BETAWRAP: successful prediction of parallel beta -helices from primary sequence reveals an association with many microbial pathogens

Structural insight into the catalytic mechanism of the bifunctional enzyme l-fucokinase/GDP-fucose pyrophosphorylase

The bifunctional l-fucokinase/GDP-β-l-fucose pyrophosphorylase (FKP) from Bacteroides fragilis catalyzes the conversion from l-fucose to GDP-β-l-fucose. The reaction product, representing the activated form of l-fucose, is used by all l-fucosyltransferases to incorporate l-fucose. Herein, we report the first X-ray crystal structures of FKP in complex with substrate-product, leading to the dissection of both activity domains and corresponding catalytic mechanisms. The full-length FKP (FKP-FL, 949 amino acids) exists as a tetramer in solution, but the individually prepared N-terminal domain (FKP-NTD corresponding to the sequence 1-496, also containing a SUMO tag) and C-terminal domain (FKP-CTD, the sequence 519-949) form a monomer and a dimer, respectively. FKP-NTD has a single α/β domain and a β-helix-containing domain, whereas FKP-CTD folds into two α/β domains and the linker comprises three α-helices. The β-l-fucose-1-phosphate (fucose-1-P) and GTP bound separately to the active sites of fucokinase (located at FKP-CTD) and pyrophosphorylase (FKP-NTD), and a third nucleotide-binding site is adjacent to the β-helix (also in FKP-NTD). Furthermore, Asp762 was proposed to serve as the general base in the reaction of fucokinase, to deprotonate the C1-OH of fucose in the nucleophilic attack to γ-phosphate of ATP, resulting in the formation of fucose-1-P. At the same time, Arg592 and magnesium ion stabilize the developing negative charge in the leaving group (ADP). Subsequently, in the pyrophosphorylase-catalyzed reaction, the Lys187 side chain facilitates the nucleophilic attack of fucose-1-P toward GTP, leading to the formation of GDP-fucose.

Recent Advances in Computational Prediction of Secondary and Supersecondary Structures from Protein Sequences

The secondary structures (SSs) and supersecondary structures (SSSs) underlie the three-dimensional structure of proteins. Prediction of the SSs and SSSs from protein sequences enjoys high levels of use and finds numerous applications in the development of a broad range of other bioinformatics tools. Numerous sequence-based predictors of SS and SSS were developed and published in recent years. We survey and analyze 45 SS predictors that were released since 2018, focusing on their inputs, predictive models, scope of their prediction, and availability. We also review 32 sequence-based SSS predictors, which primarily focus on predicting coiled coils and beta-hairpins and which include five methods that were published since 2018. Substantial majority of these predictive tools rely on machine learning models, including a variety of deep neural network architectures. They also frequently use evolutionary sequence profiles. We discuss details of several modern SS and SSS predictors that are currently available to the users and which were published in higher impact venues.

Identification of potential antigenic proteins and epitopes for the development of a monkeypox virus vaccine: an in silico approach

Virus assembly, budding, or surface proteins play important roles such as viral attachment to cells, fusion, and entry into cells. The present study aimed to identify potential antigenic proteins and epitopes that could be used to develop a vaccine or diagnostic assay against the Monkeypox virus (MPXV) which may cause a potential epidemic. To do this, 39 MPXV proteins (including assembly, budding, and surface proteins) were analyzed using an in silico approach. Of these 39 proteins, the F5L virus protein was found to be the best vaccine candidate due to its signal peptide properties, negative GRAVY value, low transmembrane helix content, moderate aliphatic index, large molecular weight, long-estimated half-life, beta wrap motifs, and being stable, soluble, and containing non-allergic features. Moreover, the F5L protein exhibited alpha-helical secondary structures, making it a potential "structural antigen" recognized by antibodies. The other viral protein candidates were A9 and A43, but A9 lacked beta wrap motifs, while A43 had a positive GRAVY value and was insoluble. These two proteins were not as suitable candidates as the F5L protein. The KRVNISLTCL epitope from the F5L protein demonstrated the highest antigen score (2.4684) for MHC-I, while the GRFGYVPYVGYKCI epitope from the A9 protein exhibited the highest antigenicity (1.754) for MHC-II. Both epitopes met the criteria for high antigenicity, non-toxicity, solubility, non-allergenicity, and the presence of cleavage sites. Molecular docking and dynamics (MD) simulations further validated their potential, revealing stable and energetically favorable interactions with MHC molecules. The immunogenicity assessment showed that GRFGYVPYVGYKCI could strongly induce immune responses through both IFN-γ and IL-4 pathways, suggesting its capacity to provoke a balanced Th1 and Th2 response. In contrast, KRVNISLTCL exhibited limited immunostimulatory potential. Overall, these findings lay the groundwork for future vaccine development, indicating that F5L, particularly the GRFGYVPYVGYKCI epitope, may serve as an effective candidate for peptide-based vaccine design against MPXV.

Computational identification of monkeypox virus epitopes to generate a novel vaccine antigen against Mpox

Monkeypox virus (MPXV) belonging to poxviridae family causes chronic viral disease in various mammals including human and monkeys. Conventional vaccines developed against smallpox of poxviridae, are not specific against Mpox. Also, they can cause various side effects after vaccination. In this study, we aimed to analyze the A17L, A28L, A37R, A43R, E8L, H3L, B6R, and M1R structural proteins of MPXV and identify epitopes in them which can be used to generate vaccine antigens. Among the proteins analyzed, the M1R protein was predicted to be more appropriate for use in vaccine research due to its high antigenicity value and other physicochemical features. Also, A17L, B6R and E8L had high antigenicity values. E8L protein was more conserved while the A37R, A43R, and B6R proteins had signal peptides. Although a total of eight B cell epitopes were predicted in all proteins analyzed, CNGETK epitope belonging to B6R protein had the highest antigenicity value (1.7083), as well as was non-allergenic, non-toxic, and soluble. Based on T cell epitope analyses performed on all proteins, fourteen MHC-I/II epitopes were predicted that are antigenic, non-allergenic and non-toxic, as well as soluble. Among them, MHC-I related-HEIYDRNVGF epitope in A28L protein had the highest antigenicity value (1.6650) and MHC-II related-IGNIKIVQIDIRDIK epitope in A37R protein had the highest antigenicity value (2.0280). In conclusion, eight structural proteins of MPXV were successfully analyzed and 22 important epitopes were identified that could serve as vaccine antigens or in serological studies to develop diagnostic tools.

Structural and functional insights from the sequences and complex domain architecture of adhesin-like proteins from Methanobrevibacter smithii and Methanosphaera stadtmanae

Methanogenic archaea, or methanogens, are crucial in guts and rumens, consuming hydrogen, carbon dioxide, and other fermentation products. While their molecular interactions with other microorganisms are not fully understood, genomic sequences provide information. The first genome sequences of human gut methanogens, Methanosphaera stadtmanae and Methanobrevibacter smithii, revealed genes encoding adhesin-like proteins (ALPs). These proteins were also found in other gut and rumen methanogens, but their characteristics and functions remain largely unknown. This study analyzes the ALP repertoire of M. stadtmanae and M. smithii using AI-guided protein structure predictions of unique ALP domains. Both genomes encode more than 40 ALPs each, comprising over 10% of their genomes. ALPs contain repetitive sequences, many of which are unmatched in protein domain databases. We present unique sequence signatures of conserved ABD repeats in ALPs and propose a classification based on domain architecture. Our study offers insights into ALP features and how methanogens may interact with other microorganisms.

Sequence, structure prediction, and epitope analysis of the polymorphic membrane protein family in Chlamydia trachomatis

The polymorphic membrane proteins (Pmps) are a family of autotransporters that play an important role in infection, adhesion and immunity in Chlamydia trachomatis. Here we show that the characteristic GGA(I,L,V) and FxxN tetrapeptide repeats fit into a larger repeat sequence, which correspond to the coils of a large beta-helical domain in high quality structure predictions. Analysis of the protein using structure prediction algorithms provided novel insight to the chlamydial Pmp family of proteins. While the tetrapeptide motifs themselves are predicted to play a structural role in folding and close stacking of the beta-helical backbone of the passenger domain, we found many of the interesting features of Pmps are localized to the side loops jutting out from the beta helix including protease cleavage, host cell adhesion, and B-cell epitopes; while T-cell epitopes are predominantly found in the beta-helix itself. This analysis more accurately defines the Pmp family of Chlamydia and may better inform rational vaccine design and functional studies.

In silico discovery of diagnostic/vaccine candidate antigenic epitopes and a multi-epitope peptide vaccine (NaeVac) design for the brain-eating amoeba Naegleria fowleri causing human meningitis

Naegleria fowleri, the brain-eating amoeba, is a free-living amoeboflagellate with three different life cycles (trophozoite, flagellated, and cyst) that lives in a variety of habitats around the world including warm freshwater and soil. It causes a disease called naegleriasis leading meningitis and primary amoebic meningoencephalitis (PAM) in humans. N. fowleri is transmitted through contaminated water sources such as insufficiently chlorinated swimming pool water or contaminated tap water, and swimmers are at risk. N. fowleri is found all over the world, and most infections were reported in both developed and developing countries with high mortality rates and serious clinical findings. Until now, there is no FDA approved vaccine and early diagnosis is urgent against this pathogen. In this study, by analyzing the N. fowleri vaccine candidate proteins (Mp2CL5, Nfa1, Nf314, proNP-A and proNP-B), it was aimed to discover diagnostic/vaccine candidate epitopes and to design a multi-epitope peptide vaccine against this pathogen. After the in silico evaluation, three prominent diagnostic/vaccine candidate epitopes (EAKDSK, LLPHIRILVY, and FYAKLLPHIRILVYS) with the highest antigenicities were discovered and a potentially highly immunogenic/antigenic multi-epitope peptide vaccine (NaeVac) was designed against the brain-eating amoeba N. fowleri causing human meningitis.

Molecular characterization of Anaplasma ovis Msp4 protein in strains isolated from ticks in Turkey: A multi-epitope synthetic vaccine antigen design against Anaplasma ovis using immunoinformatic tools

Tick-borne pathogens increasingly threaten animal and human health as well as cause great economic loss in the livestock industry. Among these pathogens, Anaplasma ovis causing a decrease in meat and milk yield is frequently detected in sheep in many countries including Turkey. This study aimed to reveal potential vaccine candidate epitopes in Msp4 protein using sequence data from Anaplasma ovis isolates and then to design a multi-epitope protein to be used in vaccine formulations against Anaplasma ovis. For this purpose, Msp4 gene was sequenced from Anaplasma ovis isolates (n:6) detected in ticks collected from sheep in Turkey and the sequence data was compared with previous sequences from different countries in order to detect the variations of Msp4 gene/protein. Potential vaccine candidate and diagnostic epitopes were predicted using various immunoinformatics tools. Among the discovered vaccine candidate epitopes, antigenic and conserved were selected, and then a multi-epitope protein was designed. The designed vaccine protein was tested for the assessment of TLR-2, IgG, and IFN-g responses by molecular docking and immune simulation analyses. Among the discovered epitopes, EVASEGSGVM and YQFTPEISLV epitopes with properties of high antigenicity, non-allergenicity, and non-toxicity were proposed to be used for Anaplasma ovis in further serodiagnostic and vaccine studies.

In silico discovery of epitopes of gag and env proteins for the development of a multi-epitope vaccine candidate against Maedi Visna Virus using reverse vaccinology approach

Maedi Visna Virus (MVV) causes a chronic viral disease in sheep. Since there is no specific therapeutic drug that targets MVV, development of a vaccine against the MVV is inevitable. This study aimed to analyze the gag and env proteins as vaccine candidate proteins and to identify epitopes in these proteins. In addition, it was aimed to construct a multi-epitope vaccine candidate. According to the obtained results, the gag protein was detected to be more conserved and had a higher antigenicity value. Also, the number of alpha helix in the secondary structure was higher and transmembrane helices were not detected. Although many B cell and MHC-I/II epitopes were predicted, only 19 of them were detected to have the properties of antigenic, non-allergenic, non-toxic, soluble, and non-hemolytic. Of these epitopes, five were remarkable due to having the highest antigenicity value. However, the final multi-epitope vaccine was constructed with 19 epitopes. A strong affinity was shown between the final multi-epitope vaccine and TLR-2/4. In conclusion, the gag protein was a better antigen. However, both proteins had epitopes with high antigenicity value. Also, the final multi-epitope vaccine construct had a potential to be used as a peptide vaccine due to its immuno-informatics results.

Klebsiella phage KP34gp57 capsular depolymerase structure and function: from a serendipitous finding to the design of active mini-enzymes against K. pneumoniae

IMPORTANCE

In this work, we determined the structure of Klebsiella phage KP34p57 capsular depolymerase and dissected the role of individual domains in trimerization and functional activity. The crystal structure serendipitously revealed that the enzyme can exist in a monomeric state once deprived of its C-terminal domain. Based on the crystal structure and site-directed mutagenesis, we localized the key catalytic residues in an intra-subunit deep groove. Consistently, we show that C-terminally trimmed KP34p57 variants are monomeric, stable, and fully active. The elaboration of monomeric, fully active phage depolymerases is innovative in the field, as no previous example exists. Indeed, mini phage depolymerases can be combined in chimeric enzymes to extend their activity ranges, allowing their use against multiple serotypes.

CBD resistant Salmonella strains are susceptible to epsilon 34 phage tailspike protein

The rise of antimicrobial resistance is a global public health crisis that threatens the effective control and prevention of infections. Due to the emergence of pandrug-resistant bacteria, most antibiotics have lost their efficacy. Bacteriophages or their components are known to target bacterial cell walls, cell membranes, and lipopolysaccharides (LPS) and hydrolyze them. Bacteriophages being the natural predators of pathogenic bacteria, are inevitably categorized as "human friends", thus fulfilling the adage that "the enemy of my enemy is my friend". Leveraging on their lethal capabilities against pathogenic bacteria, researchers are searching for more ways to overcome the current antibiotic resistance challenge. In this study, we expressed and purified epsilon 34 phage tailspike protein (E34 TSP) from the E34 TSP gene, then assessed the ability of this bacteriophage protein in the killing of two CBD-resistant strains of Salmonella spp. We also assessed the ability of the tailspike protein to cause bacteria membrane disruption, and dehydrogenase depletion. We observed that the combined treatment of CBD-resistant strains of Salmonella with CBD and E34 TSP showed poor killing ability whereas the monotreatment with E34 TSP showed considerably higher killing efficiency. This study demonstrates that the inhibition of the bacteria by E34 TSP was due in part to membrane disruption, and dehydrogenase inactivation by the protein. The results of this work provides an interesting background to highlight the crucial role phage protein such as E34 TSP could play in pathogenic bacterial control.

Pantoea stewartii WceF is a glycan biofilm-modifying enzyme with a bacteriophage tailspike-like fold

Pathogenic microorganisms often reside in glycan-based biofilms. Concentration and chain length distribution of these mostly anionic exopolysaccharides (EPS) determine the overall biophysical properties of a biofilm and result in a highly viscous environment. Bacterial communities regulate this biofilm state via intracellular small-molecule signaling to initiate EPS synthesis. Reorganization or degradation of this glycan matrix, however, requires the action of extracellular glycosidases. So far, these were mainly described for bacteriophages that must degrade biofilms for gaining access to host bacteria. The plant pathogen Pantoea stewartii (P. stewartii) encodes the protein WceF within its EPS synthesis cluster. WceF has homologs in various biofilm forming plant pathogens of the Erwinia family. In this work, we show that WceF is a glycosidase active on stewartan, the main P. stewartii EPS biofilm component. WceF has remarkable structural similarity with bacteriophage tailspike proteins (TSPs). Crystal structure analysis showed a native trimer of right-handed parallel β-helices. Despite its similar fold, WceF lacks the high stability found in bacteriophage TSPs. WceF is a stewartan hydrolase and produces oligosaccharides, corresponding to single stewartan repeat units. However, compared with a stewartan-specific glycan hydrolase of bacteriophage origin, WceF showed lectin-like autoagglutination with stewartan, resulting in notably slower EPS cleavage velocities. This emphasizes that the bacterial enzyme WceF has a role in P. stewartii biofilm glycan matrix reorganization clearly different from that of a bacteriophage exopolysaccharide depolymerase.

In silico discovery of antigenic proteins and epitopes of SARS-CoV-2 for the development of a vaccine or a diagnostic approach for COVID-19

In the genome of SARS-CoV-2, the 5′-terminus encodes a polyprotein, which is further cleaved into 15 non-structural proteins whereas the 3′ terminus encodes four structural proteins and eight accessory proteins. Among these 27 proteins, the present study aimed to discover likely antigenic proteins and epitopes to be used for the development of a vaccine or serodiagnostic assay using an in silico approach. For this purpose, after the full genome analysis of SARS-CoV-2 Wuhan isolate and variant proteins that are detected frequently, surface proteins including spike, envelope, and membrane proteins as well as proteins with signal peptide were determined as probable vaccine candidates whereas the remaining were considered as possible antigens to be used during the development of serodiagnostic assays. According to results obtained, among 27 proteins, 26 of them were predicted as probable antigen. In 26 proteins, spike protein was selected as the best vaccine candidate because of having a signal peptide, negative GRAVY value, one transmembrane helix, moderate aliphatic index, a big molecular weight, a long-estimated half-life, beta wrap motifs as well as having stable, soluble and non-allergic features. In addition, orf7a, orf8, and nsp-10 proteins with signal peptide were considered as potential vaccine candidates. Nucleocapsid protein and a highly antigenic GGDGKMKD epitope were identified as ideal antigens to be used in the development of serodiagnostic assays. Moreover, considering MHC-I alleles, highly antigenic KLNDLCFTNV and ITLCFTLKRK epitopes can be used to develop an epitope-based peptide vaccine.

Origin and Evolution of Studiervirinae Bacteriophages Infecting Pectobacterium: Horizontal Transfer Assists Adaptation to New Niches

Black leg and soft rot are devastating diseases causing up to 50% loss of potential potato yield. The search for, and characterization of, bacterial viruses (bacteriophages) suitable for the control of these diseases is currently a sought-after task for agricultural microbiology. Isolated lytic Pectobacterium bacteriophages Q19, PP47 and PP81 possess a similar broad host range but differ in their genomic properties. The genomic features of characterized phages have been described and compared to other Studiervirinae bacteriophages. Thorough phylogenetic analysis has clarified the taxonomy of the phages and their positioning relative to other genera of the Autographiviridae family. Pectobacterium phage Q19 seems to represent a new genus not described previously. The genomes of the phages are generally similar to the genome of phage T7 of the Teseptimavirus genus but possess a number of specific features. Examination of the structure of the genes and proteins of the phages, including the tail spike protein, underlines the important role of horizontal gene exchange in the evolution of these phages, assisting their adaptation to Pectobacterium hosts. The results provide the basis for the development of bacteriophage-based biocontrol of potato soft rot as an alternative to the use of antibiotics.

Structural and Functional Studies of a Klebsiella Phage Capsule Depolymerase Tailspike: Mechanistic Insights into Capsular Degradation

Capsule polysaccharide is a major virulence factor of Klebsiella pneumoniae, a nosocomial pathogen associated with a wide range of infections. It protects bacteria from harsh environmental conditions, immune system response, and phage infection. To access cell wall-located receptors, some phages possess tailspike depolymerases that degrade the capsular polysaccharide. Here, we present the crystal structure of a tailspike against Klebsiella, KP32gp38, whose primary sequence shares no similarity to other proteins of known structure. In the trimeric structure of KP32gp38, each chain contains a flexible N-terminal domain, a right-handed parallel β helix domain and two β sandwiches with carbohydrate binding features. The crystal structure and activity assays allowed us to locate the catalytic site. Also, our data provide experimental evidence of a branching architecture of depolymerases in KP32 Klebsiella viruses, as KP32gp38 displays nanomolar affinity to another depolymerase from the same phage, KP32gp37. Results provide a structural framework for enzyme engineering to produce serotype-broad-active enzyme complexes against K. pneumoniae.

Computational Prediction of Secondary and Supersecondary Structures from Protein Sequences

Many new methods for the sequence-based prediction of the secondary and supersecondary structures have been developed over the last several years. These and older sequence-based predictors are widely applied for the characterization and prediction of protein structure and function. These efforts have produced countless accurate predictors, many of which rely on state-of-the-art machine learning models and evolutionary information generated from multiple sequence alignments. We describe and motivate both types of predictions. We introduce concepts related to the annotation and computational prediction of the three-state and eight-state secondary structure as well as several types of supersecondary structures, such as β hairpins, coiled coils, and α-turn-α motifs. We review 34 predictors focusing on recent tools and provide detailed information for a selected set of 14 secondary structure and 3 supersecondary structure predictors. We conclude with several practical notes for the end users of these predictive methods.

Target highlights from the first post-PSI CASP experiment (CASP12, May-August 2016)

The functional and biological significance of the selected CASP12 targets are described by the authors of the structures. The crystallographers discuss the most interesting structural features of the target proteins and assess whether these features were correctly reproduced in the predictions submitted to the CASP12 experiment.

Identification of the Autochaperone Domain in the Type Va Secretion System (T5aSS): Prevalent Feature of Autotransporters with a β-Helical Passenger

Autotransporters (ATs) belong to a family of modular proteins secreted by the Type V, subtype a, secretion system (T5aSS) and considered as an important source of virulence factors in lipopolysaccharidic diderm bacteria (archetypical Gram-negative bacteria). While exported by the Sec pathway, the ATs are further secreted across the outer membrane via their own C-terminal translocator forming a β-barrel, through which the rest of the protein, namely the passenger, can pass. In several ATs, an autochaperone domain (AC) present at the C-terminal region of the passenger and upstream of the translocator was demonstrated as strictly required for proper secretion and folding. However, considering it was functionally characterised and identified only in a handful of ATs, wariness recently fells on the commonality and conservation of this structural element in the T5aSS. To circumvent the issue of sequence divergence and taking advantage of the resolved three-dimensional structure of some ACs, identification of this domain was performed following structural alignment among all AT passengers experimentally resolved by crystallography before searching in a dataset of 1523 ATs. While demonstrating that the AC is indeed a conserved structure found in numerous ATs, phylogenetic analysis further revealed a distribution into deeply rooted branches, from which emerge 20 main clusters. Sequence analysis revealed that an AC could be identified in the large majority of SAATs (self-associating ATs) but not in any LEATs (lipase/esterase ATs) nor in some PATs (protease autotransporters) and PHATs (phosphatase/hydrolase ATs). Structural analysis indicated that an AC was present in passengers exhibiting single-stranded right-handed parallel β-helix, whatever the type of β-solenoid, but not with α-helical globular fold. From this investigation, the AC of type 1 appears as a prevalent and conserved structural element exclusively associated to β-helical AT passenger and should promote further studies about the protein secretion and folding via the T5aSS, especially toward α-helical AT passengers.

Advanced In Silico Tools for Designing of Antigenic Epitope as Potential Vaccine Candidates Against Coronavirus

Vaccines are the most economical and potent substitute of available medicines to cure various bacterial and viral diseases. Earlier, killed or attenuated pathogens were employed for vaccine development. But in present era, the peptide vaccines are in much trend and are favoured over whole vaccines because of their superiority over conventional vaccines. These vaccines are either based on single proteins or on synthetic peptides including several B-cell and T-cell epitopes. However, the overall mechanism of action remains the same and works by prompting the immune system to activate the specific B-cell- and T-cell-mediated responses against the pathogen. Rino Rappuoli and others have contributed in this field by plotting the design of the most potent and fully computational approach for discovery of potential vaccine candidates which is popular as reverse vaccinology. This is quite an unambiguous advance for vaccine evolution where one begins with the genome information of the pathogen and ends up with the list of certain epitopes after application of multiple bioinformatics tools. This book chapter is an effort to bring this approach of reverse vaccinology into notice of readers using example of coronavirus.

Structure of a Reptilian Adenovirus Reveals a Phage Tailspike Fold Stabilizing a Vertebrate Virus Capsid

Although non-human adenoviruses (AdVs) might offer solutions to problems posed by human AdVs as therapeutic vectors, little is known about their basic biology. In particular, there are no structural studies on the complete virion of any AdV with a non-mammalian host. We combine mass spectrometry, cryo-electron microscopy, and protein crystallography to characterize the composition and structure of a snake AdV (SnAdV-1, Atadenovirus genus). SnAdV-1 particles contain the genus-specific proteins LH3, p32k, and LH2, a previously unrecognized structural component. Remarkably, the cementing protein LH3 has a trimeric β helix fold typical of bacteriophage host attachment proteins. The organization of minor coat proteins differs from that in human AdVs, correlating with higher thermostability in SnAdV-1. These findings add a new piece to the intriguing puzzle of virus evolution, hint at the use of cell entry pathways different from those in human AdVs, and will help development of new, thermostable SnAdV-1-based vectors.

Bacteriophage-encoded virion-associated enzymes to overcome the carbohydrate barriers during the infection process

Bacteriophages are bacterial viruses that infect the host after successful receptor recognition and adsorption to the cell surface. The irreversible adherence followed by genome material ejection into host cell cytoplasm must be preceded by the passage of diverse carbohydrate barriers such as capsule polysaccharides (CPSs), O-polysaccharide chains of lipopolysaccharide (LPS) molecules, extracellular polysaccharides (EPSs) forming biofilm matrix, and peptidoglycan (PG) layers. For that purpose, bacteriophages are equipped with various virion-associated carbohydrate active enzymes, termed polysaccharide depolymerases and lysins, that recognize, bind, and degrade the polysaccharide compounds. We discuss the existing diversity in structural locations, variable architectures, enzymatic specificities, and evolutionary aspects of polysaccharide depolymerases and virion-associated lysins (VALs) and illustrate how these aspects can correlate with the host spectrum. In addition, we present methods that can be used for activity determination and the application potential of these enzymes as antibacterials, antivirulence agents, and diagnostic tools.

Immunoinformatics as a Tool for New Antifungal Vaccines

Immunoinformatics aids in screening for vaccine candidates, which can be experimentally tested for their efficacy. This chapter describes methods to use immunoinformatics to screen fungal vaccines candidates. Surface-localized molecules called adhesins could elicit immune response and serve as efficient vaccine candidates. The screening process is patterned on two steps, namely, a First Layer screen mostly used for value addition and prioritization based on characteristics of known antigens and a Second Layer highly focussed on core immunoinformatics analysis involving the binding and interactions of the molecules of the immune system. Together they offer a comprehensive objective evaluation of vaccine candidates selection in silico for fungal pathogens.

The Chlamydia pneumoniae Adhesin Pmp21 Forms Oligomers with Adhesive Properties

Chlamydiae sp. are obligate intracellular pathogens that cause a variety of diseases in humans. The adhesion of Chlamydiae to the eukaryotic host cell is a pivotal step in pathogenesis. The adhesin family of polymorphic membrane proteins (Pmp) in Chlamydia pneumoniae consists of 21 members. Pmp21 binds to the epidermal growth factor receptor (EGFR). Pmps contain large numbers of FXXN (where X is any amino acid) and GGA(I/L/V) motifs. At least two of these motifs are crucial for adhesion by certain Pmp21 fragments. Here we describe how the two FXXN motifs in Pmp21-D (D-Wt), a domain of Pmp21, influence its self-interaction, folding, and adhesive capacities. Refolded D-Wt molecules form oligomers with high sedimentation values (8-85 S). These oligomers take the form of elongated protofibrils, which exhibit Thioflavin T fluorescence, like the amyloid protein fragment β42. A mutant version of Pmp21-D (D-Mt), with FXXN motifs replaced by SXXV, shows a markedly reduced capacity to form oligomers. Secondary-structure assays revealed that monomers of both variants exist predominantly as random coils, whereas the oligomers form predominantly β-sheets. Adhesion studies revealed that oligomers of D-Wt (D-Wt-O) mediate significantly enhanced binding to human epithelial cells relative to D-Mt-O and monomeric protein species. Moreover, D-Wt-O binds EGFR more efficiently than D-Wt monomers. Importantly, pretreatment of human cells with D-Wt-O reduces infectivity upon subsequent challenge with C. pneumoniae more effectively than all other protein species. Hence, the FXXN motif in D-Wt induces the formation of β-sheet-rich oligomeric protofibrils, which are important for adhesion to, and subsequent infection of human cells.

Structural Insights into an Oxalate-producing Serine Hydrolase with an Unusual Oxyanion Hole and Additional Lyase Activity

In Burkholderia species, the production of oxalate, an acidic molecule, is a key event for bacterial growth in the stationary phase. Oxalate plays a central role in maintaining environmental pH, which counteracts inevitable population-collapsing alkaline toxicity in amino acid-based culture medium. In the phytopathogen Burkholderia glumae, two enzymes are responsible for oxalate production. First, the enzyme oxalate biosynthetic component A (ObcA) catalyzes the formation of a tetrahedral C6-CoA adduct from the substrates acetyl-CoA and oxaloacetate. Then the ObcB enzyme liberates three products from the C6-CoA adduct: oxalate, acetoacetate, and CoA. Interestingly, these two stepwise reactions are catalyzed by a single bifunctional enzyme, Obc1, from Burkholderia thailandensis and Burkholderia pseudomallei Obc1 has an ObcA-like N-terminal domain and shows ObcB activity in its C-terminal domain despite no sequence homology with ObcB. We report the crystal structure of Obc1 in its apo and glycerol-bound form at 2.5 Å and 2.8 Å resolution, respectively. The Obc1 N-terminal domain is essentially identical both in structure and function to that of ObcA. Its C-terminal domain has an α/β hydrolase fold that has a catalytic triad for oxalate production and a novel oxyanion hole distinct from the canonical HGGG motif in other α/β hydrolases. Functional analyses through mutagenesis studies suggested that His-934 is an additional catalytic acid/base for its lyase activity and liberates two additional products, acetoacetate and CoA. These results provide structural and functional insights into bacterial oxalogenesis and an example of divergent evolution of the α/β hydrolase fold, which has both hydrolase and lyase activity.

Genome-Wide Prediction of Vaccine Candidates for Leishmania major: An Integrated Approach

Despite the wealth of information regarding genetics of the causative parasite and experimental immunology of the cutaneous leishmaniasis, there is currently no licensed vaccine against it. In the current study, a two-level data mining strategy was employed, to screen the Leishmania major genome for promising vaccine candidates. First, we screened a set of 25 potential antigens from 8312 protein coding sequences, based on presence of signal peptides, GPI anchors, and consensus antigenicity predictions. Second, we conducted a comprehensive immunogenic analysis of the 25 antigens based on epitopes predicted by NetCTL tool. Interestingly, results revealed that candidate antigen number 1 (LmjF.03.0550) had greater number of potential T cell epitopes, as compared to five well-characterized control antigens (CSP-Plasmodium falciparum, M1 and NP-Influenza A virus, core protein-Hepatitis B virus, and PSTA1-Mycobacterium tuberculosis). In order to determine an optimal set of epitopes among the highest scoring predicted epitopes, the OptiTope tool was employed for populations susceptible to cutaneous leishmaniasis. The epitope (127SLWSLLAGV) from antigen number 1, found to bind with the most prevalent allele HLA-A⁎0201 (25% frequency in Southwest Asia), was predicted as most immunogenic for all the target populations. Thus, our study reasserts the potential of genome-wide screening of pathogen antigens and epitopes, for identification of promising vaccine candidates.

Of linkers and autochaperones: an unambiguous nomenclature to identify common and uncommon themes for autotransporter secretion

Autotransporter (AT) proteins provide a diverse array of important virulence functions to Gram-negative bacterial pathogens, and have also been adapted for protein surface display applications. The 'autotransporter' moniker refers to early models that depicted these proteins facilitating their own translocation across the bacterial outer membrane. Although translocation is less autonomous than originally proposed, AT protein segments upstream of the C-terminal transmembrane β-barrel have nevertheless consistently been found to contribute to efficient translocation and/or folding of the N-terminal virulence region (the 'passenger'). However, defining the precise secretion functions of these AT regions has been complicated by the use of multiple overlapping and ambiguous terms to define AT sequence, structural, and functional features, including 'autochaperone', 'linker' and 'junction'. Moreover, the precise definitions and boundaries of these features vary among ATs and even among research groups, leading to an overall murky picture of the contributions of specific features to translocation. Here we propose a unified, unambiguous nomenclature for AT structural, functional and conserved sequence features, based on explicit criteria. Applied to 16 well-studied AT proteins, this nomenclature reveals new commonalities for translocation but also highlights that the autochaperone function is less closely associated with a conserved sequence element than previously believed.

Prediction of virulence factors using bioinformatics approaches

Virulence factors produced by a pathogen are essential for causing disease in the host. They enable the pathogen to establish itself within the host thus enhancing its potential to cause disease and in some instances underlie evasion of host defense mechanisms. Identification of these molecules, especially those of immunological interest and their use in vaccine development are attractive and are among the initial steps of reverse vaccinology. Surface localized virulence factors such as adhesins serve as excellent immunogenic candidates in this regard. In this chapter we have described the bioinformatics approaches for adhesin prediction, which include specific adhesin prediction algorithms.

All subtypes of the Pmp adhesin family are implicated in chlamydial virulence and show species-specific function

The bacterial pathogens Chlamydia trachomatis and C. pneumoniae are obligate intracellular parasites, cause a number of serious diseases, and can infect various cell types in humans. Chlamydial infections are probably initiated by binding of the bacterial outer membrane protein OmcB to host cell glycosaminoglycans (GAGs). Here, we show that all nine members of the polymorphic membrane protein (Pmp) family of C. trachomatis mediate adhesion to human epithelial and endothelial cells. Importantly, exposure of infectious particles to soluble recombinant Pmps blocks subsequent infection, thus implicating an important function of the entire protein family in the infection process. Analogous experiments with pairs of recombinant Pmps or a combination of Pmp and OmcB revealed that all Pmps probably act in an adhesion pathway that is distinct from the OmcB-GAG pathway. Finally, we provide evidence that the Pmps of C. trachomatis and C. pneumoniae exhibit species and tissue specificity. These findings argue for the involvement of C. trachomatis Pmps in the initial phase of infection and suggest that they may interact with a receptor other than the epidermal growth factor receptor recently identified for their counterparts in C. pneumoniae.

Simultaneous alignment and folding of protein sequences

Accurate comparative analysis tools for low-homology proteins remains a difficult challenge in computational biology, especially sequence alignment and consensus folding problems. We present partiFold-Align, the first algorithm for simultaneous alignment and consensus folding of unaligned protein sequences; the algorithm's complexity is polynomial in time and space. Algorithmically, partiFold-Align exploits sparsity in the set of super-secondary structure pairings and alignment candidates to achieve an effectively cubic running time for simultaneous pairwise alignment and folding. We demonstrate the efficacy of these techniques on transmembrane β-barrel proteins, an important yet difficult class of proteins with few known three-dimensional structures. Testing against structurally derived sequence alignments, partiFold-Align significantly outperforms state-of-the-art pairwise and multiple sequence alignment tools in the most difficult low-sequence homology case. It also improves secondary structure prediction where current approaches fail. Importantly, partiFold-Align requires no prior training. These general techniques are widely applicable to many more protein families (partiFold-Align is available at http://partifold.csail.mit.edu/ ).

Integrative immunoinformatics for Mycobacterial diseases in R platform

The sequencing of genomes of the pathogenic Mycobacterial species causing pulmonary and extrapulmonary tuberculosis, leprosy and other atypical mycobacterial infections, offer immense opportunities for discovering new therapeutics and identifying new vaccine candidates. Enhanced RV, which uses additional algorithms to Reverse Vaccinology (RV), has increased potential to reduce likelihood of undesirable features including allergenicity and immune cross reactivity to host. The starting point for MycobacRV database construction includes collection of known vaccine candidates and a set of predicted vaccine candidates identified from the whole genome sequences of 22 mycobacterium species and strains pathogenic to human and one non-pathogenic Mycobacterium tuberculosis H37Ra strain. These predicted vaccine candidates are the adhesins and adhesin-like proteins obtained using SPAAN at Pad > 0.6 and screening for putative extracellular or surface localization characteristics using PSORTb v.3.0 at very stringent cutoff. Subsequently, these protein sequences were analyzed through 21 publicly available algorithms to obtain Orthologs, Paralogs, BetaWrap Motifs, Transmembrane Domains, Signal Peptides, Conserved Domains, and similarity to human proteins, T cell epitopes, B cell epitopes, Discotopes and potential Allergens predictions. The Enhanced RV information was analysed in R platform through scripts following well structured decision trees to derive a set of nonredundant 233 most probable vaccine candidates. Additionally, the degree of conservation of potential epitopes across all orthologs has been obtained with reference to the M. tuberculosis H37Rv strain, the most commonly used strain in M. tuberculosis studies. Utilities for the vaccine candidate search and analysis of epitope conservation across the orthologs with reference to M. tuberculosis H37Rv strain are available in the mycobacrvR package in R platform accessible from the "Download" tab of MycobacRV webserver. MycobacRV an immunoinformatics database of known and predicted mycobacterial vaccine candidates has been developed and is freely available at http://mycobacteriarv.igib.res.in.

Sequential unfolding of beta helical protein by single-molecule atomic force microscopy

The parallel βhelix is a common fold among extracellular proteins, however its mechanical properties remain unexplored. In Gram-negative bacteria, extracellular proteins of diverse functions of the large ‘TpsA’ family all fold into long βhelices. Here, single-molecule atomic force microscopy and steered molecular dynamics simulations were combined to investigate the mechanical properties of a prototypic TpsA protein, FHA, the major adhesin of Bordetella pertussis. Strong extension forces were required to fully unfold this highly repetitive protein, and unfolding occurred along a stepwise, hierarchical process. Our analyses showed that the extremities of the βhelix unfold early, while central regions of the helix are more resistant to mechanical unfolding. In particular, a mechanically resistant subdomain conserved among TpsA proteins and critical for secretion was identified. This nucleus harbors structural elements packed against the βhelix that might contribute to stabilizing the N-terminal region of FHA. Hierarchical unfolding of the βhelix in response to a mechanical stress may maintain β-helical portions that can serve as templates for regaining the native structure after stress. The mechanical properties uncovered here might apply to many proteins with β-helical or related folds, both in prokaryotes and in eukaryotes, and play key roles in their structural integrity and functions.

Two-partner secretion: as simple as it sounds?

The two-partner secretion (TPS) pathway is a branch of type V secretion. TPS systems are dedicated to the secretion across the outer membrane of long proteins that form extended β-helices. They are composed of a 'TpsA' cargo protein and a 'TpsB' transporter, which belongs to the Omp85 superfamily. This basic design can be supplemented by additional components in some TPS systems. X-ray structures are available for the conserved TPS domain of several TpsA proteins and for one TpsB transporter. However, the molecular mechanisms of two-partner secretion remain to be deciphered, and in particular, the specific role(s) of the TPS domain and the conformational dynamics of the TpsB transporter. Deciphering the TPS pathway may reveal functional features of other transporters of the Omp85 superfamily.

The MULTICOM toolbox for protein structure prediction

Background

As genome sequencing is becoming routine in biomedical research, the total number of protein sequences is increasing exponentially, recently reaching over 108 million. However, only a tiny portion of these proteins (i.e. ~75,000 or < 0.07%) have solved tertiary structures determined by experimental techniques. The gap between protein sequence and structure continues to enlarge rapidly as the throughput of genome sequencing techniques is much higher than that of protein structure determination techniques. Computational software tools for predicting protein structure and structural features from protein sequences are crucial to make use of this vast repository of protein resources.

Results

To meet the need, we have developed a comprehensive MULTICOM toolbox consisting of a set of protein structure and structural feature prediction tools. These tools include secondary structure prediction, solvent accessibility prediction, disorder region prediction, domain boundary prediction, contact map prediction, disulfide bond prediction, beta-sheet topology prediction, fold recognition, multiple template combination and alignment, template-based tertiary structure modeling, protein model quality assessment, and mutation stability prediction.

Conclusions

These tools have been rigorously tested by many users in the last several years and/or during the last three rounds of the Critical Assessment of Techniques for Protein Structure Prediction (CASP7-9) from 2006 to 2010, achieving state-of-the-art or near performance. In order to facilitate bioinformatics research and technological development in the field, we have made the MULTICOM toolbox freely available as web services and/or software packages for academic use and scientific research. It is available at http://sysbio.rnet.missouri.edu/multicom_toolbox/.

SMURFLite: combining simplified Markov random fields with simulated evolution improves remote homology detection for beta-structural proteins into the twilight zone

Motivation: One of the most successful methods to date for recognizing protein sequences that are evolutionarily related has been profile hidden Markov models (HMMs). However, these models do not capture pairwise statistical preferences of residues that are hydrogen bonded in beta sheets. These dependencies have been partially captured in the HMM setting by simulated evolution in the training phase and can be fully captured by Markov random fields (MRFs). However, the MRFs can be computationally prohibitive when beta strands are interleaved in complex topologies. We introduce SMURFLite, a method that combines both simplified MRFs and simulated evolution to substantially improve remote homology detection for beta structures. Unlike previous MRF-based methods, SMURFLite is computationally feasible on any beta-structural motif.

Results: We test SMURFLite on all propeller and barrel folds in the mainly-beta class of the SCOP hierarchy in stringent cross-validation experiments. We show a mean 26% (median 16%) improvement in area under curve (AUC) for beta-structural motif recognition as compared with HMMER (a well-known HMM method) and a mean 33% (median 19%) improvement as compared with RAPTOR (a well-known threading method) and even a mean 18% (median 10%) improvement in AUC over HHPred (a profile–profile HMM method), despite HHpred's use of extensive additional training data. We demonstrate SMURFLite's ability to scale to whole genomes by running a SMURFLite library of 207 beta-structural SCOP superfamilies against the entire genome of Thermotoga maritima, and make over a 100 new fold predictions.

Availability and implementaion: A webserver that runs SMURFLite is available at: http://smurf.cs.tufts.edu/smurflite/

Contact:lenore.cowen@tufts.edu; bab@mit.edu

Computer Aided Knowledge Discovery in Biomedicine

This chapter provides a perspective on 3 important collaborative areas in systems biology research. These areas represent biological problems of clinical significance. The first area deals with macromolecular crystallization, which is a crucial step in protein structure determination. The second area deals with proteomic biomarker discovery from high-throughput mass spectral technologies; while the third area is protein structure prediction and complex fold recognition from sequence and prior knowledge of structure properties. For each area, successful case studies are revisited from the perspective of computer- aided knowledge discovery using machine learning and statistical methods. Information about protein sequence, structure, and function is slowly accumulating in standardized forms within databases. Methods are needed to maximize the use of this prior information for prediction and analysis purposes. This chapter provides insights into such methods by which available information in existing databases can be processed and combined with systems biology expertise to expedite biomedical discoveries.

Long noncontractile tail machines of bacteriophages

In this chapter, we describe the structure, assembly, function, and evolution of the long, noncontractile tail of the siphophages, which comprise ∼60% of the phages on earth. We place -particular emphasis on features that are conserved among all siphophages, and trace evolutionary connections between these phages and myophages, which possess long contractile tails. The large number of high-resolution structures of tail proteins solved recently coupled to studies of tail-related complexes by electron microscopy have provided many new insights in this area. In addition, the availability of thousands of phage and prophage genome sequences has allowed the delineation of several large families of tail proteins that were previously unrecognized. We also summarize current knowledge pertaining to the mechanisms by which siphophage tails recognize the bacterial cell surface and mediate DNA injection through the cell envelope. We show that phages infecting Gram-positive and Gram-negative bacteria possess distinct families of proteins at their tail tips that are involved in this process. Finally, we speculate on the evolutionary advantages provided by long phage tails.

Computational prediction of secondary and supersecondary structures

The sequence-based prediction of the secondary and supersecondary structures enjoys strong interest and finds applications in numerous areas related to the characterization and prediction of protein structure and function. Substantial efforts in these areas over the last three decades resulted in the development of accurate predictors, which take advantage of modern machine learning models and availability of evolutionary information extracted from multiple sequence alignment. In this chapter, we first introduce and motivate both prediction areas and introduce basic concepts related to the annotation and prediction of the secondary and supersecondary structures, focusing on the β hairpin, coiled coil, and α-turn-α motifs. Next, we overview state-of-the-art prediction methods, and we provide details for 12 modern secondary structure predictors and 4 representative supersecondary structure predictors. Finally, we provide several practical notes for the users of these prediction tools.

STITCHER: Dynamic assembly of likely amyloid and prion β-structures from secondary structure predictions

The supersecondary structure of amyloids and prions, proteins of intense clinical and biological interest, are difficult to determine by standard experimental or computational means. In addition, significant conformational heterogeneity is known or suspected to exist in many amyloid fibrils. Previous work has demonstrated that probability-based prediction of discrete β-strand pairs can offer insight into these structures. Here, we devise a system of energetic rules that can be used to dynamically assemble these discrete β-strand pairs into complete amyloid β-structures. The STITCHER algorithm progressively 'stitches' strand-pairs into full β-sheets based on a novel free-energy model, incorporating experimentally observed amino-acid side-chain stacking contributions, entropic estimates, and steric restrictions for amyloidal parallel β-sheet construction. A dynamic program computes the top 50 structures and returns both the highest scoring structure and a consensus structure taken by polling this list for common discrete elements. Putative structural heterogeneity can be inferred from sequence regions that compose poorly. Predictions show agreement with experimental models of Alzheimer's amyloid beta peptide and the Podospora anserina Het-s prion. Predictions of the HET-s homolog HET-S also reflect experimental observations of poor amyloid formation. We put forward predicted structures for the yeast prion Sup35, suggesting N-terminal structural stability enabled by tyrosine ladders, and C-terminal heterogeneity. Predictions for the Rnq1 prion and alpha-synuclein are also given, identifying a similar mix of homogenous and heterogeneous secondary structure elements. STITCHER provides novel insight into the energetic basis of amyloid structure, provides accurate structure predictions, and can help guide future experimental studies.

Salmonella Typhimurium-specific bacteriophage ΦSH19 and the origins of species specificity in the Vi01-like phage family

Background

Whole genome sequencing of bacteriophages suitable for biocontrol of pathogens in food products is a pre-requisite to any phage-based intervention procedure. Trials involving the biosanitization of Salmonella Typhimurium in the pig production environment identified one such candidate, ΦSH19.

Results

This phage was sequenced and analysis of its 157,785 bp circular dsDNA genome revealed a number of interesting features. ΦSH19 constitutes another member of the recently-proposed Myoviridae Vi01-like family of phages, containing S. Typhi-specific Vi01 and Shigella-specific SboM-AG3. At the nucleotide level ΦSH19 is highly similar to phage Vi01 (80-98% pairwise identity over the length of the genome), with the major differences lying in the region associated with host-range determination. Analyses of the proteins encoded within this region by ΦSH19 revealed a cluster of three putative tail spikes. Of the three tail spikes, two have protein domains associated with the pectate lyase family of proteins (Tsp2) and P22 tail spike family (Tsp3) with the prospect that these enable Salmonella O antigen degradation. Tail spike proteins of Vi01 and SboM-AG3 are predicted to contain conserved right-handed parallel β-helical structures but the internal protein domains are varied allowing different host specificities.

Conclusions

The addition or exchange of tail spike protein modules is a major contributor to host range determination in the Vi01-like phage family.

A method for probing the mutational landscape of amyloid structure

Motivation: Proteins of all kinds can self-assemble into highly ordered β-sheet aggregates known as amyloid fibrils, important both biologically and clinically. However, the specific molecular structure of a fibril can vary dramatically depending on sequence and environmental conditions, and mutations can drastically alter amyloid function and pathogenicity. Experimental structure determination has proven extremely difficult with only a handful of NMR-based models proposed, suggesting a need for computational methods.

Results: We present AmyloidMutants, a statistical mechanics approach for de novo prediction and analysis of wild-type and mutant amyloid structures. Based on the premise of protein mutational landscapes, AmyloidMutants energetically quantifies the effects of sequence mutation on fibril conformation and stability. Tested on non-mutant, full-length amyloid structures with known chemical shift data, AmyloidMutants offers roughly 2-fold improvement in prediction accuracy over existing tools. Moreover, AmyloidMutants is the only method to predict complete super-secondary structures, enabling accurate discrimination of topologically dissimilar amyloid conformations that correspond to the same sequence locations. Applied to mutant prediction, AmyloidMutants identifies a global conformational switch between Aβ and its highly-toxic ‘Iowa’ mutant in agreement with a recent experimental model based on partial chemical shift data. Predictions on mutant, yeast-toxic strains of HET-s suggest similar alternate folds. When applied to HET-s and a HET-s mutant with core asparagines replaced by glutamines (both highly amyloidogenic chemically similar residues abundant in many amyloids), AmyloidMutants surprisingly predicts a greatly reduced capacity of the glutamine mutant to form amyloid. We confirm this finding by conducting mutagenesis experiments.

Availability: Our tool is publically available on the web at http://amyloid.csail.mit.edu/.

Contact:lindquist_admin@wi.mit.edu; bab@csail.mit.edu

Supplementary information:Supplementary data are available at Bioinformatics online.

Structure-based prediction reveals capping motifs that inhibit β-helix aggregation

The parallel β-helix is a geometrically regular fold commonly found in the proteomes of bacteria, viruses, fungi, archaea, and some vertebrates. β-helix structure has been observed in monomeric units of some aggregated amyloid fibers. In contrast, soluble β-helices, both right- and left-handed, are usually "capped" on each end by one or more secondary structures. Here, an in-depth classification of the diverse range of β-helix cap structures reveals subtle commonalities in structural components and in interactions with the β-helix core. Based on these uncovered commonalities, a toolkit of automated predictors was developed for the two distinct types of cap structures. In vitro deletion of the toolkit-predicted C-terminal cap from the pertactin β-helix resulted in increased aggregation and the formation of soluble oligomeric species. These results suggest that β-helix cap motifs can prevent specific, β-sheet-mediated oligomeric interactions, similar to those observed in amyloid formation.

FungalRV: adhesin prediction and immunoinformatics portal for human fungal pathogens

Background

The availability of sequence data of human pathogenic fungi generates opportunities to develop Bioinformatics tools and resources for vaccine development towards benefitting at-risk patients.

Description

We have developed a fungal adhesin predictor and an immunoinformatics database with predicted adhesins. Based on literature search and domain analysis, we prepared a positive dataset comprising adhesin protein sequences from human fungal pathogens Candida albicans, Candida glabrata, Aspergillus fumigatus, Coccidioides immitis, Coccidioides posadasii, Histoplasma capsulatum, Blastomyces dermatitidis, Pneumocystis carinii, Pneumocystis jirovecii and Paracoccidioides brasiliensis. The negative dataset consisted of proteins with high probability to function intracellularly. We have used 3945 compositional properties including frequencies of mono, doublet, triplet, and multiplets of amino acids and hydrophobic properties as input features of protein sequences to Support Vector Machine. Best classifiers were identified through an exhaustive search of 588 parameters and meeting the criteria of best Mathews Correlation Coefficient and lowest coefficient of variation among the 3 fold cross validation datasets. The "FungalRV adhesin predictor" was built on three models whose average Mathews Correlation Coefficient was in the range 0.89-0.90 and its coefficient of variation across three fold cross validation datasets in the range 1.2% - 2.74% at threshold score of 0. We obtained an overall MCC value of 0.8702 considering all 8 pathogens, namely, C. albicans, C. glabrata, A. fumigatus, B. dermatitidis, C. immitis, C. posadasii, H. capsulatum and P. brasiliensis thus showing high sensitivity and specificity at a threshold of 0.511. In case of P. brasiliensis the algorithm achieved a sensitivity of 66.67%. A total of 307 fungal adhesins and adhesin like proteins were predicted from the entire proteomes of eight human pathogenic fungal species. The immunoinformatics analysis data on these proteins were organized for easy user interface analysis. A Web interface was developed for analysis by users. The predicted adhesin sequences were processed through 18 immunoinformatics algorithms and these data have been organized into MySQL backend. A user friendly interface has been developed for experimental researchers for retrieving information from the database.

Conclusion

FungalRV webserver facilitating the discovery process for novel human pathogenic fungal adhesin vaccine has been developed.

Bayesian models and algorithms for protein β-sheet prediction

Prediction of the 3D structure greatly benefits from the information related to secondary structure, solvent accessibility, and nonlocal contacts that stabilize a protein's structure. We address the problem of \beta-sheet prediction defined as the prediction of \beta--strand pairings, interaction types (parallel or antiparallel), and \beta-residue interactions (or contact maps). We introduce a Bayesian approach for proteins with six or less \beta-strands in which we model the conformational features in a probabilistic framework by combining the amino acid pairing potentials with a priori knowledge of \beta-strand organizations. To select the optimum \beta-sheet architecture, we significantly reduce the search space by heuristics that enforce the amino acid pairs with strong interaction potentials. In addition, we find the optimum pairwise alignment between \beta-strands using dynamic programming in which we allow any number of gaps in an alignment to model \beta-bulges more effectively. For proteins with more than six \beta-strands, we first compute \beta-strand pairings using the BetaPro method. Then, we compute gapped alignments of the paired \beta-strands and choose the interaction types and \beta--residue pairings with maximum alignment scores. We performed a 10-fold cross-validation experiment on the BetaSheet916 set and obtained significant improvements in the prediction accuracy.

Evolution of mosaically related tailed bacteriophage genomes seen through the lens of phage P22 virion assembly

The mosaic composition of the genomes of dsDNA tailed bacteriophages (Caudovirales) is well known. Observations of this mosaicism have generally come from comparisons of small numbers of often rather distantly related phages, and little is known about the frequency or detailed nature of the processes that generate this kind of diversity. Here we review and examine the mosaicism within fifty-seven clusters of virion assembly genes from bacteriophage P22 and its "close" relatives. We compare these orthologous gene clusters, discuss their surprising diversity and document horizontal exchange of genetic information between subgroups of the P22-like phages as well as between these phages and other phage types. We also point out apparent restrictions in the locations of mosaic sequence boundaries in this gene cluster. The relatively large sample size and the fact that phage P22 virion structure and assembly are exceptionally well understood make the conclusions especially informative and convincing.

Recognition of beta-structural motifs using hidden Markov models trained with simulated evolution

Motivation: One of the most successful methods to date for recognizing protein sequences that are evolutionarily related, has been profile hidden Markov models. However, these models do not capture pairwise statistical preferences of residues that are hydrogen bonded in β-sheets. We thus explore methods for incorporating pairwise dependencies into these models.

Results: We consider the remote homology detection problem for β-structural motifs. In particular, we ask if a statistical model trained on members of only one family in a SCOP β-structural superfamily, can recognize members of other families in that superfamily. We show that HMMs trained with our pairwise model of simulated evolution achieve nearly a median 5% improvement in AUC for β-structural motif recognition as compared to ordinary HMMs.

Availability: All datasets and HMMs are available at: http://bcb.cs.tufts.edu/pairwise/

Contact:anoop.kumar@tufts.edu; lenore.cowen@tufts.edu

Insight into the structure of an endopolygalacturonase from the phytopathogen Burkholderia cepacia: a biochemical and computational study

We have recently investigated and characterized the mode of action of BcPeh28A, an endopolygalacturonase (endoPG) from the phytopathogen Burkholderia cepacia. EndoPGs belong to glycoside hydrolase family 28 and are responsible for the hydrolysis of the non-esterified regions of pectins. Here we report a 3-D structural model of BcPeh28A by combining mass spectrometry (MS) analysis, aimed at disulphide bridges mapping, and computational modelling tools. MS analyses have revealed the complete pattern of disulphide bridges in BcPeh28A, pointing out the presence of three disulphide bonds, defined as Cys3-25, Cys216-244 and Cys309-421. A 3-D model of BcPeh28A was generated by computational methods based on profile-profile sequence alignments and fold recognition algorithms. The final model exhibits a right-handed β-helix fold with eleven β-helical coils and includes the disulphide bonds as additional spatial restraints. Molecular dynamics simulations have been performed to test the conformational stability of the model. Finally, the structural analysis of the BcPeh28A model allows defining the architecture and the amino acid topology of the subsites involved in the catalysis and in the substrate binding specificity.

Complete genomic sequence analysis of the temperate bacteriophage phiSASD1 of Streptomyces avermitilis

The bacteriophage phiSASD1, isolated from a failed industrial avermectin fermentation, belongs to the Siphoviridae family. Its four predominant structural proteins, which include the major capsid, portal and two tail-related proteins, were separated and identified by SDS-PAGE and N-terminal sequence analysis. The entire double-stranded DNA genome of phiSASD1 consists of 37,068 bp, with 3'-protruding cohesive ends of nine nucleotides. Putative biological functions have been assigned to 24 of the 43 potential open reading frames. Comparative analysis shows perfect assembly of three "core" gene modules: the morphogenesis and head module, the tail module and the right arm gene module, which displays obvious similarity to the right arm genes of Streptomyces phage phiC31 in function and arrangement. Meanwhile, structural module flexibility within phiSASD1 suggests that assignment of phage taxonomy based on comparative genomics of structural genes will be more complex than expected due to the exchangeability of functional genetic elements.