Stability and solubility of proteins from extremophiles

Charges are important for hyperthermophile protein structure and function. However, the number of charges and their predicted contributions to folded state stability are not correlated, implying that more charge does not imply greater stability. The charge properties that distinguish hyperthermophile proteins also differentiate psychrophile proteins from mesophile proteins, but in the opposite direction and to a smaller extent. We conclude that charge number relates to solubility, whereas protein stability is determined by charge location. Most other structural properties are poorly separated over the ambient temperature range, apart from the burial of certain amino acids. Of particular interest are large non-polar sidechains that tend to increased exposure in proteins evolved to function at higher temperatures. Looking at tryptophan in more detail, this increase is often located close to the termini of secondary structure elements, and is discussed in terms of a novel potential role in protein thermostabilisation.     

Small heat shock proteins from extremophiles: a review

Many microorganisms from extreme environments have been well characterized, and increasing access to genomic sequence data has recently allowed the analysis of the protein families related to stress responses. Heat shock proteins appear to be ubiquitous in extremophiles. In this review, we focus on the family of small heat shock proteins (sHSPs) from extremophiles, which are -crystallin homologues. Like the -crystallin eye lens proteins, sHSPs act as molecular chaperones and prevent aggregation of denatured proteins under heat and desiccation stress. Many putative sHSP homologues have been identified in the genomic sequences of all classes of extremophiles. Current studies of shsp gene expression have revealed mechanisms of regulation and activity distinct from other known hsp gene regulation systems. Biochemical studies on sHSPs are limited to thermophilic and hyperthermophilic organisms, and the only two available crystal structures of sHSPs from Methanocaldococcus jannaschii, a hyperthermophilic archaeon and a mesophilic eukaryote, have contributed significantly to an understanding of the mechanisms of action of sHSPs, although many aspects remain unclear.Communicated by D.A. Cowan     

The affinity of GXXXG motifs in transmembrane helix-helix interactions is modulated by long-range communication

Sequence motifs are responsible for ensuring the proper assembly of transmembrane (TM) helices in the lipid bilayer. To understand the mechanism by which the affinity of a common TM-TM interactive motif is controlled at the sequence level, we compared two well characterized GXXXG motif-containing homodimers, those formed by human erythrocyte protein glycophorin A (GpA, high-affinity dimer) and those formed by bacteriophage M13 major coat protein (MCP, low affinity dimer). In both constructs, the GXXXG motif is necessary for TM-TM association. Although the remaining interfacial residues (underlined) in GpA (LIXXGVXXGVXXT) differ from those in MCP (VVXXGAXXGIXXF), molecular modeling performed here indicated that GpA and MCP dimers possess the same overall fold. Thus, we could introduce GpA interfacial residues, alone and in combination, into the MCP sequence to help decrypt the determinants of dimer affinity. Using both in vivo TOXCAT assays and SDS-PAGE gel migration rates of synthetic peptides derived from TM regions of the proteins, we found that the most distal interfacial sites, 12 residues apart (and approximately 18 A in structural space), work in concert to control TM-TM affinity synergistically.     

Linear motifs: evolutionary interaction switches

Linear motifs are short sequence patterns associated with a particular function. They differ fundamentally from longer, globular protein domains in terms of their binding affinities, evolution and in how they are found experimentally or computationally. In this Minireview, we discuss various aspects of these critically important functional regions.     

MUSTA--a general, efficient, automated method for multiple structure alignment and detection of common motifs: application to proteins.

Here we present an algorithm designed to carry out multiple structure alignment and to detect recurring substructural motifs. So far we have implemented it for comparison of protein structures. However, this general method is applicable to comparisons of RNA structures and to detection of a pharmacophore in a series of drug molecules. Further, its sequence order independence permits its application to detection of motifs on protein surfaces, interfaces, and binding/active sites. While there are many methods designed to carry out pairwise structure comparisons, there are only a handful geared toward the multiple structure alignment task. Most of these tackle multiple structure comparison as a collection of pairwise structure comparison tasks. The multiple structural alignment algorithm presented here automatically finds the largest common substructure (core) of atoms that appears in all the molecules in the ensemble. The detection of the core and the structural alignment are done simultaneously. The algorithm begins by finding small substructures that are common to all the proteins in the ensemble. One of the molecules is considered the reference; the others are the source molecules. The small substructures are stored in special arrays termed combinatorial buckets, which define sets of multistructural alignments from the source molecules that coincide with the same small set of reference atoms (C(alpha)-atoms here). These substructures are initial small fragments that have congruent copies in each of the proteins. The substructures are extended, through the processing of the combinatorial buckets, by clustering the superpositions (transformations). The method is very efficient.     

Differential G-alpha interaction capacities of the GoLoco motifs in Rap GTPase activating proteins

GoLoco motif proteins act as guanine nucleotide dissociation inhibitors (GDIs) for G-protein alpha subunits of the adenylyl cyclase-inhibitory (Galpha(i/o)) class. Rap1GAP2 is a newly identified GoLoco motif- and RapGAP domain-containing protein, and thus is considered a potential integrator of heterotrimeric and monomeric GTPase signaling. Primary sequence analysis indicated that the Rap1GAP2 GoLoco motif contains a lysine (Lys-75), rather than an arginine, at the crucial residue responsible for binding the alpha and beta phosphates of GDP and exerting GDI activity. To determine the functional outcome of this sequence variation we conducted a biophysical analysis of the human Rap1GAP2b/c GoLoco motif. We found that human Rap1GAP2b/c was deficient in GDI activity and Galpha interaction capability. Mutation of lysine-75 to arginine could not regain functional activity of the Rap1GAP2b/c GoLoco motif. Thus, the Rap1GAP2b/c GoLoco motif can be classed as inactive towards Galpha subunits. We also found that the Rap1GAP1a GoLoco motif, which lacks seven N-terminal amino acid residues present in canonical GoLoco motifs, does not interact with Galpha(i1). In contrast, the GoLoco motif of Rap1GAP1b, which is canonical in primary sequence, was found to interact with Galpha(i1).GDP.     

The cohesin complex: sequence homologies, interaction networks and shared motifs

Background  

Cohesin is a macromolecular complex that links sister chromatids together at the metaphase plate during mitosis. The links are formed during DNA replication and destroyed during the metaphase-to-anaphase transition. In budding yeast, the 14S cohesin complex comprises at least two classes of SMC (structural maintenance of chromosomes) proteins - Smc1 and Smc3 - and two SCC (sister-chromatid cohesion) proteins - Scc1 and Scc3. The exact function of these proteins is unknown.     

A trimeric, alpha-helical, coiled coil peptide: association stoichiometry and interaction strength by analytical ultracentrifugation

Alpha-helical coiled coils are proving to be almost ideal systems for the modelling of peptide and protein self-association processes. Stable oligomeric systems, in which the stoichiometry is well defined, can be produced by the careful selection of the appropriate amino acid sequence, although the principles behind this are still not fully understood. Here we report on a 35 residue peptide, FZ, synthesized by the solid phase method, which was originally designed to form a dimer, but which, in fact, associates to the trimeric state. A detailed characterization of the associative properties of the peptide has been performed by circular dichroism spectroscopy and, in particular, by sedimentation equilibrium in the analytical ultracentrifuge. The presence of the trimeric state, which is stable even at low peptide concentrations, has been confirmed by various, independent methods of analysis for molar mass. The effects of both temperature and of guanidinium chloride on the peptide have been investigated and both found to be peptide-concentration dependent. The unfolding induced by the denaturant cannot be adequately described by a simple, two state monomer-trimer equilibrium. Received: 29 November 1996 / Accepted: 2 December 1996     

A predictor of membrane class: Discriminating alpha-helical and beta-barrel membrane proteins from non-membranous proteins

Accurate protein structure prediction remains an active objective of research in bioinformatics. Membrane proteins comprise approximately 20% of most genomes. They are, however, poorly tractable targets of experimental structure determination. Their analysis using bioinformatics thus makes an important contribution to their on-going study. Using a method based on Bayesian Networks, which provides a flexible and powerful framework for statistical inference, we have addressed the alignment-free discrimination of membrane from non-membrane proteins. The method successfully identifies prokaryotic and eukaryotic alpha-helical membrane proteins at 94.4% accuracy, beta-barrel proteins at 72.4% accuracy, and distinguishes assorted non-membranous proteins with 85.9% accuracy. The method here is an important potential advance in the computational analysis of membrane protein structure. It represents a useful tool for the characterisation of membrane proteins with a wide variety of potential applications.     

Accurate extraction of functional associations between proteins based on common interaction partners and common domains

MOTIVATION: Genomic and proteomic approaches have accumulated a huge amount of data which provide clues to protein function. However, interpreting single omic data for predicting uncharacterized protein functions has been a challenging task, because the data contain a lot of false positives. To overcome this problem, methods for integrating data from various omic approaches are needed for more accurate function prediction. RESULT: In this paper, we have developed a method which extracts functionally similar proteins with high confidence by integrating protein-protein interaction data and domain information. We used this method to analyze publicly available data from Saccharomyces cerevisiae. We identified 1042 functional associations, involving 765 proteins of which 98 (12.8%) had no previously ascribed function. Our method extracts functionally similar protein pairs more accurately than conventional methods, and predicting function for previously uncharacterized proteins can be achieved. Our method can of course be applied to protein-protein interaction data for any species.     

SMotif: a server for structural motifs in proteins

SMotif is a server that identifies important structural segments or motifs for a given protein structure(s) based on conservation of both sequential as well as important structural features such as solvent inaccessibility, secondary structural content, hydrogen bonding pattern and residue packing. This server also provides three-dimensional orientation patterns of the identified motifs in terms of inter-motif distances and torsion angles. These motifs may form the common core and therefore, can also be employed to design and rationalize protein engineering and folding experiments. AVAILABILITY: SMotif server is available via the URL http://caps.ncbs.res.in/SMotif/index.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

Database of structural motifs in proteins

SUMMARY: The database of structural motifs in proteins (DSMP) contains data relevant to helices, beta-turns, gamma-turns, beta-hairpins, psi-loops, beta-alpha-beta motifs, beta-sheets, beta-strands and disulphide bridges extracted from all proteins in the Protein Data Bank primarily using the PROMOTIF program and implemented as a web-based network service using the SRS. The data corresponding to the structural motifs includes; sequence, position in polypeptide chain, geometry, type, unique code, keywords and resolution of crystal structure. This data is available for a representative data set of 1028 protein chains and also for all 10 213 proteins in the Protein Data Bank. The three-dimensional coordinates for all structural motifs (except sheet and disulphide bridge) are also available for the representative data set. Using features in SRS, DSMP can be queried to extract information from one or more structural motifs that may be useful for sequence-structure analysis, prediction, modelling or design. AVAILABILITY: http://www. cdfd.org.in/dsmp.html     

Conserved motifs in voltage sensing proteins

This paper was aimed to study conserved motifs of voltage sensing proteins (VSPs) and establish a voltage sensing model. All VSPs were collected from the Uniprot database using a comprehensive keyword search followed by manual curation, and the results indicated that there are only two types of known VSPs, voltage gated ion channels and voltage dependent phosphatases. All the VSPs have a common domain of four helical transmembrane segments (TMS, S1-S4), which constitute the voltage sensing module of the VSPs. The S1 segment was shown to be responsible for membrane targeting and insertion of these proteins, while S2-S4 segments, which can sense membrane potential, for protein properties. Conserved motifs/residues and their functional significance of each TMS were identified using profile-to-profile sequence alignments. Conserved motifs in these four segments are strikingly similar for all VSPs, especially, the conserved motif [RK]-X(2)-R-X(2)-R-X(2)-[RK] was presented in all the S4 segments, with positively charged arginine (R) alternating with two hydrophobic or uncharged residues. Movement of these arginines across the membrane electric field is the core mechanism by which the VSPs detect changes in membrane potential. The negatively charged aspartate (D) in the S3 segment is universally conserved in all the VSPs, suggesting that the aspartate residue may be involved in voltage sensing properties of VSPs as well as the electrostatic interactions with the positively charged residues in the S4 segment, which may enhance the thermodynamic stability of the S4 segments in plasma membrane.     

Tutorial section: domains and motifs - proteins in bite-sized chunks

Possibly the ultimate goal of bioinformatics is to be able to predict protein tertiary structure and chemical functionality from the initial amino acid sequence. Despite the best efforts of many researchers over the past two decades, a reliable modelling method has yet to be found and the folding problem continues to be a hurdle for scientists.     

D-SLIMMER: domain-SLiM interaction motifs miner for sequence based protein-protein interaction data

Many biologically important protein-protein interactions (PPIs) have been found to be mediated by short linear motifs (SLiMs). These interactions are mediated by the binding of a protein domain, often with a nonlinear interaction interface, to a SLiM. We propose a method called D-SLIMMER to mine for SLiMs in PPI data on the basis of the interaction density between a nonlinear motif (i.e., a protein domain) in one protein and a SLiM in the other protein. Our results on a benchmark of 113 experimentally verified reference SLiMs showed that D-SLIMMER outperformed existing methods notably for discovering domain-SLiMs interaction motifs. To illustrate the significance of the SLiMs detected, we highlighted two SLiMs discovered from the PPI data by D-SLIMMER that are variants of the known ELM SLiM, as well as a literature-backed SLiM that is yet to be listed in the reference databases. We also presented a novel SLiM predicted by D-SLIMMER that was strongly supported by existing biological literatures. These examples showed that D-SLIMMER is able to find SLiMs that are biologically relevant.     

Interactome-wide prediction of short, disordered protein interaction motifs in humans

Many of the specific functions of intrinsically disordered protein segments are mediated by Short Linear Motifs (SLiMs) interacting with other proteins. Well known examples include SLiMs that interact with 14-3-3, PDZ, SH2, SH3, and WW domains but the true extent and diversity of SLiM-mediated interactions is largely unknown. Here, we attempt to expand our knowledge of human SLiMs by applying in silico SLiM prediction to the human interactome. Combining data from seven different interaction databases, we analysed approximately 6000 protein-centred and 1600 domain-centred human interaction datasets of 3+ unrelated proteins that interact with a common partner. Results were placed in context through comparison to randomised datasets of similar size and composition. The search returned thousands of evolutionarily conserved, intrinsically disordered occurrences of hundreds of significantly enriched recurring motifs, including many that have never been previously identified (). In addition to True Positive results for at least 25 different known SLiMs, a striking number of "off-target" proteins/domains also returned significantly enriched known motifs. Often, this was due to the non-independence of the datasets, with many proteins sharing interaction partners or contributing interactions to multiple domain datasets. The majority of these motif classes, however, were also found to be significantly enriched in one or more randomised datasets. This highlights the need for care when interpreting motif predictions of this nature but also raises the possibility that SLiM occurrences may be successfully identified independently of interaction data. Although not as compositionally biased as previous studies, patterns matching known SLiMs tended to cluster into a few large groups of similar sequence, while novel predictions tended to be more distinctive and less abundant. Whether this is due to ascertainment bias or a true functional composition bias of SLiMs is not clear and warrants further investigation.     

The importance of being proline: the interaction of proline-rich motifs in signaling proteins with their cognate domains.

Acommon focus among molecular and cellular biologists is the identification of proteins that interact with each other. Yeast two-hybrid, cDNA expression library screening, and coimmunoprecipitation experiments are powerful methods for identifying novel proteins that bind to one's favorite protein for the purpose of learning more regarding its cellular function. These same techniques, coupled with truncation and mutagenesis experiments, have been used to define the region of interaction between pairs of proteins. One conclusion from this work is that many interactions occur over short regions, often less than 10 amino acids in length within one protein. For example, mapping studies and 3-dimensional analyses of antigen-antibody interactions have revealed that epitopes are typically 4-7 residues long (1). Other examples include protein-interaction modules, such as Src homology (SH) 2 and 3 domains, phosphotyrosine binding domains (PTB), postsynaptic density/disc-large/ZO1 (PDZ) domains, WW domains, Eps15 homology (EH) domains, and 14-3-3 proteins that typically recognize linear regions of 3-9 amino acids. Each of these domains has been the subject of recent reviews published elsewhere (2 3 4 5 6 7). Among the primary structures of many ligands for protein-protein interactions, the amino acid proline is critical. In particular, SH3, WW, and several new protein-interaction domains prefer ligand sequences that are proline-rich. In addition, even though ligands for EH domains and 14-3-3 domains are not proline-rich, they do include a single proline residue. This review highlights the analysis of those protein-protein interactions that involve proline residues, the biochemistry of proline, and current drug discovery efforts based on proline peptidomimetics.-Kay, B. K., Williamson, M. P., Sudol, M. The importance of being proline: the interaction of proline-rich motifs in signaling proteins with their cognate domains.