Evaluation of 1‐arylpiperazine derivative of hydroxybenzamides as 5‐HT1A and 5‐HT7 serotonin receptor ligands: An experimental and molecular modeling approach

The synthesis and evaluation as 5‐HT_1A and 5‐HT₇ serotonin receptor ligands of the two sets of O‐substituted hydroxybenzamides, structurally related to 2‐{3‐[4‐(2‐methoxyphenyl)piperazin‐1‐yl]propoxy}benzamide ( 1 ), (K_i 5‐HT_1A = 21 nM, 5‐HT₇ = 234 nM) are reported. To affect the affinity for 5‐HT_1A and 5‐HT₇ receptors, an amide moiety ( 2 , 3 , 4 , 5 , 6 ) and a hydrocarbon chain length ( 7 , 8 , 9 , 10 ) were modified. The serotonergic activity of compounds 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 was generally higher in the case of 5‐HT_1A receptors compared with 5‐HT₇ ones; the most active 5‐HT_1A ligands being meta‐isomer 2 (K_i = 7 nM) and both analogs of 1 with the longest spacer, i.e., penta‐ and hexa‐methylene derivatives 9 and 10 (K_i = 4 and 3 nM, respectively). The observed biological properties of compounds 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 were elucidated using molecular modeling procedures. J. Heterocyclic Chem., (2010).     

High-affinity interactions of ligands at recombinant Guinea pig 5HT7 receptors

The serotonin 5HT₇ receptor has been implicated in numerous physiological and pathological processes from circadian rhythms [1] to depression and schizophrenia. Clonal cell lines heterologously expressing recombinant receptors offer good models for understanding drug-receptor interactions and development of quantitative structure-activity relationships (QSAR). Comparative Molecular Field Analysis (CoMFA) is an important modern QSAR procedure that relates the steric and electrostatic fields of a set of aligned compounds to affinity. Here, we utilized CoMFA to predict affinity for a number of high-affinity ligands at the recombinant guinea pig 5HT₇ receptor. Using R-lisuride as the template, a final CoMFA model was derived using procedures similar to those of our recent papers [2, 3, 4] The final cross-validated model accounted for >85% of the variance in the compound affinity data, while the final non-cross validated model accounted for >99% of the variance. Model evaluation was done using cross-validation methods with groups of 5 ligands. Twenty cross-validation runs yielded an average predictive r²(q²) of 0.779 ± 0.015 (range: 0.669–0.867). Furthermore, 3D-chemical database search queries derived from the model yielded hit lists of promising agents with high structural similarity to the template. Together, these results suggest a possible basis for high-affinity drug action at 5HT₇ receptors.     

Chemoproteomic Approach to Explore the Target Profile of GPCR ligands: Application to 5‐HT1A and 5‐HT6 Receptors

Determination of the targets of a compound remains an essential aspect in drug discovery. A complete understanding of all binding interactions is critical to recognize in advance both therapeutic effects and undesired consequences. However, the complete polypharmacology of many drugs currently in clinical development is still unknown, especially in the case of G protein‐coupled receptor (GPCR) ligands. In this work we have developed a chemoproteomic platform based on the use of chemical probes to explore the target profile of a compound in biological systems. As proof of concept, this methodology has been applied to selected ligands of the therapeutically relevant serotonin 5‐HT_1A and 5‐HT₆ receptors, and we have identified and validated some of their off‐targets. This approach could be extended to other drugs of interest to study the targeted proteome in disease‐relevant systems.     

维甲化合物与维甲X受体相互作用模拟及QSAR研究

用分子对接确定了一系列RXR激动剂与受体的作用方式,与X衍射测得的晶体复合物中9-cis-RA的作用方式相近。对接后的配体-受体复和物经分子力学优化后更接近药效构象,两者相互作用能与活性具有一定的相关性,相关系数R^2=0.64。用活性构象建立的CoMFA模型比低能构象建立的CoMFA模型有更高的可信度,其交叉验证相关系q^2=0.791,非交叉验证相关系数γ^2=0.988,绝对误差SE=0.099,f6,33=456.8。     

Multiple-injection affinity capillary electrophoresis to estimate binding constants of receptors to ligands

Multiple-injection affinity capillary electrophoresis (MIACE) is used to determine binding constants (K _b) between receptors and ligands using as model systems vancomycin and teicoplanin from Streptomyces orientalis and Actinoplanes teichomyceticus, respectively, and their binding to D-Ala-D-Ala peptides and carbonic anhydrase B (CAB. EC 4.2.1.1) and the binding of the latter to arylsulfonamides. A sample plug containing a non-interacting standard is first injected followed by multiple plugs of sample containing the receptor and then a final injection of sample containing a second standard. Between each injection of sample, a small plug of buffer is injected which contains an increasing concentration of ligand to effect separation between the multiple injections of sample. Electrophoresis is then carried out in an increasing concentration of ligand in the running buffer. Continued electrophoresis results in a shift in the migration time of the receptor in the sample plugs upon binding to their respective ligand. Analysis of the change in the relative migration time ratio (RMTR) or electrophoretic mobility (μ) of the resultant receptor–ligand complex relative to the non-interacting standards, as a function of the concentration of ligand yields a value for K _b. The MIACE technique is a modification in the ACE method that allows for the estimation of binding affinities between biological interactions on a timescale faster than that found for standard ACE. In addition sample volume requirements for the technique are reduced compared to traditional ACE assays. These findings demonstrate the advantage of using MIACE to estimate binding parameters between receptors and ligands.     

Theoretical studies on opioid receptors and ligands. I. Molecular modeling and QSAR studies on the interaction mechanism of fentanyl analogs binding to μ‐opioid receptor

Based on our previous result of the three‐dimensional model of the μ‐opioid receptor, binding conformations of 13 fentanyl analogs and three‐dimensional structures for the complexs of these analogs with μ‐opioid receptor were constructed employing the molecular modeling method and our binding conformation search program for ligands (BCSPL). Energetic calculation and quantitative structure–activity relationship (QSAR) analysis indicated a good correlation between the calculated binding energies of fentanyl analogs and their binding affinities, pK_i's and pK's, and analgesic activities, − log ED₅₀'s. Based on the three‐dimensional models, the possible interaction mechanism of fentanyl analogs with μ‐opioid receptor can be illustrated and the available structure–activity relationship of these analgesic agents can be explained reasonably. © 2000 John Wiley & Sons, Inc. Int J Quant Chem 78: 285–293, 2000     

Structure-based approach for the study of estrogen receptor binding affinity and subtype selectivity

Estrogens exert important physiological effects through the modulation of two human estrogen receptor (hER) subtypes, alpha (hERalpha) and beta (hERbeta). Because the levels and relative proportion of hERalpha and hERbeta differ significantly in different target cells, selective hER ligands could target specific tissues or pathways regulated by one receptor subtype without affecting the other. To understand the structural and chemical basis by which small molecule modulators are able to discriminate between the two subtypes, we have applied three-dimensional target-based approaches employing a series of potent hER-ligands. Comparative molecular field analysis (CoMFA) studies were applied to a data set of 81 hER modulators, for which binding affinity values were collected for both hERalpha and hERbeta. Significant statistical coefficients were obtained (hERalpha, q(2) = 0.76; hERbeta, q(2) = 0.70), indicating the internal consistency of the models. The generated models were validated using external test sets, and the predicted values were in good agreement with the experimental results. Five hER crystal structures were used in GRID/PCA investigations to generate molecular interaction fields (MIF) maps. hERalpha and hERbeta were separated using one factor. The resulting 3D information was integrated with the aim of revealing the most relevant structural features involved in hER subtype selectivity. The final QSAR and GRID/PCA models and the information gathered from 3D contour maps should be useful for the design of novel hER modulators with improved selectivity.     

Multi-KNN-SVR组合预测在含氟化合物QSAR研究中的应用

为深入认识含氟农药生物活性与其结构之间的关系, 建立了理想的QSAR模型, 从化合物油水分配系数等7个分子结构描述符出发, 基于支持向量回归(SVR)和MSE最小原则, 经自动寻找最优核函数和非线性筛选描述符, 构建了多个K-最近邻(KNN)预测子模型. 再经非线性筛选获得保留子模型, 以保留子模型实施组合预测(Multi-KNN-SVR). 33种含氟化合物对5种不同病害生物活性的留一法组合预测结果表明, 采用非线性筛选描述符和KNN子模型能有效地提高预测精度, 基于多个KNN子模型的非线性组合能进一步提高预测性能. Multi-KNN-SVR组合预测在QSAR以及其它相关预测研究中具有广泛应用前景.     

Molecular modeling studies focused on 5-HT7 versus 5-HT1A selectivity. Discovery of novel phenylpyrrole derivatives with high affinity for 5-HT7 receptors

The present study discusses the well-known 5-HT7/5-HT1A selectivity issue through a new series of phenylpyrrole derivatives. The first hits emerged from a virtual screening performed on a chemolibrary. Further study led to an optimization of a preliminary 5-HT7 pharmacophore model. The importance of each pharmacophoric feature is confirmed, but these characteristics have to be coupled to geometric constraints in order to achieve a 5-HT7 selectivity. Indeed, 5-HT1A affinity probably arises from extended conformations, whereas a bent one appears to be best suited for 5-HT7 selectivity.     

Approaches to the description and prediction of the binding affinity of small-molecule ligands to macromolecular receptors

The influence of a xenobiotic compound on an organism is usually summarized by the expression biological activity. If a controlled, therapeutically relevant, and regulatory action is observed the compound has potential as a drug, otherwise its toxicity on the biological system is of interest. However, what do we understand by the biological activity? In principle, the overall effect on an organism has to be considered. However, because of the complexity of the interrelated processes involved, as a simplification primarily the "main action" on the organism is taken into consideration. On the molecular level, biological activity corresponds to the binding of a (low-molecular weight) compound to a macromolecular receptor, usually a protein. Enzymatic reactions or signal-transduction cascades are thereby influenced with respect to their function for the organism. We regard this binding as a process under equilibrium conditions; thus, binding can be described as an association or dissociation process. Accordingly, biological activity is expressed as the affinity of both partners for each other, as a thermodynamic equilibrium quantity. How well do we understand these terms and how well are they theoretically predictable today? The holy grail of rational drug design is the prediction of the biological activity of a compound. The processes involving ligand binding are extremely complicated, both ligand and protein are flexible molecules, and the energy inventory between the bound and unbound states must be considered in aqueous solution. How sophisticated and reliable are our experimental approaches to obtaining the necessary insight? The present review summarizes our current understanding of the binding affinity of a small-molecule ligand to a protein. Both theoretical and empirical approaches for predicting binding affinity, starting from the three-dimensional structure of a protein-ligand complex, will be described and compared. Experimental methods, primarily microcalorimetry, will be discussed. As a perspective, our own knowledge-based approach towards affinity prediction and experimental data on factorizing binding contributions to protein-ligand binding will be presented.     

Scavenger receptors: diverse activities and promiscuous binding of polyanionic ligands

Scavenger receptors are a diverse family of proteins that share a common property - the binding of modified lipoprotein - but they have recently been shown to recognise a diverse range of ligands. Understanding the molecular interaction of receptor-ligand binding should provide insight into how scavenger receptors contribute to important biological processes.     

Subtype selectivity and flexibility of ionotropic glutamate receptors upon antagonist ligand binding

The binding modes of a set of known ionotropic glutamate receptor antagonist-ligands have been studied using homology modeling, molecular docking, molecular dynamics (MD) simulations and ab initio quantum mechanical calculations. The core structure of the studied ligands is the decahydroisoquinoline ring, which has a carboxylic acid group at position three and different negatively-charged substituents (R) at position six. The binding affinities of these molecules have been reported earlier. From the current study, the carboxylate group of the decahydroisoquinoline ring hydrogen bonds with Arg485, the amino group with Pro478 and Thr480, and the negatively charged substituent R interacts with the positively charged N-terminus of helix-F. The subtype selectivity of these ligands seems to be strongly dependent on the amino acid at position 650 (GluR2: leucine, GluR5: valine), which affects the conformation of the ligand and ligand-receptor interactions, but depends considerably on the size of the R-group of the ligand. In addition, the MD simulations also revealed that the relative positions of the S1 and S2 domains can alter significantly showing different "closure" and "rotational movements" depending on the antagonist-ligand that is bound. Accordingly, molecular docking of antagonist ligands into static crystal structures cannot sufficiently explain ligand binding and subtype selectivity.     

Molecular dynamics of 5-HT1A and 5-HT2A serotonin receptors with methylated buspirone analogues

In the present study experimentally determined ligand selectivity of three methylated buspirone analogues (denoted as MM2, MM5 and P55) towards 5-HT_1A and 5-HT_2A serotonin receptors was theoretically investigated on a molecular level. The relationships between the ligand structure and 5-HT_1A and 5-HT_2A receptor affinities were studied and the results were found to be in agreement with the available site-directed mutagenesis and binding affinity data. Molecular dynamics (MD) simulations of ligand-receptor complexes were performed for each investigated analogue, docked twice into the central cavity of 5-HT_1A/5-HT_2A, each time in a different orientation. Present results were compared with our previous theoretical results, obtained for buspirone and its non-methylated analogues. It was found that due to the presence of the methyl group in the piperazine ring the ligand position alters and the structure of the ligand-receptor complex is modified. Further, the positions of derivatives with pyrimidinyl aromatic moiety and quinolinyl moiety are significantly different at the 5-HT_2A receptor. Thus, methylation of such derivatives alters the 3D structures of ligand-receptor complexes in different ways. The ligand-induced changes of the receptor structures were also analysed. The obtained results suggest, that helical domains of both receptors have different dynamical behaviour. Moreover, both location and topography of putative binding sites for buspirone analogues are different at 5-HT_1A and 5-HT_2A receptors.     

Computer modeling of binding of diverse weak toxins to nicotinic acetylcholine receptors

Weak toxins are the "three-fingered" snake venoms toxins grouped together by having an additional disulfide in the N-terminal loop I. In general, weak toxins have low toxicity, and biological targets have been identified for some of them only, recently by detecting the effects on the nicotinic acetylcholine receptors (nAChR). Here the methods of docking and molecular dynamics simulations are used for comparative modeling of the complexes between four weak toxins of known spatial structure (WTX, candoxin, bucandin, gamma-bungarotoxin) and nAChRs. WTX and candoxin are those toxins whose blocking of the neuronal alpha7- and muscle-type nAChR has been earlier shown in binding assays and electrophysiological experiments, while for the other two toxins no such activity has been reported. Only candoxin and WTX are found here to give stable solutions for the toxin-nAChR complexes. These toxins appear to approach the binding site similarly to short alpha-neurotoxins, but their final position resembles that of alpha-cobratoxin, a long alpha-neurotoxin, in the complex with the acetylcholine-binding protein. The final spatial structures of candoxin and WTX complexes with the alpha7 neuronal or muscle-type nAChR are very similar and do not provide immediate answer why candoxin has a much higher affinity than WTX, but both of them share a virtually irreversible mode of binding to one or both these nAChR subtypes. Possible explanation comes from docking and MD simulations which predict fast kinetics of candoxin association with nAChR, no gross changes in the toxin conformation (with smaller toxin flexibility on alpha7 nAChR), while slow WTX binding to nAChR is associated with slow irreversible rearrangement both of the tip of the toxin loop II and of the binding pocket residues locking finally the toxin molecule. Computer modeling showed that the additional disulfide in the loop I is not directly involved in receptor binding of WTX and candoxin, but it stabilizes the structure of loop I which plays an important role in toxin delivery to the binding site. In summary, computer modeling visualized possible modes of binding for those weak toxins which interact with the nAChR, provided no solutions for those weak toxins whose targets are not the nAChRs, and demonstrated that the additional disulfide in loop I cannot be a sound criteria for joining all weak toxins into one group; the conclusion about the diversity of weak toxins made from computer modeling is in accord with the earlier phylogenetic analysis.     

Estimation of binding constants of receptors and ligands by affinity capillary electrophoresis

An estimation method for determination of binding constants of receptors to ligands by affinity capillary electrophoresis was evaluated. On the basis of the theories of pseudostationary phase or so-called dynamic stationary phase, the retention factor (k) was used to represent the interaction between the receptor and ligand. k could be easily deduced from the migration times of the ligand and the receptor. Then, with the linear relationship of k versus the concentration of ligand in the running buffer, the binding constant K _b was calculated from the slope and intercept. In order to test its feasibility, the calculation method was demonstrated using three model systems: the interactions between vancomycin and N-acetyl-d-Ala-d-Ala, ristocetin and N-acetyl-d-Ala-d-Ala, and carbonic anhydrase B and an arylsulfonamide. Estimated binding constants were compared with those determined by other techniques. The results showed that this estimation method was reliable. This calculation method offers a simple and easy approach to estimating binding constants of ligands to receptors.     

Through-a-chip partial filling affinity capillary electrophoresis for estimating binding constants of ligands to receptors

In this paper, we describe the development of a microfluidic/capillary electrophoresis (CE) technique employing partial filling affinity capillary electrophoresis (PFACE) to estimate binding constants of ligands to receptors using as model systems carbonic anhydrase B (CAB, EC 4.2.1.1) and vancomycin from Streptomyces orientalis. Using multilayer soft lithography (MSL), a microfluidic device (MD) consisting of fluid and control channels is fabricated and fitted with an external capillary column. Multiple flow channels allows for manipulation of a zone of ligand and sample containing receptor and non-interacting standards into the MD and subsequently into the capillary column. Upon electrophoresis the sample components migrate into the zone of ligand where equilibrium is established. Changes in migration time of the receptor are used in the analysis to obtain a value for the binding interaction. The manipulation of small volumes of solution on the MD minimizes the need of time-consuming pipetting steps.