Charged single alpha-helices in proteomes revealed by a consensus prediction approach

Generalized Born Implicit Solvent Models Do Not Reproduce Secondary Structures of De Novo Designed Glu/Lys Peptides

We test a range of standard generalized Born (GB) models and protein force fields for a set of five experimentally characterized, designed peptides comprising alternating blocks of glutamate and lysine, which have been shown to differ significantly in α-helical content. Sixty-five combinations of force fields and GB models are evaluated in >800 μs of molecular dynamics simulations. GB models generally do not reproduce the experimentally observed α-helical content, and none perform well for all five peptides. These results illustrate that these models are not usefully predictive in this context. These peptides provide a useful test set for simulation methods.

Disentangling the complexity of low complexity proteins

There are multiple definitions for low complexity regions (LCRs) in protein sequences, with all of them broadly considering LCRs as regions with fewer amino acid types compared to an average composition. Following this view, LCRs can also be defined as regions showing composition bias. In this critical review, we focus on the definition of sequence complexity of LCRs and their connection with structure. We present statistics and methodological approaches that measure low complexity (LC) and related sequence properties. Composition bias is often associated with LC and disorder, but repeats, while compositionally biased, might also induce ordered structures. We illustrate this dichotomy, and more generally the overlaps between different properties related to LCRs, using examples. We argue that statistical measures alone cannot capture all structural aspects of LCRs and recommend the combined usage of a variety of predictive tools and measurements. While the methodologies available to study LCRs are already very advanced, we foresee that a more comprehensive annotation of sequences in the databases will enable the improvement of predictions and a better understanding of the evolution and the connection between structure and function of LCRs. This will require the use of standards for the generation and exchange of data describing all aspects of LCRs.

Short abstract

There are multiple definitions for low complexity regions (LCRs) in protein sequences. In this critical review, we focus on the definition of sequence complexity of LCRs and their connection with structure. We present statistics and methodological approaches that measure low complexity (LC) and related sequence properties. Composition bias is often associated with LC and disorder, but repeats, while compositionally biased, might also induce ordered structures. We illustrate this dichotomy, plus overlaps between different properties related to LCRs, using examples.

LCD-Composer: an intuitive, composition-centric method enabling the identification and detailed functional mapping of low-complexity domains

Low complexity domains (LCDs) in proteins are regions predominantly composed of a small subset of the possible amino acids. LCDs are involved in a variety of normal and pathological processes across all domains of life. Existing methods define LCDs using information-theoretical complexity thresholds, sequence alignment with repetitive regions, or statistical overrepresentation of amino acids relative to whole-proteome frequencies. While these methods have proven valuable, they are all indirectly quantifying amino acid composition, which is the fundamental and biologically-relevant feature related to protein sequence complexity. Here, we present a new computational tool, LCD-Composer, that directly identifies LCDs based on amino acid composition and linear amino acid dispersion. Using LCD-Composer's default parameters, we identified simple LCDs across all organisms available through UniProt and provide the resulting data in an accessible form as a resource. Furthermore, we describe large-scale differences between organisms from different domains of life and explore organisms with extreme LCD content for different LCD classes. Finally, we illustrate the versatility and specificity achievable with LCD-Composer by identifying diverse classes of LCDs using both simple and multifaceted composition criteria. We demonstrate that the ability to dissect LCDs based on these multifaceted criteria enhances the functional mapping and classification of LCDs.

ER/K-link-Leveraging a native protein linker to probe dynamic cellular interactions

ER/K α-helices are a subset of single alpha helical domains, which exhibit unusual stability as isolated protein secondary structures. They adopt an elongated structural conformation, while regulating the frequency of interactions between proteins or polypeptides fused to their ends. Here we review recent advances on the structure, stability and function of ER/K α-helices as linkers (ER/K linkers) in native proteins. We describe methodological considerations in the molecular cloning, protein expression and measurement of interaction strengths, using sensors incorporating ER/K linkers. We highlight biological insights obtained over the last decade by leveraging distinct biophysical features of ER/K-linked sensors. We conclude with the outlook for the use of ER/K linkers in the selective modulation of dynamic cellular interactions.

Unfolding mechanism and free energy landscape of single, stable, alpha helices at low pull speeds

Single alpha helices (SAHs) stable in isolated form are often found in motor proteins where they bridge functional domains. Understanding the mechanical response of SAHs is thus critical to understand their function. The quasi-static force-extension relation of a small number of SAHs is known from single-molecule experiments. Unknown, or still controversial, are the molecular scale details behind those observations. We show that the deformation mechanism of SAHs pulled from the termini at pull speeds approaching the quasi-static limit differs from that of typical helices found in proteins, which are stable only when interacting with other protein domains. Using molecular dynamics simulations with atomistic resolution at low pull speeds previously inaccessible to simulation, we show that SAHs start unfolding from the termini at all pull speeds we investigated. Unfolding proceeds residue-by-residue and hydrogen bond breaking is not the main event determining the barrier to unfolding. We use the molecular simulation data to test the cooperative sticky chain model. This model yields excellent fits of the force-extension curves and quantifies the distance, xE = 0.13 nm, to the transition state, the natural frequency of bond vibration, ν0 = 0.82 ns-1, and the height, V0 = 2.9 kcal mol-1, of the free energy barrier associated with the deformation of single residues. Our results demonstrate that the sticky chain model could advantageously be used to analyze experimental force-extension curves of SAHs and other biopolymers.

Modulating the Stiffness of the Myosin VI Single α-Helical Domain

Highly charged, single α-helical (SAH) domains contain a high percentage of Arg, Lys, and Glu residues. Their dynamic salt bridge pairing creates the exceptional stiffness of these helical rods, with a persistence length of more than 200 Å for the myosin VI SAH domain. With the aim of modulating the stiffness of the helical structure, we investigated the effect, using NMR spectroscopy, of substituting key charged Arg, Lys, Glu, and Asp residues by Gly or His. Results indicate that such mutations result in the transient breaking of the helix at the site of mutation but with noticeable impact on amide hydrogen exchange rates extending as far as ±2 helical turns, pointing to a substantial degree of cooperativity in SAH stability. Whereas a single Gly substitution caused transient breaks ∼20% of the time, two consecutive Gly substitutions break the helix ∼65% of the time. NMR relaxation measurements indicate that the exchange rate between an intact and a broken helix is fast (>300,000 s^-1) and that for the wild-type sequence, the finite persistence length is dominated by thermal fluctuations of backbone torsion angles and H-bond lengths, not by transient helix breaking. The double mutation D27H/E28H causes a pH-dependent fraction of helix disruption, in which the helix breakage increases from 26% at pH 7.5 to 53% at pH 5.5. The ability to modulate helical integrity by pH may enable incorporation of externally tunable dynamic components in the design of molecular machines.

q-Canonical Monte Carlo Sampling for Modeling the Linkage between Charge Regulation and Conformational Equilibria of Peptides

The overall charge content and the patterning of charged residues have a profound impact on the conformational ensembles adopted by intrinsically disordered proteins. These parameters can be altered by charge regulation, which refers to the effects of post-translational modifications, pH-dependent changes to charge, and conformational fluctuations that modify the pKa values of ionizable residues. Although atomistic simulations have played a prominent role in uncovering the major sequence-ensemble relationships of IDPs, most simulations assume fixed charge states for ionizable residues. This may lead to erroneous estimates for conformational equilibria if they are linked to charge regulation. Here, we report the development of a new method we term q-canonical Monte Carlo sampling for modeling the linkage between charge regulation and conformational equilibria. The method, which is designed to be interoperable with the ABSINTH implicit solvation model, operates as follows: For a protein sequence with n ionizable residues, we start with all 2n charge microstates and use a criterion based on model compound pKa values to prune down to a subset of thermodynamically relevant charge microstates. This subset is then grouped into mesostates, where all microstates that belong to a mesostate have the same net charge. Conformational distributions, drawn from a canonical ensemble, are generated for each of the charge microstates that make up a mesostate using a method we designate as proton walk sampling. This method combines Metropolis Monte Carlo sampling in conformational space with an auxiliary Markov process that enables interconversions between charge microstates along a mesostate. Proton walk sampling helps identify the most likely charge microstate per mesostate. We then use thermodynamic integration aided by the multistate Bennett acceptance ratio method to estimate the free energies for converting between mesostates. These free energies are then combined with the per-microstate weights along each mesostate to estimate standard state free energies and pH-dependent free energies for all thermodynamically relevant charge microstates. The results provide quantitative estimates of the probabilities and preferred conformations associated with every thermodynamically accessible charge microstate. We showcase the application of q-canonical sampling using two model systems. The results establish the soundness of the method and the importance of charge regulation in systems characterized by conformational heterogeneity.

Dynamic ion pair behavior stabilizes single α-helices in proteins

Ion pairs are key stabilizing interactions between oppositely charged amino acid side chains in proteins. They are often depicted as single conformer salt bridges (hydrogen-bonded ion pairs) in crystal structures, but it is unclear how dynamic they are in solution. Ion pairs are thought to be particularly important in stabilizing single α-helix (SAH) domains in solution. These highly stable domains are rich in charged residues (such as Arg, Lys, and Glu) with potential ion pairs across adjacent turns of the helix. They provide a good model system to investigate how ion pairs can contribute to protein stability. Using NMR spectroscopy, small-angle X-ray light scattering (SAXS), and molecular dynamics simulations, we provide here experimental evidence that ion pairs exist in a SAH in murine myosin 7a (residues 858-935), but that they are not fixed or long lasting. In silico modeling revealed that the ion pairs within this α-helix exhibit dynamic behavior, rapidly forming and breaking and alternating between different partner residues. The low-energy helical state was compatible with a great variety of ion pair combinations. Flexible ion pair formation utilizing a subset of those available at any one time avoided the entropic penalty of fixing side chain conformations, which likely contributed to helix stability overall. These results indicate the dynamic nature of ion pairs in SAHs. More broadly, thermodynamic stability in other proteins is likely to benefit from the dynamic behavior of multi-option solvent-exposed ion pairs.

Detection of single alpha-helices in large protein sequence sets using hardware acceleration

Single alpha-helices (SAHs) are increasingly recognized as important structural and functional elements of proteins. Comprehensive identification of SAH segments in large protein datasets was largely hindered by the slow speed of the most restrictive prediction tool for their identification, FT_CHARGE on common hardware. We have previously implemented an FPGA-based version of this tool allowing fast analysis of a large number of sequences. Using this implementation, we have set up of a semi-automated pipeline capable of analyzing full UniProt releases in reasonable time and compiling monthly updates of a comprehensive database of SAH segments. Releases of this database, denoted CSAHDB, is available on the CSAHserver 2 website at csahserver.itk.ppke.hu. An overview of human SAH-containing sequences combined with a literature survey suggests specific roles of SAH segments in proteins involved in RNA-based regulation processes as well as cytoskeletal proteins, a number of which is also linked to the development and function of synapses.

Waggawagga-CLI: A command-line tool for predicting stable single α-helices (SAH-domains), and the SAH-domain distribution across eukaryotes

Stable single-alpha helices (SAH-domains) function as rigid connectors and constant force springs between structural domains, and can provide contact surfaces for protein-protein and protein-RNA interactions. SAH-domains mainly consist of charged amino acids and are monomeric and stable in polar solutions, characteristics which distinguish them from coiled-coil domains and intrinsically disordered regions. Although the number of reported SAH-domains is steadily increasing, genome-wide analyses of SAH-domains in eukaryotic genomes are still missing. Here, we present Waggawagga-CLI, a command-line tool for predicting and analysing SAH-domains in protein sequence datasets. Using Waggawagga-CLI we predicted SAH-domains in 24 datasets from eukaryotes across the tree of life. SAH-domains were predicted in 0.5 to 3.5% of the protein-coding content per species. SAH-domains are particularly present in longer proteins supporting their function as structural building block in multi-domain proteins. In human, SAH-domains are mainly used as alternative building blocks not being present in all transcripts of a gene. Gene ontology analysis showed that yeast proteins with SAH-domains are particular enriched in macromolecular complex subunit organization, cellular component biogenesis and RNA metabolic processes, and that they have a strong nuclear and ribonucleoprotein complex localization and function in ribosome and nucleic acid binding. Human proteins with SAH-domains have roles in all types of RNA processing and cytoskeleton organization, and are predicted to function in RNA binding, protein binding involved in cell and cell-cell adhesion, and cytoskeletal protein binding. Waggawagga-CLI allows the user to adjust the stabilizing and destabilizing contribution of amino acid interactions in i,i+3 and i,i+4 spacings, and provides extensive flexibility for user-designed analyses.

Improving prediction accuracy using decision-tree-based meta-strategy and multi-threshold sequential-voting exemplified by miRNA target prediction

Lots of computational predictors have been developed for fast and large-scale analysis of biological data. However, many of them were developed long time ago when training datasets or sets of input features were rather small. Consequently, the utility of these predictors in much large datasets, which are very common in nowadays, need to be examined carefully. In addition, with the rapid development of scientific research, the expectation on the prediction accuracy of computational predictors is continuously uplifting. Therefore, developing novel strategies to improve the prediction accuracies of computational predictors becomes critical. In this study, the predictive results of existing individual miRNA target predictors were integrated into a decision-tree to make meta-prediction. When the multi-threshold sequential-voting technique was used, the prediction accuracy of the decision-tree was significantly improved by at least thirty percentage points compared to the individual predictors.

Distribution and evolution of stable single α-helices (SAH domains) in myosin motor proteins

Stable single-alpha helices (SAHs) are versatile structural elements in many prokaryotic and eukaryotic proteins acting as semi-flexible linkers and constant force springs. This way SAH-domains function as part of the lever of many different myosins. Canonical myosin levers consist of one or several IQ-motifs to which light chains such as calmodulin bind. SAH-domains provide flexibility in length and stiffness to the myosin levers, and may be particularly suited for myosins working in crowded cellular environments. Although the function of the SAH-domains in human class-6 and class-10 myosins has well been characterised, the distribution of the SAH-domain in all myosin subfamilies and across the eukaryotic tree of life remained elusive. Here, we analysed the largest available myosin sequence dataset consisting of 7919 manually annotated myosin sequences from 938 species representing all major eukaryotic branches using the SAH-prediction algorithm of Waggawagga, a recently developed tool for the identification of SAH-domains. With this approach we identified SAH-domains in more than one third of the supposed 79 myosin subfamilies. Depending on the myosin class, the presence of SAH-domains can range from a few to almost all class members indicating complex patterns of independent and taxon-specific SAH-domain gain and loss.

Characterization of long and stable de novo single alpha-helix domains provides novel insight into their stability

Naturally-occurring single α-helices (SAHs), are rich in Arg (R), Glu (E) and Lys (K) residues, and stabilized by multiple salt bridges. Understanding how salt bridges promote their stability is challenging as SAHs are long and their sequences highly variable. Thus, we designed and tested simple de novo 98-residue polypeptides containing 7-residue repeats (AEEEXXX, where X is K or R) expected to promote salt-bridge formation between Glu and Lys/Arg. Lys-rich sequences (EK3 (AEEEKKK) and EK2R1 (AEEEKRK)) both form SAHs, of which EK2R1 is more helical and thermo-stable suggesting Arg increases stability. Substituting Lys with Arg (or vice versa) in the naturally-occurring myosin-6 SAH similarly increased (or decreased) its stability. However, Arg-rich de novo sequences (ER3 (AEEERRR) and EK1R2 (AEEEKRR)) aggregated. Combining a PDB analysis with molecular modelling provides a rational explanation, demonstrating that Glu and Arg form salt bridges more commonly, utilize a wider range of rotamer conformations, and are more dynamic than Glu–Lys. This promiscuous nature of Arg helps explain the increased propensity of de novo Arg-rich SAHs to aggregate. Importantly, the specific K:R ratio is likely to be important in determining helical stability in de novo and naturally-occurring polypeptides, giving new insight into how single α-helices are stabilized.

Ca2+-Induced Rigidity Change of the Myosin VIIa IQ Motif-Single α Helix Lever Arm Extension

Several unconventional myosins contain a highly charged single α helix (SAH) immediately following the calmodulin (CaM) binding IQ motifs, functioning to extend lever arms of these myosins. How such SAH is connected to the IQ motifs and whether the conformation of the IQ motifs-SAH segments are regulated by Ca²⁺ fluctuations are not known. Here, we demonstrate by solving its crystal structure that the predicted SAH of myosin VIIa (Myo7a) forms a stable SAH. The structure of Myo7a IQ5-SAH segment in complex with apo-CaM reveals that the SAH sequence can extend the length of the Myo7a lever arm. Although Ca²⁺-CaM remains bound to IQ5-SAH, the Ca²⁺-induced CaM binding mode change softens the conformation of the IQ5-SAH junction, revealing a Ca²⁺-induced lever arm flexibility change for Myo7a. We further demonstrate that the last IQ motif of several other myosins also binds to both apo- and Ca²⁺-CaM, suggesting a common Ca²⁺-induced conformational regulation mechanism.

Consensus Prediction of Charged Single Alpha-Helices with CSAHserver

Charged single alpha-helices (CSAHs) constitute a rare structural motif. CSAH is characterized by a high density of regularly alternating residues with positively and negatively charged side chains. Such segments exhibit unique structural properties; however, there are only a handful of proteins where its existence is experimentally verified. Therefore, establishing a pipeline that is capable of predicting the presence of CSAH segments with a low false positive rate is of considerable importance. Here we describe a consensus-based approach that relies on two conceptually different CSAH detection methods and a final filter based on the estimated helix-forming capabilities of the segments. This pipeline was shown to be capable of identifying previously uncharacterized CSAH segments that could be verified experimentally. The method is available as a web server at http://csahserver.itk.ppke.hu and also a downloadable standalone program suitable to scan larger sequence collections.

Integrated Strategy Improves the Prediction Accuracy of miRNA in Large Dataset

MiRNAs are short non-coding RNAs of about 22 nucleotides, which play critical roles in gene expression regulation. The biogenesis of miRNAs is largely determined by the sequence and structural features of their parental RNA molecules. Based on these features, multiple computational tools have been developed to predict if RNA transcripts contain miRNAs or not. Although being very successful, these predictors started to face multiple challenges in recent years. Many predictors were optimized using datasets of hundreds of miRNA samples. The sizes of these datasets are much smaller than the number of known miRNAs. Consequently, the prediction accuracy of these predictors in large dataset becomes unknown and needs to be re-tested. In addition, many predictors were optimized for either high sensitivity or high specificity. These optimization strategies may bring in serious limitations in applications. Moreover, to meet continuously raised expectations on these computational tools, improving the prediction accuracy becomes extremely important. In this study, a meta-predictor mirMeta was developed by integrating a set of non-linear transformations with meta-strategy. More specifically, the outputs of five individual predictors were first preprocessed using non-linear transformations, and then fed into an artificial neural network to make the meta-prediction. The prediction accuracy of meta-predictor was validated using both multi-fold cross-validation and independent dataset. The final accuracy of meta-predictor in newly-designed large dataset is improved by 7% to 93%. The meta-predictor is also proved to be less dependent on datasets, as well as has refined balance between sensitivity and specificity. This study has two folds of importance: First, it shows that the combination of non-linear transformations and artificial neural networks improves the prediction accuracy of individual predictors. Second, a new miRNA predictor with significantly improved prediction accuracy is developed for the community for identifying novel miRNAs and the complete set of miRNAs. Source code is available at:https://github.com/xueLab/mirMeta

Functional and Structural Characterization of Novel Type of Linker Connecting Capsid and Nucleocapsid Protein Domains in Murine Leukemia Virus

The assembly of immature retroviral particles is initiated in the cytoplasm by the binding of the structural polyprotein precursor Gag with viral genomic RNA. The protein interactions necessary for assembly are mediated predominantly by the capsid (CA) and nucleocapsid (NC) domains, which have conserved structures. In contrast, the structural arrangement of the CA-NC connecting region differs between retroviral species. In HIV-1 and Rous sarcoma virus, this region forms a rod-like structure that separates the CA and NC domains, whereas in Mason-Pfizer monkey virus, this region is densely packed, thus holding the CA and NC domains in close proximity. Interestingly, the sequence connecting the CA and NC domains in gammaretroviruses, such as murine leukemia virus (MLV), is unique. The sequence is called a charged assembly helix (CAH) due to a high number of positively and negatively charged residues. Although both computational and deletion analyses suggested that the MLV CAH forms a helical conformation, no structural or biochemical data supporting this hypothesis have been published. Using an in vitro assembly assay, alanine scanning mutagenesis, and biophysical techniques (circular dichroism, NMR, microcalorimetry, and electrophoretic mobility shift assay), we have characterized the structure and function of the MLV CAH. We provide experimental evidence that the MLV CAH belongs to a group of charged, E(R/K)-rich, single α-helices. This is the first single α-helix motif identified in viral proteins.

The clear and dark sides of water: influence on the coiled coil folding domain

The essential role of water in extra- and intracellular coiled coil structures of proteins is critically evaluated, and the different protein types incorporating coiled coil units are overviewed. The following subjects are discussed: i) influence of water on the formation and degradation of the coiled coil domain together with the stability of this conformer type; ii) the water's paradox iii) design of coiled coil motifs and iv) expert opinion and outlook is presented. The clear and dark sides refer to the positive and negative aspects of the water molecule, as it may enhance or inhibit a given folding event. This duplicity can be symbolized by the Roman 'Janus-face' which means that water may facilitate and stimulate coiled coil structure formation, however, it may contribute to the fatal processes of oligomerization and amyloidosis of the very same polypeptide chain.

A conserved charged single α-helix with a putative steric role in paraspeckle formation

Paraspeckles are subnuclear particles involved in the regulation of mRNA expression. They are formed by the association of DBHS family proteins and the NEAT1 long noncoding RNA. Here, we show that a recently identified structural motif, the charged single α-helix, is largely conserved in the DBHS family. Based on the available structural data and a previously suggested multimerization scheme of DBHS proteins, we built a structural model of a (PSPC1/NONO)(n) multimer that might have relevance in paraspeckle formation. Our model contains an extended coiled-coil region that is followed by and partially overlaps with the predicted charged single α-helix. We suggest that the charged single α-helix can act as an elastic ruler governing the exact positioning of the dimeric core structures relative to each other during paraspeckle assembly along the NEAT1 noncoding RNA.

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.

Myosin tails and single α-helical domains

The human genome contains 39 myosin genes, divided up into 12 different classes. The structure, cellular function and biochemical properties of many of these isoforms remain poorly characterized and there is still some controversy as to whether some myosin isoforms are monomers or dimers. Myosin isoforms 6 and 10 contain a stable single α-helical (SAH) domain, situated just after the canonical lever. The SAH domain is stiff enough to be able to lengthen the lever allowing the myosin to take a larger step. In addition, atomic force microscopy and atomistic simulations show that SAH domains unfold at relatively low forces and have a high propensity to refold. These properties are likely to be important for protein function, enabling motors to carry cargo in dense actin networks, and other proteins to remain attached to binding partners in the crowded cell.

Role of water in protein folding, oligomerization, amyloidosis and miniprotein

The essential involvement of water in most fundamental extra-cellular and intracellular processes of proteins is critically reviewed and evaluated in this article. The role of water in protein behavior displays structural ambivalence; it can protect the disordered peptide-chain by hydration or helps the globular chain-folding, but promotes also the protein aggregation, as well (see: diseases). A variety of amyloid diseases begins as benign protein monomers but develops then into toxic amyloid aggregates of fibrils. Our incomplete knowledge of this process emphasizes the essential need to reveal the principles of governing this oligomerization. To understand the biophysical basis of the simpler in vitro amyloid formation may help to decipher also the in vivo way. Nevertheless, to ignore the central role of the water's effect among these events means to receive an uncompleted picture of the true phenomenon. Therefore this review represents a stopgap role, because the most published studies--with a few exceptions--have been neglected the crucial importance of water in the protein research. The following questions are discussed from the water's viewpoint: (i) interactions between water and proteins, (ii) protein hydration/dehydration, (iii) folding of proteins and miniproteins, (iv) peptide/protein oligomerization, and (v) amyloidosis.

Harnessing the unique structural properties of isolated α-helices

The α-helix is a ubiquitous secondary structural element that is almost exclusively observed in proteins when stabilized by tertiary or quaternary interactions. However, beginning with the unexpected observations of α-helix formation in the isolated C-peptide in ribonuclease A, there is growing evidence that a significant percentage (0.2%) of all proteins contain isolated stable single α-helical domains (SAH). These SAH domains provide unique structural features essential for normal protein function. A subset of SAH domains contain a characteristic ER/K motif, composed of a repeating sequence of ∼4 consecutive glutamic acids followed by ∼4 consecutive basic arginine or lysine (R/K) residues. The ER/K α-helix, also termed the ER/K linker, has been extensively characterized in the context of the myosin family of molecular motors and is emerging as a versatile structural element for protein and cellular engineering applications. Here, we review the structure and function of SAH domains, as well as the tools to identify them in natural proteins. We conclude with a discussion of recent studies that have successfully used the modular ER/K linker for engineering chimeric myosin proteins with altered mechanical properties, as well as synthetic polypeptides that can be used to monitor and systematically modulate protein interactions within cells.

Are proposed early genetic codes capable of encoding viable proteins?

Proteins are elaborate biopolymers balancing between contradicting intrinsic propensities to fold, aggregate, or remain disordered. Assessing their primary structural preferences observable without evolutionary optimization has been reinforced by the recent identification of de novo proteins that have emerged from previously non-coding sequences. In this paper we investigate structural preferences of hypothetical proteins translated from random DNA segments using the standard genetic code and three of its proposed evolutionarily predecessor models encoding 10, 6, and 4 amino acids, respectively. Our only main assumption is that the disorder, aggregation, and transmembrane helix predictions used are able to reflect the differences in the trends of the protein sets investigated. We found that the 10-residue code encodes proteins that resemble modern proteins in their predicted structural properties. All of the investigated early genetic codes give rise to proteins with enhanced disorder and diminished aggregation propensities. Our results suggest that an ancestral genetic code similar to the proposed 10-residue one is capable of encoding functionally diverse proteins but these might have existed under conditions different from today's common physiological ones. The existence of a protein functional repertoire for the investigated earlier stages which is quite distinct as it is today can be deduced from the presented results.

Is Five Percent Too Small? Analysis of the Overlaps between Disorder, Coiled Coil and Collagen Predictions in Complete Proteomes

Identification of intrinsic disorder in proteins and proteomes has revealed important novel aspects of protein function and interactions. However, it has been pointed out that several oligomeric fibrillar protein motifs such as coiled coils and collagen triple helical segments can also identified as intrinsically disordered. This feature has not yet been investigated in more detail at the proteome level. The present work aims at the identification and quantification of such overlaps in full proteomes to assess their significance in large-scale studies of protein disorder. It was found that the percentage of cross-predicted residues is around 5% in the human proteome and is generally near that value in other metazoan ones but shows remarkable variation in different organisms. In particular, smaller proteomes are increasingly prone to such cross-predictions, thus, especially the analysis of viral proteomes requires the use of specific prediction tools.