Classifying G-protein coupled receptors with bagging classification tree

G-protein coupled receptors (GPCRs) play a key role in different biological processes, such as regulation of growth, death and metabolism of cells. They are major therapeutic targets of numerous prescribed drugs. However, the ligand specificity of many receptors is unknown and there is little structural information available. Bioinformatics may offer one approach to bridge the gap between sequence data and functional knowledge of a receptor. In this paper, we use a bagging classification tree algorithm to predict the type of the receptor based on its amino acid composition. The prediction is performed for GPCR at the sub-family and sub-sub-family level. In a cross-validation test, we achieved an overall predictive accuracy of 91.1% for GPCR sub-family classification, and 82.4% for sub-sub-family classification. These results demonstrate the applicability of this relative simple method and its potential for improving prediction accuracy.     

Structure-activity relationship studies of gymnocin-A

The structural elements required for cytotoxicity of gymnocin-A, a polycyclic ether isolated from the red tide-forming dinoflagellate, Karenia mikimotoi, were investigated by the total synthesis and evaluation of the structural analogues. The results of the structure-activity relationship studies indicated that the α,β-unsaturated aldehyde functionality of the side chain as well as the molecular length were needed for exhibiting the cytotoxicity of gymnocin-A.     

Antibodies against G-protein coupled receptors: novel uses in screening and drug development

Antibodies are components of the body's humoral immune system that are generated in response to foreign pathogens. Modern biomedical research has employed these very specific and efficient molecules designed by nature in the diagnosis of diseases, localization of gene products as well as in the rapid screening of targets for drug discovery and testing. In addition, the introduction of antibodies with fluorescent or enzymatic tags has significantly contributed to advances in imaging and microarray technology, which are revolutionizing disease research and the search for effective therapeutics. More recently antibodies have been used in the isolation of dimeric G protein-coupled receptor (GPCR) complexes. In this review, we discuss antibodies as powerful research tools for studying GPCRs, and their potential to be developed as drugs themselves.     

High throughput screening of G-protein coupled receptors via flow cytometry

The molecular assemblies of signal transduction components, for example kinases and their target proteins or receptor-ligand complexes and intracellular signaling molecules, are critical for biological functions in cells. To better understand the interactions of these molecular assemblies and to screen for new pharmaceutics that could control and modulate these types of interactions, we have focused on developing high throughput approaches for the analysis of G-protein coupled receptors via flow cytometry. Flow cytometry offers a number of advantages including real-time collection of multicomponent data, and together with improvements in sample handling, the high throughput sampling rate is up to 100 samples per minute. For our targets, assemblies of solubilized GPCRs, a screening platform of a dextran bead has proven to be flexible, allowing different surface chemistries on the beads. The bead can be either ligand-labeled or have epitope-linked proteins attached to the bead surface, enabling several molecular assemblies to be constructed and analyzed. A major improvement with this system is that for screening ligands for GPCRs the underlying mechanism of action for these compounds can be investigated and incorporated into the definition of a 'hit'. Our current screening system is capable of simultaneously distinguishing GPCR agonists and antagonists.     

A combined ligand-based and target-based drug design approach for G-protein coupled receptors: application to salvinorin A,a selective kappa opioid receptor agonist

Combined ligand-based and target-based drug design approaches provide a synergistic advantage over either method individually. Therefore, we set out to develop a powerful virtual screening model to identify novel molecular scaffolds as potential leads for the human KOP (hKOP) receptor employing a combined approach. Utilizing a set of recently reported derivatives of salvinorin A, a structurally unique KOP receptor agonist, a pharmacophore model was developed that consisted of two hydrogen bond acceptor and three hydrophobic features. The model was cross-validated by randomizing the data using the CatScramble technique. Further validation was carried out using a test set that performed well in classifying active and inactive molecules correctly. Simultaneously, a bovine rhodopsin based “agonist-bound” hKOP receptor model was also generated. The model provided more accurate information about the putative binding site of salvinorin A based ligands. Several protein structure-checking programs were used to validate the model. In addition, this model was in agreement with the mutation experiments carried out on KOP receptor. The predictive ability of the model was evaluated by docking a set of known KOP receptor agonists into the active site of this model. The docked scores correlated reasonably well with experimental pK _i values. It is hypothesized that the integration of these two independently generated models would enable a swift and reliable identification of new lead compounds that could reduce time and cost of hit finding within the drug discovery and development process, particularly in the case of GPCRs.Electronic supplementary material Supplementary material is available in the online version of this article at and is accessible for authorized users.     

Ab initio computational modeling of long loops in G-protein coupled receptors

A newly developed approach for predicting the structure of segments that connect known elements of secondary structure in proteins has been applied to some of the longer loops in the G-protein coupled receptors (GPCRs) rhodopsin and the dopamine receptor D2R. The algorithm uses Monte Carlo (MC) simulation in a temperature annealing protocol combined with a scaled collective variables (SCV) technique to search conformation space for loop structures that could belong to the native ensemble. Except for rhodopsin, structural information is only available for the transmembrane helices (TMHs), and therefore the usual approach of finding a single conformation of lowest energy has to be abandoned. Instead the MC search aims to find the ensemble located at the absolute minimum free energy, i.e., the native ensemble. It is assumed that structures in the native ensemble can be found by an MC search starting from any conformation in the native funnel. The hypothesis is that native structures are trapped in this part of conformational space because of the high-energy barriers that surround the native funnel. In this work it is shown that the crystal structure of the second extracellular loop (e2) of rhodopsin is a member of this loop’s native ensemble. In contrast, the crystal structure of the third intracellular loop is quite different in the different crystal structures that have been reported. Our calculations indicate, that of three crystal structures examined, two show features characteristic of native ensembles while the other one does not. Finally the protocol is used to calculate the structure of the e2 loop in D2R. Here, the crystal structure is not known, but it is shown that several side chains that are involved in interaction with a class of substituted benzamides assume conformations that point into the active site. Thus, they are poised to interact with the incoming ligand.     

环氧酮肽蛋白酶体抑制剂的构效关系及基于分子相似性的分子设计

针对56个环氧酮肽衍生物,分别采用比较分子场分析(comparative molecular field analysis,CoMFA)、比较分子相似性形状指数分析(comparative molecular similarity indices analysis,CoMSIA)、Topomer CoMFA、Holo-gram QSAR(HQSAR)以及基于一维和二维描述符的支持向量机(support vector machine,SVM)方法进行了细致的构效关系研究。研究显示:通过引入一维和二维描述符的SVM建模方法,避免了柔性分子在三维构效关系研究中的构象选择和叠合难题,亦可有效避免过拟合现象的发生。所建最优SVM模型的决定系数R2、均方根误差(RMS)、交互验证系数Q2和外部预测R2pred分别为0.681,0.436,0.572和0.641。分析结果显示:电性、拓扑特征、疏水性和分子体积是影响环氧酮肽蛋白酶体抑制活性的主要因素。在此基础上,以活性最高样本分子(CID:42638286的)为模板,基于相似性评价方法对其侧链进行设计,结合Lipinski"5规则"类药性筛选,共得到12个新颖目标分子,且预测活性均达到纳摩尔水平。     

Structure-activity relationship studies of the two-component lantibiotic haloduracin

The lantibiotic haloduracin consists of two posttranslationally processed peptides, Halalpha and Halbeta, which act in synergy to provide bactericidal activity. An in vitro haloduracin production system was used to examine the biological impact of disrupting individual thioether rings in each peptide. Surprisingly, the Halalpha B ring, which contains a highly conserved CTLTXEC motif, was expendable. This motif has been proposed to interact with haloduracin's predicted target, lipid II. Exchange of the glutamate residue in this motif for alanine or glutamine completely abolished antibacterial activity. This study also established that Halalpha-Ser26 and Halbeta-Ser22 escape dehydration, requiring revision of the Halbeta structure previously proposed. Extracellular proteases secreted by the producer strain can remove the leader peptide, and the Halalpha cystine that is dispensable for bioactivity protects Halalpha from further proteolytic degradation.     

Structure-activity relationship studies of illudins: analogues possessing a spiro-cyclobutane ring

Bicyclic and tricyclic analogues of anticancer sesquiterpene illudin S have been synthesized. These contain a spiro-cyclobutane instead of spiro-cyclopropane structure. The cytotoxicity of the former is less than that of the corresponding cyclopropane-containing compounds.     

Getting it together: signal transduction in G-protein coupled receptors by association of receptor domains

The mechanism of signal transduction by G-protein coupled receptors is unknown. Here, we propose that these receptors signal in a way that is qualitatively similar to that seen in the chemokine and endocrine hormone receptor families; the signal occurs when two domains of the receptor are brought together, although this is not the only requirement for signaling.     

Improving homology modeling of G-protein coupled receptors through multiple-template derived conserved inter-residue interactions

Journal of Computer-Aided Molecular Design - Evidenced by the three-rounds of G-protein coupled receptors (GPCR) Dock competitions, improving homology modeling methods of helical transmembrane...     

Structure-guided design of CPPC-paired disulfide-rich peptide libraries for ligand and drug discovery

Peptides constrained through multiple disulfides (or disulfide-rich peptides, DRPs) have been an emerging frontier for ligand and drug discovery. Such peptides have the potential to combine the binding capability of biologics with the stability and bioavailability of smaller molecules. However, DRPs with stable three-dimensional (3D) structures are usually of natural origin or engineered from natural ones. Here, we report the discovery and identification of CPPC (cysteine–proline–proline–cysteine) motif-directed DRPs with stable 3D structures (i.e., CPPC–DRPs). A range of new CPPC–DRPs were designed or selected from either random or structure–convergent peptide libraries. Thus, for the first time we revealed that the CPPC–DRPs can maintain diverse 3D structures by taking advantage of constraints from unique dimeric CPPC mini-loops, including irregular structures and regular α-helix and β-sheet folds. New CPPC–DRPs that can specifically bind the receptors (CD28) on the cell surface were also successfully discovered and identified using our DRP-discovery platform. Overall, this study provides the basis for accessing an unconventional peptide structure space previously inaccessible by natural DRPs and computational designs, inspiring the development of new peptide ligands and therapeutics.

CPPC-paired disulfide-rich peptides with stable 3D structures have been discovered through rational library design and screening, providing unconventional peptide scaffolds for the development of new peptide therapeutics.     

Development and application of hybrid structure based method for efficient screening of ligands binding to G-protein coupled receptors

G-protein coupled receptors (GPCRs) comprise a large superfamily of proteins that are targets for nearly 50% of drugs in clinical use today. In the past, the use of structure-based drug design strategies to develop better drug candidates has been severely hampered due to the absence of the receptor’s three-dimensional structure. However, with recent advances in molecular modeling techniques and better computing power, atomic level details of these receptors can be derived from computationally derived molecular models. Using information from these models coupled with experimental evidence, it has become feasible to build receptor pharmacophores. In this study, we demonstrate the use of the Hybrid Structure Based (HSB) method that can be used effectively to screen and identify prospective ligands that bind to GPCRs. Essentially; this multi-step method combines ligand-based methods for building enriched libraries of small molecules and structure-based methods for screening molecules against the GPCR target. The HSB method was validated to identify retinal and its analogues from a random dataset of ∼300,000 molecules. The results from this study showed that the 9 top-ranking molecules are indeed analogues of retinal. The method was also tested to identify analogues of dopamine binding to the dopamine D2 receptor. Six of the ten top-ranking molecules are known analogues of dopamine including a prodrug, while the other thirty-four molecules are currently being tested for their activity against all dopamine receptors. The results from both these test cases have proved that the HSB method provides a realistic solution to bridge the gap between the ever-increasing demand for new drugs to treat psychiatric disorders and the lack of efficient screening methods for GPCRs. Electronic supplementary material Supplementary material is available in the online version of this article at and is accessible for authorized users.     

Structure-activity relationship studies on CXCR4 antagonists having cyclic pentapeptide scaffolds

Structure-activity relationship studies on CXCR4 antagonists, which were previously found by using cyclic pentapeptide libraries, were performed to optimize side-chain functional groups, involving conformationally constrained analogues. In addition, a new lead of cyclic pentapeptides with the introduction of a novel pharmacophore was developed.     

Rational design of affinity peptide ligand by flexible docking simulation

Rational design of affinity peptide ligands of proteins by flexible docking simulation is performed using the SYBYL program package. This approach involves the use of experimental data to verify a scoring function that can be used to assess the affinity of a peptide for its target protein. The enzyme-linked immunosorbent assay (ELISA) data of several peptides displayed on phage surfaces for insulin and lysozyme, respectively, reported in literature are used for the purpose. It is found that the absolute values of the Dscore calculated from the docking correspond well to the ELISA data that relate to the affinity between the peptides and the target molecule. So, the Dscore function is used to assess the affinity of docked peptides in a pentapeptide library designed on the basis of protein (alpha-amylase) structure. As a result, a pentapeptide with a high Dscore value is selected and a hexapeptide (FHENWS) is built by linking serine to its C-terminal to lengthen the peptide. Molecular surface analysis with the MOLCAD program reveals that electrostatic interactions (including hydrogen bonds) and Van der Waals forces contribute to the affinity of the hexapeptide for alpha-amylase. Chromatographic experiments with the immobilized peptide have given further evidence for this observation. Adsorption isotherm described by the Langmuir equation indicates that the apparent binding constant of alpha-amylase to the immobilized hexapeptide was 2.5x10(5)L/mol. Finally, high affinity and specificity of the affinity adsorbent is exemplified by the purification of alpha-amylase from crude fermentation broth of Bacillus subtilis.     

Structure-activity relationship of Ca2+ channel blockers: A study using conformational analysis and chemometric methods

Summary A structure-activity relationship study has been done on 8 compounds with the activity known as Ca²⁺ channel blockers. Conformational analysis was carried out using a molecular mechanics method. The 3D-QSAR approach was used and the most polar functional groups present in all the molecules were considered. Eight interatomic distances are necessary to define the relative spatial disposition of these relevant molecular fragments. The structure-activity relationship between interatomic distances and biological activity was performed using statistic and chemometric methods. In particular, with Principal Component Analysis, it was possible to reduce the number of interatomic distances: only six of the eight distances are sufficient to describe the system in a useful way. A classification method was iteratively used to select the most probable conformations linked to the biological activity and to build a model able to classify conformations according to their biological behaviour. Cluster analysis on the active selected conformations subsequently allowed the identification of two different geometrical patterns for the active compounds. Finally the validity of the model was verified by correctly predicting the activity of other molecules not used in the construction of the model but possessing known activity.