Complex networks govern coiled-coil oligomerization--predicting and profiling by means of a machine learning approach

CoCoNat: a novel method based on deep learning for coiled-coil prediction

MOTIVATION

Coiled-coil domains (CCD) are widespread in all organisms and perform several crucial functions. Given their relevance, the computational detection of CCD is very important for protein functional annotation. State-of-the-art prediction methods include the precise identification of CCD boundaries, the annotation of the typical heptad repeat pattern along the coiled-coil helices as well as the prediction of the oligomerization state.

RESULTS

In this article, we describe CoCoNat, a novel method for predicting coiled-coil helix boundaries, residue-level register annotation, and oligomerization state. Our method encodes sequences with the combination of two state-of-the-art protein language models and implements a three-step deep learning procedure concatenated with a Grammatical-Restrained Hidden Conditional Random Field for CCD identification and refinement. A final neural network predicts the oligomerization state. When tested on a blind test set routinely adopted, CoCoNat obtains a performance superior to the current state-of-the-art both for residue-level and segment-level CCD. CoCoNat significantly outperforms the most recent state-of-the-art methods on register annotation and prediction of oligomerization states.

AVAILABILITY AND IMPLEMENTATION

CoCoNat web server is available at https://coconat.biocomp.unibo.it. Standalone version is available on GitHub at https://github.com/BolognaBiocomp/coconat.

CoCoPRED: coiled-coil protein structural feature prediction from amino acid sequence using deep neural networks

MOTIVATION

Coiled-coil is composed of two or more helices that are wound around each other. It widely exists in proteins and has been discovered to play a variety of critical roles in biology processes. Generally, there are three types of structural features in coiled-coil: coiled-coil domain (CCD), oligomeric state and register. However, most of the existing computational tools only focus on one of them.

RESULTS

Here, we describe a new deep learning model, CoCoPRED, which is based on convolutional layers, bidirectional long short-term memory, and attention mechanism. It has three networks, i.e. CCD network, oligomeric state network, and register network, corresponding to the three types of structural features in coiled-coil. This means CoCoPRED has the ability of fulfilling comprehensive prediction for coiled-coil proteins. Through the 5-fold cross-validation experiment, we demonstrate that CoCoPRED can achieve better performance than the state-of-the-art models on both CCD prediction and oligomeric state prediction. Further analysis suggests the CCD prediction may be a performance indicator of the oligomeric state prediction in CoCoPRED. The attention heads in CoCoPRED indicate that registers a, b and e are more crucial for the oligomeric state prediction.

AVAILABILITY AND IMPLEMENTATION

CoCoPRED is available at http://www.csbio.sjtu.edu.cn/bioinf/CoCoPRED. The datasets used in this research can also be downloaded from the website.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Critical assessment of coiled-coil predictions based on protein structure data

Coiled-coil regions were among the first protein motifs described structurally and theoretically. The simplicity of the motif promises that coiled-coil regions can be detected with reasonable accuracy and precision in any protein sequence. Here, we re-evaluated the most commonly used coiled-coil prediction tools with respect to the most comprehensive reference data set available, the entire Protein Data Bank, down to each amino acid and its secondary structure. Apart from the 30-fold difference in minimum and maximum number of coiled coils predicted the tools strongly vary in where they predict coiled-coil regions. Accordingly, there is a high number of false predictions and missed, true coiled-coil regions. The evaluation of the binary classification metrics in comparison with naïve coin-flip models and the calculation of the Matthews correlation coefficient, the most reliable performance metric for imbalanced data sets, suggests that the tested tools' performance is close to random. This implicates that the tools' predictions have only limited informative value. Coiled-coil predictions are often used to interpret biochemical data and are part of in-silico functional genome annotation. Our results indicate that these predictions should be treated very cautiously and need to be supported and validated by experimental evidence.

StackSSSPred: A Stacking-Based Prediction of Supersecondary Structure from Sequence

Supersecondary structure (SSS) refers to specific geometric arrangements of several secondary structure (SS) elements that are connected by loops. The SSS can provide useful information about the spatial structure and function of a protein. As such, the SSS is a bridge between the secondary structure and tertiary structure. In this chapter, we propose a stacking-based machine learning method for the prediction of two types of SSSs, namely, β-hairpins and β-α-β, from the protein sequence based on comprehensive feature encoding. To encode protein residues, we utilize key features such as solvent accessibility, conservation profile, half surface exposure, torsion angle fluctuation, disorder probabilities, and more. The usefulness of the proposed approach is assessed using a widely used threefold cross-validation technique. The obtained empirical result shows that the proposed approach is useful and prediction can be improved further.

Prediction of gene regulatory enhancers across species reveals evolutionarily conserved sequence properties

Genomic regions with gene regulatory enhancer activity turnover rapidly across mammals. In contrast, gene expression patterns and transcription factor binding preferences are largely conserved between mammalian species. Based on this conservation, we hypothesized that enhancers active in different mammals would exhibit conserved sequence patterns in spite of their different genomic locations. To investigate this hypothesis, we evaluated the extent to which sequence patterns that are predictive of enhancers in one species are predictive of enhancers in other mammalian species by training and testing two types of machine learning models. We trained support vector machine (SVM) and convolutional neural network (CNN) classifiers to distinguish enhancers defined by histone marks from the genomic background based on DNA sequence patterns in human, macaque, mouse, dog, cow, and opossum. The classifiers accurately identified many adult liver, developing limb, and developing brain enhancers, and the CNNs outperformed the SVMs. Furthermore, classifiers trained in one species and tested in another performed nearly as well as classifiers trained and tested on the same species. We observed similar cross-species conservation when applying the models to human and mouse enhancers validated in transgenic assays. This indicates that many short sequence patterns predictive of enhancers are largely conserved. The sequence patterns most predictive of enhancers in each species matched the binding motifs for a common set of TFs enriched for expression in relevant tissues, supporting the biological relevance of the learned features. Thus, despite the rapid change of active enhancer locations between mammals, cross-species enhancer prediction is often possible. Our results suggest that short sequence patterns encoding enhancer activity have been maintained across more than 180 million years of mammalian evolution.

Investigating nanohybrid material based on 3D CNTs@Cu nanoparticle composite and imprinted polymer for highly selective detection of chloramphenicol

Nanotechnology holds great promise for the fabrication of versatile materials that can be used as sensor platforms for the highly selective detection of analytes. In this research article we report a new nanohybrid material, where 3D imprinted nanostructures are constructed. First, copper nanoparticles are deposited on carbon nanotubes and then a hybrid structure is formed by coating molecularly imprinted polymer on 3D CNTs@Cu NPs; and a layer by layer assembly is achieved. SEM and AFM revealed the presence of Cu NPs (100-500nm) anchored along the whole length of CNTs, topped with imprinted layer. This material was applied to fabricate an electrochemical sensor to monitor a model veterinary drug, chloramphenicol. The high electron transfer ability and conductivity of the prepared material produced sensitive response, whereas, molecular imprinting produces selectivity towards drug detection. The sensor responses were found concentration dependent and the detection limit was calculated to be 10μM (S/N=3). Finally, we showed how changing the polymer composition, the extent of cross linking, and sensor layer thickness greatly affects the number of binding sites for the recognition of drug. This work paves the way to build variants of 3D imprinted materials for the detection of other kinds of biomolecules and antibiotics.

Genetic landscape of papillary thyroid carcinoma in the Chinese population

Improvement in the clinical outcome of human cancers requires characterization of the genetic alterations underlying their pathogenesis. Large-scale genomic and transcriptomic characterization of papillary thyroid carcinomas (PTCs) in Western populations has revealed multiple oncogenic drivers which are essential for understanding pathogenic mechanisms of this disease, while, so far, the genetic landscape in Chinese patients with PTC remains uncharacterized. Here, we conducted a large-scale genetic analysis of PTCs from patients in China to determine the mutational landscape of this cancer. By performing targeted DNA amplicon and targeted RNA deep-sequencing, we elucidated the landscape of somatic genetic alterations in 355 Chinese patients with PTC. A total of 88.7% of PTCs were found to harbor at least one candidate oncogenic driver genetic alteration. Among them, around 72.4% of the cases carried BRAF mutations; 2.8% of cases harbored RAS mutations; and 13.8% of cases were characterized with in-frame gene fusions, including seven newly identified kinase gene fusions. TERT promoter mutations were likely to occur in a sub-clonal manner in our PTC cohort. The prevalence of somatic genetic alterations in PTC was significantly different between our Chinese cohort and TCGA datasets for American patients. Additionally, combined analyses of genetic alterations and clinicopathologic features demonstrated that kinase gene fusion was associated with younger age at diagnosis, larger tumor size, and lymph node metastasis in PTC. With the analyses of DNA rearrangement sites of RET gene fusions in PTC, signatures of chromosome translocations related to RET fusion events were also depicted. Collectively, our results provide fundamental insight into the pathogenesis of PTC in the Chinese population. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Designed Protein Origami

Proteins are highly perfected natural molecular machines, owing their properties to the complex tertiary structures with precise spatial positioning of different functional groups that have been honed through millennia of evolutionary selection. The prospects of designing new molecular machines and structural scaffolds beyond the limits of natural proteins make design of new protein folds a very attractive prospect. However, de novo design of new protein folds based on optimization of multiple cooperative interactions is very demanding. As a new alternative approach to design new protein folds unseen in nature, folds can be designed as a mathematical graph, by the self-assembly of interacting polypeptide modules within the single chain. Orthogonal coiled-coil dimers seem like an ideal building module due to their shape, adjustable length, and above all their designability. Similar to the approach of DNA nanotechnology, where complex tertiary structures are designed from complementary nucleotide segments, a polypeptide chain composed of a precisely specified sequence of coiled-coil forming segments can be designed to self-assemble into polyhedral scaffolds. This modular approach encompasses long-range interactions that define complex tertiary structures. We envision that by expansion of the toolkit of building blocks and design strategies of the folding pathways protein origami technology will be able to construct diverse molecular machines.

The Nup62 Coiled-Coil Motif Provides Plasticity for Triple-Helix Bundle Formation

The central transport channel of the vertebrate nuclear pore complex (NPC) consists of nucleoporins: Nup62, Nup54, and Nup58. The coiled-coil domains in α-helical regions of these nucleoporins are thought to be crucial for several protein-protein interactions in the NPC subcomplexes. In this study, we determined the crystal structure of the coiled-coil domain of rat Nup62 fragment (residues 362-425) to 2.4 Å resolution. The crystal structure shows the conserved coiled-coil domain as a parallel three-helix bundle for the Nup62(362-425) fragment. On the basis of our size exclusion chromatography coupled to multiangle light scattering analysis and glutaraldehyde cross-linking experiments, we conclude that the Nup62(362-425) fragment displays dynamic behavior in solution and can also exist in either homodimeric or homotrimeric states. Our comparative analysis of the rat Nup62(362-425) homotrimeric structure with previously reported heterotrimeric structures [rat Nup62(362-425)·Nup54(346-407) and Xenopus Nup62(358-485)·Nup54(315-450)·Nup58(283-406) complexes] demonstrates the structural basis for parallel triple-helix bundle formation for Nup62 with different partners. Moreover, we show that the coiled-coil domain of Nup62 is sufficient for interaction with the coiled-coil domain of rat Exo70, a protein in an exocyst complex. On the basis of these observations, we suggest the plausible chain replacement mechanism that yields to diverse protein assemblies with Nup62. In summary, the coiled-coil motif present in Nup62 imparts the ability to form a homotrimer and heterotrimers either with Nup54 or with Nup54-Nup58 within the NPCs as well as with Exo70 beyond the NPCs. These complexes of Nup62 suggest the crucial role of the coiled-coil motifs in providing plasticity to various modular assemblies.

Electron Microscopy Structural Insights into CPAP Oligomeric Behavior: A Plausible Assembly Process of a Supramolecular Scaffold of the Centrosome

Centrosomal P4.1-associated protein (CPAP) is a cell cycle regulated protein fundamental for centrosome assembly and centriole elongation. In humans, the region between residues 897–1338 of CPAP mediates interactions with other proteins and includes a homodimerization domain. CPAP mutations cause primary autosomal recessive microcephaly and Seckel syndrome. Despite of the biological/clinical relevance of CPAP, its mechanistic behavior remains unclear and its C-terminus (the G-box/TCP domain) is the only part whose structure has been solved. This situation is perhaps due in part to the challenges that represent obtaining the protein in a soluble, homogeneous state for structural studies. Our work constitutes a systematic structural analysis on multiple oligomers of HsCPAP^897−1338, using single-particle electron microscopy (EM) of negatively stained (NS) samples. Based on image classification into clearly different regular 3D maps (putatively corresponding to dimers and tetramers) and direct observation of individual images representing other complexes of HsCPAP^897−1338 (i.e., putative flexible monomers and higher-order multimers), we report a dynamic oligomeric behavior of this protein, where different homo-oligomers coexist in variable proportions. We propose that dimerization of the putative homodimer forms a putative tetramer which could be the structural unit for the scaffold that either tethers the pericentriolar material to centrioles or promotes procentriole elongation. A coarse fitting of atomic models into the NS 3D maps at resolutions around 20 Å is performed only to complement our experimental data, allowing us to hypothesize on the oligomeric composition of the different complexes. In this way, the current EM work represents an initial step toward the structural characterization of different oligomers of CPAP, suggesting further insights to understand how this protein works, contributing to the elucidation of control mechanisms for centriole biogenesis.

ACCORD: an assessment tool to determine the orientation of homodimeric coiled-coils

The coiled-coil (CC) domain is a very important structural unit of proteins that plays critical roles in various biological functions. The major oligomeric state of CCs is a dimer, which can be either parallel or antiparallel. The orientation of each α-helix in a CC domain is critical for the molecular function of CC-containing proteins, but cannot be determined easily by sequence-based prediction. We developed a biochemical method for assessing differences between parallel and antiparallel CC homodimers and named it ACCORD (Assessment tool for homodimeric Coiled-Coil ORientation Decision). To validate this technique, we applied it to 15 different CC proteins with known structures, and the ACCORD results identified these proteins well, especially with long CCs. Furthermore, ACCORD was able to accurately determine the orientation of a CC domain of unknown directionality that was subsequently confirmed by X-ray crystallography and small angle X-ray scattering. Thus, ACCORD can be used as a tool to determine CC directionality to supplement the results of in silico prediction.

MEDI1873, a potent, stabilized hexameric agonist of human GITR with regulatory T-cell targeting potential

Glucocorticoid-induced tumor necrosis factor receptor-related protein (GITR) is part of a system of signals involved in controlling T-cell activation. Targeting and agonizing GITR in mice promotes antitumor immunity by enhancing the function of effector T cells and inhibiting regulatory T cells. Here, we describe MEDI1873, a novel hexameric human GITR agonist comprising an IgG1 Fc domain, a coronin 1A trimerization domain and the human GITRL extracellular domain (ECD). MEDI1873 was optimized through systematic testing of different trimerization domains, aglycosylation of the GITRL ECD and comparison of different Fc isotypes. MEDI1873 exhibits oligomeric heterogeneity and superiority to an anti-GITR antibody with respect to evoking robust GITR agonism, T-cell activation and clustering of Fc gamma receptors. Further, it recapitulates, in vitro, several aspects of GITR targeting described in mice, including modulation of regulatory T-cell suppression and the ability to increase the CD8⁺:CD4⁺ T-cell ratio via antibody-dependent T-cell cytotoxicity. To support translation into a therapeutic setting, we demonstrate that MEDI1873 is a potent T-cell agonist in vivo in non-human primates, inducing marked enhancement of humoral and T-cell proliferative responses against protein antigen, and demonstrate the presence of GITR- and FoxP3-expressing infiltrating lymphocytes in a range of human tumors. Overall our data provide compelling evidence that MEDI1873 is a novel, potent GITR agonist with the ability to modulate T-cell responses, and suggest that previously described GITR biology in mice may translate to the human setting, reinforcing the potential of targeting the GITR pathway as a therapeutic approach to cancer.

The Structure and Topology of α-Helical Coiled Coils

α-Helical coiled coils constitute one of the most diverse folds yet described. They range in length over two orders of magnitude; they form rods, segmented ropes, barrels, funnels, sheets, spirals, and rings, which encompass anywhere from two to more than 20 helices in parallel or antiparallel orientation; they assume different helix crossing angles, degrees of supercoiling, and packing geometries. This structural diversity supports a wide range of biological functions, allowing them to form mechanically rigid structures, provide levers for molecular motors, project domains across large distances, mediate oligomerization, transduce conformational changes and facilitate the transport of other molecules. Unlike almost any other protein fold known to us, their structure can be computed from parametric equations, making them an ideal model system for rational protein design. Here we outline the principles by which coiled coils are structured, review the determinants of their folding and stability, and present an overview of their diverse architectures.

Critical evaluation of in silico methods for prediction of coiled-coil domains in proteins

Coiled-coils refer to a bundle of helices coiled together like strands of a rope. It has been estimated that nearly 3% of protein-encoding regions of genes harbour coiled-coil domains (CCDs). Experimental studies have confirmed that CCDs play a fundamental role in subcellular infrastructure and controlling trafficking of eukaryotic cells. Given the importance of coiled-coils, multiple bioinformatics tools have been developed to facilitate the systematic and high-throughput prediction of CCDs in proteins. In this article, we review and compare 12 sequence-based bioinformatics approaches and tools for coiled-coil prediction. These approaches can be categorized into two classes: coiled-coil detection and coiled-coil oligomeric state prediction. We evaluated and compared these methods in terms of their input/output, algorithm, prediction performance, validation methods and software utility. All the independent testing data sets are available at http://lightning.med.monash.edu/coiledcoil/. In addition, we conducted a case study of nine human polyglutamine (PolyQ) disease-related proteins and predicted CCDs and oligomeric states using various predictors. Prediction results for CCDs were highly variable among different predictors. Only two peptides from two proteins were confirmed to be CCDs by majority voting. Both domains were predicted to form dimeric coiled-coils using oligomeric state prediction. We anticipate that this comprehensive analysis will be an insightful resource for structural biologists with limited prior experience in bioinformatics tools, and for bioinformaticians who are interested in designing novel approaches for coiled-coil and its oligomeric state prediction.

Nuclear Speckle-related Protein 70 Binds to Serine/Arginine-rich Splicing Factors 1 and 2 via an Arginine/Serine-like Region and Counteracts Their Alternative Splicing Activity

Nuclear speckles are subnuclear storage sites containing pre-mRNA splicing machinery. Proteins assembled in nuclear speckles are known to modulate transcription and pre-mRNA processing. We have previously identified nuclear speckle-related protein 70 (NSrp70) as a novel serine/arginine (SR)-related protein that co-localizes with classical SR proteins such as serine/arginine-rich splicing factor 1 (SRSF1 or ASF/SF2) and SRSF2 (SC35). NSrp70 mediates alternative splice site selection, targeting several pre-mRNAs, including CD44 exon v5. Here we demonstrated that NSrp70 interacts physically with two SR proteins, SRSF1 and SRSF2, and reverses their splicing activity in terms of CD44 exon v5 as exon exclusion. The NSrp70 RS-like region was subdivided into three areas. Deletion of the first arginine/serine-rich-like region (RS1) completely abrogated binding to the SR proteins and to target mRNA and also failed to induce splicing of CD44 exon v5, suggesting that RS1 is critical for NSrp70 functioning. Interestingly, RS1 deletion also resulted in the loss of NSrp70 and SR protein speckle positioning, implying a potential scaffolding role for NSrp70 in nuclear speckles. NSrp70 contains an N-terminal coiled-coil domain that is critical not only for self-oligomerization but also for splicing activity. Consistently, deletion of the coiled-coil domain resulted in indefinite formation of nuclear speckles. Collectively, these results demonstrate that NSrp70 acts as a new molecular counterpart for alternative splicing of target RNA, counteracting SRSF1 and SRSF2 splicing activity.

Self-sorting heterodimeric coiled coil peptides with defined and tuneable self-assembly properties

Coiled coils with defined assembly properties and dissociation constants are highly attractive components in synthetic biology and for fabrication of peptide-based hybrid nanomaterials and nanostructures. Complex assemblies based on multiple different peptides typically require orthogonal peptides obtained by negative design. Negative design does not necessarily exclude formation of undesired species and may eventually compromise the stability of the desired coiled coils. This work describe a set of four promiscuous 28-residue de novo designed peptides that heterodimerize and fold into parallel coiled coils. The peptides are non-orthogonal and can form four different heterodimers albeit with large differences in affinities. The peptides display dissociation constants for dimerization spanning from the micromolar to the picomolar range. The significant differences in affinities for dimerization make the peptides prone to thermodynamic social self-sorting as shown by thermal unfolding and fluorescence experiments, and confirmed by simulations. The peptides self-sort with high fidelity to form the two coiled coils with the highest and lowest affinities for heterodimerization. The possibility to exploit self-sorting of mutually complementary peptides could hence be a viable approach to guide the assembly of higher order architectures and a powerful strategy for fabrication of dynamic and tuneable nanostructured materials.

Computational characterization of parallel dimeric and trimeric coiled-coils using effective amino acid indices

RFCoil is a novel predictor for parallel coiled-coil dimer and trimer.

AAFreqCoil: a new classifier to distinguish parallel dimeric and trimeric coiled coils

Coiled coils are characteristic rope-like protein structures, constituted by one or more heptad repeats.

A set of computationally designed orthogonal antiparallel homodimers that expands the synthetic coiled-coil toolkit

Molecular engineering of protein assemblies, including the fabrication of nanostructures and synthetic signaling pathways, relies on the availability of modular parts that can be combined to give different structures and functions. Currently, a limited number of well-characterized protein interaction components are available. Coiled-coil interaction modules have been demonstrated to be useful for biomolecular design, and many parallel homodimers and heterodimers are available in the coiled-coil toolkit. In this work, we sought to design a set of orthogonal antiparallel homodimeric coiled coils using a computational approach. There are very few antiparallel homodimers described in the literature, and none have been measured for cross-reactivity. We tested the ability of the distance-dependent statistical potential DFIRE to predict orientation preferences for coiled-coil dimers of known structure. The DFIRE model was then combined with the CLASSY multistate protein design framework to engineer sets of three orthogonal antiparallel homodimeric coiled coils. Experimental measurements confirmed the successful design of three peptides that preferentially formed antiparallel homodimers that, furthermore, did not interact with one additional previously reported antiparallel homodimer. Two designed peptides that formed higher-order structures suggest how future design protocols could be improved. The successful designs represent a significant expansion of the existing protein-interaction toolbox for molecular engineers.

STRIPAK complexes: structure, biological function, and involvement in human diseases

The mammalian striatin family consists of three proteins, striatin, S/G2 nuclear autoantigen, and zinedin. Striatin family members have no intrinsic catalytic activity, but rather function as scaffolding proteins. Remarkably, they organize multiple diverse, large signaling complexes that participate in a variety of cellular processes. Moreover, they appear to be regulatory/targeting subunits for the major eukaryotic serine/threonine protein phosphatase 2A. In addition, striatin family members associate with germinal center kinase III kinases as well as other novel components, earning these assemblies the name striatin-interacting phosphatase and kinase (STRIPAK) complexes. Recently, there has been a great increase in functional and mechanistic studies aimed at identifying and understanding the roles of STRIPAK and STRIPAK-like complexes in cellular processes of multiple organisms. These studies have identified novel STRIPAK and STRIPAK-like complexes and have explored their roles in specific signaling pathways. Together, the results of these studies have sparked increased interest in striatin family complexes because they have revealed roles in signaling, cell cycle control, apoptosis, vesicular trafficking, Golgi assembly, cell polarity, cell migration, neural and vascular development, and cardiac function. Moreover, STRIPAK complexes have been connected to clinical conditions, including cardiac disease, diabetes, autism, and cerebral cavernous malformation. In this review, we discuss the expression, localization, and protein domain structure of striatin family members. Then we consider the diverse complexes these proteins and their homologs form in various organisms, emphasizing what is known regarding function and regulation. Finally, we explore possible roles of striatin family complexes in disease, especially cerebral cavernous malformation.

Prediction and analysis of higher-order coiled-coils: insights from proteins of the extracellular matrix, tenascins and thrombospondins

α-Helical coiled-coil domains (CCDs) direct protein oligomerisation in many biological processes and are of great interest as tools in protein engineering. Although CCDs are recognizable from protein sequences, prediction of oligomer state remains challenging especially for trimeric states and above. Here we evaluate LOGICOIL, a new multi-state predictor for CCDs, with regard to families of extracellular matrix proteins. Tenascins, which are known to assemble as trimers, were the first test case. LOGICOIL out-performed other algorithms in predicting trimerisation of these proteins and sequence analyses identified features associated with many other trimerising CCDs. The thrombospondins are a larger and more ancient family that includes sub-groups that assemble as trimers or pentamers. LOGICOIL predicted the pentamerising CCDs accurately. However, prediction of TSP trimerisation was relatively poor, although accuracy was improved by analyzing only the central regions of the CCDs. Sequence clustering and phylogenetic analyses grouped the TSP CCDs into three clades comprising trimers and pentamers from vertebrates, and TSPs from invertebrates. Sequence analyses revealed distinctive, conserved features that distinguish trimerising and pentamerising CCDs. Together, these analyses provide insight into the specification of higher-order CCDs that should direct improved CCD predictions and future experimental investigations of sequence-to-structure functional relationships.

Mutations in CERS3 cause autosomal recessive congenital ichthyosis in humans

Autosomal recessive congenital ichthyosis (ARCI) is a rare genetic disorder of the skin characterized by abnormal desquamation over the whole body. In this study we report four patients from three consanguineous Tunisian families with skin, eye, heart, and skeletal anomalies, who harbor a homozygous contiguous gene deletion syndrome on chromosome 15q26.3. Genome-wide SNP-genotyping revealed a homozygous region in all affected individuals, including the same microdeletion that partially affects two coding genes (ADAMTS17, CERS3) and abolishes a sequence for a long non-coding RNA (FLJ42289). Whereas mutations in ADAMTS17 have recently been identified in autosomal recessive Weill-Marchesani-like syndrome in humans and dogs presenting with ophthalmologic, cardiac, and skeletal abnormalities, no disease associations have been described for CERS3 (ceramide synthase 3) and FLJ42289 so far. However, analysis of additional patients with non-syndromic ARCI revealed a splice site mutation in CERS3 indicating that a defect in ceramide synthesis is causative for the present skin phenotype of our patients. Functional analysis of patient skin and in vitro differentiated keratinocytes demonstrated that mutations in CERS3 lead to a disturbed sphingolipid profile with reduced levels of epidermis-specific very long-chain ceramides that interferes with epidermal differentiation. Taken together, these data present a novel pathway involved in ARCI development and, moreover, provide the first evidence that CERS3 plays an essential role in human sphingolipid metabolism for the maintenance of epidermal lipid homeostasis.

Autosomal recessive congenital ichthyosis (ARCI) is a heterogeneous group of human keratinization disorders mainly characterized by generalized abnormal scaling of the skin. To date, positional cloning and homozygosity mapping of families with ARCI have identified disease-associated mutations in seven genes: ABCA12, ALOX12B, ALOXE3, CYP4F22, ICHTHYIN, PNPLA1, and TGM1. The reported molecular mechanisms underlying disease development are related to defects in epidermal lipid pathways that interfere with terminal keratinocyte differentiation and skin barrier function. In this study we used genome-wide SNP mapping, which identified homozygous mutations in the CERS3 (ceramide synthase 3) gene that cause a new type of ARCI. Functional analysis of a skin sample and in vitro differentiated keratinocytes from one patient demonstrated that mutated CERS3 impairs the synthesis of ceramides with very long-chain acyl moieties. The defect in sphingolipid metabolism disturbs the epidermal lipid profile, which leads to an abnormal terminal differentiation process. In summary, mutations in CERS3 are causative for ARCI and illustrate the important role of ceramide synthesis in human skin physiology.

The α-helical regions of KERP1 are important in Entamoeba histolytica adherence to human cells

The lysine and glutamic acid rich protein KERP1 is a unique surface adhesion factor associated with virulence in the human pathogen Entamoeba histolytica. Both the function and structure of this protein remain unknown to this date. Here, we used circular dichroism, analytical ultracentrifugation and bioinformatics modeling to characterize the structure of KERP1. Our findings revealed that it is an α-helical rich protein organized as a trimer, endowed with a very high thermal stability (Tm = 89.6°C). Bioinformatics sequence analyses and 3D-structural modeling indicates that KERP1 central segments could account for protein trimerization. Relevantly, expressing the central region of KERP1 in living parasites, impair their capacity to adhere to human cells. Our observations suggest a link between the inhibitory effect of the isolated central region and the structural features of KERP1.

Genome-wide chromatin remodeling identified at GC-rich long nucleosome-free regions

To gain deeper insights into principles of cell biology, it is essential to understand how cells reorganize their genomes by chromatin remodeling. We analyzed chromatin remodeling on next generation sequencing data from resting and activated T cells to determine a whole-genome chromatin remodeling landscape. We consider chromatin remodeling in terms of nucleosome repositioning which can be observed most robustly in long nucleosome-free regions (LNFRs) that are occupied by nucleosomes in another cell state. We found that LNFR sequences are either AT-rich or GC-rich, where nucleosome repositioning was observed much more prominently in GC-rich LNFRs - a considerable proportion of them outside promoter regions. Using support vector machines with string kernels, we identified a GC-rich DNA sequence pattern indicating loci of nucleosome repositioning in resting T cells. This pattern appears to be also typical for CpG islands. We found out that nucleosome repositioning in GC-rich LNFRs is indeed associated with CpG islands and with binding sites of the CpG-island-binding ZF-CXXC proteins KDM2A and CFP1. That this association occurs prominently inside and also prominently outside of promoter regions hints at a mechanism governing nucleosome repositioning that acts on a whole-genome scale.

LOGICOIL--multi-state prediction of coiled-coil oligomeric state

MOTIVATION

The coiled coil is a ubiquitous α-helical protein-structure domain that directs and facilitates protein-protein interactions in a wide variety of biological processes. At the protein-sequence level, the coiled coil is readily recognized via a conspicuous heptad repeat of hydrophobic and polar residues. However, structurally coiled coils are more complicated, existing in a wide range of oligomer states and topologies. As a consequence, predicting these various states from sequence remains an unmet challenge.

RESULTS

This work introduces LOGICOIL, the first algorithm to address the problem of predicting multiple coiled-coil oligomeric states from protein-sequence information alone. By covering >90% of the known coiled-coil structures, LOGICOIL is a net improvement compared with other existing methods, which achieve a predictive coverage of ∼31% of this population. This leap in predictive power offers better opportunities for genome-scale analysis, and analyses of coiled-coil containing protein assemblies.

AVAILABILITY

LOGICOIL is available via a web-interface at http://coiledcoils.chm.bris.ac.uk/LOGICOIL. Source code, training sets and supporting information can be downloaded from the same site.

Investigation of the network of preferred interactions in an artificial coiled-coil association using the peptide array technique

We screened a randomized library and identified natural peptides that bound selectively to a chimeric peptide containing α-, β- and γ-amino acids. The SPOT arrays provide a means for the systematic study of the possible interaction space accessible to the αβγ-chimera. The mutational analysis reveals the dependence of the binding affinities of α-peptides to the αβγ-chimera, on the hydrophobicity and bulkiness of the side chains at the corresponding hydrophobic interface. The stability of the resulting heteroassemblies was further confirmed in solution by CD and thermal denaturation.

Crystal structure and characterization of coiled-coil domain of the transient receptor potential channel PKD2L1

The cation-permeable channel PKD2L1 forms a homomeric assembly as well as heteromeric associations with both PKD1 and PKD1L3, with the cytoplasmic regulatory domain (CRD) of PKD2L1 often playing a role in assembly and/or function. Our previous work indicated that the isolated PKD2L1 CRD assembles as a trimer in a manner dependent on the presence of a proposed oligomerization domain. Herein we describe the 2.7Å crystal structure of a segment containing the PKD2L1 oligomerization domain which indicates that trimerization is driven by the β-branched residues at the first and fourth positions of a heptad repeat (commonly referred to as "a" and "d") and by a conserved R-h-x-x-h-E salt bridge motif that is largely unique to parallel trimeric coiled coils. Further analysis of the PKD2L1 CRD indicates that trimeric association is sufficiently strong that no other species are present in solution in an analytical ultracentrifugation experiment at the lowest measurable concentration of 750nM. Conversely, mutation of the "a" and "d" residues leads to formation of an exclusively monomeric species, independent of concentration. Although both monomeric and WT CRDs are stable in solution and bind calcium with 0.9μM affinity, circular dichroism studies reveal that the monomer loses 25% more α-helical content than WT when stripped of this ligand, suggesting that the CRD structure is stabilized by trimerization in the ligand-free state. This stability could play a role in the function of the full-length complex, indicating that trimerization may be important for both homo- and possibly heteromeric assemblies of PKD2L1.

APCluster: an R package for affinity propagation clustering

SUMMARY

Affinity propagation (AP) clustering has recently gained increasing popularity in bioinformatics. AP clustering has the advantage that it allows for determining typical cluster members, the so-called exemplars. We provide an R implementation of this promising new clustering technique to account for the ubiquity of R in bioinformatics. This article introduces the package and presents an application from structural biology.

AVAILABILITY

The R package apcluster is available via CRAN-The Comprehensive R Archive Network: http://cran.r-project.org/web/packages/apcluster

CONTACT

apcluster@bioinf.jku.at; bodenhofer@bioinf.jku.at.