体结合作用的三维构效关系

准确地预测配体受体的结合常数是基于受体结构设计（ｓｔｒｕｃｔｕｒｅｂａｓｅｄｄｅｓｉｇｎ）的一个重要方面。目前几乎所有的全新设计（ｄｅｎｏｖｏｄｅｓｉｇｎ）或３Ｄ数据库搜寻的方法都侧重于结构的生成而忽视了对结构的定量评价。本文以副睾维Ａ酸结合蛋白（ＥＲＡＢＰ）为模板，用ＤＯＣＫ程序研究了一组维Ａ类化合物与受体的相互作用，得到一个预测受体结合常数的方程。另外，对ＤＯＣＫ后的分子构象进行了ＣｏＭＦＡ分析，得到这类化合物的作用模型。     

Combining pharmacophore search, automated docking, and molecular dynamics simulations as a novel strategy for flexible docking. Proof of concept: docking of arginine-glycine-aspartic acid-like compounds into the alphavbeta3 binding site

A novel and highly efficient flexible docking approach is presented where the conformations (internal degrees of freedom) and orientations (external degrees of freedom) of the ligands are successively considered. This hybrid method takes advantage of the synergistic effects of structure-based and ligand-based drug design techniques. Preliminary antagonist-derived pharmacophore determination provides the postulated bioactive conformation. Subsequent docking of this pharmacophore to the receptor crystal structure results in a postulated pharmacophore/receptor binding mode. Pharmacophore-oriented docking of antagonists is subsequently achieved by matching ligand interacting groups with pharmacophore points. Molecular dynamics in water refines the proposed complexes. To validate the method, arginine-glycine-aspartic acid (RGD) containing peptides, pseudopeptides, and RGD-like antagonists were docked to the crystal structure of alphavbeta3 holoprotein and apoprotein. The proposed directed docking was found to be more accurate, faster, and less biased with respect to the protein structure (holo and apoprotein) than DOCK, Autodock, and FlexX docking methods. The successful docking of an antagonist recently cocrystallized with the receptor to both apo and holoprotein is particularly appealing. The results summarized in this report illustrated the efficiency of our light CoMFA/rigid body docking hybrid method.     

Selectivity fields: comparative molecular field analysis (CoMFA) of the glycine/NMDA and AMPA receptors

An approach for evaluation of binding selectivity was suggested and exemplified using glycine/NMDA and AMPA receptors. For analyzing the pairwise selectivity, we propose to use the difference between biological activities (expressed as -log Ki) of ligands with respect to different receptor subtypes as a dependent variable for building comparative molecular field analysis (CoMFA) models. The resulting fields (which will be referred to as the "selectivity fields") indicate the ways of increasing selectivity of binding, inhibition, etc. As an example, CoMFA of a set of pyrazolo[1,5-c]quinazolines and triazolo[1,5-c]quinazolines was used for considering the binding selectivity with respect to glycine/NMDA and AMPA receptors. In addition, the mapping of these fields onto the molecular models of the corresponding receptors makes it possible to reveal the reasons for experimentally observed selectivity as well as to suggest additional ways of increasing selectivity.     

Design and quantitative structure-activity relationship of 3-amidinobenzyl-1H-indole-2-carboxamides as potent,nonchiral, and selective inhibitors of blood coagulation factor Xa

A series of 138 nonchiral 3-amidinobenzyl-1H-indole-2-carboxamides and analogues as inhibitors of the blood coagulation enzyme factor Xa (fXa) were designed, synthesized, and investigated by X-ray structure analysis and 3D quantitative structure-activity relationship (QSAR) studies (CoMFA, CoMSIA) in order to identify important protein-ligand interactions responsible for biological affinity and selectivity. Several compounds from this series are highly potent and selective inhibitors of this important enzyme linking extrinsic and intrinsic coagulation pathways. To rationalize biological affinity and to provide guidelines for further design, all compounds were docked into the factor Xa binding site. Those docking studies were based on X-ray structures of factor Xa in complex with literature-known inhibitors. It was possible to validate those binding modes by four X-ray crystal structures of representative ligands in factor Xa, while one ligand was additionally crystallized in trypsin to rationalize requirements for selective factor Xa inhibition. The 3D-QSAR models based on a superposition rule derived from these docking studies were validated using conventional and cross-validated r(2) values using the leave-one-out method and repeated analyses using two randomly chosen cross-validation groups plus randomization of biological activities. This led to consistent and highly predictive 3D-QSAR models with good correlation coefficients for both CoMFA and CoMSIA, which were found to correspond to experimentally determined factor Xa binding site topology in terms of steric, electrostatic, and hydrophobic complementarity. Subsets selected as smaller training sets using 2D fingerprints and maximum dissimilarity methods resulted in 3D-QSAR models with remarkable correlation coefficients and a high predictive power. The final quantitative SAR information agrees with all experimental data for the binding topology and thus provides reasonable activity predictions for novel factor Xa inhibitors.     

Development of a pharmacophore model for histamine H3 receptor antagonists, using the newly developed molecular modeling program SLATE

New molecular modeling tools were developed to construct a qualitative pharmacophore model for histamine H3 receptor antagonists. The program SLATE superposes ligands assuming optimum hydrogen bond geometry. One or two ligands are allowed to flex in the procedure, thereby enabling the determination of the bioactive conformation of flexible H3 antagonists. In the derived model, four hydrogen-bonding site points and two hydrophobic pockets available for binding antagonists are revealed. The model results in a better understanding of the structure-activity relationships of H3 antagonists. To validate the model, a series of new antagonists was synthesized. The compounds were designed to interact with all four hydrogen-bonding site points and the two hydrophobic pockets simultaneously. These ligands have high H3 receptor affinity, thereby illustrating how the model can be used in the design of new classes of H3 antagonists.     

3H]5,7-dichlorokynurenic acid, a novel radioligand labels NMDA receptor-associated glycine binding sites.

A strychnine-insensitive glycine binding site is located on the N-methyl-D-aspartate (NMDA)-preferring glutamate receptor complex. Kynurenic acid analogs are antagonists at this binding site. A derivative of kynurenic acid, 5,7-dichlorokynurenic acid (5,7-DCKA) was radiolabeled with 3H and used to study antagonist binding to the glycine recognition site. This ligand ( [3H]5,7-DCKA) showed high affinity (Kd = 69 nM), saturable (Bmax = 14.5 pmol/mg protein) binding to rat brain membranes. A variety of agonists and antagonists inhibited the binding of [3H]5,7-DCKA and [3H]glycine in a similar fashion (r = 0.93). In addition, glutamate site agonists and antagonists exerted opposite allosteric effects on [3H]5,7-DCKA binding suggesting that [3H]5,7-DCKA preferentially binds to the agonist-activated conformation of the receptor.     

Ligand‐binding affinity of alternative conformers of human β2‐adrenergic receptor in the presence of intracellular loop 3 (ICL3) and their potential use in virtual screening studies

This study investigates the structural distinctiveness of orthosteric ligand‐binding sites of several human β₂ adrenergic receptor (β₂‐AR) conformations that have been obtained from a set of independent molecular dynamics (MD) simulations in the presence of intracellular loop 3 (ICL3). A docking protocol was established in order to classify each receptor conformation via its binding affinity to selected ligands with known efficacy. This work's main goal was to reveal many subtle features of the ligand‐binding site, presenting alternative conformations, which might be considered as either active‐ or inactive‐like but mostly specific for that ligand. Agonists, inverse agonists, and antagonists were docked to each MD conformer with distinct binding pockets, using different docking tools and scoring functions. Mostly favored receptor conformation persistently observed in all docking/scoring evaluations was classified as active or inactive based on the type of ligand's biological effect. Classified MD conformers were further tested for their ability to discriminate agonists from inverse agonists/antagonists, and several conformers were proposed as important targets to be used in virtual screening experiments that were often limited to a single X‐ray structure.