Hydroxamate类抑制剂与MMP-2的分子对接研究

通过分子动力学模拟研究了MMP-2和hydroxamate抑制剂之间的作用模式。在分子动力学模拟中,对于催化区的锌离子和其共价结合的配体(包括抑制剂和组氨酸)采用了键合的模型。从模拟的结果可以看到,R^1取代基和MMP-2的S1疏水口袋中的部分残基能形成很好的几何匹配,从而可以产生很强的范德华和疏水相互作用。模拟结果也表明,两个抑制剂和MMP-2之间分别能形成5个和8个氢键,抑制剂B比A活性更高的原因就是能够形成更加有利氢键作用模式。在整个模拟过程中,催化锌都能保持好的五配位形式,配位键的长度也处于稳定的状态,预测得到的MMP-2和其抑制剂的相互作用模式对于全新抑制剂的设计提供了非常重要的结构信息。     

Key issues in the computational simulation of GPCR function: representation of loop domains

Some key concerns raised by molecular modeling and computational simulation of functional mechanisms for membrane proteins are discussed and illustrated for members of the family of G protein coupled receptors (GPCRs). Of particular importance are issues related to the modeling and computational treatment of loop regions. These are demonstrated here with results from different levels of computational simulations applied to the structures of rhodopsin and a model of the 5-HT2A serotonin receptor, 5-HT2AR. First, comparative Molecular Dynamics (MD) simulations are reported for rhodopsin in vacuum and embedded in an explicit representation of the membrane and water environment. It is shown that in spite of a partial accounting of solvent screening effects by neutralization of charged side chains, vacuum MD simulations can lead to severe distortions of the loop structures. The primary source of the distortion appears to be formation of artifactual H-bonds, as has been repeatedly observed in vacuum simulations. To address such shortcomings, a recently proposed approach that has been developed for calculating the structure of segments that connect elements of secondary structure with known coordinates, is applied to 5-HT2AR to obtain an initial representation of the loops connecting the transmembrane (TM) helices. The approach consists of a simulated annealing combined with biased scaled collective variables Monte Carlo technique, and is applied to loops connecting the TM segments on both the extra-cellular and the cytoplasmic sides of the receptor. Although this initial calculation treats the loops as independent structural entities, the final structure exhibits a number of interloop interactions that may have functional significance. Finally, it is shown here that in the case where a given loop from two different GPCRs (here rhodopsin and 5-HT2AR) has approximately the same length and some degree of sequence identity, the fold adopted by the loops can be similar. Thus, in such special cases homology modeling might be used to obtain initial structures of these loops. Notably, however, all other loops in these two receptors appear to be very different in sequence and structure, so that their conformations can be found reliably only by ab initio, energy based methods and not by homology modeling.     

毒蕈碱型M1受体的同源模建和分子对接

采用同源模建方法对M1受体的三维结构进行了模拟, 将得到的模型分别与M受体完全激动剂乙酰胆碱和M1受体选择性激动剂占诺美林进行分子对接, 形成非特异性激动和特异性激动的受体-配体复合物. 用分子动力学模拟方法分别将未与小分子对接的M1受体、M1受体-乙酰胆碱复合物、M1受体-占诺美林复合物置于磷脂双膜中模拟10 ns. 将模拟后的蛋白质结构与包含活性分子的测试库对接并将结果打分, 以top5%富集因子(EF)作为评价依据, 用占诺美林优化后的M1受体模型的EF为8.0, 用乙酰胆碱优化后M1受体模型的EF为6.5, 非复合物的EF为1.5. 说明M1受体选择性激动剂复合物进行分子动力学模拟后得到的三维结构模型比较合理, 可以作为化合物虚拟筛选的模型对新化合物进行虚拟筛选, 为找到新的选择性M1受体激动剂奠定了基础.     

Molecular dynamics simulations of the ligand-induced chemical information transfer in the 5-HT(1A) receptor

Comparative molecular dynamics simulations of the 5-HT(1A) receptor in its empty as well as agonist- (i.e. active) and antagonist-bound (i.e. nonactive) forms have been carried out. The agonists 5-HT and (R)-8-OH-DPAT as well as the antagonist WAY100635 have been employed. The results of this study strengthen the hypothesis that the receptor portions close to the E/DRY/W motif, with prominence to the cytosolic extensions of helices 3 and 6, are particularly susceptible to undergo structural modification in response to agonist binding. Despite the differences in the structural/dynamics behavior of the two agonists when docked into the 5-HT(1A) receptor, they both exert a destabilization of the intrahelical and interhelical interactions found in the empty and antagonist-bound receptor forms between the arginine of the E/DRY sequence and both D133(3.49) and E340(6.30). For both agonists, the chemical information transfer from the extracellular to the cytosolic domains is mediated by a cluster of aromatic amino acids in helix 6, following the ligand interaction with selected amino acids in the extracellular half of the receptor, such as D116(3.32), S199(5.42), Y195(5.38), and F361(6.51). A significant reduction in the bend at P360(6.50), as compared to the empty and the antagonist-bound receptor forms, is one of the features of the agonist-bound forms that is related to the breakage of the interhelical salt bridge between the E/DRY arginine and E340(6.30). Another structural feature, shared by the agonist-bound receptor forms and not by the empty and antagonist-bound forms, is the detachment of helices 2 and 4, as marked by the movement of W161(4.50) away from helix 2, toward the membrane space.     

Atomistic insights into rhodopsin activation from a dynamic model

Rhodopsin, the light sensitive receptor responsible for blue-green vision, serves as a prototypical G protein-coupled receptor (GPCR). Upon light absorption, it undergoes a series of conformational changes that lead to the active form, metarhodopsin II (META II), initiating a signaling cascade through binding to the G protein transducin (G(t)). Here, we first develop a structural model of META II by applying experimental distance restraints to the structure of lumi-rhodopsin (LUMI), an earlier intermediate. The restraints are imposed by using a combination of biased molecular dynamics simulations and perturbations to an elastic network model. We characterize the motions of the transmembrane helices in the LUMI-to-META II transition and the rearrangement of interhelical hydrogen bonds. We then simulate rhodopsin activation in a dynamic model to study the path leading from LUMI to our META II model for wild-type rhodopsin and a series of mutants. The simulations show a strong correlation between the transition dynamics and the pharmacological phenotypes of the mutants. These results help identify the molecular mechanisms of activation in both wild type and mutant rhodopsin. While static models can provide insights into the mechanisms of ligand recognition and predict ligand affinity, a dynamic model of activation could be applicable to study the pharmacology of other GPCRs and their ligands, offering a key to predictions of basal activity and ligand efficacy.     

Correlation of protein structure and dynamics to scalar couplings across hydrogen bonds

NMR-observable scalar couplings across hydrogen bonds in nucleic acids and proteins present a quantitative measure for the geometry and--by the implicit experimental time averaging--dynamics of hydrogen bonds. We have carried out in-depth molecular dynamics (MD) simulations with various force fields on three proteins: ubiquitin, the GB1 domain of protein G, and the SMN Tudor domain, for which experimental h3JNC' scalar couplings of backbone hydrogen bonds and various high-resolution X-ray structures are available. Theoretical average values for h3JNC' were calculated from the snapshots of these MD simulations either by density functional theory or by a geometric parametrization (Barfield, M. J. Am. Chem. Soc. 2002, 124, 4158-4168). No significant difference was found between the two methods. The results indicate that time-averaging using explicit water solvation in the MD simulations improves significantly the agreement between experimental and theoretical values for the lower resolution structures ubiquitin (1.8 A), Tudor domain (1.8 A), and protein G (2.1 A). Only marginal improvement is found for the high-resolution structure (1.1 A) of protein G. Hence, experimental h3JNC' values are compatible with a static, high-resolution structural model. The MD averaging of the low-resolution structures moves the averages of the rHO distance and the H...O=C angle theta closer to their respective values in the high-resolution structures, thereby improving the agreement using experimental h3JNC' data. In contrast, MD averaging with implicit water models deteriorates the agreement with experiment for all proteins. The differing behavior can be explained by an artifactual lengthening of H-bonds caused by the implicit water models.     

DIRECT‐ID: An automated method to identify and quantify conformational variations—application to β2‐adrenergic GPCR

The conformational dynamics of a macromolecule can be modulated by a number of factors, including changes in environment, ligand binding, and interactions with other macromolecules, among others. We present a method that quantifies the differences in macromolecular conformational dynamics and automatically extracts the structural features responsible for these changes. Given a set of molecular dynamics (MD) simulations of a macromolecule, the norms of the differences in covariance matrices are calculated for each pair of trajectories. A matrix of these norms thus quantifies the differences in conformational dynamics across the set of simulations. For each pair of trajectories, covariance difference matrices are parsed to extract structural elements that undergo changes in conformational properties. As a demonstration of its applicability to biomacromolecular systems, the method, referred to as DIRECT‐ID, was used to identify relevant ligand‐modulated structural variations in the β₂‐adrenergic (β₂AR) G‐protein coupled receptor. Micro‐second MD simulations of the β₂AR in an explicit lipid bilayer were run in the apo state and complexed with the ligands: BI‐167107 (agonist), epinephrine (agonist), salbutamol (long‐acting partial agonist), or carazolol (inverse agonist). Each ligand modulated the conformational dynamics of β₂AR differently and DIRECT‐ID analysis of the inverse‐agonist vs. agonist‐modulated β₂AR identified residues known through previous studies to selectively propagate deactivation/activation information, along with some previously unidentified ligand‐specific microswitches across the GPCR. This study demonstrates the utility of DIRECT‐ID to rapidly extract functionally relevant conformational dynamics information from extended MD simulations of large and complex macromolecular systems. © 2015 Wiley Periodicals, Inc.     

An inhibitory compound against the interaction between G alpha(s) and the third intracellular loop region of serotonin receptor subtype 6 (5-HT6) disrupts the signaling pathway of 5-HT6

Serotonin receptor subtype 6 (5-HT(6)) is a neurotransmitter receptor, which is involved in various brain functions such as memory and mood. It mediates signaling via the interaction with a stimulatory G-protein. Especially, the third intracellular loop (iL3) of 5-HT(6) and the alpha subunit of stimulatory G protein (G alpha(s)) are responsible for the signaling process of 5-HT(6). Chemical compounds that could inhibit the interaction between the iL3 region of 5-HT(6) and G alpha(s) were screened from a chemical library consisted of 5,600 synthetic compounds. One of the identified compounds bound to G alpha(s) and effectively blocked the interaction between G alpha(s) and the iL3 region of 5-HT(6). The identified compound was further shown to reduce the serotonin-induced accumulation of cAMP in 293T cells transformed with 5-HT(6) cDNA. It also lowered the Ca(2+) efflux induced by serotonin in cells expressing 5-HT(6) and chimeric G alpha(s5/q). These results indicate that the interaction between the iL3 of 5-HT(6) and G alpha(s) can be exploited for screening of regulatory compounds against the signaling pathway of 5-HT(6).     

Selection of in silico drug screening results for G-protein-coupled receptors by using universal active probes

We developed a new protocol for in silico drug screening for G-protein-coupled receptors (GPCRs) using a set of "universal active probes" (UAPs) with an ensemble docking procedure. UAPs are drug-like compounds, which are actual active compounds of a variety of known proteins. The current targets were nine human GPCRs whose three-dimensional (3D) structures are unknown, plus three GPCRs, namely β(2)-adrenergic receptor (ADRB2), A(2A) adenosine receptor (A(2A)), and dopamine D3 receptor (D(3)), whose 3D structures are known. Homology-based models of the GPCRs were constructed based on the crystal structures with careful sequence inspection. After subsequent molecular dynamics (MD) simulation taking into account the explicit lipid membrane molecules with periodic boundary conditions, we obtained multiple model structures of the GPCRs. For each target structure, docking-screening calculations were carried out via the ensemble docking procedure, using both true active compounds of the target proteins and the UAPs with the multiple target screening (MTS) method. Consequently, the multiple model structures showed various screening results with both poor and high hit ratios, the latter of which could be identified as promising for use in in silico screening to find candidate compounds to interact with the proteins. We found that the hit ratio of true active compounds showed a positive correlation to that of the UAPs. Thus, we could retrieve appropriate target structures from the GPCR models by applying the UAPs, even if no active compound is known for the GPCRs. Namely, the screening result that showed a high hit ratio for the UAPs could be used to identify actual hit compounds for the target GPCRs.     

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 modeling of A1 and A2A adenosine receptors: comparison of rhodopsin- and beta2-adrenergic-based homology models through the docking studies

Adenosine receptors (ARs) are members of the superfamily of G protein-coupled receptors. The homology models of adenosine A1 and A2A receptors were constructed. The high-resolution X-ray structure of bovine rhodopsin and crystal structure of beta2-adrenergic receptor were used as templates. The binding sites of the A1 and A2A ARs were constructed by using data obtained from mutagenesis experiments as well as docking simulations of the respective AR antagonsists DPCPX and XAC. To compare rhodopsin- and beta2-adrenergic-based models, the binding mode of A1 (KW-3902, LUF-5437) and A2A (KW-6002, ZM-241385) ARs antagonists were also examined. The differences in the binding ability of both models were noted during the study. The beta2-adrenergic-based A2A AR model was much more capable to stabilize the ligand in the binding site cavity than the corresponding rhodopsin-based A2A AR model, however, such differences were not so clear in case of A1 AR models. It was suggested that for the A1 AR it is possible to use the crystal structure of rhodopsin as a template as well as beta2-adrenergic receptor, but for A2A AR, with the now available beta2-adrenergic receptor X-ray structure, docking studies should be avoided on the rhodopsin-based model. However, taking into account that the beta2AR shares about 31% of the residues with the AR in comparison to 21% in case of bRho, we suggest using beta2-adrenergic-based models for the A1 and A2A ARs for further in silico ligand screening also because of their generally better ability to stabilize ligands inside the binding pocket.     

Synthesis of conformationally constrained aryl- or heteroarylpiperazinyl derivatives of selected imides as 5-HT1A receptor ligands

The preparation of a number of cyclic imide 5-HT(1A) receptor ligand derivatives has been described. Their structures were conformationally constrained by introducing rigid linkers containing unsaturated bonds or aromatic benzene rings. These compounds are expected to possess anxiolytic and antidepressant activity.     

A first step towards the understanding of the 5-HT(3) receptor subunit heterogeneity from a computational point of view

The functional serotonin type-3 receptor (5-HT(3)-R), which is the target of many neuroactive drugs, is known to be a homopentamer made of five identical subunits A (5-HT(3A)-R) or a binary heteropentamer made of subunits A and B (5-HT(3A/B)-R) with a still debated arrangement and stoichiometry. This complex picture has been recently further complicated by the discovery of additional 5-HT(3)-R subunits, C, D, and E, which, similarly to the B subunit, are apparently able to form functional receptors only if co-expressed with subunit A. Being the binding site for both serotonin and antagonists (i.e. drugs) located at the extracellular interface between two adjacent subunits, the large variability of the 5-HT(3)-R composition becomes a crucial issue, since it can originate many different interfaces providing non-equivalent ligand binding sites and complicating the pharmacological modulation. Here, the different 5-HT(3)-R interfaces are analysed, on the bases of the structural conformations of previously built 3D homology models and of the known subunit sequences, by addressing their physicochemical characterization. The results confirm the presence of an aromatic cluster located in the core of the A-A interface as a key determinant for having an interface both stable and functional. This is used as a discriminant to make hypotheses about the capability of all the other possible interfaces constituted by the known 5-HT(3)-R sequences A, B, C, D, and E to build active receptors.     

GPCR structure-based virtual screening approach for CB2 antagonist search

The potential for therapeutic specificity in regulating diseases has made cannabinoid (CB) receptors one of the most important G-protein-coupled receptor (GPCR) targets in search for new drugs. Considering the lack of related 3D experimental structures, we have established a structure-based virtual screening protocol to search for CB2 bioactive antagonists based on the 3D CB2 homology structure model. However, the existing homology-predicted 3D models often deviate from the native structure and therefore may incorrectly bias the in silico design. To overcome this problem, we have developed a 3D testing database query algorithm to examine the constructed 3D CB2 receptor structure model as well as the predicted binding pocket. In the present study, an antagonist-bound CB2 receptor complex model was initially generated using flexible docking simulation and then further optimized by molecular dynamic and mechanical (MD/MM) calculations. The refined 3D structural model of the CB2-ligand complex was then inspected by exploring the interactions between the receptor and ligands in order to predict the potential CB2 binding pocket for its antagonist. The ligand-receptor complex model and the predicted antagonist binding pockets were further processed and validated by FlexX-Pharm docking against a testing compound database that contains known antagonists. Furthermore, a consensus scoring (CScore) function algorithm was established to rank the binding interaction modes of a ligand on the CB2 receptor. Our results indicated that the known antagonists seeded in the testing database can be distinguished from a significant amount of randomly chosen molecules. Our studies demonstrated that the established GPCR structure-based virtual screening approach provided a new strategy with a high potential for in silico identifying novel CB2 antagonist leads based on the homology-generated 3D CB2 structure model.     

神经介素B受体与拮抗剂、激动剂的分子模拟研究

大鼠神经介素B受体(rat neuromedin B receptor, rNMBR)属于G蛋白偶联受体(G-protein coupled receptor, GPCR) A家族的成员. GPCR的结构特征和在信号传导中的重要作用决定了其可以作为很好的药物靶标. 关于rNMBR与内源性激动剂神经介素B (neuromedin B, NMB)以及与非肽类拮抗剂pd168368作用机制的研究对于合理设计受体药物分子有重要的指导意义. 在这一研究中, 我们使用同源模建, 构建受体的三维结构, 进行分子对接和分子动力学的计算. 基于受体三维结构, 通过10 ns的空载受体、激动剂-受体、拮抗剂-受体的分子动力学模拟, 探讨受体与激动剂与拮抗剂的作用机制. 研究表明rNMB-R中跨膜(transmembrane, TM)螺旋3, 5, 6, 7参与配体的结合. NMB与受体的结合, 使受体转变为活性构象, 而受体同拮抗剂pd168368恰好相反.     

New serotonin 5-HT(6) ligands from common feature pharmacophore hypotheses

Serotonin 5-HT6 receptor antagonists are thought to play an important role in the treatment of psychiatry, Alzheimer's disease, and probably obesity. To find novel and potent 5-HT6 antagonists and to provide a new idea for drug design, we used a ligand-based pharmacophore to perform the virtual screening of a commercially available database. A three-dimensional common feature pharmacophore model was developed by using the HipHop program provided in Catalyst software and was used as a query for screening the database. A recursive partitioning (RP) model which can separate active and inactive compounds was used as a filtering system. Finally a sequential virtual screening procedure (SQSP) was conducted, wherein both the common feature pharmacophore and the RP model were used in succession to improve the results. Some of the hits were selected based on druglikeness, ADME properties, structural diversity, and synthetic accessibility for real biological evaluation. The best hit compound showed a significant IC50 value of 9.6 nM and can be used as a lead for further drug development.     

Mechanical properties of surfactant bilayer membranes from atomistic and coarse-grained molecular dynamics simulations

We use simulations to predict the stability and mechanical properties of two amphiphilic bilayer membranes. We carry out atomistic MD simulations and investigate whether it is possible to use an existing coarse-grained (CG) surfactant model to map the membrane properties. We find that certain membranes can be represented well by the CG model, whereas others cannot. Atomistic MD simulations of the erucate membrane yield a headgroup area per surfactant a(0) of 0.26 nm(2), an elastic modulus K(A) of 1.7 N/m, and a bending rigidity kappa of 5 k(B)T. We find that the CG model, with the right choice for the size and potential well depth of the head, correctly reproduces a(0), kappa, as well as the fluctuation spectrum over the whole range of q values. Atomistic MD simulations of EHAC, on the other hand, suggest that this membrane is unstable. This is indicated by the fact that kappa is of the order of k(B)T, which means that the interface is extremely flexible and diffuse, and K(A) is close to zero, which means that the surface tension is zero. We argue that the CG model can be used if the headgroups are uncharged, dipolar, or effectively dipolar due to headgroup charge screening induced by counterion condensation.     

Screening of 5-HT1A receptor antagonists using molecularly imprinted polymers

Molecular imprinting produces network polymers with recognition sites for imprint molecules. The high binding affinity and selectivity in conjunction with the polymers' physical robustness positions molecular imprinted polymers (MIPs) as candidates for use as preliminary screens in drug discovery. As such, MIPs can serve as crude mimics of native receptors. In an effort to evaluate the relationship between MIPs and native receptors, imprinted polymers for WAY-100635, an antagonist of the serotonin (5-HT) receptor subtype 5-HT1A were prepared. The resulting MIP P(WAY) was evaluated as an affinity matrix in the screening of serotonin receptor antagonists with known affinities for the native receptor. Rough correlations in affinity between the synthetic P(WAY) and native receptor 5-HT1A were found. These findings provide some support for the analogy between MIPs and native receptors and their possible use as surrogates.     

An improved relaxed complex scheme for receptor flexibility in computer-aided drug design

The interactions among associating (macro)molecules are dynamic, which adds to the complexity of molecular recognition. While ligand flexibility is well accounted for in computational drug design, the effective inclusion of receptor flexibility remains an important challenge. The relaxed complex scheme (RCS) is a promising computational methodology that combines the advantages of docking algorithms with dynamic structural information provided by molecular dynamics (MD) simulations, therefore explicitly accounting for the flexibility of both the receptor and the docked ligands. Here, we briefly review the RCS and discuss new extensions and improvements of this methodology in the context of ligand binding to two example targets: kinetoplastid RNA editing ligase 1 and the W191G cavity mutant of cytochrome c peroxidase. The RCS improvements include its extension to virtual screening, more rigorous characterization of local and global binding effects, and methods to improve its computational efficiency by reducing the receptor ensemble to a representative set of configurations. The choice of receptor ensemble, its influence on the predictive power of RCS, and the current limitations for an accurate treatment of the solvent contributions are also briefly discussed. Finally, we outline potential methodological improvements that we anticipate will assist future development. Rommie E. Amaro and Riccardo Baron contributed equally to this work.