Computational model of the complex between GR113808 and the 5-HT4 receptor guided by site-directed mutagenesis and the crystal structure of rhodopsin

Synthesis and structure-activity relationship studies in serotonin 5-HT4 receptor ligands based on a benzo[de][2,6]naphthridine scaffold

A small series of serotonin 5-HT4 receptor ligands has been designed from flexible 2-methoxyquinoline compounds 7a,b by applying the conformational constraint approach. Ligands 7a,b and the corresponding conformationally constrained analogues 8a-g were synthesized and their interactions with the 5-HT4 receptor were examined by measuring both binding affinity and the ability to promote or inhibit receptor-G protein coupling. Ester derivative 7a and conformationally constrained compound 8b were demonstrated to be the most interesting compounds showing a nanomolar 5-HT4R affinity similar to that shown by reference ligands cisapride (1) and RS-23,597-190 (4). The result was rationalized by docking studies in term of high similarity in the binding modalities of flexible 7a and conformationally constrained 8b. The intrinsic efficacy of some selected ligands was determined by evaluating the receptor-G protein coupling and the results obtained demonstrated that the nature and the position of substituents play a critical role in the interaction of these ligands with their receptor.

Preferential binding of allosteric modulators to active and inactive conformational states of metabotropic glutamate receptors

Metabotropic glutamate receptors (mGluRs) are G protein coupled receptors that play important roles in synaptic plasticity and other neuro-physiological and pathological processes. Allosteric mGluR ligands are particularly promising drug targets because of their modulatory effects--enhancing or suppressing the response of mGluRs to glutamate. The mechanism by which this modulation occurs is not known. Here, we propose the hypothesis that positive and negative modulators will differentially stabilize the active and inactive conformations of the receptors, respectively. To test this hypothesis, we have generated computational models of the transmembrane regions of different mGluR subtypes in two different conformations. The inactive conformation was modeled using the crystal structure of the inactive, dark state of rhodopsin as template and the active conformation was created based on a recent model of the light-activated state of rhodopsin. Ligands for which the nature of their allosteric effects on mGluRs is experimentally known were docked to the modeled mGluR structures using ArgusLab and Autodock softwares. We find that the allosteric ligand binding pockets of mGluRs are overlapping with the retinal binding pocket of rhodopsin, and that ligands have strong preferences for the active and inactive states depending on their modulatory nature. In 8 out of 14 cases (57%), the negative modulators bound the inactive conformations with significant preference using both docking programs, and 6 out of 9 cases (67%), the positive modulators bound the active conformations. Considering results by the individual programs only, even higher correlations were observed: 12/14 (86%) and 8/9 (89%) for ArgusLab and 10/14 (71%) and 7/9 (78%) for AutoDock. These findings strongly support the hypothesis that mGluR allosteric modulation occurs via stabilization of different conformations analogous to those identified in rhodopsin where they are induced by photochemical isomerization of the retinal ligand--despite the extensive differences in sequences between mGluRs and rhodopsin.

Modeling GPCRs

Many GPCR models have been built over the years for many different purposes, of which drug-design undoubtedly has been the most frequent one. The release of the structure of bovine rhodopsin in August 2000 enabled us to analyze models built before that period to learn things for the models we build today. We conclude that the GPCR modeling field is riddled with "common knowledge". Several characteristics of the bovine rhodopsin structure came as a big surprise, and had obviously not been predicted, which led to large errors in the models. Some of these surprises, however, could have been predicted if the modelers had more rigidly stuck to the rule that holds for all models, namely that a model should explain all experimental facts, and not just those facts that agree with the modeler's preconceptions.

Homology Modeling and Molecular Dynamics Simulations of the Mu Opioid Receptor in a Membrane-Aqueous System

Three types of opioid receptors-mu, delta, and kappa-belong to the rhodopsin subfamily in the G protein-coupled receptor superfamily. With the recent characterization of the high-resolution X-ray crystal structure of bovine rhodopsin, considerable attention has been focused on molecular modeling of these transmembrane proteins. In this study, a homology model of the mu opioid receptor was constructed based on the X-ray crystal structure of bovine rhodopsin. A phospholipid bilayer was built around the receptor, and two water layers were placed on both surfaces of the lipid bilayer. Molecular-dynamics simulations were carried out by using CHARMM for the entire system, which consisted of 316 amino acid residues, 92 phospholipid molecules, 8327 water molecules, and 11 chloride counter ions-40 931 atoms altogether. The whole system was equilibrated for 250 ps followed by another 2 ns dynamic simulation. The opioid ligand naltrexone was docked into the optimized model, and the critical amino acid residues for binding were identified. The mu opioid receptor homology model optimized in a complete membrane-aqueous system should provide a good starting point for further characterization of the binding modes for opioid ligands. Furthermore, the method developed herein will be applicable to molecular model building to other opioid receptors as well as other GPCRs.

New insights into the human 5-HT4 receptor binding site: exploration of a hydrophobic pocket

A body of evidences suggests that a hydrophobic pocket of the human 5-HT(4) receptor contributes to the high affinity of some bulky 5-HT(4) ligands. A thorough study of this pocket was performed using mutagenesis and molecular modeling. Ligand binding or competition studies with selected bulky ligands (RS39604, RS100235, [(3)H]GR113808 and ML11411) and small ligands (5-HT and ML10375) were carried out on wild-type and mutant receptors (W7.40A/F, Y7.43F, R3.28L) transiently transfected in COS-7 cells. The functional activity of the mutated receptors was evaluated by measuring the ability of 5-HT to stimulate adenylyl cyclase. For W7.40F mutation, no changes in the affinity of studied ligands and in the functional activity of the mutant receptor were observed, in contrary to W7.40A mutation, which abolished both binding of ligands and 5-HT-induced cAMP production. Mutation R3.28L revealed a totally silent receptor with a basal level of cAMP production similar to the mock control despite its ability to product cAMP in the presence of 5-HT. Moreover, a one order loss of affinity of RS39604 and a 45-fold increase of ML11411 affinity were observed. Mutation Y7.43F modified the affinity of GR113808, which displays a 13-fold lower affinity for the mutant than for the wild-type receptor. In conclusion, in the hydrophobic pocket, two polar amino acids are able to interact through hydrogen bonds with bulky ligands depending on their chemical properties. Moreover, these experimental data may validate the proposed new three-dimensional model of the human 5-HT(4) receptor.

Heavier-than-air flying machines are impossible

Many G protein-coupled receptor (GPCR) models have been built over the years. The release of the structure of bovine rhodopsin in August 2000 enabled us to analyze models built before that period to learn more about the models we build today. We conclude that the GPCR modelling field is riddled with 'common knowledge' similar to Lord Kelvin's remark in 1895 that "heavier-than-air flying machines are impossible", and we summarize what we think are the (im)possibilities of modelling GPCRs using the coordinates of bovine rhodopsin as a template. Associated WWW pages: www.gpcr.org/articles/2003_mod

Ligand-supported homology modelling of protein binding-sites using knowledge-based potentials

A new approach, MOBILE, is presented that models protein binding-sites including bound ligand molecules as restraints. Initially generated, homology models of the target protein are refined iteratively by including information about bioactive ligands as spatial restraints and optimising the mutual interactions between the ligands and the binding-sites. Thus optimised models can be used for structure-based drug design and virtual screening. In a first step, ligands are docked into an averaged ensemble of crude homology models of the target protein. In the next step, improved homology models are generated, considering explicitly the previously placed ligands by defining restraints between protein and ligand atoms. These restraints are expressed in terms of knowledge-based distance-dependent pair potentials, which were compiled from crystallographically determined protein-ligand complexes. Subsequently, the most favourable models are selected by ranking the interactions between the ligands and the generated pockets using these potentials. Final models are obtained by selecting the best-ranked side-chain conformers from various models, followed by an energy optimisation of the entire complex using a common force-field. Application of the knowledge-based pair potentials proved efficient to restrain the homology modelling process and to score and optimise the modelled protein-ligand complexes. For a test set of 46 protein-ligand complexes, taken from the Protein Data Bank (PDB), the success rate of producing near-native binding-site geometries (rmsd<2.0A) with MODELLER is 70% when the ligand restrains the homology modelling process in its native orientation. Scoring these complexes with the knowledge-based potentials, in 66% of the cases a pose with rmsd <2.0A is found on rank 1. Finally, MOBILE has been applied to two case studies modelling factor Xa based on trypsin and aldose reductase based on aldehyde reductase.

Mutational analysis and molecular modeling of the allosteric binding site of a novel, selective, noncompetitive antagonist of the metabotropic glutamate 1 receptor

A model of the rmGlu1 seven-transmembrane domain complexed with a negative allosteric modulator, 1-ethyl-2-methyl-6-oxo-4-(1,2,4,5-tetrahydro-benzo[d]azepin-3-yl)- 1,6-dihydro-pyrimidine-5-carbonitrile (EM-TBPC) was constructed. Although the mGlu receptors belong to the family 3 G-protein-coupled receptors with a low primary sequence similarity to rhodopsin-like receptors, the high resolution crystal structure of rhodopsin was successfully applied as a template in this model and used to select residues for site-directed mutagenesis. Three mutations, F801(6.51)A, Y805(6.55)A, and T815(7.39)M caused complete loss of the [(3)H]EM-TBPC binding and blocked the EM-TBPC-mediated inhibition of glutamate-evoked G-protein-coupled inwardly rectifying K(+) channel current and [Ca(2+)](i) response. The mutation W798(6.48)F increased the binding affinity of antagonist by 10-fold and also resulted in a marked decrease in the IC(50) value (4 versus 128 nm) compared with wild type. The V757(5.47)L mutation led to a dramatic reduction in binding affinity by 13-fold and a large increase in the IC(50) value (1160 versus 128 nm). Two mutations, N7474(5.51)A and N7504(5.54)A, increased the efficacy of the EM-TBPC block of the glutamate-evoked [Ca(2+)](i) response. We observed a striking conservation in the position of critical residues. The residues Val-757(5.47), Trp-798(6.48), Phe-801(6.51), Tyr-805(6.55), and Thr-815(7.39) are critical determinants of the EM-TBPC-binding pocket of the mGlu1 receptor, validating the rhodopsin crystal structure as a template for the family 3 G-protein-coupled receptors. In our model, the aromatic ring of EM-TBPC might interact with the cluster of aromatic residues formed from Trp-798(6.48), Phe-801(6.51), and Tyr-805(6.55), thereby blocking the movement of the TM6 helix, which is crucial for receptor activation.

Benzimidazole derivatives. 3. 3D-QSAR/CoMFA model and computational simulation for the recognition of 5-HT(4) receptor antagonists

A three-dimensional quantitative structure-affinity relationship study (3D-QSAR), using the comparative molecular field analysis (CoMFA) method, and subsequent computational simulation of ligand recognition have been successfully applied to explain the binding affinities for the 5-HT(4) receptor (5-HT(4)R) of a series of benzimidazole-4-carboxamides and carboxylates derivatives 1-24. The K(i) values of these compounds are in the range from 0.11 to 10 000 nM. The derived 3D-QSAR model shows high predictive ability (q(2) = 0.789 and r(2) = 0.997). Steric (contribution of 43.5%) and electrostatic (50.3%) fields and solvation energy (6.1%) of this novel class of 5-HT(4)R antagonists are relevant descriptors for structure-activity relationships. Computational simulation of the complexes between the benzimidazole-4-carboxamide UCM-21195 (5) and the carboxylate UCM-26995 (21) and a 3D model of the transmembrane domain of the 5-HT(4)R, constructed using the reported crystal structure of rhodopsin, have allowed us to define the molecular details of the ligand-receptor interaction that includes (i) the ionic interaction between the NH group of the protonated piperidine of the ligand and the carboxylate group of Asp(3.32), (ii) the hydrogen bond between the carbonyl oxygen of the ligand and the hydroxyl group of Ser(5.43), (iii) the hydrogen bond between the NH group of Asn(6.55) and the aromatic ring of carboxamides or the ether oxygen of carboxylates, (iv) the interaction of the electron-rich clouds of the aromatic ring of Phe(6.51) and the electron-poor hydrogens of the carbon atoms adjacent to the protonated piperidine nitrogen of the ligand, and (v) the pi-sigma stacking interaction between the benzimidazole system of the ligand and the benzene ring of Tyr(5.38). Moreover, the noticeable increase in potency at the 5-HT(4)R sites, by the introduction of a chloro or bromo atom at the 6-position of the aromatic ring, is attributed to the additional electrostatic and van der Waals interaction of the halogen atom in a small cavity located between transmembrane domains 5 and 6.