The intrinsic disorder status of the human hepatitis C virus proteome

Hepatitis C Virus Infection and Intrinsic Disorder in the Signaling Pathways Induced by Toll-Like Receptors

In this study, we examined the interplay between protein intrinsic disorder, hepatitis C virus (HCV) infection, and signaling pathways induced by Toll-like receptors (TLRs). To this end, 10 HCV proteins, 10 human TLRs, and 41 proteins from the TLR-induced downstream pathways were considered from the prevalence of intrinsic disorder. Mapping of the intrinsic disorder to the HCV-TLR interactome and to the TLR-based pathways of human innate immune response to the HCV infection demonstrates that substantial levels of intrinsic disorder are characteristic for proteins involved in the regulation and execution of these innate immunity pathways and in HCV-TLR interaction. Disordered regions, being commonly enriched in sites of various posttranslational modifications, may play important functional roles by promoting protein-protein interactions and support the binding of the analyzed proteins to other partners such as nucleic acids. It seems that this system represents an important illustration of the role of intrinsic disorder in virus-host warfare.

Shell Disorder Models Detect That Omicron Has Harder Shells with Attenuation but Is Not a Descendant of the Wuhan-Hu-1 SARS-CoV-2

Before the SARS-CoV-2 Omicron variant emergence, shell disorder models (SDM) suggested that an attenuated precursor from pangolins may have entered humans in 2017 or earlier. This was based on a shell disorder analysis of SARS-CoV-1/2 and pangolin-Cov-2017. The SDM suggests that Omicron is attenuated with almost identical N (inner shell) disorder as pangolin-CoV-2017 (N-PID (percentage of intrinsic disorder): 44.8% vs. 44.9%—lower than other variants). The outer shell disorder (M-PID) of Omicron is lower than that of other variants and pangolin-CoV-2017 (5.4% vs. 5.9%). COVID-19-related CoVs have the lowest M-PIDs (hardest outer shell) among all CoVs. This is likely to be responsible for the higher contagiousness of SARS-CoV-2 and Omicron, since hard outer shell protects the virion from salivary/mucosal antimicrobial enzymes. Phylogenetic study using M reveals that Omicron branched off from an ancestor of the Wuhan-Hu-1 strain closely related to pangolin-CoVs. M, being evolutionarily conserved in COVID-19, is most ideal for COVID-19 phylogenetic study. Omicron may have been hiding among burrowing animals (e.g., pangolins) that provide optimal evolutionary environments for attenuation and increase shell hardness, which is essential for fecal–oral–respiratory transmission via buried feces. Incoming data support SDM e.g., the presence of fewer infectious particles in the lungs than in the bronchi upon infection.

Role of structural disorder in the multi-functionality of flavivirus proteins

INTRODUCTION

The life cycle of a virus involves interacting with the host cell, entry, hijacking host machinery for viral replication, evading the host's immune system, and releasing mature virions. However, viruses, being small in size, can only harbor a genome large enough to code for the minimal number of proteins required for the replication and maturation of the virions. As a result, many viral proteins are multifunctional machines that do not directly obey the classic structure-function paradigm. Often, such multifunctionality is rooted in intrinsic disorder that allows viral proteins to interact with various cellular factors and remain functional in the hostile environment of different cellular compartments.

AREAS COVERED

This report covers the classification of flaviviruses, their proteome organization, and the prevalence of intrinsic disorder in the proteomes of different flaviviruses. Further, we have summarized the speculations made about the apparent roles of intrinsic disorder in the observed multifunctionality of flaviviral proteins.

EXPERT OPINION

Small sizes of viral genomes impose multifunctionality on their proteins, which is dependent on the excessive usage of intrinsic disorder. In fact, intrinsic disorder serves as a universal functional tool, weapon, and armor of viruses and clearly plays an important role in their functionality and evolution.

Comprehensive Intrinsic Disorder Analysis of 6108 Viral Proteomes: From the Extent of Intrinsic Disorder Penetrance to Functional Annotation of Disordered Viral Proteins

Much of our understanding of proteins and proteomes comes from the traditional protein structure-function paradigm. However, in the last 2 decades, both computational and experimental studies have provided evidence that a large fraction of functional proteomes across different domains of life consists of intrinsically disordered proteins, thus triggering a quest to unravel and decipher protein intrinsic disorder. Unlike structured/ordered proteins, intrinsically disordered proteins/regions (IDPs/IDRs) do not possess a well-defined structure under physiological conditions and exist as highly dynamic conformational ensembles. In spite of this peculiarity, these proteins have crucial roles in cell signaling and regulation. To date, studies on the abundance and function of IDPs/IDRs in viruses are rather limited. To fill this gap, we carried out an extensive and thorough bioinformatics analysis of 283 000 proteins from 6108 reference viral proteomes. We analyzed protein intrinsic disorder from multiple perspectives, such as abundance of IDPs/IDRs across diverse virus types, their functional annotations, and subcellular localization in taxonomically divergent hosts. We show that the content of IDPs/IDRs in viral proteomes varies broadly as a function of virus genome types and taxonomically divergent hosts. We have combined the two most commonly used and accurate IDP predictors' results with charge-hydropathy (CH) versus cumulative distribution function (CDF) plots to categorize the viral proteins according to their IDR content and physicochemical properties. Mapping of gene ontology on the disorder content of viral proteins reveals that IDPs are primarily involved in key virus-host interactions and host antiviral immune response downregulation, which are reinforced by the post-translational modifications tied to disorder-enriched viral proteins. The present study offers detailed insights into the prevalence of the intrinsic disorder in viral proteomes and provides appealing targets for the design of novel therapeutics.

IDPology of the living cell: intrinsic disorder in the subcellular compartments of the human cell

Intrinsic disorder can be found in all proteomes of all kingdoms of life and in viruses, being particularly prevalent in the eukaryotes. We conduct a comprehensive analysis of the intrinsic disorder in the human proteins while mapping them into 24 compartments of the human cell. In agreement with previous studies, we show that human proteins are significantly enriched in disorder relative to a generic protein set that represents the protein universe. In fact, the fraction of proteins with long disordered regions and the average protein-level disorder content in the human proteome are about 3 times higher than in the protein universe. Furthermore, levels of intrinsic disorder in the majority of human subcellular compartments significantly exceed the average disorder content in the protein universe. Relative to the overall amount of disorder in the human proteome, proteins localized in the nucleus and cytoskeleton have significantly increased amounts of disorder, measured by both high disorder content and presence of multiple long intrinsically disordered regions. We empirically demonstrate that, on average, human proteins are assigned to 2.3 subcellular compartments, with proteins localized to few subcellular compartments being more disordered than the proteins that are localized to many compartments. Functionally, the disordered proteins localized in the most disorder-enriched subcellular compartments are primarily responsible for interactions with nucleic acids and protein partners. This is the first-time disorder is comprehensively mapped into the human cell. Our observations add a missing piece to the puzzle of functional disorder and its organization inside the cell.

On the Prevalence and Potential Functionality of an Intrinsic Disorder in the MERS-CoV Proteome

Middle East respiratory syndrome is a severe respiratory illness caused by an infectious coronavirus. This virus is associated with a high mortality rate, but there is as of yet no effective vaccine or antibody available for human immunity/treatment. Drug design relies on understanding the 3D structures of viral proteins; however, arriving at such understanding is difficult for intrinsically disordered proteins, whose disorder-dependent functions are key to the virus’s biology. Disorder is suggested to provide viral proteins with highly flexible structures and diverse functions that are utilized when invading host organisms and adjusting to new habitats. To date, the functional roles of intrinsically disordered proteins in the mechanisms of MERS-CoV pathogenesis, transmission, and treatment remain unclear. In this study, we performed structural analysis to evaluate the abundance of intrinsic disorder in the MERS-CoV proteome and in individual proteins derived from the MERS-CoV genome. Moreover, we detected disordered protein binding regions, namely, molecular recognition features and short linear motifs. Studying disordered proteins/regions in MERS-CoV could contribute to unlocking the complex riddles of viral infection, exploitation strategies, and drug development approaches in the near future by making it possible to target these important (yet challenging) unstructured regions.

Comparative Assessment of Intrinsic Disorder Predictions with a Focus on Protein and Nucleic Acid-Binding Proteins

With over 60 disorder predictors, users need help navigating the predictor selection task. We review 28 surveys of disorder predictors, showing that only 11 include assessment of predictive performance. We identify and address a few drawbacks of these past surveys. To this end, we release a novel benchmark dataset with reduced similarity to the training sets of the considered predictors. We use this dataset to perform a first-of-its-kind comparative analysis that targets two large functional families of disordered proteins that interact with proteins and with nucleic acids. We show that limiting sequence similarity between the benchmark and the training datasets has a substantial impact on predictive performance. We also demonstrate that predictive quality is sensitive to the use of the well-annotated order and inclusion of the fully structured proteins in the benchmark datasets, both of which should be considered in future assessments. We identify three predictors that provide favorable results using the new benchmark set. While we find that VSL2B offers the most accurate and robust results overall, ESpritz-DisProt and SPOT-Disorder perform particularly well for disordered proteins. Moreover, we find that predictions for the disordered protein-binding proteins suffer low predictive quality compared to generic disordered proteins and the disordered nucleic acids-binding proteins. This can be explained by the high disorder content of the disordered protein-binding proteins, which makes it difficult for the current methods to accurately identify ordered regions in these proteins. This finding motivates the development of a new generation of methods that would target these difficult-to-predict disordered proteins. We also discuss resources that support users in collecting and identifying high-quality disorder predictions.

Japanese encephalitis virus - exploring the dark proteome and disorder-function paradigm

Japanese encephalitis virus (JEV) is one of the major causes of viral encephalitis all around the globe. Approximately 3 billion people in endemic areas are at risk of Japanese encephalitis. To develop a wholistic understanding of the viral proteome, it is important to investigate both its ordered and disordered proteins. However, the functional and structural significance of disordered regions in the JEV proteome has not been systematically investigated as of yet. To fill this gap, we used here a set of bioinformatics tools to analyze the JEV proteome for the predisposition of its proteins for intrinsic disorder and for the presence of the disorder-based binding regions (also known as molecular recognition features, MoRFs). We also analyzed all JEV proteins for the presence of the probable nucleic acid-binding (DNA and RNA) sites. The results of these computational studies are experimentally validated using JEV capsid protein as an illustrative example. In agreement with bioinformatic analysis, we found that the N-terminal region of the JEV capsid (residues 1-30) is intrinsically disordered. We showed that this region is characterized by the temperature response typical for highly disordered proteins. Furthermore, we have experimentally shown that this disordered N-terminal domain of a capsid protein has a noticeable 'gain-of-structure' potential. In addition, using DOPS liposomes, we demonstrated the presence of pronounced membrane-mediated conformational changes in the N-terminal region of JEV capsid. In our view, this disorder-centric analysis would be helpful for a better understanding of the JEV pathogenesis.

Quality assessment for the putative intrinsic disorder in proteins

MOTIVATION

While putative intrinsic disorder is widely used, none of the predictors provides quality assessment (QA) scores. QA scores estimate the likelihood that predictions are correct at a residue level and have been applied in other bioinformatics areas. We recently reported that QA scores derived from putative disorder propensities perform relatively poorly for native disordered residues. Here we design and validate a general approach to construct QA predictors for disorder predictions.

RESULTS

The QUARTER (QUality Assessment for pRotein inTrinsic disordEr pRedictions) toolbox of methods accommodates a diverse set of ten disorder predictors. It builds upon several innovative design elements including use and scaling of selected physicochemical properties of the input sequence, post-processing of disorder propensity scores, and a feature selection that optimizes the predictive models to a specific disorder predictor. We empirically establish that each one of these elements contributes to the overall predictive performance of our tool and that QUARTER's outputs significantly outperform QA scores derived from the outputs generated the disorder predictors. The best performing QA scores for a single disorder predictor identify 13% of residues that are predicted with 98% precision. QA scores computed by combining results of the ten disorder predictors cover 40% of residues with 95% precision. Case studies are used to show how to interpret the QA scores. QA scores based on the high precision combined predictions are applied to analyze disorder in the human proteome.

AVAILABILITY AND IMPLEMENTATION

http://biomine.cs.vcu.edu/servers/QUARTER/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Understanding the penetrance of intrinsic protein disorder in rotavirus proteome

Rotavirus is a major cause of severe acute gastroenteritis in the infants and young children. The past decade has evidenced the role of intrinsically disordered proteins/regions (IDPs)/(IDPRs) in viral and other diseases. In general, (IDPs)/(IDPRs) are considered as dynamic conformational ensembles that devoid of a specific 3D structure, being associated with various important biological phenomena. Viruses utilize IDPs/IDPRs to survive in harsh environments, to evade the host immune system, and to highjack and manipulate host cellular proteins. The role of IDPs/IDPRs in Rotavirus biology and pathogenicity are not assessed so far, therefore, we have designed this study to deeply look at the penetrance of intrinsic disorder in rotavirus proteome consisting 12 proteins encoded by 11 segments of viral genome. Also, for all human rotaviral proteins, we have deciphered molecular recognition features (MoRFs), which are disorder based binding sites in proteins. Our study shows the wide spread of intrinsic disorder in several rotavirus proteins, primarily the nonstructural proteins NSP3, NSP4, and NSP5 that are involved in viral replication, translation, viroplasm formation and/or maturation. This study may serve as a primer for understanding the role of IDPs/MoRFs in rotavirus biology, design of alternative therapeutic strategies, and development of disorder-based drugs.

Computational Prediction of Intrinsic Disorder in Protein Sequences with the disCoP Meta-predictor

Intrinsically disordered proteins are either entirely disordered or contain disordered regions in their native state. These proteins and regions function without the prerequisite of a stable structure and were found to be abundant across all kingdoms of life. Experimental annotation of disorder lags behind the rapidly growing number of sequenced proteins, motivating the development of computational methods that predict disorder in protein sequences. DisCoP is a user-friendly webserver that provides accurate sequence-based prediction of protein disorder. It relies on meta-architecture in which the outputs generated by multiple disorder predictors are combined together to improve predictive performance. The architecture of disCoP is presented, and its accuracy relative to several other disorder predictors is briefly discussed. We describe usage of the web interface and explain how to access and read results generated by this computational tool. We also provide an example of prediction results and interpretation. The disCoP's webserver is publicly available at http://biomine.cs.vcu.edu/servers/disCoP/ .

Prediction of Intrinsic Disorder with Quality Assessment Using QUARTER

Intrinsically disordered regions (IDRs) are estimated to be highly abundant in nature. While only several thousand proteins are annotated with experimentally derived IDRs, computational methods can be used to predict IDRs for the millions of currently uncharacterized protein chains. Several dozen disorder predictors were developed over the last few decades. While some of these methods provide accurate predictions, unavoidably they also make some mistakes. Consequently, one of the challenges facing users of these methods is how to decide which predictions can be trusted and which are likely incorrect. This practical problem can be solved using quality assessment (QA) scores that predict correctness of the underlying (disorder) predictions at a residue level. We motivate and describe a first-of-its-kind toolbox of QA methods, QUARTER (QUality Assessment for pRotein inTrinsic disordEr pRedictions), which provides the scores for a diverse set of ten disorder predictors. QUARTER is available to the end users as a free and convenient webserver at http://biomine.cs.vcu.edu/servers/QUARTER/ . We briefly describe the predictive architecture of QUARTER and provide detailed instructions on how to use the webserver. We also explain how to interpret results produced by QUARTER with the help of a case study.

DISOselect: Disorder predictor selection at the protein level

The intense interest in the intrinsically disordered proteins in the life science community, together with the remarkable advancements in predictive technologies, have given rise to the development of a large number of computational predictors of intrinsic disorder from protein sequence. While the growing number of predictors is a positive trend, we have observed a considerable difference in predictive quality among predictors for individual proteins. Furthermore, variable predictor performance is often inconsistent between predictors for different proteins, and the predictor that shows the best predictive performance depends on the unique properties of each protein sequence. We propose a computational approach, DISOselect, to estimate the predictive performance of 12 selected predictors for individual proteins based on their unique sequence-derived properties. This estimation informs the users about the expected predictive quality for a selected disorder predictor and can be used to recommend methods that are likely to provide the best quality predictions. Our solution does not depend on the results of any disorder predictor; the estimations are made based solely on the protein sequence. Our solution significantly improves predictive performance, as judged with a test set of 1,000 proteins, when compared to other alternatives. We have empirically shown that by using the recommended methods the overall predictive performance for a given set of proteins can be improved by a statistically significant margin. DISOselect is freely available for non-commercial users through the webserver at http://biomine.cs.vcu.edu/servers/DISOselect/.

DEPICTER: Intrinsic Disorder and Disorder Function Prediction Server

Computational predictions of the intrinsic disorder and its functions are instrumental to facilitate annotation for the millions of unannotated proteins. However, access to these predictors is fragmented and requires substantial effort to find them and to collect and combine their results. The DEPICTER (DisorderEd PredictIon CenTER) server provides first-of-its-kind centralized access to 10 popular disorder and disorder function predictions that cover protein and nucleic acids binding, linkers, and moonlighting regions. It automates the prediction process, runs user-selected methods on the server side, visualizes the results, and outputs all predictions in a consistent and easy-to-parse format. DEPICTER also includes two accurate consensus predictors of disorder and disordered protein binding. Empirical tests on an independent (low similarity) benchmark dataset reveal that the computational tools included in DEPICTER generate accurate predictions that are significantly better than the results secured using sequence alignment. The DEPICTER server is freely available at http://biomine.cs.vcu.edu/servers/DEPICTER/.

Sequence-Derived Markers of Drug Targets and Potentially Druggable Human Proteins

Recent research shows that majority of the druggable human proteome is yet to be annotated and explored. Accurate identification of these unexplored druggable proteins would facilitate development, screening, repurposing, and repositioning of drugs, as well as prediction of new drug–protein interactions. We contrast the current drug targets against the datasets of non-druggable and possibly druggable proteins to formulate markers that could be used to identify druggable proteins. We focus on the markers that can be extracted from protein sequences or names/identifiers to ensure that they can be applied across the entire human proteome. These markers quantify key features covered in the past works (topological features of PPIs, cellular functions, and subcellular locations) and several novel factors (intrinsic disorder, residue-level conservation, alternative splicing isoforms, domains, and sequence-derived solvent accessibility). We find that the possibly druggable proteins have significantly higher abundance of alternative splicing isoforms, relatively large number of domains, higher degree of centrality in the protein-protein interaction networks, and lower numbers of conserved and surface residues, when compared with the non-druggable proteins. We show that the current drug targets and possibly druggable proteins share involvement in the catalytic and signaling functions. However, unlike the drug targets, the possibly druggable proteins participate in the metabolic and biosynthesis processes, are enriched in the intrinsic disorder, interact with proteins and nucleic acids, and are localized across the cell. To sum up, we formulate several markers that can help with finding novel druggable human proteins and provide interesting insights into the cellular functions and subcellular locations of the current drug targets and potentially druggable proteins.

Zika and Flavivirus Shell Disorder: Virulence and Fetal Morbidity

Zika virus (ZIKV) was first discovered in 1947 in Africa. Since then, sporadic ZIKV infections of humans have been reported in Africa and Asia. For a long time, this virus was mostly unnoticed due to its mild symptoms and low fatality rates. However, during the 2015-2016 epidemic in Central and South America, when millions of people were infected, it was discovered that ZIKV causes microcephaly in the babies of mothers infected during pregnancy. An examination of the M and C proteins of the ZIKV shell using the disorder predictor PONDR VLXT revealed that the M protein contains relatively high disorder levels comparable only to those of the yellow fever virus (YFV). On the other hand, the disorder levels in the C protein are relatively low, which can account for the low case fatality rate (CFR) of this virus in contrast to the more virulent YFV, which is characterized by high disorder in its C protein. A larger variation was found in the percentage of intrinsic disorder (PID) in the C protein of various ZIKV strains. Strains of African lineage are characterized by higher PIDs. Using both in vivo and in vitro experiments, laboratories have also previously shown that strains of African origin have a greater potential to inflict higher fetal morbidity than do strains of Asian lineage, with dengue-2 virus (DENV-2) having the least potential. Strong correlations were found between the potential to inflict fetal morbidity and shell disorder in ZIKV (r² = 0.9) and DENV-2 (DENV-2 + ZIKV, r² = 0.8). A strong correlation between CFR and PID was also observed when ZIKV was included in an analysis of sets of shell proteins from a variety of flaviviruses (r² = 0.8). These observations have potential implications for antiviral vaccine development and for the design of cancer therapeutics in terms of developing therapeutic viruses that penetrate hard-to-reach organs.

Accuracy of protein-level disorder predictions

Experimental annotations of intrinsic disorder are available for 0.1% of 147 000 000 of currently sequenced proteins. Over 60 sequence-based disorder predictors were developed to help bridge this gap. Current benchmarks of these methods assess predictive performance on datasets of proteins; however, predictions are often interpreted for individual proteins. We demonstrate that the protein-level predictive performance varies substantially from the dataset-level benchmarks. Thus, we perform first-of-its-kind protein-level assessment for 13 popular disorder predictors using 6200 disorder-annotated proteins. We show that the protein-level distributions are substantially skewed toward high predictive quality while having long tails of poor predictions. Consequently, between 57% and 75% proteins secure higher predictive performance than the currently used dataset-level assessment suggests, but as many as 30% of proteins that are located in the long tails suffer low predictive performance. These proteins typically have relatively high amounts of disorder, in contrast to the mostly structured proteins that are predicted accurately by all 13 methods. Interestingly, each predictor provides the most accurate results for some number of proteins, while the best-performing at the dataset-level method is in fact the best for only about 30% of proteins. Moreover, the majority of proteins are predicted more accurately than the dataset-level performance of the most accurate tool by at least four disorder predictors. While these results suggests that disorder predictors outperform their current benchmark performance for the majority of proteins and that they complement each other, novel tools that accurately identify the hard-to-predict proteins and that make accurate predictions for these proteins are needed.

Portrait of the Intrinsically Disordered Side of the HTLV-1 Proteome

Intrinsically disordered proteins (IDPs) lack an ordered 3D structure. These proteins contain one or more intrinsically disordered protein regions (IDPRs). IDPRs interact promiscuously with other proteins, which leads to their structural transition from a disordered to an ordered state. Such interaction-prone regions of IDPs are known as molecular recognition features. Recent studies suggest that IDPs provide structural plasticity and functional diversity to viral proteins that are involved in rapid replication and immune evasion within the host cells. In the present study, we evaluated the prevalence of IDPs and IDPRs in human T lymphotropic virus type 1 (HTLV-1) proteome. We also investigated the presence of MoRF regions in the structural and nonstructural proteins of HTLV-1. We found abundant IDPRs in HTLV-1 bZIP factor, p30, Rex, and structural nucleocapsid p15 proteins, which are involved in diverse functions such as virus proliferation, mRNA export, and genomic RNA binding. Our study analyzed the HTLV-1 proteome with the perspective of intrinsic disorder identification. We propose that the intrinsic disorder analysis of HTLV-1 proteins may form the basis for the development of protein disorder-based drugs.

Computational prediction of functions of intrinsically disordered regions

Intrinsically disorder regions (IDRs) are abundant in nature, particularly among Eukaryotes. While they facilitate a wide spectrum of cellular functions including signaling, molecular assembly and recognition, translation, transcription and regulation, only several hundred IDRs are annotated functionally. This annotation gap motivates the development of fast and accurate computational methods that predict IDR functions directly from protein sequences. We introduce and describe a comprehensive collection of 25 methods that provide accurate predictions of IDRs that interact with proteins and nucleic acids, that function as flexible linkers and that moonlight multiple functions. Virtually all of these predictors can be accessed online and many were developed in the last few years. They utilize a wide range of predictive architectures and take advantage of modern machine learning algorithms. Our empirical analysis shows that predictors that are available as webservers enjoy high rates of citations, attesting to their practical value and popularity. The most cited methods include DISOPRED3, ANCHOR, alpha-MoRFpred, MoRFpred, fMoRFpred and MoRFCHiBi. We present two case studies to demonstrate that predictions produced by these computational tools are relatively easy to interpret and that they deliver valuable functional clues. However, the current computational tools cover a relatively narrow range of disorder functions. Further development efforts that would cover a broader range of functions should be pursued. We demonstrate that a sufficient amount of functionally annotated IDRs that are associated with several other disorder functions is already available and can be used to design and validate novel predictors.

HIV Vaccine Mystery and Viral Shell Disorder

Hundreds of billions of dollars have been spent for over three decades in the search for an effective human immunodeficiency virus (HIV) vaccine with no success. There are also at least two other sexually transmitted viruses, for which no vaccine is available, the herpes simplex virus (HSV) and the hepatitis C virus (HCV). Traditional textbook explanatory paradigm of rapid mutation of retroviruses cannot adequately address the unavailability of vaccine for many sexually transmissible viruses, since HSV and HCV are DNA and non-retroviral RNA viruses, respectively, whereas effective vaccine for the horsefly-transmitted retroviral cousin of HIV, equine infectious anemia virus (EIAV), was found in 1973. We reported earlier the highly disordered nature of proteins in outer shells of the HIV, HCV, and HSV. Such levels of disorder are completely absent among the classical viruses, such as smallpox, rabies, yellow fever, and polio viruses, for which efficient vaccines were discovered. This review analyzes the physiology and shell disorder of the various related and non-related viruses to argue that EIAV and the classical viruses need harder shells to survive during harsher conditions of non-sexual transmissions, thus making them vulnerable to antibody detection and neutralization. In contrast, the outer shell of the HIV-1 (with its preferential sexual transmission) is highly disordered, thereby allowing large scale motions of its surface glycoproteins and making it difficult for antibodies to bind to them. The theoretical underpinning of this concept is retrospectively traced to a classical 1920s experiment by the legendary scientist, Oswald Avery. This concept of viral shapeshifting has implications for improved treatment of cancer and infections via immune evasion.

Computational Prediction of MoRFs, Short Disorder-to-order Transitioning Protein Binding Regions

Molecular recognition features (MoRFs) are short protein-binding regions that undergo disorder-to-order transitions (induced folding) upon binding protein partners. These regions are abundant in nature and can be predicted from protein sequences based on their distinctive sequence signatures. This first-of-its-kind survey covers 14 MoRF predictors and six related methods for the prediction of short protein-binding linear motifs, disordered protein-binding regions and semi-disordered regions. We show that the development of MoRF predictors has accelerated in the recent years. These predictors depend on machine learning-derived models that were generated using training datasets where MoRFs are annotated using putative disorder. Our analysis reveals that they generate accurate predictions. We identified eight methods that offer area under the ROC curve (AUC) ≥ 0.7 on experimentally-validated test datasets. We show that modern MoRF predictors accurately find experimentally annotated MoRFs even though they were trained using the putative disorder annotations. They are relatively highly-cited, particularly the methods available as webservers that on average secure three times more citations than methods without this option. MoRF predictions contribute to the experimental discovery of protein-protein interactions, annotation of protein functions and computational analysis of a variety of proteomes, protein families, and pathways. We outline future development and application directions for these tools, stressing the importance to develop novel tools that would target interactions of disordered regions with other types of partners.

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.

Unconventional RNA-binding proteins step into the virus-host battlefront

The crucial participation of cellular RNA‐binding proteins (RBPs) in virtually all steps of virus infection has been known for decades. However, most of the studies characterizing this phenomenon have focused on well‐established RBPs harboring classical RNA‐binding domains (RBDs). Recent proteome‐wide approaches have greatly expanded the census of RBPs, discovering hundreds of proteins that interact with RNA through unconventional RBDs. These domains include protein–protein interaction platforms, enzymatic cores, and intrinsically disordered regions. Here, we compared the experimentally determined census of RBPs to gene ontology terms and literature, finding that 472 proteins have previous links with viruses. We discuss what these proteins are and what their roles in infection might be. We also review some of the pioneering examples of unorthodox RBPs whose RNA‐binding activity has been shown to be critical for virus infection. Finally, we highlight the potential of these proteins for host‐based therapies against viruses.

This article is categorized under:

RNA Interactions with Proteins and Other Molecules > Protein–RNA Interactions: Functional Implications

RNA in Disease and Development > RNA in Disease

RNA Interactions with Proteins and Other Molecules > RNA–Protein Complexes

HCV adaptation to HIV coinfection

Human immunodeficiency virus (HIV) infection is rising as a leading cause of morbidity and mortality among hepatitis C virus (HCV)-infected patients. Both viruses interact in co-infected hosts, which may affect their intra-host evolution, potentially leading to differing genetic composition of viral populations in co-infected (CIP) and mono-infected (MIP) patients. Here, we investigate genetic differences between intra-host variants of the HCV hypervariable region 1 (HVR1) sampled from CIP and MIP. Nucleotide (nt) sequences of intra-host HCV HVR1 variants (N = 28,622) obtained from CIP (N = 112) and MIP (n = 176) were represented using 148 physical-chemical (PhyChem) indexes of DNA nt dimers. Significant (p < .0001) differences in the means and frequency distributions of 7 PhyChem properties were found between HVR1 variants from both groups. Linear projection analysis of 29 PhyChem features extracted from such PhyChem properties showed that the CIP and MIP HVR1 variants have a distinct distribution in the modeled 2D-space, with only ~1.3% of PhyChem profiles (N = 6782), shared by all HVR1 variants, being found in both groups. Probabilistic neural network (PNN) and naïve Bayesian (NB) classifiers trained on the PhyChem features accurately classified HVR1 variants by the group in cross-validation experiments (AUROC ≥ 0.96). Similarly, both models showed a high accuracy (AUROC ≥ 0.95) when evaluated on a test dataset of HVR1 sequences obtained from 10 patients, data from whom were not used for model building. Both models performed at the expected lower accuracy on randomly labeled datasets in cross-validation experiments (AUROC = 0.50). The random-label trained PNN showed a similar drop in accuracy on the test dataset (AUROC = 0.48), indicating that the detected associations were unlikely due to random correlations. Marked differences in genetic composition of HCV HVR1 variants sampled from CIP and MIP suggest differing intra-host HCV evolution in the presence of HIV infection. PhyChem features identified here may be used for detection of HIV infection from intra-host HCV variants alone in co-infected patients, thus facilitating monitoring for HIV introduction to high-risk populations with high HCV prevalence.

Drawing on disorder: How viruses use histone mimicry to their advantage

Humans carry trillions of viruses that thrive because of their ability to exploit the host. In this exploitation, viruses promote their own replication by suppressing the host antiviral response and by inducing changes in host biosynthetic processes, often with extremely small genomes of their own. In the review, we discuss the phenomenon of histone mimicry by viral proteins and how this mimicry allows the virus to dial in to the cell's transcriptional processes and establish a cell state that promotes infection. We suggest that histone mimicry is part of a broader viral strategy to use intrinsic protein disorder as a means to overcome the size limitations of its own genome and to maximize its impact on host protein networks. In particular, we discuss how intrinsic protein disorder may enable viral proteins to interfere with phase-separated host protein condensates, including those that contribute to chromatin-mediated control of gene expression.

On the Regularities of the Polar Profiles of Proteins Related to Ebola Virus Infection and their Functional Domains

The number of fatalities and economic losses caused by the Ebola virus infection across the planet culminated in the havoc that occurred between August and November 2014. However, little is known about the molecular protein profile of this devastating virus. This work represents a thorough bioinformatics analysis of the regularities of charge distribution (polar profiles) in two groups of proteins and their functional domains associated with Ebola virus disease: Ebola virus proteins and Human proteins interacting with Ebola virus. Our analysis reveals that a fragment exists in each of these proteins—one named the “functional domain”—with the polar profile similar to the polar profile of the protein that contains it. Each protein is formed by a group of short sub-sequences, where each fragment has a different and distinctive polar profile and where the polar profile between adjacent short sub-sequences changes orderly and gradually to coincide with the polar profile of the whole protein. When using the charge distribution as a metric, it was observed that it effectively discriminates the proteins from their functional domains. As a counterexample, the same test was applied to a set of synthetic proteins built for that purpose, revealing that any of the regularities reported here for the Ebola virus proteins and human proteins interacting with Ebola virus were not present in the synthetic proteins. Our results indicate that the polar profile of each protein studied and its corresponding functional domain are similar. Thus, when building each protein from its functional domai—adding one amino acid at a time and plotting each time its polar profile—it was observed that the resulting graphs can be divided into groups with similar polar profiles.

Understanding the interactability of chikungunya virus proteinsviamolecular recognition feature analysis

The chikungunya virus (CHIKV) is an alphavirus that has an enveloped icosahedral capsid and is transmitted byAedessp. mosquitos.

Conformational Plasticity of Hepatitis C Virus Core Protein Enables RNA-Induced Formation of Nucleocapsid-like Particles

Many of the unanswered questions associated with hepatitis C virus assembly are related to the core protein (HCVcp), which forms an oligomeric nucleocapsid encompassing the viral genome. The structural properties of HCVcp have been difficult to quantify, at least in part because it is an intrinsically disordered protein. We have used single-molecule Förster Resonance Energy Transfer techniques to study the conformational dimensions and dynamics of the HCVcp nucleocapsid domain (HCVncd) at various stages during the RNA-induced formation of nucleocapsid-like particles. Our results indicate that HCVncd is a typical intrinsically disordered protein. When it forms small ribonucleoprotein complexes with various RNA hairpins from the 3' end of the HCV genome, it compacts but remains intrinsically disordered and conformationally dynamic. Above a critical RNA concentration, these ribonucleoprotein complexes rapidly and cooperatively assemble into large nucleocapsid-like particles, wherein the individual HCVncd subunits become substantially more extended.

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.

Virucidal activity of human α- and β-defensins against hepatitis C virus genotype 4

Hepatitis C virus (HCV) is the major etiological agent of human non-A and non-B hepatitis affecting about 180 million people worldwide. The goal of the current study was to find effective anti-HCV proteins. As a result, defensins were selected as promising candidates due to their well-known anti-viral potential and small size. We conducted in vitro evaluation of two kinds of defensins (human α- and β-defensins and synthetic linear avian α-defensins) using tissue culture combined with reverse transcription nested PCR (RT-nested-PCR) and real-time PCR. Human α- and β-defensins showed strong anti-HCV activity in experiments on cellular protection, neutralization, and treatment at all concentrations used (10, 20 and 50 μg). The synthetic linear defensins could reach similar anti-HCV potential only at a noticeably higher concentration (250 μg) and do not show noticeable activity at 10 and 20 μg. This study suggests that defensins are potent anti-HCV agents.

Correlating Flavivirus virulence and levels of intrinsic disorder in shell proteins: protective roles vs. immune evasion

Computational analyses revealed correlations between the intrinsic disorder propensity of shell proteins and case fatality rates (CFRs) among Flaviviruses and within at least two Flavivirus species, such as tick-borne encephalitis virus (TBEV) and dengue virus (DENV). The shell proteins analyzed in this study are capsid (C) and membrane (PrM, Pr, and M) proteins. The highest correlations can be found when regression analyses were conducted using Pr (Flavivirus: r(2) = 0.78, p < 0.01) or M (Flavivirus: r(2) = 0.91, p < 0.01) as an independent variable with C and CFR as co-explanatory and dependent variables, respectively. Interestingly, while predicted intrinsic disorder levels (PIDs) of both C and M are positively correlated with the virulence, the PIDs of Pr and CFR are negatively correlated. This is likely due to the fact that the Pr portion of PrM plays various roles in protecting the virion from damage, whereas M and C are assisted by greater potential in binding promiscuity as a result of greater disorder. The C protein of yellow fever virus (YFV), which is the most virulent virus in the sample, has the highest PID levels, whereas the second most virulent TBEV FE subtype has the second highest PID score due to its C protein, and the least virulent West Nile virus (WNV) has the least disordered C protein. This knowledge can be used while working on the development and identification of attenuated strains for vaccine. Curiously, unlike Flaviviruses, a disordered outer shell was described for hepatitis C virus (HCV), human immunodeficiency virus (HIV), and human simplex virus 2 (HSV-2), which currently have no effective vaccine.

Functional correlations of respiratory syncytial virus proteins to intrinsic disorder

Protein intrinsic disorder is an important characteristic demonstrated by the absence of higher order structure, and is commonly detected in multifunctional proteins encoded by RNA viruses. Intrinsically disordered regions (IDRs) of proteins exhibit high flexibility and solvent accessibility, which permit several distinct protein functions, including but not limited to binding of multiple partners and accessibility for post-translational modifications. IDR-containing viral proteins can therefore execute various functional roles to enable productive viral replication. Respiratory syncytial virus (RSV) is a globally circulating, non-segmented, negative sense (NNS) RNA virus that causes severe lower respiratory infections. In this study, we performed a comprehensive evaluation of predicted intrinsic disorder of the RSV proteome to better understand the functional role of RSV protein IDRs. We included 27 RSV strains to sample major RSV subtypes and genotypes, as well as geographic and temporal isolate differences. Several types of disorder predictions were applied to the RSV proteome, including per-residue (PONDR®-FIT and PONDR® VL-XT), binary (CH, CDF, CH-CDF), and disorder-based interactions (ANCHOR and MoRFpred). We classified RSV IDRs by size, frequency and function. Finally, we determined the functional implications of RSV IDRs by mapping predicted IDRs to known functional domains of each protein. Identification of RSV IDRs within functional domains improves our understanding of RSV pathogenesis in addition to providing potential therapeutic targets. Furthermore, this approach can be applied to other NNS viruses that encode essential multifunctional proteins for the elucidation of viral protein regions that can be manipulated for attenuation of viral replication.

Solution conformations of Zika NS2B-NS3pro and its inhibition by natural products from edible plants

The recent Zika viral (ZIKV) epidemic has been associated with severe neurological pathologies such as neonatal microcephaly and Guillain-Barre syndrome but unfortunately no vaccine or medication is effectively available yet. Zika NS2B-NS3pro is essential for the proteolysis of the viral polyprotein and thereby viral replication. Thus NS2B-NS3pro represents an attractive target for anti-Zika drug discovery/design. Here, we have characterized the solution conformations and catalytic parameters of both linked and unlinked Zika NS2B-NS3pro complexes and found that the unlinked complex manifested well-dispersed NMR spectra. Subsequently with selective isotope-labeling using NMR spectroscopy, we demonstrated that C-terminal residues (R73-K100) of NS2B is highly disordered without any stable tertiary and secondary structures in the Zika NS2B-NS3pro complex in the free state. Upon binding to the well-characterized serine protease inhibitor, bovine pancreatic trypsin inhibitor (BPTI), only the extreme C-terminal residues (L86-K100) remain disordered. Additionally, we have identified five flavonoids and one natural phenol rich in edible plants including fruits and vegetables, which inhibit Zika NS2B-NS3pro in a non-competitive mode, with Ki ranging from 770 nM for Myricetin to 34.02 μM for Apigenin. Molecular docking showed that they all bind to a pocket on the back of the active site and their structure-activity relationship was elucidated. Our study provides valuable insights into the solution conformation of Zika NS2B-NS3pro and further deciphers its susceptibility towards allosteric inhibition by natural products. As these natural product inhibitors fundamentally differ from the currently-known active site inhibitors in terms of both inhibitory mode and chemical scaffold, our finding might open a new avenue for development of better allosteric inhibitors to fight ZIKV infection.

Quarterly intrinsic disorder digest (April-May-June, 2014)

This is the 6^th issue of the Digested Disorder series that continues to use only 2 criteria for inclusion of a paper to this digest: The publication date (a paper should be published within the covered time frame) and the topic (a paper should be dedicated to any aspect of protein intrinsic disorder). The current digest issue covers papers published during the second quarter of 2014; i.e., during the period of April, May, and June of 2014. Similar to previous issues, the papers are grouped hierarchically by topics they cover, and for each of the included papers a short description is given on its major findings.

How to Predict Disorder in a Protein of Interest

Currently available computational tools, which are many, provide a researcher with the multitude of options for prediction of intrinsic disorder in a protein of interest and for finding at least some of its disorder-based functions. This chapter provides a highly subjective guideline on how not to be lost in the "dark forest" of available tools for the analysis of intrinsic disorder. By no means it gives a unique pathway through this forest, but simply presents some of the tools the author uses in his everyday research.

Overlapping Regions in HIV-1 Genome Act as Potential Sites for Host-Virus Interaction

More than a decade, overlapping genes in RNA viruses became a subject of research which has explored various effect of gene overlapping on the evolution and function of viral genomes like genome size compaction. Additionally, overlapping regions (OVRs) are also reported to encode elevated degree of protein intrinsic disorder (PID) in unspliced RNA viruses. With the aim to explore the roles of OVRs in HIV-1 pathogenesis, we have carried out an in-depth analysis on the association of gene overlapping with PID in 35 HIV1- M subtypes. Our study reveals an over representation of PID in OVR of HIV-1 genomes. These disordered residues endure several vital, structural features like short linear motifs (SLiMs) and protein phosphorylation (PP) sites which are previously shown to be involved in massive host–virus interaction. Moreover, SLiMs in OVRs are noticed to be more functionally potential as compared to that of non-overlapping region. Although, density of experimentally verified SLiMs, resided in 9 HIV-1 genes, involved in host–virus interaction do not show any bias toward clustering into OVR, tat and rev two important proteins mediates host–pathogen interaction by their experimentally verified SLiMs, which are mostly localized in OVR. Finally, our analysis suggests that the acquisition of SLiMs in OVR is mutually exclusive of the occurrence of disordered residues, while the enrichment of PPs in OVR is solely dependent on PID and not on overlapping coding frames. Thus, OVRs of HIV-1 genomes could be demarcated as potential molecular recognition sites during host–virus interaction.

Intrinsically Disordered Side of the Zika Virus Proteome

Over the last few decades, concepts of protein intrinsic disorder have been implicated in different biological processes. Recent studies have suggested that intrinsically disordered proteins (IDPs) provide structural plasticity and functional diversity to viral proteins that are involved in rapid replication and immune evasion in host cells. In case of Zika virus, the roles of protein intrinsic disorder in mechanisms of pathogenesis are not completely understood. In this study, we have analyzed the prevalence of intrinsic disorder in Zika virus proteome (strain MR 766). Our analyses revealed that Zika virus polyprotein is enriched with intrinsically disordered protein regions (IDPRs) and this finding is consistent with previous reports on the involvement of IDPs in shell formation and virulence of the Flaviviridae family. We found abundant IDPRs in Capsid, NS2B, NS3, NS4A, and NS5 proteins that are involved in mature particle formation and replication. In our view, the intrinsic disorder-focused analysis of ZIKV proteins could be important for the development of disorder-based drugs.

Protein intrinsic disorder within the Potyvirus genus: from proteome-wide analysis to functional annotation

Within proteins, intrinsically disordered regions (IDRs) are devoid of stable secondary and tertiary structures under physiological conditions and rather exist as dynamic ensembles of inter-converting conformers. Although ubiquitous in all domains of life, the intrinsic disorder content is highly variable in viral genomes. Over the years, functional annotations of disordered regions at the scale of the whole proteome have been conducted for several animal viruses. But to date, similar studies applied to plant viruses are still missing. Based on disorder prediction tools combined with annotation programs and evolutionary studies, we analyzed the intrinsic disorder content in Potyvirus, using a 10-species dataset representative of this genus diversity. In this paper, we revealed that: (i) the Potyvirus proteome displays high disorder content, (ii) disorder is conserved during Potyvirus evolution, suggesting a functional advantage of IDRs, (iii) IDRs evolve faster than ordered regions, and (iv) IDRs may be associated with major biological functions required for the Potyvirus cycle. Notably, the proteins P1, Coat protein (CP) and Viral genome-linked protein (VPg) display a high content of conserved disorder, enriched in specific motifs mimicking eukaryotic functional modules and suggesting strategies of host machinery hijacking. In these three proteins, IDRs are particularly conserved despite their high amino acid polymorphism, indicating a link to adaptive processes. Through this comprehensive study, we further investigate the biological relevance of intrinsic disorder in Potyvirus biology and we propose a functional annotation of potyviral proteome IDRs.

The Disordered Region of the HCV Protein NS5A: Conformational Dynamics, SH3 Binding, and Phosphorylation

Intrinsically disordered proteins (IDPs) perform their physiological role without possessing a well-defined three-dimensional structure. Still, residual structure and conformational dynamics of IDPs are crucial for the mechanisms underlying their functions. For example, regions of transient secondary structure are often involved in molecular recognition, with the structure being stabilized (or not) upon binding. Long-range interactions, on the other hand, determine the hydrodynamic radius of the IDP, and thus the distance over which the protein can catch binding partners via so-called fly-casting mechanisms. The modulation of long-range interactions also presents a convenient way of fine-tuning the protein's interaction network, by making binding sites more or less accessible. Here we studied, mainly by nuclear magnetic resonance spectroscopy, residual secondary structure and long-range interactions in nonstructural protein 5A (NS5A) from hepatitis C virus (HCV), a typical viral IDP with multiple functions during the viral life cycle. NS5A comprises an N-terminal folded domain, followed by a large (∼250-residue) disordered C-terminal part. Comparing nuclear magnetic resonance spectra of full-length NS5A with those of a protein construct composed of only the C-terminal residues 191-447 (NS5A-D2D3) allowed us to conclude that there is no significant interaction between the globular and disordered parts of NS5A. NS5A-D2D3, despite its overall high flexibility, shows a large extent of local residual (α-helical and β-turn) structure, as well as a network of electrostatic long-range interactions. Furthermore, we could demonstrate that these long-range interactions become modulated upon binding to the host protein Bin1, as well as after NS5A phosphorylation by CK2. As the charged peptide regions involved in these interactions are well conserved among the different HCV genotypes, these transient long-range interactions may be important for some of the functions of NS5A over the course of the HCV life cycle.

Detection of links between Ebola nucleocapsid and virulence using disorder analysis

The underlying reasons for the differences in the virulence of various types of Ebola virus (EBOV) remain unknown. Comparison of the percentage of disorder (PID) in nucleocapsid proteins VP30 and NP reveals high correlation between nucleocapsid PIDs and the case-fatality rates of EBOV. The higher disorder of these proteins is likely to be needed for more efficient multiplication of virus copies via more efficient viral RNA transcription and more promiscuous protein binding potential. This is important for the more efficient assistance of nucleocapsid in viral particle budding and of the assembly and mobility of viral proteins across the host membrane and within the cytoplasm. A more comprehensive knowledge of the molecular mechanisms of EBOV virulence would also lead to new and more effective strategies in vaccine development.

Molecular recognition features (MoRFs) in three domains of life

MoRFs are widespread intrinsically disordered protein-binding regions that have similar abundance and amino acid composition across the three domains of life.

A Proline-Tryptophan Turn in the Intrinsically Disordered Domain 2 of NS5A Protein Is Essential for Hepatitis C Virus RNA Replication

Hepatitis C virus (HCV) nonstructural protein 5A (NS5A) and its interaction with the human chaperone cyclophilin A are both targets for highly potent and promising antiviral drugs that are in the late stages of clinical development. Despite its high interest in regards to the development of drugs to counteract the worldwide HCV burden, NS5A is still an enigmatic multifunctional protein poorly characterized at the molecular level. NS5A is required for HCV RNA replication and is involved in viral particle formation and regulation of host pathways. Thus far, no enzymatic activity or precise molecular function has been ascribed to NS5A that is composed of a highly structured domain 1 (D1), as well as two intrinsically disordered domains 2 (D2) and 3 (D3), representing half of the protein. Here, we identify a short structural motif in the disordered NS5A-D2 and report its NMR structure. We show that this structural motif, a minimal Pro(314)-Trp(316) turn, is essential for HCV RNA replication, and its disruption alters the subcellular distribution of NS5A. We demonstrate that this Pro-Trp turn is required for proper interaction with the host cyclophilin A and influences its peptidyl-prolyl cis/trans isomerase activity on residue Pro(314) of NS5A-D2. This work provides a molecular basis for further understanding of the function of the intrinsically disordered domain 2 of HCV NS5A protein. In addition, our work highlights how very small structural motifs present in intrinsically disordered proteins can exert a specific function.

Understanding dengue virus capsid protein disordered N-Terminus and pep14-23-based inhibition

Dengue virus (DENV) infection affects millions of people and is becoming a major global disease for which there is no specific available treatment. pep14-23 is a recently designed peptide, based on a conserved segment of DENV capsid (C) protein. It inhibits the interaction of DENV C with host intracellular lipid droplets (LDs), which is crucial for viral replication. Combining bioinformatics and biophysics, here, we analyzed pep14-23 structure and ability to bind different phospholipids, relating that information with the full-length DENV C. We show that pep14-23 acquires α-helical conformation upon binding to negatively charged phospholipid membranes, displaying an asymmetric charge distribution structural arrangement. Structure prediction for the N-terminal segment reveals four viable homodimer orientations that alternatively shield or expose the DENV C hydrophobic pocket. Taken together, these findings suggest a new biological role for the disordered N-terminal region, which may function as an autoinhibitory domain mediating DENV C interaction with its biological targets. The results fit with our current understanding of DENV C and pep14-23 structure and function, paving the way for similar approaches to understanding disordered proteins and improved peptidomimetics drug development strategies against DENV and similar Flavivirus infections.

Comparative salivary proteome of hepatitis B- and C-infected patients

Hepatitis B and C virus (HBV and HCV) infections are an important cause of cirrhosis and hepatocellular carcinoma. The natural history has a prominent latent phase, and infected patients may remain undiagnosed; this situation may lead to the continuing spread of these infections in the community. Compelling reasons exist for using saliva as a diagnostic fluid because it meets the demands of being an inexpensive, noninvasive and easy-to-use diagnostic method. Indeed, comparative analysis of the salivary proteome using mass spectrometry is a promising new strategy for identifying biomarkers. Our goal is to apply an Orbitrap-based quantitative approach to explore the salivary proteome profile in HBV- and HCV-infected patients. In the present study, whole saliva was obtained from 20 healthy, (control) 20 HBV-infected and 20 HCV-infected subjects. Two distinct pools containing saliva from 10 subjects of each group were obtained. The samples were ultracentrifuged and fractionated, and all fractions were hydrolyzed (trypsin) and injected into an LTQ-VELOS ORBITRAP. The identification and analyses of peptides were performed using Proteome Discoverer1.3 and ScaffoldQ + v.3.3.1. From a total of 362 distinct proteins identified, 344 proteins were identified in the HBV, 326 in the HCV and 303 in the control groups. Some blood proteins, such as flavin reductase (which converts biliverdin to bilirubin), were detected only in the HCV group. The data showed a reduced presence of complement C3, ceruloplasmin, alpha(1)-acid glycoprotein and alpha(2)-acid glycoprotein in the hepatitis-infected patients. Peptides of serotransferrin and haptoglobin were less detected in the HCV group. This study provides an integrated perspective of the salivary proteome, which should be further explored in future studies targeting specific disease markers for HBV and HCV infection.

Molecular principles of human virus protein-protein interactions

MOTIVATION

Viruses, from the human protein-protein interaction network perspective, target hubs, bottlenecks and interconnected nodes enriched in certain biological pathways. However, not much is known about the general characteristic features of the human proteins interacting with viral proteins (referred to as hVIPs) as well as the motifs and domains utilized by human-virus protein-protein interactions (referred to as Hu-Vir PPIs).

RESULTS

Our study has revealed that hVIPs are mostly disordered proteins, whereas viral proteins are mostly ordered proteins. Protein disorder in viral proteins and hVIPs varies from one subcellular location to another. In any given viral-human PPI pair, at least one of the two proteins is structurally disordered suggesting that disorder associated conformational flexibility as one of the characteristic features of virus-host interaction. Further analyses reveal that hVIPs are (i) slowly evolving proteins, (ii) associated with high centrality scores in human-PPI network, (iii) involved in multiple pathways, (iv) enriched in eukaryotic linear motifs (ELMs) associated with protein modification, degradation and regulatory processes, (v) associated with high number of splice variants and (vi) expressed abundantly across multiple tissues. These aforementioned findings suggest that conformational flexibility, spatial diversity, abundance and slow evolution are the characteristic features of the human proteins targeted by viral proteins. Hu-Vir PPIs are mostly mediated via domain-motif interactions (DMIs) where viral proteins employ motifs that mimic host ELMs to bind to domains in human proteins. DMIs are shared among viruses belonging to different families indicating a possible convergent evolution of these motifs to help viruses to adopt common strategies to subvert host cellular pathways.

AVAILABILITY AND IMPLEMENTATION

Hu-Vir PPI data, DDI and DMI data for human-virus PPI can be downloaded from http://cdfd.org.in/labpages/computational_biology_datasets.html.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Potential lactoferrin activity against pathogenic viruses

Lactoferrin (LF) is an 80-kDa globular glycoprotein with high affinity for metal ions, particularly for iron. This protein possesses many biological functions, including the binding and release of iron and serves as one of the important components of the innate immune system, where it acts as a potent inhibitor of several pathogens. LF has efficacious antibacterial and antiviral activities against a wide range of Gram-positive and Gram-negative bacteria and against both naked and enveloped DNA and RNA viruses. In its antiviral pursuit, LF acts predominantly at the acute phase of the viral infection or even at the intracellular stage, as in hepatitis C virus infection. LF inhibits the entry of viral particles into host cells, either by direct attachment to the viral particles or by blocking their cellular receptors. This wide range of activities may be attributed to the capacity of LF to bind iron and its ability to interfere with the cellular receptors of both hosts and pathogenic microbes.

Screening the anti infectivity potentials of native N- and C-lobes derived from the camel lactoferrin against hepatitis C virus

BACKGROUND

Hepatitis C virus (HCV) infection represents a worldwide health threat that still needs efficient protective vaccine and/or effective drug. The traditional medicine, such as camel milk, is heavily used by the large sector of HCV patients to control the infection due to the high cost of the available standard therapy. Camel milk contains lactoferrin, which plays an important and multifunctional role in innate immunity and specific host defense against microbial infection. Continuing the analysis of the effectiveness of camel lactoferrin against HCV, the current study aimed to separate and purify the native N- and C-lobes from the proteolytically cleaved camel lactoferrin (cLF) and to compare their in vitro activities against the HCV infection in Huh7.5 cells in order to determine the most active domain.

METHODS

Lactoferrin and its digested N- and C-lobes were purified by Mono S 5/50 GL column and Superdex 200 5/150 column. The purified proteins were assessed through three venues: 1. To inhibit intracellular replication, HCV infected cells were treated with the proteins at different concentrations and time intervals; 2. The proteins were directly incubated with the viral particles (neutralization) and then such neutralized viruses were used to infect cells; 3. The cells were protected with proteins before exposure to the virus. The antiviral potentials of the cLf and its lobes were determined using three techniques: 1. RT-nested PCR, 2. Real-time PCR, and 3. Flow cytometry.

RESULTS

N- and C-lobes were purified in two consecutive steps; using Mono-S and Superdex 200 columns. The molecular mass of N- and C-lobes was about 40 kDa. cLF and its lobes could prevent HCV entry into Huh 7.5 cells with activity reached 100% through direct interaction with the virus. The inhibition of intracellular viral replication by N-lobe is 2-fold and 3-fold more effective than that of the cLF and C-lobe, respectively.

CONCLUSION

Generated native N- and C-lobes from camel lactoferrin demonstrated a range of noticeably different potentials against HCV cellular infectivity. The anti-HCV activities were sorted as N-lobe > cLf > C-lobe.