DisProt: the Database of Disordered Proteins

Understanding the evolutionary trend of intrinsically structural disorders in cancer relevant proteins as probed by Shannon entropy scoring and structure network analysis

BACKGROUND

Malignant diseases have become a threat for health care system. A panoply of biological processes is involved as the cause of these diseases. In order to unveil the mechanistic details of these diseased states, we analyzed protein families relevant to these diseases.

RESULTS

Our present study pivots around four apparently unrelated cancer types among which two are commonly occurring viz. Prostate Cancer, Breast Cancer and two relatively less frequent viz. Acute Lymphoblastic Leukemia and Lymphoma. Eight protein families were found to have implications for these cancer types. Our results strikingly reveal that some of the proteins with implications in the cancerous cellular states were showing the structural organization disparate from the signature of the family it constitutes. The sequences were further mapped onto respective structures and compared with the entropic profile. The structures reveal that entropic scores were able to reveal the inherent structural bias of these proteins with quantitative precision, otherwise unseen from other analysis. Subsequently, the betweenness centrality scoring of each residue from the structure network models was resorted to explore the changes in dependencies on residue owing to structural disorder.

CONCLUSION

These observations help to obtain the mechanistic changes resulting from the structural orchestration of protein structures. Finally, the hydropathy indexes were obtained to validate the sequence space observations using Shannon entropy and in-turn establishing the compatibility.

Structural disorder in the proteome and interactome of Alkhurma virus (ALKV)

Infection by the Alkhurma virus (ALKV) leading to the Alkhurma hemorrhagic fever is a common thread in Saudi Arabia, with no efficient treatment or prevention available as of yet. Although the rational drug design traditionally uses information on known 3D structures of viral proteins, intrinsically disordered proteins (i.e., functional proteins that do not possess unique 3D structures), with their multitude of disorder-dependent functions, are crucial for the biology of viruses. Here, viruses utilize disordered regions in their invasion of the host organisms and in hijacking and repurposing of different host systems. Furthermore, the ability of viruses to efficiently adjust and accommodate to their hostile habitats is also intrinsic disorder-dependent. However, little is currently known on the level of penetrance and functional utilization of intrinsic disorder in the ALKV proteome. To fill this gap, we used here multiple computational tools to evaluate the abundance of intrinsic disorder in the ALKV genome polyprotein. We also analyzed the peculiarities of intrinsic disorder predisposition of the individual viral proteins, as well as human proteins known to be engaged in interaction with the ALKV proteins. Special attention was paid to finding a correlation between protein functionality and structural disorder. To the best of our knowledge, this work represents the first systematic study of the intrinsic disorder status of ALKV proteome and interactome.

Misprediction of Structural Disorder in Halophiles

Whereas the concept of intrinsic disorder derives from biophysical observations of the lack of structure of proteins or protein regions under native conditions, many of our respective concepts rest on proteome-scale bioinformatics predictions. It is established that most predictors work reliably on proteins commonly encountered, but it is often neglected that we know very little about their performance on proteins of microorganisms that thrive in environments of extreme temperature, pH, or salt concentration, which may cause adaptive sequence composition bias. To address this issue, we predicted structural disorder for the complete proteomes of different extremophile groups by popular prediction methods and compared them to those of the reference mesophilic group. While significant deviations from mesophiles could be explained by a lack or gain of disordered regions in hyperthermophiles and radiotolerants, respectively, we found systematic overprediction in the case of halophiles. Additionally, examples were collected from the Protein Data Bank (PDB) to demonstrate misprediction and to help understand the underlying biophysical principles, i.e., halophilic proteins maintain a highly acidic and hydrophilic surface to avoid aggregation in high salt conditions. Although sparseness of data on disordered proteins from extremophiles precludes the development of dedicated general predictors, we do formulate recommendations for how to address their disorder with current bioinformatics tools.

Troubleshooting Guide to Expressing Intrinsically Disordered Proteins for Use in NMR Experiments

Intrinsically disordered proteins (IDPs) represent a structural class of proteins that do not have a well-defined, 3D fold in solution, and often have little secondary structure. To characterize their function and molecular mechanism, it is helpful to examine their structure using nuclear magnetic resonance (NMR), which can report on properties, such as residual structure (at both the secondary and tertiary levels), ligand binding affinity, and the effect of ligand binding on IDP structure, all on a per residue basis. This brief review reports on the common problems and decisions that are involved when preparing a disordered protein for NMR studies. The paper covers gene design, expression host choice, protein purification, and the initial NMR experiments that are performed. While many of these steps are essentially identical to those for ordered proteins, a few key differences are highlighted, including the extreme sensitivity of IDPs to proteolytic cleavage, the ability to use denaturing conditions without having to refold the protein, the optimal chromatographic system choice, and the challenges of quantifying an IDP. After successful purification, characterization by NMR can be done using the standard ¹⁵N-heteronuclear single quantum coherence (¹⁵N-HSQC) experiment, or the newer CON series of experiments that are superior for disordered proteins.

In Silico and In Vitro Considerations of Keratinocyte Nuclear Receptor Protein Structural Order for Improving Experimental Analysis

Nuclear receptors (NR) regulate gene expression critical in keratinocyte replication and differentiation. In addition to a ligand-binding domain, NR like other transcription factor families have a DNA-binding domain that must attain a particular conformation for effective interaction with the three-dimensional structure in promoters of target genes for control of their expression. Such protein-DNA assemblies extend the classic "lock and key" idea typified by protein-protein interactions. However, it is becoming increasingly clear that multi-subdomain transcription factors like NR frequently range along the length of the protein from structured, ordered regions expected for interaction with a preset partner to more flexible, intrinsically disordered regions which are more available for diverse posttranslational modifications and/or interaction with differing partners. The extended amino terminus of NR (the A/B subdomain) is one such intrinsically disordered region. Here we provide a primer on in silico-based recognition of amino acid composition and order associated with such conformational flexibility along with adaptations of readily accessible laboratory techniques (e.g., considerations for recombinant expression, sensitivity to protease and proteasome digestion) to facilitate initial prediction and testing for intrinsic disorder in various proteins of interest to keratinocyte biologists, like NR and other transcription factors.

The C Terminus of the Ribosomal-Associated Protein LrtA Is an Intrinsically Disordered Oligomer

The 191-residue-long LrtA protein of Synechocystis sp. PCC 6803 is involved in post-stress survival and in stabilizing 70S ribosomal particles. It belongs to the hibernating promoting factor (HPF) family, intervening in protein synthesis. The protein consists of two domains: The N-terminal region (N-LrtA, residues 1–101), which is common to all the members of the HPF, and seems to be well-folded; and the C-terminal region (C-LrtA, residues 102–191), which is hypothesized to be disordered. In this work, we studied the conformational preferences of isolated C-LrtA in solution. The protein was disordered, as shown by computational modelling, 1D-¹H NMR, steady-state far-UV circular dichroism (CD) and chemical and thermal denaturations followed by fluorescence and far-UV CD. Moreover, at physiological conditions, as indicated by several biochemical and hydrodynamic techniques, isolated C-LrtA intervened in a self-association equilibrium, involving several oligomerization reactions. Thus, C-LrtA was an oligomeric disordered protein.

Folding of poly-amino acids and intrinsically disordered proteins in overcrowded milieu induced by pH change

pH-induced structural changes of the synthetic homopolypeptides poly-E, poly-K, poly-R, and intrinsically disordered proteins (IDPs) prothymosin α (ProTα) and linker histone H1, in concentrated PEG solutions simulating macromolecular crowding conditions within the membrane-less organelles, were characterized. The conformational transitions of the studied poly-amino acids in the concentrated PEG solutions depend on the polymerization degree of these homopolypeptides, the size of their side chains, the charge distribution of the side chains, and the crowding agent concentration. The results obtained for poly-amino acids are valid for IDPs having a significant total charge. The overcrowded conditions promote a significant increase in the cooperativity of the pH-induced coil-α-helix transition of ProTα and provoke histone H1 aggregation. The most favorable conditions for the pH-induced structural transitions in concentrated PEG solutions are realized when the charged residues are grouped in blocks, and when the distance between the end of the side group carrying charge and the backbone is small. Therefore, the block-wise distribution of charged residues within the IDPs not only plays an important role in the liquid-liquid phase transitions, but may also define the expressivity of structural transitions of these proteins in the overcrowded conditions of the membrane-less organelles.

Conservation of Potentially Druggable Cavities in Intrinsically Disordered Proteins

Intrinsically disordered proteins (IDPs) exist in highly dynamic conformational ensembles, which pose a major obstacle for drug development targeting IDPs because traditional rational drug design relies on unique three-dimensional structures. Here, we analyzed the conservation (especially structural conservation) of potentially druggable cavities in 22 ensembles of IDPs. It was found that there is considerable conservation for potentially druggable cavities within each ensemble. The average common atom percentage of potentially druggable cavities is as high as 54%. The average root-mean-squared deviation of common atoms ranges between 1 and 8 Å for multichain IDPs, and a common pocket is kept after direct alignment of cavities. In addition, the conservation of potentially druggable cavities varies among different proteins. In the comparison of multi- and single-chain IDPs, some multichain IDPs have an extremely high conservation, whereas another multichain IDPs' conservation appears worse, and the single-chain IDPs have relatively moderate conservations. This study is a new attempt to generally assess the potentially druggable cavities in IDPs for taking IDPs as druggable targets, and this work also lends support to the opinion of IDPs tending to bind to "multiconformational affinity" compounds.

Large-Scale Analyses of Site-Specific Evolutionary Rates across Eukaryote Proteomes Reveal Confounding Interactions between Intrinsic Disorder, Secondary Structure, and Functional Domains

Various structural and functional constraints govern the evolution of protein sequences. As a result, the relative rates of amino acid replacement among sites within a protein can vary significantly. Previous large-scale work on Metazoan (Animal) protein sequence alignments indicated that amino acid replacement rates are partially driven by a complex interaction among three factors: intrinsic disorder propensity; secondary structure; and functional domain involvement. Here, we use sequence-based predictors to evaluate the effects of these factors on site-specific sequence evolutionary rates within four eukaryotic lineages: Metazoans; Plants; Saccharomycete Fungi; and Alveolate Protists. Our results show broad, consistent trends across all four Eukaryote groups. In all four lineages, there is a significant increase in amino acid replacement rates when comparing: (i) disordered vs. ordered sites; (ii) random coil sites vs. sites in secondary structures; and (iii) inter-domain linker sites vs. sites in functional domains. Additionally, within Metazoans, Plants, and Saccharomycetes, there is a strong confounding interaction between intrinsic disorder and secondary structure-alignment sites exhibiting both high disorder propensity and involvement in secondary structures have very low average rates of sequence evolution. Analysis of gene ontology (GO) terms revealed that in all four lineages, a high fraction of sequences containing these conserved, disordered-structured sites are involved in nucleic acid binding. We also observe notable differences in the statistical trends of Alveolates, where intrinsically disordered sites are more variable than in other Eukaryotes and the statistical interactions between disorder and other factors are less pronounced.

In silico approach to identify non-synonymous SNPs with highest predicted deleterious effect on protein function in human obesity related gene, neuronal growth regulator 1 (NEGR1)

Neuronal growth regulator 1 (NEGR1) is a candidate gene for human obesity, which encodes the neural cell adhesion and growth molecule. The aim of the current study was to recognize the non-synonymous SNPs (nsSNPs) with the highest predicted deleterious effect on protein function of the NEGR1 gene. We have used five computational tools, namely, PolyPhen, SIFT, PROVEAN, MutPred and M-CAP, to predict the deleterious and pathogenic nsSNPs of the NEGR1 gene. Homology modeling approach was used to model the native and mutant NEGR1 protein models. Furthermore, structural validation was performed by the PROCHECK server to interpret the stability of the predicted models. We have predicted four potential deleterious nsSNPs, i.e., rs145524630 (Ala70Thr), rs267598710 (Pro168Leu), rs373419972 (Arg239Cys) and rs375352213 (Leu158Phe), which might be involved in causing obesity phenotypes. The predicted mutant models showed higher root mean square deviation and free energy values under the PyMoL and SWISS-PDB viewer, respectively. Additionally, the FTSite server predicted one nsSNP, i.e., rs145524630 (Ala70Thr) out of four identified nsSNPs found in the NEGR1 protein-binding site. There were four potential deleterious and pathogenic nsSNPs, i.e., rs145524630, rs267598710, rs373419972 and rs375352213, identified from the above-mentioned tools. In future, further functional in vitro and in vivo analysis could lead to better knowledge about these nsSNPs on the influence of the NEGR1 gene in causing human obesity. Hence, the present computational examination suggest that predicated nsSNPs may feasibly be a drug target and play an important role in contributing to human obesity.

Helical Polyampholyte Sequences Have Unique Thermodynamic Properties

Helices are the most common structural pattern observed in structured proteins. Polypeptide sequences that form helices in isolation have been identified and extensively studied. These are generally rich in alanine, the amino acid with strongest helical propensity. Insertion of charged or polar amino acids has been shown to be necessary to make alanine-rich peptides soluble and sometimes even increase the helicity of the peptides. More recently sequences that contain mostly charged residues (E-R/K rich) have been found in naturally occurring proteins that are highly helical, soluble, and extended regardless their length. Artificial sequences composed mostly or exclusively of charged amino acids have been designed that are also highly helical, depending on the specific pattern of oppositely charged residues. Here we explore the thermodynamic properties of a number of 16-residue long peptides with varying helical propensity by performing equilibrium simulations over a broad range of temperatures. We observe quantitative differences in the peptides' helical propensities that can be related to qualitative differences in the free energy landscape, depending on the ampholytic patterns in the sequence. The results provide hints on how the specific physical properties of naturally occurring long sequences with similar patterns of charged residues may relate to their biological function.

Virus discovery in all three major lineages of terrestrial arthropods highlights the diversity of single-stranded DNA viruses associated with invertebrates

Viruses encoding a replication-associated protein (Rep) within a covalently closed, single-stranded (ss)DNA genome are among the smallest viruses known to infect eukaryotic organisms, including economically valuable agricultural crops and livestock. Although circular Rep-encoding ssDNA (CRESS DNA) viruses are a widespread group for which our knowledge is rapidly expanding, biased sampling toward vertebrates and land plants has limited our understanding of their diversity and evolution. Here, we screened terrestrial arthropods for CRESS DNA viruses and report the identification of 44 viral genomes and replicons associated with specimens representing all three major terrestrial arthropod lineages, namely Euchelicerata (spiders), Hexapoda (insects), and Myriapoda (millipedes). We identified virus genomes belonging to three established CRESS DNA viral families (Circoviridae, Genomoviridae, and Smacoviridae); however, over half of the arthropod-associated viral genomes are only distantly related to currently classified CRESS DNA viral sequences. Although members of viral and satellite families known to infect plants (Geminiviridae, Nanoviridae, Alphasatellitidae) were not identified in this study, these plant-infecting CRESS DNA viruses and replicons are transmitted by hemipterans. Therefore, members from six out of the seven established CRESS DNA viral families circulate among arthropods. Furthermore, a phylogenetic analysis of Reps, including endogenous viral sequences, reported to date from a wide array of organisms revealed that most of the known CRESS DNA viral diversity circulates among invertebrates. Our results highlight the vast and unexplored diversity of CRESS DNA viruses among invertebrates and parallel findings from RNA viral discovery efforts in undersampled taxa.

Comprehensive analysis of damage associated SNPs of MMP9 gene: A computational approach

Extracellular matrix is a dynamic meshwork of macromolecules that plays an important role in biological processes such as tissue remodeling and various developmental processes. Collagen is the chief component of ECM. Upon hydrolysis, it forms an irreversible left-handed helical structure which is further hydrolyzed by a specialized group of MMP family i.e. Gelatinases (MMP2 and MMP9). Present study was carried to figure out deleterious SNPs associated with MMP9 gene. Our results showed that two nsSNP (rs8125581 and rs41529445) that are present in catalytic domain are highly conserved and affect the protein structure and function.7 SNPs located in UTRs were found to alter miRNA seed region 13 SNPs of splice site were predicted to affect splice signals thereby affecting the post translational expression of MMP9. Most of the SNPs are still uncharacterized thereby present study provides a direction that can help to validate the relation between the altered expressions and functions of MMP9 protein in terms of disease susceptibility.

Structural Capacitance in Protein Evolution and Human Diseases

Canonical mechanisms of protein evolution include the duplication and diversification of pre-existing folds through genetic alterations that include point mutations, insertions, deletions, and copy number amplifications, as well as post-translational modifications that modify processes such as folding efficiency and cellular localization. Following a survey of the human mutation database, we have identified an additional mechanism that we term "structural capacitance," which results in the de novo generation of microstructure in previously disordered regions. We suggest that the potential for structural capacitance confers select proteins with the capacity to evolve over rapid timescales, facilitating saltatory evolution as opposed to gradualistic canonical Darwinian mechanisms. Our results implicate the elements of protein microstructure generated by this distinct mechanism in the pathogenesis of a wide variety of human diseases. The benefits of rapidly furnishing the potential for evolutionary change conferred by structural capacitance are consequently counterbalanced by this accompanying risk. The phenomenon of structural capacitance has implications ranging from the ancestral diversification of protein folds to the engineering of synthetic proteins with enhanced evolvability.

The chromatin nuclear protein NUPR1L is intrinsically disordered and binds to the same proteins as its paralogue

NUPR1 is a protumoral multifunctional intrinsically disordered protein (IDP), which is activated during the acute phases of pancreatitis. It interacts with other IDPs such as prothymosin α, as well as with folded proteins such as the C-terminal region of RING1-B (C-RING1B) of the Polycomb complex; in all those interactions, residues around Ala33 and Thr68 (the ‘hot-spot’ region) of NUPR1 intervene. Its paralogue, NUPR1L, is also expressed in response to DNA damage, it is p53-regulated, and its expression down-regulates that of the NUPR1 gene. In this work, we characterized the conformational preferences of isolated NUPR1L and its possible interactions with the same molecular partners of NUPR1. Our results show that NUPR1L was an oligomeric IDP from pH 2.0 to 12.0, as judged by steady-state fluorescence, circular dichroism (CD), dynamic light scattering, 1D 1H-NMR (nuclear magnetic resonance), and as indicated by structural modelling. However, in contrast with NUPR1, there was evidence of local helical- or turn-like structures; these structures were not rigid, as judged by the lack of sigmoidal behaviour in the chemical and thermal denaturation curves obtained by CD and fluorescence. Interestingly enough, NUPR1L interacted with prothymosin α and C-RING1B, and with a similar affinity to that of NUPR1 (in the low micromolar range). Moreover, NUPR1L hetero-associated with NUPR1 with an affinity of 0.4 µM and interacted with the ‘hot-spot’ region of NUPR1. Thus, we suggest that the regulation of NUPR1 gene by NUPR1L does not only happen at the DNA level, but it could also involve direct interactions with NUPR1 natural partners.

EDEM1's mannosidase-like domain binds ERAD client proteins in a redox-sensitive manner and possesses catalytic activity

Endoplasmic reticulum (ER) degradation-enhancing α-mannosidase-like 1 protein (EDEM1) is a protein quality control factor that was initially proposed to recognize N-linked glycans on misfolded proteins through its mannosidase-like domain (MLD). However, recent studies have demonstrated that EDEM1 binds to some misfolded proteins in a glycan-independent manner, suggesting a more complex binding landscape for EDEM1. In this study, we have identified a thiol-dependent substrate interaction between EDEM1 and the α₁-antitrypsin ER-associated protein degradation (ERAD) clients Z and NHK, specifically through the single Cys residue on Z/NHK (Cys²⁵⁶), required for binding under stringent detergent conditions. In addition to the thiol-dependent interaction, the presence of weaker protein-protein interactions was confirmed, suggestive of bipartite client-binding properties. About four reactive thiols on EDEM1 were identified and were not directly responsible for the observed redox-sensitive binding by EDEM1. Moreover, a protein construct comprising the EDEM1 MLD had thiol-dependent binding properties along with its active glycan-trimming activities. Lastly, we identified an additional intrinsically disordered region (IDR) located at the C terminus of EDEM1 in addition to its previously identified N-terminal IDR. We also determined that both IDRs are required for binding to the ERAD component ERdj5 as an interaction with ERdj5 was not observed with the MLD alone. Together, our findings indicate that EDEM1 employs different binding modalities to interact with ERAD clients and ER quality control (ERQC) machinery partners and that some of these properties are shared with its homologues EDEM2 and EDEM3.

Comprehensive in-silico prediction of damage associated SNPs in Human Prolidase gene

Prolidase is cytosolic manganese dependent exopeptidase responsible for the catabolism of imido di and tripeptides. Prolidase levels have been associated with a number of diseases such as bipolar disorder, erectile dysfunction and varied cancers. Single nucleotide polymorphism present in coding region of proteins (nsSNPs) has the potential to alter the primary structure as well as function of the protein. Hence, it becomes necessary to differentiate the potential harmful nsSNPs from the neutral ones. 19 nsSNPs were predicted as damaging by in-silico analysis of 298 nsSNPs retrieved from dbSNP database. Consurf analysis showed 18 out of 19 substitutions were present in the conserved regions. 4 substitutions (D276N, D287N, E412K, and G448R) that observed to have damaging effect are present in catalytic pocket. Four SNPs listed in splice site region were found to affect splicing of mRNA by altering acceptor site. On 3′UTR scan of 77 SNPs listed in SNP database, 9 SNPs were lead to alter miRNA target sites. These results provide a filtered data to explore the effect of uncharacterized nsSNP and SNP related to UTRs and splice site of prolidase to find their association with the disease susceptibility and to design the target dependent drugs for therapeutics.

In Silico Prediction and Validation of Novel RNA Binding Proteins and Residues in the Human Proteome

Deciphering a complete landscape of protein-RNA interactions in the human proteome remains an elusive challenge. We computationally elucidate RNA binding proteins (RBPs) using an approach that complements previous efforts. We employ two modern complementary sequence-based methods that provide accurate predictions from the structured and the intrinsically disordered sequences, even in the absence of sequence similarity to the known RBPs. We generate and analyze putative RNA binding residues on the whole proteome scale. Using a conservative setting that ensures low, 5% false positive rate, we identify 1511 putative RBPs that include 281 known RBPs and 166 RBPs that were previously predicted. We empirically demonstrate that these overlaps are statistically significant. We also validate the putative RBPs based on two major hallmarks of their RNA binding residues: high levels of evolutionary conservation and enrichment in charged amino acids. Moreover, we show that the novel RBPs are significantly under-annotated functionally which coincides with the fact that they were not yet found to interact with RNAs. We provide two examples of our novel putative RBPs for which there is recent evidence of their interactions with RNAs. The dataset of novel putative RBPs and RNA binding residues for the future hypothesis generation is provided in the Supporting Information.

A novel role of C-terminus in introducing a functionally flexible structure critical for the biological activity of botulinum neurotoxin

Botulinum neurotoxin (BoNT) is responsible for botulism, a clinical condition resulting in flaccid muscle paralysis and potentially death. The light chain is responsible for its intracellular toxicity through its endopeptidase activity. Available crystal structures of BoNT/A light chains (LCA) are based on various truncated versions (tLCA) of the full-length LCA (fLCA) and do not necessarily reflect the true structure of LCA in solution. The understanding of the mechanism of action, longevity of intoxication, and an improved development of endopeptidase inhibitors are dependent on first having a better insight into the structure of LCA in solution. Using an array of biophysical techniques, we report that the fLCA structure is significantly more flexible than tLCA in solution, which may be responsible for its dramatically higher enzymatic activity. This seems to be achieved by a much stronger, more rapid binding to substrate (SNAP-25) of the fLCA compared to tLCA. These results suggest that the C-terminus of LCA plays a critical role in introducing a flexible structure, which is essential for its biological function. This is the first report of such a massive structural role of the C-terminus of a protein being critical for maintaining a functional state.

Exploring intrinsically disordered proteins in Chlamydomonas reinhardtii

The content of intrinsically disordered protein (IDP) is related to organism complexity, evolution, and regulation. In the Plantae, despite their high complexity, experimental investigation of IDP content is lacking. We identified by mass spectrometry 682 heat-resistant proteins from the green alga, Chlamydomonas reinhardtii. Using a phosphoproteome database, we found that 331 of these proteins are targets of phosphorylation. We analyzed the flexibility propensity of the heat-resistant proteins and their specific features as well as those of predicted IDPs from the same organism. Their mean percentage of disorder was about 20%. Most of the IDPs (~70%) were addressed to other compartments than mitochondrion and chloroplast. Their amino acid composition was biased compared to other classic IDPs. Their molecular functions were diverse; the predominant ones were nucleic acid binding and unfolded protein binding and the less abundant one was catalytic activity. The most represented proteins were ribosomal proteins, proteins associated to flagella, chaperones and histones. We also found CP12, the only experimental IDP from C. reinhardtii that is referenced in disordered protein database. This is the first experimental investigation of IDPs in C. reinhardtii that also combines in silico analysis.

Identification of two novel CRESS DNA viruses associated with an Avipoxvirus lesion of a blue-and-gray Tanager (Thraupis episcopus)

The discovery of circular rep-encoding single stranded (CRESS) DNA viruses has increased spectacularly over the past decade. They represent the smallest animal viruses known worldwide infecting a wide variety of invertebrates and vertebrates in different natural and human-made environments. The extremely low similarity of nucleotide and protein sequences among different CRESS DNA genomes has challenged their classification. Moreover, the existence of capsid proteins (Cp) remains difficult to demonstrate which is crucial to understand the structural properties of these viruses. Here we describe two unclassified CRESS DNA viruses isolated from a cutaneous lesion, caused by a strain of Avipoxvirus, from a blue-and-gray tanager (Thraupis episcopus) in Southern Ecuador. Both viruses present replication-associated proteins (Rep) and one to two open reading frames (ORF), one of which represents a putative Cp. The two new Rep are long proteins characterized by the existence of the several highly conserved amino acid residues characteristic of rolling circle replication. Within the putative Cp we detected intrinsically disordered regions (IDR), potential protein and DNA binding regions, and nuclear localization signals (NLS), providing further evidence of presumed Cp. Despite being found on the same host lesion, both viruses show low similarity between each other (<60%) and other known CRESS DNA viruses. Furthermore, we analyze the evolutionary relationships within the CRESS DNA diversity. Additional sampling is needed to explore the possible pathogenic effects, prevalence and diversity (both phylogenetical and structural) of these viruses in wild bird populations.

Grid-based prediction of torsion angle probabilities of protein backbone and its application to discrimination of protein intrinsic disorder regions and selection of model structures

BACKGROUND

Protein structure can be described by backbone torsion angles: rotational angles about the N-Cα bond (φ) and the Cα-C bond (ψ) or the angle between Cαi-1-Cαi-Cαi + 1 (θ) and the rotational angle about the Cαi-Cαi + 1 bond (τ). Thus, their accurate prediction is useful for structure prediction and model refinement. Early methods predicted torsion angles in a few discrete bins whereas most recent methods have focused on prediction of angles in real, continuous values. Real value prediction, however, is unable to provide the information on probabilities of predicted angles.

RESULTS

Here, we propose to predict angles in fine grids of 5° by using deep learning neural networks. We found that this grid-based technique can yield 2-6% higher accuracy in predicting angles in the same 5° bin than existing prediction techniques compared. We further demonstrate the usefulness of predicted probabilities at given angle bins in discrimination of intrinsically disorder regions and in selection of protein models.

CONCLUSIONS

The proposed method may be useful for characterizing protein structure and disorder. The method is available at http://sparks-lab.org/server/SPIDER2/ as a part of SPIDER2 package.

Sequence fingerprints distinguish erroneous from correct predictions of intrinsically disordered protein regions

More than 60 prediction methods for intrinsically disordered proteins (IDPs) have been developed over the years, many of which are accessible on the World Wide Web. Nearly, all of these predictors give balanced accuracies in the ~65%-~80% range. Since predictors are not perfect, further studies are required to uncover the role of amino acid residues in native IDP as compared to predicted IDP regions. In the present work, we make use of sequences of 100% predicted IDP regions, false positive disorder predictions, and experimentally determined IDP regions to distinguish the characteristics of native versus predicted IDP regions. A higher occurrence of asparagine is observed in sequences of native IDP regions but not in sequences of false positive predictions of IDP regions. The occurrences of certain combinations of amino acids at the pentapeptide level provide a distinguishing feature in the IDPs with respect to globular proteins. The distinguishing features presented in this paper provide insights into the sequence fingerprints of amino acid residues in experimentally determined as compared to predicted IDP regions. These observations and additional work along these lines should enable the development of improvements in the accuracy of disorder prediction algorithm.

Functional Analysis of Human Hub Proteins and Their Interactors Involved in the Intrinsic Disorder-Enriched Interactions

Some of the intrinsically disordered proteins and protein regions are promiscuous interactors that are involved in one-to-many and many-to-one binding. Several studies have analyzed enrichment of intrinsic disorder among the promiscuous hub proteins. We extended these works by providing a detailed functional characterization of the disorder-enriched hub protein-protein interactions (PPIs), including both hubs and their interactors, and by analyzing their enrichment among disease-associated proteins. We focused on the human interactome, given its high degree of completeness and relevance to the analysis of the disease-linked proteins. We quantified and investigated numerous functional and structural characteristics of the disorder-enriched hub PPIs, including protein binding, structural stability, evolutionary conservation, several categories of functional sites, and presence of over twenty types of posttranslational modifications (PTMs). We showed that the disorder-enriched hub PPIs have a significantly enlarged number of disordered protein binding regions and long intrinsically disordered regions. They also include high numbers of targeting, catalytic, and many types of PTM sites. We empirically demonstrated that these hub PPIs are significantly enriched among 11 out of 18 considered classes of human diseases that are associated with at least 100 human proteins. Finally, we also illustrated how over a dozen specific human hubs utilize intrinsic disorder for their promiscuous PPIs.

Improving protein disorder prediction by deep bidirectional long short-term memory recurrent neural networks

Motivation

Capturing long-range interactions between structural but not sequence neighbors of proteins is a long-standing challenging problem in bioinformatics. Recently, long short-term memory (LSTM) networks have significantly improved the accuracy of speech and image classification problems by remembering useful past information in long sequential events. Here, we have implemented deep bidirectional LSTM recurrent neural networks in the problem of protein intrinsic disorder prediction.

Results

The new method, named SPOT-Disorder, has steadily improved over a similar method using a traditional, window-based neural network (SPINE-D) in all datasets tested without separate training on short and long disordered regions. Independent tests on four other datasets including the datasets from critical assessment of structure prediction (CASP) techniques and >10 000 annotated proteins from MobiDB, confirmed SPOT-Disorder as one of the best methods in disorder prediction. Moreover, initial studies indicate that the method is more accurate in predicting functional sites in disordered regions. These results highlight the usefulness combining LSTM with deep bidirectional recurrent neural networks in capturing non-local, long-range interactions for bioinformatics applications.

Availability and Implementation

SPOT-disorder is available as a web server and as a standalone program at: http://sparks-lab.org/server/SPOT-disorder/index.php .

Contact

j.hanson@griffith.edu.au or yuedong.yang@griffith.edu.au or yaoqi.zhou@griffith.edu.au.

Supplementary information

Supplementary data is available at Bioinformatics online.

Intrinsic Disorder in Proteins with Pathogenic Repeat Expansions

Intrinsically disordered proteins and proteins with intrinsically disordered regions have been shown to be highly prevalent in disease. Furthermore, disease-causing expansions of the regions containing tandem amino acid repeats often push repetitive proteins towards formation of irreversible aggregates. In fact, in disease-relevant proteins, the increased repeat length often positively correlates with the increased aggregation efficiency and the increased disease severity and penetrance, being negatively correlated with the age of disease onset. The major categories of repeat extensions involved in disease include poly-glutamine and poly-alanine homorepeats, which are often times located in the intrinsically disordered regions, as well as repeats in non-coding regions of genes typically encoding proteins with ordered structures. Repeats in such non-coding regions of genes can be expressed at the mRNA level. Although they can affect the expression levels of encoded proteins, they are not translated as parts of an affected protein and have no effect on its structure. However, in some cases, the repetitive mRNAs can be translated in a non-canonical manner, generating highly repetitive peptides of different length and amino acid composition. The repeat extension-caused aggregation of a repetitive protein may represent a pivotal step for its transformation into a proteotoxic entity that can lead to pathology. The goals of this article are to systematically analyze molecular mechanisms of the proteinopathies caused by the poly-glutamine and poly-alanine homorepeat expansion, as well as by the polypeptides generated as a result of the microsatellite expansions in non-coding gene regions and to examine the related proteins. We also present results of the analysis of the prevalence and functional roles of intrinsic disorder in proteins associated with pathological repeat expansions.

Analysis of the interactome of Schistosoma mansoni histone deacetylase 8

BACKGROUND

Histone deacetylase 8 from Schistosoma mansoni (SmHDAC8) is essential to parasite growth and development within the mammalian host and is under investigation as a target for the development of selective inhibitors as novel schistosomicidal drugs. Although some protein substrates and protein partners of human HDAC8 have been characterized, notably indicating a role in the function of the cohesin complex, nothing is known of the partners and biological function of SmHDAC8.

METHODOLOGY/PRINCIPAL FINDINGS

We therefore employed two strategies to characterize the SmHDAC8 interactome. We first used SmHDAC8 as a bait protein in yeast two-hybrid (Y2H) screening of an S. mansoni cDNA library. This allowed the identification of 49 different sequences encoding proteins. We next performed co-immunoprecipitation (Co-IP) experiments on parasite extracts with an anti-SmHDAC8 antibody. Mass spectrometry (MS) analysis allowed the identification of 160 different proteins.

CONCLUSIONS/SIGNIFICANCE

SmHDAC8 partners are involved in about 40 different processes, included expected functions such as the cohesin complex, cytoskeleton organization, transcriptional and translational regulation, metabolism, DNA repair, the cell cycle, protein dephosphorylation, proteolysis, protein transport, but also some proteasome and ribosome components were detected. Our results show that SmHDAC8 is a versatile deacetylase, potentially involved in both cytosolic and nuclear processes.

Structure and function of yeast Atg20, a sorting nexin that facilitates autophagy induction

The Atg20 and Snx4/Atg24 proteins have been identified in a screen for mutants defective in a type of selective macroautophagy/autophagy. Both proteins are connected to the Atg1 kinase complex, which is involved in autophagy initiation, and bind phosphatidylinositol-3-phosphate. Atg20 and Snx4 contain putative BAR domains, suggesting a possible role in membrane deformation, but they have been relatively uncharacterized. Here we demonstrate that, in addition to its function in selective autophagy, Atg20 plays a critical role in the efficient induction of nonselective autophagy. Atg20 is a dynamic posttranslationally modified protein that engages both structurally stable (PX and BAR) and intrinsically disordered domains for its function. In addition to its PX and BAR domains, Atg20 uses a third membrane-binding module, a membrane-inducible amphipathic helix present in a previously undescribed location in Atg20 within the putative BAR domain. Taken together, these findings yield insights into the molecular mechanism of the autophagy machinery.

The effect of phosphorylation on the salt-tolerance-related functions of the soybean protein PM18, a member of the group-3 LEA protein family

Enzymatically driven post-translated modifications (PTMs) usually happen within the intrinsically disordered regions of a target protein and can modulate variety of protein functions. Late embryogenesis abundant (LEA) proteins are a family of the plant intrinsically disordered proteins (IDPs). Despite their important roles in plant stress response, there is currently limited knowledge on the presence and functional and structural effects of phosphorylation on LEA proteins. In this study, we identified three phosphorylation sites (Ser90, Tyr136, and Thr266) in the soybean PM18 protein that belongs to the group-3 LEA proteins. In yeast expression system, PM18 protein increased the salt tolerance of yeast, and the phosphorylation of this protein further enhanced its protective function. Further analysis revealed that Ser90 and Tyr136 are more important than Thr266, and these two sites might work cooperatively in regulating the salt resistance function of PM18. The circular dichroism analysis showed that PM18 protein was disordered in aqueous media, and phosphorylation did not affect the disordered status of this protein. However, phosphorylation promoted formation of more helical structure in the presence of sodium dodecyl sulfate (SDS) or trifluoroethanol (TFE). Furthermore, in dedicated in vitro experiments, phosphorylated PM18 protein was able to better protect lactate dehydrogenase (LDH) from the inactivation induced by the freeze-thaw cycles than its un- or dephosphorylated forms. All these data indicate that phosphorylation may have regulatory effects on the stress-tolerance-related function of LEA proteins. Therefore, further studies are needed to shed more light on functional and structural roles of phosphorylation in LEA proteins.

The amino-terminal domain of ELL transcription elongation factor is essential for ELL function in Schizosaccharomyces pombe

Transcriptional elongation is a critical step for regulating expression of protein-coding genes. Multiple transcription elongation factors have been identified in vitro, but the physiological roles of many of them are still not clearly understood. The ELL (Eleven nineteen Lysine rich Leukemia) family of transcription elongation factors are conserved from fission yeast to humans. Schizosaccharomyces pombe contains a single ELL homolog (SpELL) that is not essential for its survival. Therefore to gain insights into the in vivo cellular functions of SpELL, we identified phenotypes associated with deletion of ell1 in S. pombe. Our results demonstrate that SpELL is required for normal growth of S. pombe cells. Furthermore, cells lacking ell1⁺ exhibit a decrease in survival when exposed to DNA-damaging conditions, but their growth is not affected under environmental stress conditions. ELL orthologs in different organisms contain three conserved domains, an amino-terminal domain, a middle domain and a carboxyl-terminal domain. We also carried out an in vivo functional mapping of these conserved domains within S. pombe ELL and uncovered a critical role for its amino-terminus in regulating all its cellular functions, including growth under different conditions, transcriptional elongation potential and interaction with S. pombe EAF. Taken together our results suggest that the domain organization of ELL proteins is conserved across species, but the in vivo functions as well as the relationship between the various domains and roles of ELL show species-specific differences.

Comparative Analysis of Sequence Clustering Methods for Deduplication of Biological Databases

The massive volumes of data in biological sequence databases provide a remarkable resource for large-scale biological studies. However, the underlying data quality of these resources is a critical concern. A particular challenge is duplication, in which multiple records have similar sequences, creating a high level of redundancy that impacts database storage, curation, and search. Biological database deduplication has two direct applications: for database curation, where detected duplicates are removed to improve curation efficiency, and for database search, where detected duplicate sequences may be flagged but remain available to support analysis.

Clustering methods have been widely applied to biological sequences for database deduplication. Since an exhaustive all-by-all pairwise comparison of sequences cannot scale for a high volume of data, heuristic approaches have been recruited, such as the use of simple similarity thresholds. In this article, we present a comparison between CD-HIT and UCLUST, the two best-known clustering tools for sequence database deduplication. Our contributions include a detailed assessment of the redundancy remaining after deduplication, application of standard clustering evaluation metrics to quantify the cohesion and separation of the clusters generated by each method, and a biological case study that assesses intracluster function annotation consistency to demonstrate the impact of these factors on a practical application of the sequence clustering methods. Our results show that the trade-off between efficiency and accuracy becomes acute when low threshold values are used and when cluster sizes are large. This evaluation leads to practical recommendations for users for more effective uses of the sequence clustering tools for deduplication.

Comprehensive review of methods for prediction of intrinsic disorder and its molecular functions

Computational prediction of intrinsic disorder in protein sequences dates back to late 1970 and has flourished in the last two decades. We provide a brief historical overview, and we review over 30 recent predictors of disorder. We are the first to also cover predictors of molecular functions of disorder, including 13 methods that focus on disordered linkers and disordered protein-protein, protein-RNA, and protein-DNA binding regions. We overview their predictive models, usability, and predictive performance. We highlight newest methods and predictors that offer strong predictive performance measured based on recent comparative assessments. We conclude that the modern predictors are relatively accurate, enjoy widespread use, and many of them are fast. Their predictions are conveniently accessible to the end users, via web servers and databases that store pre-computed predictions for millions of proteins. However, research into methods that predict many not yet addressed functions of intrinsic disorder remains an outstanding challenge.

An Efficient Method for Estimating the Hydrodynamic Radius of Disordered Protein Conformations

Intrinsically disordered proteins play important roles throughout biology, yet our understanding of the relationship between their sequences, structural properties, and functions remains incomplete. The dynamic nature of these proteins, however, makes them difficult to characterize structurally. Many disordered proteins can attain both compact and expanded conformations, and the level of expansion may be regulated and important for function. Experimentally, the level of compaction and shape is often determined either by small-angle x-ray scattering experiments or pulsed-field-gradient NMR diffusion measurements, which provide ensemble-averaged estimates of the radius of gyration and hydrodynamic radius, respectively. Often, these experiments are interpreted using molecular simulations or are used to validate them. We here provide, to our knowledge, a new and efficient method to calculate the hydrodynamic radius of a disordered protein chain from a model of its structural ensemble. In particular, starting from basic concepts in polymer physics, we derive a relationship between the radius of gyration of a structure and its hydrodynamic ratio, which in turn can be used, for example, to compare a simulated ensemble of conformations to NMR diffusion measurements. The relationship may also be valuable when using NMR diffusion measurements to restrain molecular simulations.

Effects of short indels on protein structure and function in human genomes

Insertions and deletions (indels) represent the second most common type of genetic variations in human genomes. Indels can be deleterious and contribute to disease susceptibility as recent genome sequencing projects revealed a large number of indels in various cancer types. In this study, we investigated the possible effects of small coding indels on protein structure and function, and the baseline characteristics of indels in 2504 individuals of 26 populations from the 1000 Genomes Project. We found that each population has a distinct pattern in genes with small indels. Frameshift (FS) indels are enriched in olfactory receptor activity while non-frameshift (NFS) indels are enriched in transcription-related proteins. Structural analysis of NFS indels revealed that they predominantly adopt coil or disordered conformations, especially in proteins with transcription-related NFS indels. These results suggest that the annotated coding indels from the 1000 Genomes Project, while contributing to genetic variations and phenotypic diversity, generally do not affect the core protein structures and have no deleterious effect on essential biological processes. In addition, we found that a number of reference genome annotations might need to be updated due to the high prevalence of annotated homozygous indels in the general population.

Polymorphism and structure of style-specific arabinogalactan proteins as determinants of pollen tube growth in Nicotiana

BACKGROUND

Pollen tube growth and fertilization are key processes in angiosperm sexual reproduction. The transmitting tract (TT) of Nicotiana tabacum controls pollen tube growth in part by secreting pistil extensin-like protein III (PELPIII), transmitting-tract-specific (TTS) protein and 120 kDa glycoprotein (120 K) into the stylar extracellular matrix. The three arabinogalactan proteins (AGP) are referred to as stylar AGPs and are the focus of this research. The transmitting tract regulates pollen tube growth, promoting fertilization or rejecting pollen tubes.

RESULTS

The N-terminal domain (NTD) of the stylar AGPs is proline rich and polymorphic among Nicotiana spp. The NTD was predicted to be mainly an intrinsically disordered region (IDR), making it a candidate for protein-protein interactions. The NTD is also the location for the majority of the predicted O-glycosylation sites that were variable among Nicotiana spp. The C-terminal domain (CTD) contains an Ole e 1-like domain, that was predicted to form beta-sheets that are similar in position and length among Nicotiana spp. and among stylar AGPs. The TTS protein had the greatest amino acid and predicted O-glycosylation conservation among Nicotiana spp. relative to the PELPIII and 120 K. The PELPIII, TTS and 120 K genes undergo negative selection, with dn/ds ratios of 0.59, 0.29 and 0.38 respectively. The dn/ds ratio for individual species ranged from 0.4 to 0.9 and from 0.1 to 0.8, for PELPIII and TTS genes, respectively. These data indicate that PELPIII and TTS genes are under different selective pressures. A newly discovered AGP gene, Nicotiana tabacum Proline Rich Protein (NtPRP), was found with a similar intron-exon configuration and protein structure resembling other stylar AGPs, particularly TTS.

CONCLUSIONS

Further studies of the NtPRP gene are necessary to elucidate its biological role. Due to its high similarity to the TTS gene, NtPRP may be involved in pollen tube guidance and growth. In contrast to TTS, both PELPIII and 120 K genes are more diverse indicating a possible role in speciation or mating preference of Nicotiana spp. We hypothesize that the stylar AGPs and NtPRP share a common origin from a single gene that duplicated and diversified into four distinct genes involved in pollen-style interactions.

Predictions of Backbone Dynamics in Intrinsically Disordered Proteins Using De Novo Fragment-Based Protein Structure Predictions

Intrinsically disordaered proteins (IDPs) are a prevalent phenomenon with over 30% of human proteins estimated to have long disordered regions. Computational methods are widely used to study IDPs, however, nearly all treat disorder in a binary fashion, not accounting for the structural heterogeneity present in disordered regions. Here, we present a new de novo method, FRAGFOLD-IDP, which addresses this problem. Using 200 protein structural ensembles derived from NMR, we show that FRAGFOLD-IDP achieves superior results compared to methods which can predict related data (NMR order parameter, or crystallographic B-factor). FRAGFOLD-IDP produces very good predictions for 33.5% of cases and helps to get a better insight into the dynamics of the disordered ensembles. The results also show it is not necessary to predict the correct fold of the protein to reliably predict per-residue fluctuations. It implies that disorder is a local property and it does not depend on the fold. Our results are orthogonal to DynaMine, the only other method significantly better than the naïve prediction. We therefore combine these two using a neural network. FRAGFOLD-IDP enables better insight into backbone dynamics in IDPs and opens exciting possibilities for the design of disordered ensembles, disorder-to-order transitions, or design for protein dynamics.

AUCpreD: proteome-level protein disorder prediction by AUC-maximized deep convolutional neural fields

MOTIVATION

Protein intrinsically disordered regions (IDRs) play an important role in many biological processes. Two key properties of IDRs are (i) the occurrence is proteome-wide and (ii) the ratio of disordered residues is about 6%, which makes it challenging to accurately predict IDRs. Most IDR prediction methods use sequence profile to improve accuracy, which prevents its application to proteome-wide prediction since it is time-consuming to generate sequence profiles. On the other hand, the methods without using sequence profile fare much worse than using sequence profile.

METHOD

This article formulates IDR prediction as a sequence labeling problem and employs a new machine learning method called Deep Convolutional Neural Fields (DeepCNF) to solve it. DeepCNF is an integration of deep convolutional neural networks (DCNN) and conditional random fields (CRF); it can model not only complex sequence-structure relationship in a hierarchical manner, but also correlation among adjacent residues. To deal with highly imbalanced order/disorder ratio, instead of training DeepCNF by widely used maximum-likelihood, we develop a novel approach to train it by maximizing area under the ROC curve (AUC), which is an unbiased measure for class-imbalanced data.

RESULTS

Our experimental results show that our IDR prediction method AUCpreD outperforms existing popular disorder predictors. More importantly, AUCpreD works very well even without sequence profile, comparing favorably to or even outperforming many methods using sequence profile. Therefore, our method works for proteome-wide disorder prediction while yielding similar or better accuracy than the others.

AVAILABILITY AND IMPLEMENTATION

http://raptorx2.uchicago.edu/StructurePropertyPred/predict/

CONTACT

wangsheng@uchicago.edu, jinboxu@gmail.com

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

DFLpred: High-throughput prediction of disordered flexible linker regions in protein sequences

Motivation: Disordered flexible linkers (DFLs) are disordered regions that serve as flexible linkers/spacers in multi-domain proteins or between structured constituents in domains. They are different from flexible linkers/residues because they are disordered and longer. Availability of experimentally annotated DFLs provides an opportunity to build high-throughput computational predictors of these regions from protein sequences. To date, there are no computational methods that directly predict DFLs and they can be found only indirectly by filtering predicted flexible residues with predictions of disorder.

Results: We conceptualized, developed and empirically assessed a first-of-its-kind sequence-based predictor of DFLs, DFLpred. This method outputs propensity to form DFLs for each residue in the input sequence. DFLpred uses a small set of empirically selected features that quantify propensities to form certain secondary structures, disordered regions and structured regions, which are processed by a fast linear model. Our high-throughput predictor can be used on the whole-proteome scale; it needs <1 h to predict entire proteome on a single CPU. When assessed on an independent test dataset with low sequence-identity proteins, it secures area under the receiver operating characteristic curve equal 0.715 and outperforms existing alternatives that include methods for the prediction of flexible linkers, flexible residues, intrinsically disordered residues and various combinations of these methods. Prediction on the complete human proteome reveals that about 10% of proteins have a large content of over 30% DFL residues. We also estimate that about 6000 DFL regions are long with ≥30 consecutive residues.

Availability and implementation:http://biomine.ece.ualberta.ca/DFLpred/.

Contact:lkurgan@vcu.edu

Supplementary information:Supplementary data are available at Bioinformatics online.

Mutations in ERGIC1 cause Arthrogryposis multiplex congenita, neuropathic type

Arthrogryposis multiplex congenita (AMC) is heterogeneous group of disorders characterized by non-progressive joint contractures from birth that involve more than 1 part of the body. There are various etiologies for AMC including genetic and environmental depends on the specific type, however, for most types, the cause is not fully understood. We previously reported large Israeli Arab kindred consisting of 16 patients affected with AMC neuropathic type, and mapped the locus to a 5.5 cM interval on chromosome 5qter. Using whole exome sequencing, we have now identified homozygous pathogenic variant in the ERGIC1 gene within the previously defined linked region. ERGIC1 encodes a cycling membrane protein which has a possible role in transport between endoplasmic reticulum and Golgi. We further show that this mutation was absent in more than 200 samples of healthy unrelated individuals of the Israeli Arab population. Thus, our findings expand the spectrum of hereditary AMC and suggest that abnormalities in protein trafficking may underlie AMC-related disorders.

Predicting the functional consequences of non-synonymous single nucleotide polymorphisms in IL8 gene

Here we report an in-silico approach for identification, characterization and validation of deleterious non-synonymous SNPs (nsSNPs) in the interleukin-8 gene using three steps. In first step, sequence homology-based genetic analysis of a set of 50 coding SNPs associated with 41 rsIDs using SIFT (Sorting Intolerant from Tolerant) and PROVEAN (Protein Variation Effect Analyzer) identified 23 nsSNPs to be putatively damaging/deleterious in at least one of the two tools used. Subsequently, structure-homology based PolyPhen-2 (Polymorphism Phenotyping) analysis predicted 9 of 23 nsSNPs (K4T, E31A, E31K, S41Y, I55N, P59L, P59S, L70P and V88D) to be damaging. According to the conditional hypothesis for the study, only nsSNPs that score damaging/deleterious prediction in both sequence and structural homology-based approach will be considered as 'high-confidence' nsSNPs. In step 2, based on conservation of amino acid residues, stability analysis, structural superimposition, RSMD and docking analysis, the possible structural-functional relationship was ascertained for high-confidence nsSNPs. Finally, in a separate analysis (step 3), the IL-8 deregulation has also appeared to be an important prognostic marker for detection of patients with gastric and lung cancer. This study, for the first time, provided in-depth insights on the effects of amino acid substitutions on IL-8 protein structure, function and disease association.

Autophagy-related intrinsically disordered proteins in intra-nuclear compartments

Recent analyses indicated that autophagy can be regulated via some nuclear transcriptional networks and many important players in the autophagy and other forms of programmed cell death are known to be intrinsically disordered. To this end, we analyzed similarities and differences in the intrinsic disorder distribution of nuclear and non-nuclear proteins related to autophagy. We also looked at the peculiarities of the distribution of the intrinsically disordered autophagy-related proteins in various intra-nuclear organelles, such as the nucleolus, chromatin, Cajal bodies, nuclear speckles, promyelocytic leukemia (PML) nuclear bodies, nuclear lamina, nuclear pores, and perinucleolar compartment. This analysis revealed that the autophagy-related proteins constitute about 2.5% of the non-nuclear proteins and 3.3% of the nuclear proteins, which corresponds to a substantial enrichment by about 32% in the nucleus. Curiously, although, in general, the autophagy-related proteins share similar characteristics of disorder with a generic set of all non-nuclear proteins, chromatin and nuclear speckles are enriched in the intrinsically disordered autophagy proteins (29 and 37% of these proteins are disordered, respectively) and have high disorder content at 0.24 and 0.27, respectively. Therefore, our data suggest that some of the nuclear disordered proteins may play important roles in autophagy.

Quantiprot - a Python package for quantitative analysis of protein sequences

Background

The field of protein sequence analysis is dominated by tools rooted in substitution matrices and alignments. A complementary approach is provided by methods of quantitative characterization. A major advantage of the approach is that quantitative properties defines a multidimensional solution space, where sequences can be related to each other and differences can be meaningfully interpreted.

Results

Quantiprot is a software package in Python, which provides a simple and consistent interface to multiple methods for quantitative characterization of protein sequences. The package can be used to calculate dozens of characteristics directly from sequences or using physico-chemical properties of amino acids. Besides basic measures, Quantiprot performs quantitative analysis of recurrence and determinism in the sequence, calculates distribution of n-grams and computes the Zipf’s law coefficient.

Conclusions

We propose three main fields of application of the Quantiprot package. First, quantitative characteristics can be used in alignment-free similarity searches, and in clustering of large and/or divergent sequence sets. Second, a feature space defined by quantitative properties can be used in comparative studies of protein families and organisms. Third, the feature space can be used for evaluating generative models, where large number of sequences generated by the model can be compared to actually observed sequences.

The yeast kinesin-5 Cin8 interacts with the microtubule in a noncanonical manner

Kinesin motors play central roles in establishing and maintaining the mitotic spindle during cell division. Unlike most other kinesins, Cin8, a kinesin-5 motor in Saccharomyces cerevisiae, can move bidirectionally along microtubules, switching directionality according to biochemical conditions, a behavior that remains largely unexplained. To this end, we used biochemical rate and equilibrium constant measurements as well as cryo-electron microscopy methodologies to investigate the microtubule interactions of the Cin8 motor domain. These experiments unexpectedly revealed that, whereas Cin8 ATPase kinetics fell within measured ranges for kinesins (especially kinesin-5 proteins), approximately four motors can bind each αβ-tubulin dimer within the microtubule lattice. This result contrasted with those observations on other known kinesins, which can bind only a single "canonical" site per tubulin dimer. Competition assays with human kinesin-5 (Eg5) only partially abrogated this behavior, indicating that Cin8 binds microtubules not only at the canonical site, but also one or more separate ("noncanonical") sites. Moreover, we found that deleting the large, class-specific insert in the microtubule-binding loop 8 reverts Cin8 to one motor per αβ-tubulin in the microtubule. The novel microtubule-binding mode of Cin8 identified here provides a potential explanation for Cin8 clustering along microtubules and potentially may contribute to the mechanism for direction reversal.