Strategies for modeling the interactions of transmembrane helices of G protein-coupled receptors by geometric complementarity using the GRAMM computer algorithm

Preferential binding of an odor within olfactory receptors: a precursor to receptor activation

Using computational methods, which allow mechanistic insights at a molecular level, we explored the olfactory receptor (OR)-odor interactions for 2 mouse ORs, S79 and S86. Both ORs have been previously experimentally, functionally characterized. The odors used were mostly carboxylic acids, which differed in chain length, substituents on the primary carbon atom-chain and degree of unsaturation. These odors elicited varied activation responses from both ORs. Our studies revealed that both receptors have 2 distinct binding sites. Preferential binding in 1 of the 2 sites is correlated with OR activation. The activating odorants: nonanedioic acid, heptanoic acid, and octanoic acid for OR S79 and nonanoic acid for OR S86 preferentially bind in the region bound by transmembranes (TMs [helical domains]) III, IV, V, and VI. The non excitatory odorants heptanol for S79 and heptanoic acid for S86 showed a greater likelihood of binding in the region bound by TMs I, II, III, and VII. Nanosecond-scale molecular dynamics simulations of the physiologically relevant conditions of docked OR-odorant complexes enabled us to quantitatively assess the roles of individual OR amino acids in odor binding. Amino acid-odorant contact maps and distance determinations over the course of the simulations lend support to our conclusions.

Evolution and cellular function of monothiol glutaredoxins: involvement in iron-sulphur cluster assembly

A number of bacterial species, mostly proteobacteria, possess monothiol glutaredoxins homologous to the Saccharomyces cerevisiae mitochondrial protein Grx5, which is involved in iron-sulphur cluster synthesis. Phylogenetic profiling is used to predict that bacterial monothiol glutaredoxins also participate in the iron-sulphur cluster (ISC) assembly machinery, because their phylogenetic profiles are similar to the profiles of the bacterial homologues of yeast ISC proteins. High evolutionary co-occurrence is observed between the Grx5 homologues and the homologues of the Yah1 ferredoxin, the scaffold proteins Isa1 and Isa2, the frataxin protein Yfh1 and the Nfu1 protein. This suggests that a specific functional interaction exists between these ISC machinery proteins. Physical interaction analyses using low-definition protein docking predict the formation of strong and specific complexes between Grx5 and several components of the yeast ISC machinery. Two-hybrid analysis has confirmed the in vivo interaction between Grx5 and Isa1. Sequence comparison techniques and cladistics indicate that the other two monothiol glutaredoxins of S. cerevisiae, Grx3 and Grx4, have evolved from the fusion of a thioredoxin gene with a monothiol glutaredoxin gene early in the eukaryotic lineage, leading to differential functional specialization. While bacteria do not contain these chimaeric glutaredoxins, in many eukaryotic species Grx5 and Grx3/4-type monothiol glutaredoxins coexist in the cell.

The ruggedness of protein-protein energy landscape and the cutoff for 1/r(n) potentials

MOTIVATION

Computational studies of the energetics of protein association are important for revealing the underlying fundamental principles and for designing better tools to model protein complexes. The interaction cutoff contribution to the ruggedness of protein-protein energy landscape is studied in terms of relative energy fluctuations for 1/r(n) potentials based on a simplistic model of a protein complex. This artificial ruggedness exists for short cutoffs and gradually disappears with the cutoff increase.

RESULTS

The critical values of the cutoff were calculated for each of 11 popular power-type potentials with n=0/9, 12 and for two thresholds of 5% and 10%. The artificial ruggedness decreases to tolerable thresholds for cutoffs larger than the critical ones. The results showed that for both thresholds the critical cutoff is a non-monotonic function of the potential power n. The functions reach the maximum at n=3/4 and then decrease with the increase of the potential power. The difference between two cutoffs for 5% and 10% artificial ruggedness becomes negligible for potentials decreasing faster than 1/r(12). The analytical results obtained for the simple model of protein complexes agree with the analysis of artificial ruggedness in a dataset of 62 protein-protein complexes, with different parameterizations of soft Lennard-Jones potential and two types of protein representations: all-atom and coarse-grained. The results suggest that cutoffs larger than the critical ones can be recommended for protein-protein potentials.

The size of the intermolecular energy funnel in protein-protein interactions

Revealing the fundamental principles of protein interactions is essential for the basic knowledge of molecular processes and designing better predictive tools. Protein docking procedures allow systematic sampling of intermolecular energy landscapes, revealing the distribution of energy basins and their characteristics. A systematic search docking procedure GRAMM-X was applied to a comprehensive nonredundant database of nonobligate protein-protein complexes to determine the size of the intermolecular energy funnel. The unbound structures were simulated using rotamer library. The procedure generated grid-based matches, based on a smoothed Lennard-Jones potential, and minimized them off the grid with the same potential. The minimization generated a distribution of distances, based on a variety of metrics, between the grid-based and the minimized matches. The metric selected for the analysis, ligand interface RMSD, provided three independent estimates of the funnel size: based on the distribution amplitude for the near-native matches, deviation from random, and correlation with the energy values. The three methods converge to similar estimates of approximately 6-8 A ligand interface RMSD. The results indicated dependence of the funnel size on the type of the complex (smaller for antigen-antibody, medium for enzyme-inhibitor, and larger for the rest of the complexes) and the funnel size correlation with the size of the interface. Guidelines for the optimal sampling of docking coordinates, based on the funnel size estimates, were explored.

Chasing funnels on protein-protein energy landscapes at different resolutions

Studies of intermolecular energy landscapes are important for understanding protein association and adequate modeling of protein interactions. Landscape representation at different resolutions can be used for the refinement of docking predictions and detection of macro characteristics, like the binding funnel. A representative set of protein-protein complexes was used to systematically map the intermolecular landscape by grid-based docking. The change of the resolution was achieved by varying the range of the potential, according to the variable resolution GRAMM methodology. A formalism was developed to consistently parameterize the potential and describe essential characteristics of the landscape. The results of gradual landscape smoothing, from high to low resolution, indicate that i), the number of energy basins, the landscape ruggedness, and the slope decrease accordingly; ii), the number of near-native matches, defined as those inside the funnel, increases until the trend breaks down at critical resolution; the rate of the increase and the critical resolution are specific to the type of a complex (enzyme inhibitor, antigen-antibody, and other), reflect known underlying recognition factors, and correlate with earlier determined estimates of the funnel size; iii), the native/nonnative energy gap, a major characteristic of the energy minima hierarchy, remains constant; and iv), the putative funnel (defined as the deepest basin) has the largest average depth-related ruggedness and slope, at all resolutions. The results facilitate better understanding of the binding landscapes and suggest directions for implementation in practical docking protocols.

Interaction cutoff effect on ruggedness of protein-protein energy landscape

The concept of the energy landscape is important for better understanding of protein-protein interactions and for designing adequate docking procedures. The intermolecular landscape has a rugged terrain that impedes search procedures. Its inherent ruggedness is related to the conformational characteristics of the molecules and to the form of the potential function--more rugged for short-range potentials and less rugged for "soft," typically long-range potentials. Our study determined that the landscape ruggedness is further substantially exacerbated by truncation of the potentials. This additional ruggedness appears below certain critical interaction ranges that depend on the form of the potential. The theoretical model describing the cutoff effect on the landscape ruggedness is confirmed by the energy calculation on a dataset of protein-protein complexes. The negative effect of the potentials cutoff is well known. However, revealing its physical basis in terms of the energy landscape is important for better understanding of intermolecular interactions.

Quaternary structure predictions of transmembrane proteins starting from the monomer: a docking-based approach

Background

We introduce a computational protocol for effective predictions of the supramolecular organization of integral transmembrane proteins, starting from the monomer. Despite the demonstrated constitutive and functional importance of supramolecular assemblies of transmembrane subunits or proteins, effective tools for structure predictions of such assemblies are still lacking. Our computational approach consists in rigid-body docking samplings, starting from the docking of two identical copies of a given monomer. Each docking run is followed by membrane topology filtering and cluster analysis. Prediction of the native oligomer is therefore accomplished by a number of progressive growing steps, each made of one docking run, filtering and cluster analysis. With this approach, knowledge about the oligomerization status of the protein is required neither for improving sampling nor for the filtering step. Furthermore, there are no size-limitations in the systems under study, which are not limited to the transmembrane domains but include also the water-soluble portions.

Results

Benchmarks of the approach were done on ten homo-oligomeric membrane proteins with known quaternary structure. For all these systems, predictions led to native-like quaternary structures, i.e. with C_α-RMSDs lower than 2.5 Å from the native oligomer, regardless of the resolution of the structural models.

Conclusion

Collectively, the results of this study emphasize the effectiveness of the prediction protocol that will be extensively challenged in quaternary structure predictions of other integral membrane proteins.

The Origin of C1A-C2 Interdomain Interactions in Protein Kinase Cα

The regulatory domain of protein kinase Calpha (PKCalpha) contains three membrane-targeting modules, two C1 domains (C1A and C1B) that bind diacylglycerol and phorbol ester, and the C2 domain that is responsible for the Ca2+-dependent membrane binding. Accumulating evidence suggests that C1A and C2 domains of PKCalpha are tethered in the resting state and that the tethering is released upon binding to the membrane containing phosphatidylserine. The homology modeling and the docking analysis of C1A and C2 domains of PKCalpha revealed a highly complementary interface that comprises Asp55-Arg252 and Arg42-Glu282 ion pairs and a Phe72-Phe255 aromatic pair. Mutations of these residues in the predicted C1A-C2 interface showed large effects on in vitro membrane binding, enzyme activity, phosphatidylserine selectivity, and cellular membrane translocation of PKCalpha, supporting their involvement in interdomain interactions. In particular, D55A (or D55K) and R252A (or R252E) mutants showed much higher basal membrane affinity and enzyme activity and faster subcellular translocation than wild type, whereas a double charge-reversal mutant (D55K/R252E) behaved analogously to wild type, indicating that a direct electrostatic interaction between the two residues is essential for the C1A-C2 tethering. Collectively, these studies provide new structural insight into PKCalpha C1A-C2 interdomain interactions and the mechanism of lipid-mediated PKCalpha activation.

The study of G-protein coupled receptor oligomerization with computational modeling and bioinformatics

To achieve a structural context for the analysis of G-protein coupled receptor (GPCR) oligomers, molecular modeling must be used to predict the corresponding interaction interfaces. The task is complicated by the paucity of detailed structural data at atomic resolution, and the large number of possible modes in which the bundles of seven transmembrane (TM) segments of the interacting GPCR monomers can be packed together into dimers and/or higher-order oligomers. Approaches and tools offered by bioinformatics can be used to reduce the complexity of this task and, combined with computational modeling, can serve to yield testable predictions for the structural properties of oligomers. Most of the bioinformatics methods take advantage of the evolutionary relation that exists among GPCRs, as expressed in their sequences and measurable in the common elements of their structural and functional features. These common elements are responsible for the presence of detectable patterns of motifs and correlated mutations evident from the alignment of the sequences of these complex biological systems. The decoding of these patterns in terms of structural and functional determinants can provide indications about the most likely interfaces of dimerization/oligomerization of GPCRs. We review here the main approaches from bioinformatics, enhanced by computational molecular modeling, that have been used to predict likely interfaces of dimerization/oligomerization of GPCRs, and compare results from their application to rhodopsin-like GPCRs. A compilation of the most frequently predicted GPCR oligomerization interfaces points to specific regions of TMs 4-6.

Shorter side chains optimize helix-helix packing

A systematic study of helix-helix packing in a comprehensive database of protein structures revealed that the side chains inside helix-helix interfaces on average are shorter than those in the noninterface parts of the helices. The study follows our earlier study of this effect in transmembrane helices. The results obtained on the entire database of protein structures are consistent with those obtained on the transmembrane helices. The difference in the length of interface and noninterface side chains is small but statistically significant. It indicates that helices, if viewed along their main axis, statistically are not circular, but have a flattened interface. This effect brings the helices closer to each other and creates a tighter structural packing. The results provide an interesting insight into the aspects of protein structure and folding.

Identification of amino acid residues crucial for chemokine receptor dimerization

Chemokines coordinate leukocyte trafficking by promoting oligomerization and signaling by G protein-coupled receptors; however, it is not known which amino acid residues of the receptors participate in this process. Bioinformatic analysis predicted that Ile52 in transmembrane region-1 (TM1) and Val150 in TM4 of the chemokine receptor CCR5 are key residues in the interaction surface between CCR5 molecules. Mutation of these residues generated nonfunctional receptors that could not dimerize or trigger signaling. In vitro and in vivo studies in human cell lines and primary T cells showed that synthetic peptides containing these residues blocked responses induced by the CCR5 ligand CCL5. Fluorescence resonance energy transfer showed the presence of preformed, ligand-stabilized chemokine receptor oligomers. This is the first description of the residues involved in chemokine receptor dimerization, and indicates a potential target for the modification of chemokine responses.

The role of geometric complementarity in secondary structure packing: a systematic docking study

A strong similarity between the major aspects of protein folding and protein recognition is one of the emerging fundamental principles in protein science. A crucial importance of steric complementarity in protein recognition is a well-established fact. The goal of this study was to assess the importance of the steric complementarity in protein folding, namely, in the packing of the secondary structure elements. Although the tight packing of protein structures, in general, is a well-known fact, a systematic study of the role of geometric complementarity in the packing of secondary structure elements has been lacking. To assess the role of the steric complementarity, we used a docking procedure to recreate the crystallographically determined packing of secondary structure elements in known protein structures by using the geometric match only. The docking results revealed a significant percentage of correctly predicted packing configurations. Different types of pairs of secondary structure elements showed different degrees of steric complementarity (from high to low: beta-beta, loop-loop, alpha-alpha, and alpha-beta). Interestingly, the relative contribution of the steric match in different types of pairs was correlated with the number of such pairs in known protein structures. This effect may indicate an evolutionary pressure to select tightly packed elements of secondary structure to maximize the packing of the entire structure. The overall conclusion is that the steric match plays an essential role in the packing of secondary structure elements. The results are important for better understanding of principles of protein structure and may facilitate development of better methods for protein structure prediction.

The crystallographic model of rhodopsin and its use in studies of other G protein-coupled receptors

G protein-coupled receptors (GPCRs) are integral membrane proteins that respond to environmental signals and initiate signal transduction pathways activating cellular processes. Rhodopsin is a GPCR found in rod cells in retina where it functions as a photopigment. Its molecular structure is known from cryo-electron microscopic and X-ray crystallographic studies, and this has reshaped many structure/function questions important in vision science. In addition, this first GPCR structure has provided a structural template for studies of other GPCRs, including many known drug targets. After presenting an overview of the major structural elements of rhodopsin, recent literature covering the use of the rhodopsin structure in analyzing other GPCRs will be summarized. Use of the rhodopsin structural model to understand the structure and function of other GPCRs provides strong evidence validating the structural model.