Amino acid pair- and triplet-wise groupings in the interior of α-helical segments in proteins

Propensities of Some Amino Acid Pairings in α-Helices Vary with Length

The results of secondary structure prediction methods are widely used in applications in biotechnology and bioinformatics. However, the accuracy limit of these methods could be improved up to 92%. One approach to achieve this goal is to harvest information from the primary structure of the peptide. This study aims to contribute to this goal by investigating the variations in propensity of amino acid pairings to α-helices in globular proteins depending on helix length. (n):(n + 4) residue pairings were determined using a comprehensive peptide data set according to backbone hydrogen bond criterion which states that backbone hydrogen bond is the dominant driving force of protein folding. Helix length is limited to 13 to 26 residues. Findings of this study show that propensities of ALA:GLY and GLY:GLU pairings to α-helix in globular protein increase with increasing helix length but of ALA:ALA and ALA:VAL decrease. While the frequencies of ILE:ALA, LEU:ALA, LEU:GLN, LEU:GLU, LEU:LEU, MET:ILE and VAL:LEU pairings remain roughly constant with length, the 25 residue pairings have varying propensities in narrow helix lengths. The remaining pairings have no prominent propensity to α-helices.

Propensities of Amino Acid Pairings in Secondary Structure of Globular Proteins

A class of secondary structure prediction algorithms use the information from the statistics of the residue pairs found in secondary structural elements. Because the protein folding process is dominated by backbone hydrogen bonding, an approach based on backbone hydrogen-bonded residue pairings would improve the predicting capabilities of these class algorithms. The reliability of the prediction algorithms depends on the quality of the statistics, therefore, of the data set. In this study, it was aimed to determine the propensities of the backbone hydrogen-bonded residue pairings for secondary structural elements of α-helix and β-sheet in globular proteins using a new and comprehensive data set created from the peptides deposited in Worldwide Protein Data Bank. A master data set including 4882 globular peptide chains with resolution better than 2.5 Å, sequence identity smaller than 25% and length of no shorter than 100 residues were created. Separate data sub sets also were created for helix and sheet structures from master set and each sub set includes 4594 and 4483 chains, respectively. Backbone hydrogen-bonded residue pairings in helices and sheets were detected and the propensities of them were represented as odds ratios (observed/[random or expected]) in matrices. Propensities assigned by this study to the residue pairings in secondary structural elements (as helix, overall strands, parallel strands and antiparallel strands) differ from the previous studies by 19 to 34%. These dissimilarities are important and they would cause further improvements in secondary structure prediction algorithms.

Mapping side chain interactions at protein helix termini

Background

Interactions that involve one or more amino acid side chains near the ends of protein helices stabilize helix termini and shape the geometry of the adjacent loops, making a substantial contribution to overall protein structure. Previous work has identified key helix-terminal motifs, such as Asx/ST N-caps, the capping box, and hydrophobic and electrostatic interactions, but important questions remain, including: 1) What loop backbone geometries are favoured by each motif? 2) To what extent are multi-amino acid motifs likely to represent genuine cooperative interactions? 3) Can new motifs be identified in a large, recent dataset using the latest bioinformatics tools?

Results

Three analytical tools are applied here to answer these questions. First, helix-terminal structures are partitioned by loop backbone geometry using a new 3D clustering algorithm. Next, Cascade Detection, a motif detection algorithm recently published by the author, is applied to each cluster to determine which sequence motifs are overrepresented in each geometry. Finally, the results for each motif are presented in a CapMap, a 3D conformational heatmap that displays the distribution of the motif’s overrepresentation across loop geometries, enabling the rapid isolation and characterization of the associated side chain interaction. This work identifies a library of geometry-specific side chain interactions that provides a new, detailed picture of loop structure near the helix terminus. Highlights include determinations of the favoured loop geometries for the Asx/ST N-cap motifs, capping boxes, “big” boxes, and other hydrophobic, electrostatic, H-bond, and pi stacking interactions, many of which have not been described before.

Conclusions

This work demonstrates that the combination of structural clustering and motif detection in the sequence space can efficiently identify side chain motifs and map them to the loop geometries which they support. Protein designers should find this study useful, because it identifies side chain interactions which are good candidates for inclusion in synthetic helix-terminal loops with specific desired geometries, since they are used in nature to support these geometries. The techniques described here can also be applied to map side chain interactions associated with other structural components of proteins such as beta and gamma turns.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0671-4) contains supplementary material, which is available to authorized users.

Local and macroscopic electrostatic interactions in single α-helices

The noncovalent forces that stabilize protein structures are not fully understood. One way to address this is to study equilibria between unfolded states and α-helices in peptides. Electrostatic forces-which include interactions between side chains, the backbone and side chains, and side chains and the helix macrodipole-are believed to contribute to these equilibria. Here we probe these interactions experimentally using designed peptides. We find that both terminal backbone-side chain and certain side chain-side chain interactions (which include both local effects between proximal charges and interatomic contacts) contribute much more to helix stability than side chain-helix macrodipole electrostatics, which are believed to operate at larger distances. This has implications for current descriptions of helix stability, the understanding of protein folding and the refinement of force fields for biomolecular modeling and simulations. In addition, this study sheds light on the stability of rod-like structures formed by single α-helices, which are common in natural proteins such as non-muscle myosins.

Neighbor preferences of amino acids and context-dependent effects of amino acid substitutions in human, mouse, and dog

Amino acids show apparent propensities toward their neighbors. In addition to preferences of amino acids for their neighborhood context, amino acid substitutions are also considered to be context-dependent. However, context-dependence patterns of amino acid substitutions still remain poorly understood. Using relative entropy, we investigated the neighbor preferences of 20 amino acids and the context-dependent effects of amino acid substitutions with protein sequences in human, mouse, and dog. For 20 amino acids, the highest relative entropy was mostly observed at the nearest adjacent site of either N- or C-terminus except C and G. C showed the highest relative entropy at the third flanking site and periodic pattern was detected at G flanking sites. Furthermore, neighbor preference patterns of amino acids varied greatly in different secondary structures. We then comprehensively investigated the context-dependent effects of amino acid substitutions. Our results showed that nearly half of 380 substitution types were evidently context dependent, and the context-dependent patterns relied on protein secondary structures. Among 20 amino acids, P elicited the greatest effect on amino acid substitutions. The underlying mechanisms of context-dependent effects of amino acid substitutions were possibly mutation bias at a DNA level and natural selection. Our findings may improve secondary structure prediction algorithms and protein design; moreover, this study provided useful information to develop empirical models of protein evolution that consider dependence between residues.

Activity map of the Escherichia coli RNA polymerase bridge helix

Transcription, the synthesis of RNA from a DNA template, is performed by multisubunit RNA polymerases (RNAPs) in all cellular organisms. The bridge helix (BH) is a distinct feature of all multisubunit RNAPs and makes direct interactions with several active site-associated mobile features implicated in the nucleotide addition cycle and RNA and DNA binding. Because the BH has been captured in both kinked and straight conformations in different crystals structures of RNAP, recently supported by molecular dynamics studies, it has been proposed that cycling between these conformations is an integral part of the nucleotide addition cycle. To further evaluate the role of the BH, we conducted systematic alanine scanning mutagenesis of the Escherichia coli RNAP BH to determine its contributions to activities required for transcription. Combining our data with an atomic model of E. coli RNAP, we suggest that alterations in the interactions between the BH and (i) the trigger loop, (ii) fork loop 2, and (iii) switch 2 can help explain the observed changes in RNAP functionality associated with some of the BH variants. Additionally, we show that extensive defects in E. coli RNAP functionality depend upon a single previously not studied lysine residue (Lys-781) that is strictly conserved in all bacteria. It appears that direct interactions made by the BH with other conserved features of RNAP are lost in some of the E. coli alanine substitution variants, which we infer results in conformational changes in RNAP that modify RNAP functionality.