Aromatic side-chain interactions in proteins. Near- and far-sequence His–X pairs

Several studies have analysed aromatic interactions, involving mostly phenylalanine, tyrosine and tryptophan. Only a few studies have considered histidine as an interacting aromatic residue. An extensive analysis of aromatic His–X interactions is performed here on a data set of 593 PDB structures: 68% of the histidine are involved in aromatic pairs and 1271 non-redundant His–X pairs were analysed. Thirty percent of these pairs involve an aromatic partner less than 6 apart in the sequence. These near-sequence pairs correspond to conformations which stabilise secondary structures, mainly α-helices when the residues are 4 apart and β-strands when they are 2 apart in the sequence. The partners of the other His–X pairs (887, 70%) are more than 5 apart in the sequence. Of these far-sequence pairs, 35% bridge beta strands and only 9% helices. The near-sequence pairs are sterically constrained as supported by conformer distribution. The X partners of far-sequence His–X pairs are mainly “above” the histidine ring with tilted and normal rings, corresponding to a “T shape; face to edge” orientation. Phenylalanine, the only aromatic residue with no heteroatom, is a disfavoured partner, whereas histidine is the preferred one. Heteroatom–heteroatom interactions are favoured in near-sequence as well as in far-sequence His–His, His–Trp and His–Tyr pairs.     

Aromatic side-chain interactions in proteins: near- and far-sequence Tyr-X pairs

In the present study, an extensive analysis of the aromatic Tyr-X interactions is performed on a data set of 593 PDB structures, X being Phe, His, Tyr, and Trp. The nonredundant Tyr-X pairs (2645) were retained and separated by both the residue distance in the sequence and the secondary structures they bridge. Similar to the Phe-X and His-X pairs, the far-sequence Tyr-X pairs (X partner > five apart in the sequence: 74%) show comparable secondary structures and conformers for either type of X partner, in contrast with the near-sequence Tyr-X pairs (26%). As the Phe-X pairs, the near-sequence Tyr-X pairs stabilize secondary structures, mainly the alpha- helices (positions 1, 3, and 4) and the beta-strands (position 2). Like the Phe-X and His-X pairs, most far-sequence Tyr-X pairs (34%) bridge beta-strands and only 11% bridge helices. As for the Phe-X and the His-X pairs, the X partners of the far-sequence Tyr-X pairs are frequently "above" the tyrosine ring with tilted and normal rings, whereas the X partner of the near-sequence Tyr-X pairs gradually moves from the "aside" to the "above" location, together with a progressive decrease of normal and increase of parallel rings, respectively. Unlike the His-X pairs, the interactions of the hetroatom in Tyr-X pairs are only favored with a sequence position +4 and over, owing to the spatial accessibility of the heteroatom.     

Aromatic side-chain interactions in proteins. I. Main structural features

In a data set of 593 nonhomologous proteins from the PDB, we have analyzed the pairing of phenylalanine, tyrosine, tryptophan, and histidine residues with their closest aromatic partner. The frequency distribution of the shortest interatomic distance of partners is bimodal with a sharp peak at approximately 3.8 A and a wider one at a longer distance. Only the 3.8 A peak corresponds to direct ring-ring interactions thus aromatic pairs. The aromatic pairs were separated into two classes, near-sequence pairs and far-sequence pairs. Near sequence pairs stabilize local structure, and far-sequence pairs stabilize tertiary structure. Far-sequence pairs (74% of all pairs) mainly bridge two beta-strands, followed by pairs that bridge a beta-strand and a helix, and pairs that bridge a beta-strand and a random coil structure. Pairs that bridge helices are rare. The secondary structure of the near-sequence pairs depends on the partner distance in the sequence. When the partners are 1, 3, or 4 residues apart in the sequence, pairs are mostly found in helical structures. When the partners are two apart, pairs are mostly found in the same beta-strand. Analysis of the frequency of near sequence pairs supports the hypothesis that aromatic pairing occurs after, rather than before, the formation of secondary structures.     

Aromatic side-chain interactions in proteins. II. Near- and far-sequence Phe-X pairs

We have collected all aromatic pairs (3152) involving an N-phenyl partner in a dataset of 593 proteins of the PDB: 728 of these pairs involve a partner residue less than 6 apart in the sequence. These near-sequence Phe-X pairs correspond to specific conformations that stabilize secondary structures, mainly alpha-helices when the residues are 1, 3, and 4 apart, and beta-strands when they are 2 apart in the sequence. These conformations are not spatially random and have been examined in detail. The remaining phenylalanine pairs (2424) are between partners more than 5 apart in the sequence. Of these far-sequence pairs, 34% of occurrences are in sheets. Next in frequencies are pairs that bridge a beta-strand to a helix (24%), followed by pairs that bridge a beta-strand to a random coiled structure (15%). Helix to helix pairs only constitute 12% of these far-sequence pairs. Analysis of the pairing frequency supports the hypothesis that aromatic interactions are late events of protein folding.     

Two-dimensional NMR studies of the zinc finger motif: solution structures and dynamics of mutant ZFY domains containing aromatic substitutions in the hydrophobic core.

Solution structures of mutant Zn fingers containing aromatic substitutions in the hydrophobic core are determined by 2D-NMR spectroscopy and distance-geometry/simulated annealing (DG/SA). The wild-type domain (designated ZFY-6) is derived from the human male-associated protein ZFY and represents a sequence motif (Cys-X2-Cys-X-Ar-X7-Leu-X2-His-X4-His) that differs from the consensus (Cys-X2,4-Cys-X3-Phe-X5-Leu-X2-His-X3-His) in the location ("aromatic swap") and diversity (Ar = tyrosine, phenylalanine, or histidine) of the central aromatic residue (underlined). In a given ZFY domain the choice of a particular aromatic residue is invariant among vertebrates, suggesting that alternative "swapped" aromatic residues are functionally inequivalent. 2D-NMR studies of analogues containing tyrosine, phenylalanine, or histidine at the swapped site yield the following results. (i) The three DG/SA structures each retain the beta beta alpha motif and exhibit similar staggered-horizontal packing between the variant aromatic residue and the proximal histidine in the hydrophobic core. (ii) The structures and stabilities of the tyrosine and phenylalanine analogues are essentially identical, differing only by local exposure of polar (Tyr p-OH) or nonpolar (Phe p-H) surfaces. (iii) The dynamic stability of the histidine analogue is reduced as indicated by more rapid protein-deuterium exchange of hydrogen bonds related to secondary structure and amide-sulfur coordination (slowly exchanging amide resonances in D2O) and by more extensive averaging of main-chain dihedral angles (3J alpha NH coupling constants). An aspartic acid in the putative DNA recognition surface, whose configuration is well-defined as a possible helix N-cap in the tyrosine and phenylalanine analogues, exhibits multiple weak main-chain contacts in the NOESY spectrum of the histidine analogue; such NOEs are geometrically inconsistent and so provide complementary evidence for structural fluctuations. (iv) Because the three DG ensembles have similar apparent precision, the finding of reduced dynamic stability in the histidine analogue emphasizes the importance of experiments that directly probe fluctuations at several time scales. Our results provide insight into the design of biological metal-binding sites and the relationship of protein sequence to structure and dynamics.     

Determinants of strand register in antiparallel beta-sheets of proteins.

Antiparallel beta-sheets present two distinct environments to inter-strand residue pairs: beta(A,HB) sites have two backbone hydrogen bonds; whereas at beta(A,NHB) positions backbone hydrogen bonding is precluded. We used statistical methods to compare the frequencies of amino acid pairs at each site. Only approximately 10% of the 210 possible pairs showed occupancies that differed significantly between the two sites. Trends were clear in the preferred pairs, and these could be explained using stereochemical arguments. Cys-Cys, Aromatic-Pro, Thr-Thr, and Val-Val pairs all preferred the beta(A,NHB) site. In each case, the residues usually adopted sterically favored chi1 conformations, which facilitated intra-pair interactions: Cys-Cys pairs formed disulfide bonds; Thr-Thr pairs made hydrogen bonds; Aromatic-Pro and Val-Val pairs formed close van der Waals contacts. In contrast, to make intimate interactions at a beta(A,HB) site, one or both residues had to adopt less favored chi1 geometries. Nonetheless, pairs containing glycine and/or aromatic residues were favored at this site. Where glycine and aromatic side chains combined, the aromatic residue usually adopted the gauche conformation, which promoted novel aromatic ring-peptide interactions. This work provides rules that link protein sequence and tertiary structure, which will be useful in protein modeling, redesign, and de novo design. Our findings are discussed in light of previous analyses and experimental studies.     

Effect of pressure on helix‐coil transition of an alanine‐based peptide: An FTIR study

Protein–protein interactions are mediated by complementary amino acids defining complementary surfaces. Typically not all members of a family of related proteins interact equally well with all members of a partner family; thus analysis of the sequence record can reveal the complementary amino acid partners that confer interaction specificity. This article develops methods for learning and using probabilistic graphical models of such residue “cross‐coupling” constraints between interacting protein families, based on multiple sequence alignments and information about which pairs of proteins are known to interact. Our models generalize traditional consensus sequence binding motifs, and provide a probabilistic semantics enabling sound evaluation of the plausibility of new possible interactions. Furthermore, predictions made by the models can be explained in terms of the underlying residue interactions. Our approach supports different levels of prior knowledge regarding interactions, including both one‐to‐one (e.g., pairs of proteins from the same organism) and many‐to‐many (e.g., experimentally identified interactions), and we present a technique to account for possible bias in the represented interactions. We apply our approach in studies of PDZ domains and their ligands, fundamental building blocks in a number of protein assemblies. Our algorithms are able to identify biologically interesting cross‐coupling constraints, to successfully identify known interactions, and to make explainable predictions about novel interactions. Proteins 2009. © 2009 Wiley‐Liss, Inc.     

Inter-Protein Sequence Co-Evolution Predicts Known Physical Interactions in Bacterial Ribosomes and the Trp Operon

Interaction between proteins is a fundamental mechanism that underlies virtually all biological processes. Many important interactions are conserved across a large variety of species. The need to maintain interaction leads to a high degree of co-evolution between residues in the interface between partner proteins. The inference of protein-protein interaction networks from the rapidly growing sequence databases is one of the most formidable tasks in systems biology today. We propose here a novel approach based on the Direct-Coupling Analysis of the co-evolution between inter-protein residue pairs. We use ribosomal and trp operon proteins as test cases: For the small resp. large ribosomal subunit our approach predicts protein-interaction partners at a true-positive rate of 70% resp. 90% within the first 10 predictions, with areas of 0.69 resp. 0.81 under the ROC curves for all predictions. In the trp operon, it assigns the two largest interaction scores to the only two interactions experimentally known. On the level of residue interactions we show that for both the small and the large ribosomal subunit our approach predicts interacting residues in the system with a true positive rate of 60% and 85% in the first 20 predictions. We use artificial data to show that the performance of our approach depends crucially on the size of the joint multiple sequence alignments and analyze how many sequences would be necessary for a perfect prediction if the sequences were sampled from the same model that we use for prediction. Given the performance of our approach on the test data we speculate that it can be used to detect new interactions, especially in the light of the rapid growth of available sequence data.     

Significance of aromatic-backbone amide interactions in protein structure

Weakly polar interactions between aromatic rings of amino acids and hydrogens of backbone amides (Ar-HN) have been shown to support local structures in proteins. Their role in secondary structures, however, has not been elucidated. To investigate the relationship between Ar-HN interaction and the stability of local and secondary structures of polypeptides and to improve the prediction of this interaction based on amino acid sequence, the structures of 560 nonhomologous proteins, from the Protein Data Bank, were searched for Ar-HN interactions between the aromatic ring of each Phe, Tyr, and Trp residue at position i and the backbone amide group of any residue, except Pro, at the positions i, i - 1, i - 2, i - 3, i + 1, i + 2, and i + 3. Ar-HN interactions were identified by calculating the chemical shift of the amide hydrogen caused by the proximal aromatic ring. Ar(i)-HN(i + 1, i + 2 and i + 3) interactions were more common (7.10%, 2.08%, and 0.54%, respectively) than were Ar(i)-HN(i - 1, i - 2, and i - 3) interactions (0.66%, <0.1%, and 0.18%, respectively). The value of the chi(1) torsion angle of the aromatic residue in position i depended on the direction of the Ar-HN interaction. The position of the aromatic ring in Ar(i)-HN(i + 1, i + 2, and i + 3) interactions was mostly trans, in Ar(i)-HN(i - 1, i - 2, and i - 3) interactions mainly gauche(-), and in Ar(i)-HN(i) interactions mostly gauche(+). The analyses of the secondary structures of the protein fragments containing Ar-HN interactions showed that Ar-HN interactions were in all types of secondary structures. Search results suggest that Ar-HN interactions have a stabilizing effect on all types of secondary structures.     

Electrostatic stabilization in myoglobin. Interactive free energies between individual sites.

The pattern of electrostatic interactions between pairs of charge sites in sperm whale ferrimyoglobin was examined as a function of pH in terms of proton site occupancy, static solvent accessibility, and distance of separation. By grouping all examples of the most stabilizing interactions and all examples of the most destabilizing interactions, we can easily show that at pH 7.50 the former is much stronger; that is, the negative contributions to electrostatic free energy far outweigh the positive contributions. Much of the electrostatic energy of stabilization in native myoglobin is provided by specific charge-pair partners that are very highly conserved among 53 mammalian myoglobin species and is invariant substantially from pH 8.5 to 3.5. Destablizing interactions that become most significant, but not actually dominant, near the acid unfolding pH range can be recognized in emerging clusters of uncompensated positive charges. Binding of azide ion by the heme iron effectively reduces the most prominent destabilizing set of such interactions. In general, thoe charged residues that experience the largest summed stabilizing interactions with other groups are the most conserved between species. The histidine residues, however, show their best correlation of conservation with low values of static accessibility. Although histidine residue 64 has an effective pK corresponding to the midpoint of the unfolding transition near pH 4.2 at an ionic strength of 0.10 M and so might be called a "trigger group", its interactions contribute only a modest fraction of the overall pH-dependent free energy change. An examination of the primary stabilizing interactions represented by the charge-pair partners indicates a probably major role of electrostatic interactions in the nucleation and docking stages of the condensation of the polypeptide chain into the compact native structure.     

Importance of long-range interactions in (α/β)8 barrel fold

Protein structures are stabilized by both local and long-range interactions. In this work, we analyzed the importance of long-range interactions in (α/β)₈ barrel proteins in terms of residue distances. We found that the residues occurring in the range of 21–30 residues apart contribute more toward long-range contacts. Indeed, about 50% of successive strands in these proteins are found to occur at a sequential distance of 21–30 residues. The aromatic amino acid residues Phe, Trp, and Tyr prefer the 4–10 range and all other residues prefer the 21–30 range. Hydrophobic-hydrophobic resideu pairs are the most preferred ones for long-range interactions and they may play a key role in the folding and stabilization of (α/β)₈ barrel proteins.     

Importance of long-range interactions in (α/β)8 barrel fold

Protein structures are stabilized by both local and long-range interactions. In this work, we analyzed the importance of long-range interactions in (α/β)₈ barrel proteins in terms of residue distances. We found that the residues occurring in the range of 21–30 residues apart contribute more toward long-range contacts. Indeed, about 50% of successive strands in these proteins are found to occur at a sequential distance of 21–30 residues. The aromatic amino acid residues Phe, Trp, and Tyr prefer the 4–10 range and all other residues prefer the 21–30 range. Hydrophobic-hydrophobic resideu pairs are the most preferred ones for long-range interactions and they may play a key role in the folding and stabilization of (α/β)₈ barrel proteins.     

Helix-helix packing and interfacial pairwise interactions of residues in membrane proteins

Helix-helix packing plays a critical role in maintaining the tertiary structures of helical membrane proteins. By examining the overall distribution of voids and pockets in the transmembrane (TM) regions of helical membrane proteins, we found that bacteriorhodopsin and halorhodopsin are the most tightly packed, whereas mechanosensitive channel is the least tightly packed. Large residues F, W, and H have the highest propensity to be in a TM void or a pocket, whereas small residues such as S, G, A, and T are least likely to be found in a void or a pocket. The coordination number for non-bonded interactions for each of the residue types is found to correlate with the size of the residue. To assess specific interhelical interactions between residues, we have developed a new computational method to characterize nearest neighboring atoms that are in physical contact. Using an atom-based probabilistic model, we estimate the membrane helical interfacial pairwise (MHIP) propensity. We found that there are many residue pairs that have high propensity for interhelical interactions, but disulfide bonds are rarely found in the TM regions. The high propensity pairs include residue pairs between an aromatic residue and a basic residue (W-R, W-H, and Y-K). In addition, many residue pairs have high propensity to form interhelical polar-polar atomic contacts, for example, residue pairs between two ionizable residues, between one ionizable residue and one N or Q. Soluble proteins do not share this pattern of diverse polar-polar interhelical interaction. Exploratory analysis by clustering of the MHIP values suggests that residues similar in side-chain branchness, cyclic structures, and size tend to have correlated behavior in participating interhelical interactions. A chi-square test rejects the null hypothesis that membrane protein and soluble protein have the same distribution of interhelical pairwise propensity. This observation may help us to understand the folding mechanism of membrane proteins.     

Environment of tryptophan side chains in proteins

Although relatively rare, the tryptophan residue (Trp), with its large hydrophobic surface, has a unique role in the folded structure and the binding site of many proteins, and its fluorescence properties make it very useful in studying the structures and dynamics of protein molecules in solution. An analysis has been made of its environment and the geometry of its interaction with neighbors using 719 Trp residues in 180 different protein structures. The distribution of the number of partners interacting with the Trp aromatic ring shows a peak at 6 (considering protein residues only) and 8 (including water and substrate molecules also). The means of the solvent-accessible surface areas of the ring show an exponential decrease with the increase in the number of partners; this relationship can be used to assess the efficiency of packing of residues around Trp. Various residues exhibit different propensities of binding the Trp side chain. The aromatic residues, Met and Pro have high values, whereas the smaller and polar-chain residues have weaker propensities. Most of the interactions are with residues far away in sequence, indicating the importance of Trp in stabilizing the tertiary structure. Of all the ring atoms NE1 shows the highest number of interactions, both along the edge (hydrogen bonding) as well as along the face. Various weak but specific interactions, engendering stability to the protein structure, have been identified.     

Sequence specificity, statistical potentials, and three-dimensional structure prediction with self-correcting distance geometry calculations of beta-sheet formation in proteins

A statistical analysis of a representative data set of 169 known protein structures was used to analyze the specificity of residue interactions between spatial neighboring strands in beta-sheets. Pairwise potentials were derived from the frequency of residue pairs in nearest contact, second nearest and third nearest contacts across neighboring beta-strands compared to the expected frequency of residue pairs in a random model. A pseudo-energy function based on these statistical pairwise potentials recognized native beta-sheets among possible alternative pairings. The native pairing was found within the three lowest energies in 73% of the cases in the training data set and in 63% of beta-sheets in a test data set of 67 proteins, which were not part of the training set. The energy function was also used to detect tripeptides, which occur frequently in beta-sheets of native proteins. The majority of native partners of tripeptides were distributed in a low energy range. Self-correcting distance geometry (SECODG) calculations using distance constraints sets derived from possible low energy pairing of beta-strands uniquely identified the native pairing of the beta-sheet in pancreatic trypsin inhibitor (BPTI). These results will be useful for predicting the structure of proteins from their amino acid sequence as well as for the design of proteins containing beta-sheets.     

Influence of medium and long range interactions in protein folding.

Protein structures are stabilized by both local and long range interactions. In this work, we analyze the residue-residue contacts and the role of medium- and long-range interactions in globular proteins belonging to different structural classes. The results show that while medium range interactions predominate in all-alpha class proteins, long-range interactions predominate in all-beta class. Based on this, we analyze the performance of several structure prediction methods in different structural classes of globular proteins and found that all the methods predict the secondary structures of all-alpha proteins more accurately than other classes. Also, we observed that the residues occurring in the range of 21-30 residues apart contributes more towards long-range contacts and about 85% of residues are involved in long-range contacts. Further, the preference of residue pairs to the folding and stability of globular proteins is discussed.     

Crystal structures of an intein from the split dnaE gene of Synechocystis sp. PCC6803 reveal the catalytic model without the penultimate histidine and the mechanism of zinc ion inhibition of protein splicing

The first naturally occurring split intein was found in the dnaE gene of Synechocystis sp. PCC6803 and belongs to a subclass of inteins without a penultimate histidine residue. We describe two high-resolution crystal structures, one derived from an excised Ssp DnaE intein and the second from a splicing-deficient precursor protein. The X-ray structures indicate that His147 in the conserved block F activates the side-chain N(delta) atom of the intein C-terminal Asn159, leading to a nucleophilic attack on the peptide bond carbonyl carbon atom at the C-terminal splice site. In this process, Arg73 appears to stabilize the transition state by interacting with the carbonyl oxygen atom of the scissile bond. Arg73 also seems to substitute for the conserved penultimate histidine residue in the formation of an oxyanion hole, as previously identified in other inteins. The finding that the precursor structure contains a zinc ion chelating the highly conserved Cys160 and Asp140 reveals the structural basis of Zn2+-mediated inhibition of protein splicing. Furthermore, it is of interest to observe that the carbonyl carbon atom of Asn159 and N(eta) of Arg73 are 2.6 angstroms apart in the free intein structure and 10.6 angstroms apart in the precursor structure. The orientation change of the aromatic ring of Tyr-1 following the initial acyl shift may be a key switching event contributing to the alignment of Arg73 and the C-terminal scissile bond, and may explain the sequential reaction property of the Ssp DnaE intein.     

Statistical analyses of protein sequence alignments identify structures and mechanisms in signal activation of sensor histidine kinases

Statistical analyses of genome sequence‐derived protein sequence data can identify amino acid residues that interact between proteins or between domains of a protein. These statistical methods are based on evolution‐directed amino acid variation responding to structural and functional constraints in proteins. The identified residues form a basis for determining structure and folding of proteins as well as inferring mechanisms of protein function. When applied to two‐component systems, several research groups have shown they can be used to identify the amino acid interactions between response regulators and histidine kinases and the specificity therein. Recently, statistical studies between the HisKA and HATPase‐ATP‐binding domains of histidine kinases identified amino acid interactions for both the inactive and the active catalytic states of such kinases. The identified interactions generated a model structure for the domain conformation of the active state. This conformation requires an unwinding of a portion of the C‐terminal helix of the HisKA domain that destroys the inactive state residue contacts and suggests how signal‐binding determines the equilibrium between the inactive and active states of histidine kinases. The rapidly accumulating protein sequence databases from genome, metagenome and microbiome studies are an important resource for functional and structural understanding of proteins and protein complexes in microbes.     

Protein-Protein Interactions in a Crowded Environment: An Analysis via Cross-Docking Simulations and Evolutionary Information

Large-scale analyses of protein-protein interactions based on coarse-grain molecular docking simulations and binding site predictions resulting from evolutionary sequence analysis, are possible and realizable on hundreds of proteins with variate structures and interfaces. We demonstrated this on the 168 proteins of the Mintseris Benchmark 2.0. On the one hand, we evaluated the quality of the interaction signal and the contribution of docking information compared to evolutionary information showing that the combination of the two improves partner identification. On the other hand, since protein interactions usually occur in crowded environments with several competing partners, we realized a thorough analysis of the interactions of proteins with true partners but also with non-partners to evaluate whether proteins in the environment, competing with the true partner, affect its identification. We found three populations of proteins: strongly competing, never competing, and interacting with different levels of strength. Populations and levels of strength are numerically characterized and provide a signature for the behavior of a protein in the crowded environment. We showed that partner identification, to some extent, does not depend on the competing partners present in the environment, that certain biochemical classes of proteins are intrinsically easier to analyze than others, and that small proteins are not more promiscuous than large ones. Our approach brings to light that the knowledge of the binding site can be used to reduce the high computational cost of docking simulations with no consequence in the quality of the results, demonstrating the possibility to apply coarse-grain docking to datasets made of thousands of proteins. Comparison with all available large-scale analyses aimed to partner predictions is realized. We release the complete decoys set issued by coarse-grain docking simulations of both true and false interacting partners, and their evolutionary sequence analysis leading to binding site predictions. Download site: http://www.lgm.upmc.fr/CCDMintseris/