Accurate and Fast Prediction of Intrinsic Disorder Using flDPnn

Intrinsically disordered proteins (IDPs) that include one or more intrinsically disordered regions (IDRs) are abundant across all domains of life and viruses and play numerous functional roles in various cellular processes. Due to a relatively low throughput and high cost of experimental techniques for identifying IDRs, there is a growing need for fast and accurate computational algorithms that accurately predict IDRs/IDPs from protein sequences. We describe one of the leading disorder predictors, flDPnn. Results from a recent community-organized Critical Assessment of Intrinsic Disorder (CAID) experiment show that flDPnn provides fast and state-of-the-art predictions of disorder, which are supplemented with the predictions of several major disorder functions. This chapter provides a practical guide to flDPnn, which includes a brief explanation of its predictive model, descriptions of its web server and standalone versions, and a case study that showcases how to read and understand flDPnn's predictions.

Peptide diffusion in biomolecular condensates

Diffusion determines the turnover of biomolecules in liquid-liquid phase-separated condensates. We considered the mean square displacement and thus the diffusion constant for simple model systems of peptides GGGGG, GGQGG, and GGVGG in aqueous solutions after phase separation by simulating atomic-level models. These solutions readily separate into aqueous and peptide-rich droplet phases. We noted the effect of the peptides being in a solvated, surface, or droplet state on the peptide's diffusion coefficients. Both sequence and peptide conformational distribution were found to influence diffusion and condensate turnover in these systems, with sequence dominating the magnitude of the differences. We found that the most compact structures for each sequence diffused the fastest in the peptide-rich condensate phase. This model result may have implications for turnover dynamics in signaling systems.

Evaluation of the inhibitory potency of anti-dengue phytocompounds against DENV-2 NS2B-NS3 protease: virtual screening, ADMET profiling and molecular dynamics simulation investigations

Dengue fever has been a worldwide concern, with 50-100 million new infections each year mainly due to five different serotypes of the Dengue virus (DENV). Designing a perfect anti-dengue agent that can inhibit all the serotypes by distinguishing antigenic differences is quite difficult. Previous anti-dengue researches have included chemical compounds screening against DENV enzymes. The ongoing analysis is meant for investigation of the plant-based compounds as antagonistic to DENV-2 focusing on the specific NS2B-NS3Pro target, a trypsin like serine protease that cuts the DENV polyprotein into separate proteins crucial for viral reproduction. Initially, a virtual library of more than 130 phytocompounds was prepared from previously published reports of plants with anti-dengue properties, which were then virtually screened and shortlisted against the WT, H51N and S135A mutant of DENV-2 NS2B-NS3Pro. The three top-most compounds were viewed as Gallocatechin (GAL), Flavokawain-C (FLV), and Isorhamnetin (ISO) showing docking scores of -5.8, -5.7, -5.7 kcal/mol for WT, -7.5, -6.8, -7.6 kcal/mol for the H51N, and -6.9, -6.5, -6.1 kcal/mol for the S135A mutant protease, respectively. 100 ns long MD simulations and MM-GBSA based free energy calculations were performed on the NS2B-NS3Pro complexes to witness the relative binding affinity of the compounds and favourable molecular interactions network. A comprehensive analysis of the study reveals some promising outcomes with ISO as the topmost compound with favourable pharmacokinetic properties for the WT and mutants (H51N and S135A) as well, suggesting as a novel anti-NS2B-NS3Pro agent with better adapting characters in both the mutants.Communicated by Ramaswamy H. Sarma.

One-Dimensional HKUST-1-Decorated Glassy Carbon Electrode for the Sensitive Electrochemical Immunosensor of NS1 Dengue Virus Serotype-3

In this work, simple and sensitive detection of dengue virus serotype-3 (DENV-3) antigen was accomplished by a one-dimensional (1D) HKUST-1-functionalized electrochemical sensor. 1D HKUST-1 was synthesized via a coprecipitation method using triethanolamine (TEOA) as pH modulator and structure-directing agent. The structure, morphology, and sensing performance of the HKUST-1-decorated carbon electrode were characterized by X-ray diffraction (XRD), infrared spectroscopy (FTIR), scanning electron microscopy (SEM), cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and differential pulse voltammetry (DPV). We found that 40 wt% TEOA transforms the octahedron HKUST-1 to the nanorods while maintaining its crystal structure and providing chemical stability. The 1D HKUST-1-decorated carbon electrode successfully detects the antigen in the range of 0.001-10 ng/mL with a detection limit of 0.932 pg/mL. The immunosensor also exhibits remarkable performance in analyzing the antigen in human serum and showed recovery as high as ∼98% with excellent selectivity and reproducibility.

Dengue Vaccination: Towards a New Dawn of Curbing Dengue Infection

Dengue is an infectious disease caused by dengue virus (DENV) and is a serious global burden. Antibody-dependent enhancement and the ability of DENV to infect immune cells, along with other factors, lead to fatal Dengue Haemorrhagic Fever and Dengue Shock Syndrome. This necessitates the development of a robust and efficient vaccine but vaccine development faces a number of hurdles. In this review, we look at the epidemiology, genome structure and cellular targets of DENV and elaborate upon the immune responses generated by human immune system against DENV infection. The review further sheds light on various challenges in development of a potent vaccine against DENV which is followed by presenting a current account of different vaccines which are being developed or have been licensed.

M Protein from Dengue virus oligomerizes to pentameric channel protein: in silico analysis study

The Dengue virus M protein is a 75 amino acid polypeptide with two helical transmembranes (TM). The TM domain oligomerizes to form an ion channel, facilitating viral release from the host cells. The M protein has a critical role in the virus entry and life cycle, making it a potent drug target. The oligomerization of the monomeric protein was studied using ab initio modeling and molecular dynamics (MD) simulation in an implicit membrane environment. The representative structures obtained showed pentamer as the most stable oligomeric state, resembling an ion channel. Glutamic acid, threonine, serine, tryptophan, alanine, isoleucine form the pore-lining residues of the pentameric channel, conferring an overall negative charge to the channel with approximate length of 51.9 Å. Residue interaction analysis (RIN) for M protein shows that Ala94, Leu95, Ser112, Glu124, and Phe155 are the central hub residues representing the physicochemical interactions between domains. The virtual screening with 165 different ion channel inhibitors from the ion channel library shows monovalent ion channel blockers, namely lumacaftor, glipizide, gliquidone, glisoxepide, and azelnidipine to be the inhibitors with high docking scores. Understanding the three-dimensional structure of M protein will help design therapeutics and vaccines for Dengue infection.

Intrinsic disorder in the open reading frame 2 of hepatitis E virus: a protein with multiple functions beyond viral capsid

BACKGROUND

Hepatitis E virus (HEV) is the cause of a liver disease hepatitis E. The translation product of HEV ORF2 has recently been demonstrated as a protein involved in multiple functions besides performing its major role of a viral capsid. As intrinsically disordered regions (IDRs) are linked to various essential roles in the virus's life cycle, we analyzed the disorder pattern distribution of the retrieved ORF2 protein sequences by employing different online predictors. Our findings might provide some clues on the disorder-based functions of ORF2 protein that possibly help us in understanding its behavior other than as a HEV capsid protein.

RESULTS

The modeled three dimensional (3D) structures of ORF2 showed the predominance of random coils or unstructured regions in addition to major secondary structure components (alpha helix and beta strand). After initial scrutinization, the predictors VLXT and VSL2 predicted ORF2 as a highly disordered protein while the predictors VL3 and DISOPRED3 predicted ORF2 as a moderately disordered protein, thus categorizing HEV-ORF2 into IDP (intrinsically disordered protein) or IDPR (intrinsically disordered protein region) respectively. Thus, our initial predicted disorderness in ORF2 protein 3D structures was in excellent agreement with their predicted disorder distribution patterns (evaluated through different predictors). The abundance of MoRFs (disorder-based protein binding sites) in ORF2 was observed that signified their interaction with binding partners which might further assist in viral infection. As IDPs/IDPRs are targets of regulation, we carried out the phosphorylation analysis to reveal the presence of post-translationally modified sites. Prevalence of several disordered-based phosphorylation sites further signified the involvement of ORF2 in diverse and significant biological processes. Furthermore, ORF2 structure-associated functions revealed its involvement in several crucial functions and biological processes like binding and catalytic activities.

CONCLUSIONS

The results predicted ORF2 as a protein with multiple functions besides its role as a capsid protein. Moreover, the occurrence of IDPR/IDP in ORF2 protein suggests that its disordered region might serve as novel drug targets via functioning as potential interacting domains. Our data collectively might provide significant implication in HEV vaccine search as disorderness in viral proteins is related to mechanisms involved in immune evasion.

Targeting the DENV NS2B-NS3 protease with active antiviral phytocompounds: structure-based virtual screening, molecular docking and molecular dynamics simulation studies

Dengue fever has been a global health concern. Mitigation is a challenging problem due to non-availability of workable treatments. The most difficult objective is to design a perfect anti-dengue agent capable of inhibiting infections caused by all four serotypes. Various tactics have been employed in the past to discover dengue antivirals, including screening of chemical compounds against dengue virus enzymes. The objective of the current study is to investigate phytocompounds as anti-dengue remedies that target the non-structural 2B and non-structural 3 protease (NS2B-NS3pro), a possible therapeutic target for dengue fever. Initially, 300 + antiviral phytocompounds were collected from Duke's phytochemical and ethnobotanical database and 30 phytocompounds with anti-dengue properties were identified from previously reported studies, which were virtually screened against NS2B-NS3pro using molecular docking and toxicity evaluation. The top five most screened ligands were naringin, hesperidin, gossypol, maslinic acid and rhodiolin with binding affinities of - 8.7 kcal/mol, - 8.5 kcal/mol, - 8.5 kcal/mol, - 8.5 kcal/mol and - 8.1 kcal/mol, respectively. The finest docked compounds complexed with NS2B-NS3pro were subjected for molecular dynamics (MD) simulations and binding free energy estimations through molecular mechanics generalized born surface area-based calculations. The results of the study are intriguing in the context of computer-aided screening and the binding affinities of the phytocompounds, proposing maslinic acid (MAS) as a potent bioactive antiviral for the development of phytocompound-based anti-dengue agent.

Looking at the Pathogenesis of the Rabies Lyssavirus Strain Pasteur Vaccins through a Prism of the Disorder-Based Bioinformatics

Rabies is a neurological disease that causes between 40,000 and 70,000 deaths every year. Once a rabies patient has become symptomatic, there is no effective treatment for the illness, and in unvaccinated individuals, the case-fatality rate of rabies is close to 100%. French scientists Louis Pasteur and Émile Roux developed the first vaccine for rabies in 1885. If administered before the virus reaches the brain, the modern rabies vaccine imparts long-lasting immunity to the virus and saves more than 250,000 people every year. However, the rabies virus can suppress the host's immune response once it has entered the cells of the brain, making death likely. This study aimed to make use of disorder-based proteomics and bioinformatics to determine the potential impact that intrinsically disordered protein regions (IDPRs) in the proteome of the rabies virus might have on the infectivity and lethality of the disease. This study used the proteome of the Rabies lyssavirus (RABV) strain Pasteur Vaccins (PV), one of the best-understood strains due to its use in the first rabies vaccine, as a model. The data reported in this study are in line with the hypothesis that high levels of intrinsic disorder in the phosphoprotein (P-protein) and nucleoprotein (N-protein) allow them to participate in the creation of Negri bodies and might help this virus to suppress the antiviral immune response in the host cells. Additionally, the study suggests that there could be a link between disorder in the matrix (M) protein and the modulation of viral transcription. The disordered regions in the M-protein might have a possible role in initiating viral budding within the cell. Furthermore, we checked the prevalence of functional disorder in a set of 37 host proteins directly involved in the interaction with the RABV proteins. The hope is that these new insights will aid in the development of treatments for rabies that are effective after infection.

Investigating the conformational dynamics of Zika virus NS4B protein

Zika virus (ZIKV) NS4B protein is a membranotropic multifunctional protein. Despite its versatile functioning, its topology and dynamics are not entirely understood. There is no X-ray or cryo-EM structure available for any flaviviral NS4B full-length protein. In this study, we have investigated the structural dynamics of full-length ZIKV NS4B protein through 3D structure models using molecular dynamics simulations and experimental techniques. Also, we employed a reductionist approach to understand the dynamics of NS4B protein where we studied its N-terminal (residues 1-38), C-terminal (residues 194-251), and cytosolic (residues 131-169) regions in isolation in addition to the full-length protein. Further, using a series of circular dichroism spectroscopic experiments, we validate the cytosolic region as an intrinsically disordered protein region. The microsecond-long all atoms molecular dynamics and replica-exchange simulations complement the experimental observations. Furthermore, we have also studied the NS4B proteins C-terminal regions of four other flaviviruses viz. DENV2, JEV, WNV, and YFV through microsecond simulations to characterize their behaviour in presence and absence of lipid membranes. There are significant differences observed in the conformations of other flavivirus NS4B C-terminal regions in comparison to ZIKV NS4B. Lastly, we have proposed a ZIKV NS4B protein model illustrating its putative topology consisting of various membrane-spanning and non-membranous regions.

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.

Smartphone multiplex microcapillary diagnostics using Cygnus: Development and evaluation of rapid serotype-specific NS1 detection with dengue patient samples

Laboratory diagnosis of dengue virus (DENV) infection including DENV serotyping requires skilled labor and well-equipped settings. DENV NS1 lateral flow rapid test (LFT) provides simplicity but lacks ability to identify serotype. A simple, economical, point-of-care device for serotyping is still needed. We present a gravity driven, smartphone compatible, microfluidic device using microcapillary film (MCF) to perform multiplex serotype-specific immunoassay detection of dengue virus NS1. A novel device-termed Cygnus-with a stackable design allows analysis of 1 to 12 samples in parallel in 40 minutes. A sandwich enzyme immunoassay was developed to specifically detect NS1 of all four DENV serotypes in one 60-μl plasma sample. This test aims to bridge the gap between rapid LFT and laboratory microplate ELISAs in terms of sensitivity, usability, accessibility and speed. The Cygnus NS1 assay was evaluated with retrospective undiluted plasma samples from 205 DENV infected patients alongside 50 febrile illness negative controls. Against the gold standard RT-PCR, clinical sensitivity for Cygnus was 82% in overall (with 78, 78, 80 and 76% for DENV1-4, respectively), comparable to an in-house serotyping NS1 microplate ELISA (82% vs 83%) but superior to commercial NS1-LFT (82% vs 74%). Specificity of the Cygnus device was 86%, lower than that of NS1-microplate ELISA and NS1-LFT (100% and 98%, respectively). For Cygnus positive samples, identification of DENV serotypes DENV2-4 matched those by RT-PCR by 100%, but for DENV1 capillaries false positives were seen, suggesting an improved DENV1 capture antibody is needed to increase specificity. Overall performance of Cygnus showed substantial agreement to NS1-microplate ELISA (κ = 0.68, 95%CI 0.58-0.77) and NS1-LFT (κ = 0.71, 95%CI 0.63-0.80). Although further refinement for DENV-1 NS1 detection is needed, the advantages of multiplexing and rapid processing time, this Cygnus device could deliver point-of-care NS1 antigen testing including serotyping for timely DENV diagnosis for epidemic surveillance and outbreak prediction.

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.

Dengue virus: epidemiology, biology, and disease aetiology

Dengue is a vector-borne viral disease caused by the flavivirus dengue virus (DENV). Approximately 400 million cases and 22 000 deaths occur due to dengue worldwide each year. It has been reported in more than 100 countries in tropical and subtropical regions. A positive-stranded enveloped RNA virus (DENV) is principally transmitted by Aedes mosquitoes. It has four antigenically distinct serotypes, DENV-1 to DENV-4, with different genotypes and three structural proteins and seven non-structural proteins. Clinical symptoms of dengue range from mild fever to severe dengue hemorrhagic fever (DHF) or dengue shock syndrome (DSS), with thrombocytopenia, leucopenia, and increased vascular permeability. Although primary infection causes activation of immune responses against DENV serotypes, the severity of the disease is enhanced via heterotypic infection by various serotypes as well as antibody-dependent enhancement (ADE). The first licensed DENV vaccine was tetravalent CYD Denvaxia, but it has not been approved in all countries. The lack of a suitable animal model, a proper mechanistic study in pathogenesis, and ADE are the main hindrances in vaccine development. This review summarizes the current knowledge on DENV epidemiology, biology, and disease aetiology in the context of prevention and protection from dengue virus disease.

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.

Bioinformatics-based Identification of Proteins Expressed by Arthropod- borne Viruses Transmitted by Aedes Aegypti Mosquito

Background:

The female Aedes aegypti mosquito is a vector of several arthropod-borne viruses, such as Mayaro, Dengue, Chikungunya, Yellow Fever, and Zika. These viruses cause the death of at least 600000 people a year and temporarily disable several million more around the world. Up to date, there are no effective prophylactic measures that would prevent the contact and bite of this arthropod and, therefore, its consequential contagion.

Objective:

The objective of the present study was to search for the regularities of the proteins expressed by these five viruses, at residues level, and obtain a “bioinformatic fingerprint” to select them.

Methods:

We used two bioinformatic systems, our in-house bioinformatic system named Polarity Index Method® (PIM®) supported at residues level, and the commonly used algorithm for the prediction of intrinsic disorder predisposition, PONDR® FIT. We applied both programs to the 29 proteins that express the five groups of arboviruses studied, and we calculated for each of them their Polarity Index Method® profile and their intrinsic disorder predisposition. This information was then compared with analogous information for other protein groups, such as proteins from bacteria, fungi, viruses, and cell-penetrating peptides from the UniProt database, and a set of intrinsically disordered proteins. Once the “fingerprint” of each group of arboviruses was obtained, these “fingerprints” were searched among the 559228 “reviewed” proteins from the UniProt database.

Results:

In total, 1736 proteins were identified from the 559228 “reviewed” proteins from the UniProt database, with similar “PIM® profile” to the 29 mutated proteins that express the five groups of arboviruses.

Conclusion:

We propose that the “PIM® profile” of characterization of proteins might be useful for the identification of proteins expressed by arthropod-borne viruses transmitted by Aedes aegypti mosquito.

Drugs, host proteins and viral proteins: how their promiscuities shape antiviral design

The reciprocal nature of drug specificity and target specificity implies that the same is true for their respective promiscuities. Protein promiscuity has two broadly different types of footprint in drug design. The first is relaxed specificity of binding sites for substrates, inhibitors, effectors or cofactors. The second involves protein-protein interactions of regulatory processes such as signal transduction and transcription, and here protein intrinsic disorder plays an important role. Both viruses and host cells exploit intrinsic disorder for their survival, as do the design and discovery programs for antivirals. Drug action, strictly speaking, always relies upon promiscuous activity, with drug promiscuity enlarging its scope. Drug repurposing searches for additional promiscuity on the part of both the drug and the target in the host. Understanding the subtle nuances of these promiscuities is critical in the design of novel and more effective antivirals.

Small molecule inhibitors possibly targeting the rearrangement of Zika virus envelope protein

The recurrent public health threat imposed by Zika Virus (ZIKV) in various geographical areas necessitates the immediate development of antiviral compounds or vaccines. Flaviviral Envelope (E) proteins are essential for host-cell recognition and virion entry. Consequently, they represent an important target for antiviral therapy, with the aim of preventing viral spread during early stages of infection. Due to conformational rearrangement during entry, flavivirus E proteins present several alternative conformations as potential antiviral targets - for blocking entry or virus-host membrane fusion. We previously identified a conserved hydrophobic region, between DI/DIII of ZIKV E protein, with potential to act as an antiviral target. Here, we screened commercially available antiviral compound libraries against ZIKV E protein, using a structure-based drug discovery approach. The antiviral efficacy of the top ten screened compounds were experimentally validated for inhibition of ZIKV replication in Vero Cells. Compound F1065-0358 was observed to inhibit ZIKV replication with an IC50 of 14.0 μM. Ligand-protein complex molecular dynamic simulations confirmed the stability of ligand binding up to 100 ns. Together, results from this study indicate that F1065-0358 functions as a ZIKV virus inhibitor by interfering E protein conformational rearrangement. Furthermore, given that F1065-0358 interacts with highly conserved residues of E protein, this raises the potential for its efficacy against other pathogenic flaviviruses.

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.

Intrinsically disordered proteins of viruses: Involvement in the mechanism of cell regulation and pathogenesis

Intrinsically disordered proteins (IDPs) possess the property of inherent flexibility and can be distinguished from other proteins in terms of lack of any fixed structure. Such dynamic behavior of IDPs earned the name "Dancing Proteins." The exploration of these dancing proteins in viruses has just started and crucial details such as correlation of rapid evolution, high rate of mutation and accumulation of disordered contents in viral proteome at least understood partially. In order to gain a complete understanding of this correlation, there is a need to decipher the complexity of viral mediated cell hijacking and pathogenesis in the host organism. Further there is necessity to identify the specific patterns within viral and host IDPs such as aggregation; Molecular recognition features (MoRFs) and their association to virulence, host range and rate of evolution of viruses in order to tackle the viral-mediated diseases. The current book chapter summarizes the aforementioned details and suggests the novel opportunities for further research of IDPs senses in viruses.

Intrinsically disordered protein domains in flavivirus infection

Intrinsically disordered protein regions are at the core of biological processes and involved in key protein-ligand interactions. The Flavivirus proteins, of viruses of great biomedical importance such as Zika and dengue viruses, exemplify this. Several proteins of these viruses have disordered regions that are of the utmost importance for biological activity. Disordered proteins can adopt several conformations, each able to interact with and/or bind to different ligands. In fact, such interactions can help stabilize a particular fold. Moreover, by being promiscuous in the number of target molecules they can bind to, these protein regions increase the number of functions that their small proteome (10 proteins) can achieve. A folding energy waterfall better describes the protein folding landscape of these proteins. A disordered protein can be thought as rolling down the folding energy cascade, in order "to fall, fold and function". This is the case of many viral protein regions, as seen in the flaviviruses proteome. Given their small size, flaviviruses are a good model system for understanding the role of intrinsically disordered protein regions in viral function. Finally, studying these viruses disordered protein regions will certainly contribute to the development of therapeutic approaches against such promising (yet challenging) targets.

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/ .

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.

Development of peptide biosensor for the detection of dengue fever biomarker, nonstructural 1

Dengue virus (DENV) nonstructural 1 (NS1) protein is a specific and sensitive biomarker for the diagnosis of dengue. In this study, an efficient electrochemical biosensor that uses chemically modified affinity peptides was developed for the detection of dengue virus NS1. A series of amino acid-substituted synthetic peptides was rationally designed, chemically synthesized and covalently immobilized to a gold sensor surface. The sensor performance was monitored via square wave voltammetry (SWV) and electrochemical impedance spectroscopy (EIS). Potential affinity peptides specific for NS1 were chosen according to the dynamic current decrease in SWV experiments. Using circular dichroism, the molar ellipticity of peptides (DGV BP1–BP5) was determined, indicating that they had a mostly similar in random coil structure, not totally identical. Using SWV, DGV BP1 was selected as a promising recognition peptide and limit of detection for NS1 was found to be 1.49 μg/mL by the 3-sigma rule. DGV BP1 showed good specificity and stability for NS1, with low signal interference. The validation of the sensor to detect NS1 proteins was confirmed with four dengue virus culture broth (from serotype 1 to 4) as proof-of-concept. The detection performance of our sensor incorporating DGV BP1 peptides showed a statistically significant difference. These results indicate that this strategy can potentially be used to detect the dengue virus antigen, NS1, and to diagnosis dengue fever within a miniaturized portable device in point-of-care testing.

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.

Structure-based screening and validation of potential dengue virus inhibitors through classical and QM/MM affinity estimation

The recurrent outbreaks of dengue virus around the globe represent a huge challenge for governments and public health organizations. With the rapid growth and ease of transportation, dengue disease continues to spread, placing more of the world population under constant threat. Despite decades of research efforts, no effective small molecule antivirals are available against dengue virus. With the efficacy of the recently developed vaccine to be determined, there is an urgent unmet need for small molecule dengue virus treatments. In the current study, we employed state-of-the-art molecular modelling simulations to identify novel inhibitors of the dengue virus envelope protein. The binding modes of all compounds within the conserved β-OctylGlucoside (β-OG) pocket were studied using a combination of docking, molecular dynamics simulations and binding free energy calculations. Here, we describe ten new compounds that significantly reduce production of dengue virus as determined using standard cell-based virological assays. Moreover, we present a comprehensive structural analysis of the identified hits, focusing on their electrostatic and lipophilic binding energy contributions. Finally, we highlight the effect of the desolvation penalty in limiting the activity of some of these compounds. The data presented here paves the way toward rationally designing selective and potent novel inhibitors against dengue virus.

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

Genomics, proteomics and evolution of dengue virus

The genome of a pathogenic organism possesses a specific order of nucleotides that contains not only information about the synthesis and expression of proteomes, which are required for its growth and survival, but also about its evolution. Inhibition of any particular protein, which is required for the survival of that pathogenic organism, can be used as a potential therapeutic target for the development of effective drugs to treat its infections. In this review, the genomics, proteomics and evolution of dengue virus have been discussed, which will be helpful in better understanding of its origin, growth, survival and evolution, and may contribute toward development of new efficient anti-dengue drugs.

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.

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.

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.

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.

Comparative Normal Mode Analysis of the Dynamics of DENV and ZIKV Capsids

Key steps in the life cycle of a virus, such as the fusion event as the virus infects a host cell and its maturation process, relate to an intricate interplay between the structure and the dynamics of its constituent proteins, especially those that define its capsid, much akin to an envelope that protects its genomic material. We present a comprehensive, comparative analysis of such interplay for the capsids of two viruses from the flaviviridae family, Dengue (DENV) and Zika (ZIKV). We use for that purpose our own software suite, DD-NMA, which is based on normal mode analysis. We describe the elements of DD-NMA that are relevant to the analysis of large systems, such as virus capsids. In particular, we introduce our implementation of simplified elastic networks and justify their parametrization. Using DD-NMA, we illustrate the importance of packing interactions within the virus capsids on the dynamics of the E proteins of DENV and ZIKV. We identify differences between the computed atomic fluctuations of the E proteins in DENV and ZIKV and relate those differences to changes observed in their high resolution structures. We conclude with a discussion on additional analyses that are needed to fully characterize the dynamics of the two viruses.