Prediction of protein antigenic determinants from amino acid sequences

SPADE web service for prediction of allergen IgE epitopes

The specific interaction of allergens with IgE antibodies and the allergen mediated cross-linking of receptor-bound IgE are key events of allergic diseases. The elucidation of the IgE binding sites (the epitopes) on the allergen surface is an important goal of allergy research. Only few allergen-specific IgE epitopes have been determined experimentally to date. Epitope prediction methods represent a viable alternative to experimental methods and have worked well with linear epitopes. However, as most IgE epitopes are of conformational and/or discontinuous nature sequence based prediction methods have had limited success in these cases. Here, we present the web server of the program SPADE (https://spade.uni-graz.at), which is the server implementation of a previously published program (1). In this approach we utilize the structural homology of cross-reactive allergens combined with the immunological cross-reactivity data for the discrimination of putative IgE-binding sites from non-cross-reactive surface patches. The method, although predictive, does not rely on machine-learning algorithms and does not require training data. The SPADE server features an easy-to-use interface, an automated pipeline consisting of third-party, as well as own, newly developed routines and a comprehensive output page.

Computational identification of protein-protein interactions in model plant proteomes

Protein-protein interactions (PPIs) play essential roles in many biological processes. A PPI network provides crucial information on how biological pathways are structured and coordinated from individual protein functions. In the past two decades, large-scale PPI networks of a handful of organisms were determined by experimental techniques. However, these experimental methods are time-consuming, expensive, and are not easy to perform on new target organisms. Large-scale PPI data is particularly sparse in plant organisms. Here, we developed a computational approach for detecting PPIs trained and tested on known PPIs of Arabidopsis thaliana and applied to three plants, Arabidopsis thaliana, Glycine max (soybean), and Zea mays (maize) to discover new PPIs on a genome-scale. Our method considers a variety of features including protein sequences, gene co-expression, functional association, and phylogenetic profiles. This is the first work where a PPI prediction method was developed for is the first PPI prediction method applied on benchmark datasets of Arabidopsis. The method showed a high prediction accuracy of over 90% and very high precision of close to 1.0. We predicted 50,220 PPIs in Arabidopsis thaliana, 13,175,414 PPIs in corn, and 13,527,834 PPIs in soybean. Newly predicted PPIs were classified into three confidence levels according to the availability of existing supporting evidence and discussed. Predicted PPIs in the three plant genomes are made available for future reference.

Positions in the N-methyl-D-aspartate Receptor GluN2C Subunit M3 and M4 Domains Regulate Alcohol Sensitivity and Receptor Kinetics

BACKGROUND

Alcohol alters synaptic transmission in the brain. The N-methyl-D-aspartate (NMDA) receptor (NMDAR), a subtype of glutamate-gated ion channel, is an important synaptic target of alcohol in the brain. We and others have previously identified 4 alcohol-sensitive positions in the third and fourth membrane-associated (M) domains, designated M31-2 and M41-2 , of the GluN1, GluN2A, and GluN2B NMDAR subunits. In the present study, we tested whether the corresponding positions in the GluN2C subunit also regulate alcohol sensitivity and ion channel gating.

METHODS

We performed alanine- and tryptophan-scanning mutagenesis in the GluN2C subunit followed by expression in HEK 293 cells and electrophysiological patch-clamp recording.

RESULTS

Alanine substitution at the M31 (F634) and M41-2 (M821 and M823) positions did not alter ethanol (EtOH) sensitivity, whereas substitution of alanine at the M32 position (F635) yielded nonfunctional receptors. Tryptophan substitution at the M31-2 positions did not change EtOH sensitivity, whereas tryptophan substitution at the M41 position increased, and at the M42 position decreased, EtOH sensitivity. The increased EtOH sensitivity of the tryptophan mutant at M41 is in marked contrast to previous results observed in the GluN2A and GluN2B subunits. In addition, this mutant exhibited increased desensitization, but to a much lesser extent compared to the corresponding mutations in GluN2A and GluN2B. A series of mutations at M41 altered EtOH sensitivity, glutamate potency, and desensitization. Seven amino acid substitutions (of 15 tested) at this position yielded nonfunctional receptors. Among the remaining mutants at M41 , EtOH sensitivity was not significantly correlated with hydrophobicity, molecular volume, or polarity of the substituent, or with glutamate EC50 values, but was correlated with maximal steady-state-to-peak current ratio, a measure of desensitization.

CONCLUSIONS

The identity and characteristics of alcohol-sensitive positions in the GluN2C subunit differ from those previously reported for GluN2A and GluN2B subunits, despite the high homology among these subunits.

Human MOSPD2: A bacterial Lmb mimicked auto-antigen is involved in immune infertility

Autoantibody production is one of the leading factors of immune infertility, an autoimmune disease of the male reproductive system. The potential involvement of MHC-class II derived self-peptides against bacterial proteins in the antisperm antibody (ASA) production has been reported previously. Apparently, Streptococcus agalactiae has been considered as an important pathogen to impart infection-induced infertility in a bacteriospermia associated leukocytospermia (LCS/BS) state. Hence, the present study attempts to confirm S. agalactiae specific Laminin binding protein (Lmb) derived self-peptide ('KDSYTKKAKAFKKEA') namely human Motile Sperm domain-containing protein 2 (MOSPD2) as an auto-antigen in LCS/BS condition. Semen samples were collected from infertile men with LCS/BS (n ​= ​17) and their fertile counterparts (n ​= ​10). Gram-positive bacteria were predominantly identified in the entire 17 LCS samples using culture method followed by 16S rDNA sequencing technique. TLRs 2 and 4 expression used as markers of immune response in spermatozoa and sperm dysfunction were elevated in the LCS/BS spermatozoa as compared to their fertile counterparts. A significant increase in oxidative stress indices i.e., protein carbonylation, lipid peroxidation and acridine orange test (AOT), was also observed in the LCS/BS spermatozoa. Spermatozoa lysate (both auto and heterologous), bacterial lysate (control) and synthesized MOSPD2 self-peptide were used to test their antigenicity against the autoantibodies by rocket immunoelectrophoresis (RIEP) assay. Seminal plasma from LCS/BS patients with S. agalactiae was used as the source of autoantibodies. Spermatozoa and bacteria lysate; and MOSPD2 self-peptide were able to bind autoantibodies in the seminal plasma. Besides, the self-peptide showed a dose dependent increase in the precipitation of antibody. T-cell epitope mapping of 48 Enterococcus faecalis and 91Staphylococcus aureus surface proteins confirmed MOSPD2 as a global auto-antigen. Thus, augmentation of TLR expression in LCS/BS spermatozoa inferred MOSPD2 to be a putative immunogen. Altogether, these findings will delineate the significance of MOSPD2 auto-antigen in a bacteria derived immune infertility condition.

Advances in In-silico B-cell Epitope Prediction

Identification of B-cell epitopes in target antigens is one of the most crucial steps for epitopebased vaccine development, immunodiagnostic tests, antibody production, and disease diagnosis and therapy. Experimental methods for B-cell epitope mapping are time consuming, costly and labor intensive; in the meantime, various in-silico methods are proposed to predict both linear and conformational B-cell epitopes. The accurate identification of B-cell epitopes presents major challenges for immunoinformaticians. In this paper, we have comprehensively reviewed in-silico methods for B-cell epitope identification. The aim of this review is to stimulate the development of better tools which could improve the identification of B-cell epitopes, and further for the development of therapeutic antibodies and diagnostic tools.

Molecular and serological characterization of hepatitis B vaccine breakthrough infections in serial samples from two plasma donors

Background

Although vaccines for hepatitis B virus (HBV) are highly effective, HBV infections in vaccinees occur. Index samples of breakthrough infections are typically anti-HBc negative but HBV DNA positive with protective anti-HBs levels while HBsAg detection may be delayed or absent. HBsAg mutations have been associated with some vaccine breakthrough cases.

Methods

This research characterizes the serological and molecular profiles of vaccine breakthrough infections in serial samples from two commercially available plasma donor panels. Samples were tested with commercially available assays for HBV antigens and antibodies: HBsAg, HBeAg, anti-HBc, anti-HBc IgM, anti-HBe, and anti-HBs. Different immunoassay approaches for earlier detection of breakthrough infection were explored including hepatitis B core-related antigen (HBcrAg), a research assay for preS2 antigen, and a new prototype ARCHITECT HBsAg assay with improved sensitivity. The prototype HBsAg assay is fully automated and involves no sample pre-treatment. Molecular testing included HBV DNA quantitation and sequencing of preS1, preS2, surface, and basal core promoter/core promoter genes.

Results

Although the research preS2 antigen assay allowed earlier detection of the breakthrough infections than current HBsAg assays and HBcrAg, the new prototype ARCHITECT HBsAg assay provided the earliest serologic detection. The ability of the new prototype HBsAg assay to detect HBsAg in the presence of anti-HBs was investigated using known concentrations of native HBsAg mixed with anti-HBs from a vaccinee. The results demonstrated that the prototype ARCHITECT assay is more sensitive in detecting HBsAg in the presence of anti-HBs than current HBsAg assays. Sequencing revealed multiple substitutions in preS1, preS2, and S regions for one panel including a rare D144N substitution associated with vaccine breakthrough that emerged with increasing frequency as the breakthrough infection developed.

Conclusions

When compared with other immunoassay approaches, the new prototype ARCHITECT HBsAg assay allows earlier detection of vaccine breakthrough infections and more sensitive detection of HBsAg in the presence of anti-HBs. Molecular characterization of longitudinal samples demonstrated the progressive appearance of a rare HBsAg mutation associated with vaccine breakthrough.

Effect of Peptide Sequence on the LCST-Like Transition of Elastin-Like Peptides and Elastin-Like Peptide-Collagen-Like Peptide Conjugates: Simulations and Experiments

Elastin-like polypeptides (ELPs) are thermoresponsive biopolymers that undergo an LCST-like phase transition in aqueous solutions. The temperature of this LCST-like transition, Tt , can be tuned by varying the number of repeat units in the ELP, sequence and composition of the repeat units, the solution conditions, and via conjugation to other biomacromolecules. In this study, we show how and why the choice of guest (X) residue in the VPGXG pentad repeat tunes the Tt of short ELPs, (VPGXG)4, in the free state and when conjugated to collagen-like peptides (CLPs). In experiments, the (VPGWG)4 chain (in short, WWWW) has a Tt < 278 K, while (VPGFG)4 or FFFF has a Tt > 353 K in both free ELP and ELP-CLP systems. The Tt for the FWWF ELP sequence decreases from being >353 K for free ELP to <278 K for the corresponding ELP-CLP system. The decrease in Tt upon conjugation to CLP has been shown to be due to the crowding of ELP chains that decreases the entropic loss upon ELP aggregation. Even though the net hydrophobicity of ELP has been reasoned to drive the Tt , the origins of lower Tt of WWWW compared to FFFF are unclear, as there is disagreement in hydrophobicity scales in how phenylalanine (F) compares to tryptophan (W). Motivated by these experimental observations, we use a combination of atomistic and coarse-grained (CG) molecular dynamics simulations. Atomistic simulations of free and tethered ELPs show that WWWW are more prone to acquire β-turn structures than FFFF at lower temperatures. Also, the atomistically informed CG simulations show that the increased local stiffness in W than F due to the bulkier side chain in W compared to F, alone does not cause the shift in the transition of WWWW versus FFFF. The experimentally observed lower Tt of WWWW than FFFF is achieved in CG simulations only when the CG model incorporates both the atomistically informed local stiffness and stronger effective attractions localized at the W position versus the F position. The effective interactions localized at the guest residue in the CG model is guided by our atomistically observed increased propensity for β-turn structure in WWWW versus FFFF and by past experimental work of Urry et al. quantifying hydrophobic differences through enthalpy of association for W versus F.

Probabilistic variable-length segmentation of protein sequences for discriminative motif discovery (DiMotif) and sequence embedding (ProtVecX)

In this paper, we present peptide-pair encoding (PPE), a general-purpose probabilistic segmentation of protein sequences into commonly occurring variable-length sub-sequences. The idea of PPE segmentation is inspired by the byte-pair encoding (BPE) text compression algorithm, which has recently gained popularity in subword neural machine translation. We modify this algorithm by adding a sampling framework allowing for multiple ways of segmenting a sequence. PPE segmentation steps can be learned over a large set of protein sequences (Swiss-Prot) or even a domain-specific dataset and then applied to a set of unseen sequences. This representation can be widely used as the input to any downstream machine learning tasks in protein bioinformatics. In particular, here, we introduce this representation through protein motif discovery and protein sequence embedding. (i) DiMotif: we present DiMotif as an alignment-free discriminative motif discovery method and evaluate the method for finding protein motifs in three different settings: (1) comparison of DiMotif with two existing approaches on 20 distinct motif discovery problems which are experimentally verified, (2) classification-based approach for the motifs extracted for integrins, integrin-binding proteins, and biofilm formation, and (3) in sequence pattern searching for nuclear localization signal. The DiMotif, in general, obtained high recall scores, while having a comparable F1 score with other methods in the discovery of experimentally verified motifs. Having high recall suggests that the DiMotif can be used for short-list creation for further experimental investigations on motifs. In the classification-based evaluation, the extracted motifs could reliably detect the integrins, integrin-binding, and biofilm formation-related proteins on a reserved set of sequences with high F1 scores. (ii) ProtVecX: we extend k-mer based protein vector (ProtVec) embedding to variablelength protein embedding using PPE sub-sequences. We show that the new method of embedding can marginally outperform ProtVec in enzyme prediction as well as toxin prediction tasks. In addition, we conclude that the embeddings are beneficial in protein classification tasks when they are combined with raw amino acids k-mer features.

An RK/ST C-Terminal Motif is Required for Targeting of OEP7.2 and a Subset of Other Arabidopsis Tail-Anchored Proteins to the Plastid Outer Envelope Membrane

Tail-anchored (TA) proteins are a unique class of integral membrane proteins that possess a single C-terminal transmembrane domain and target post-translationally to the specific organelles at which they function. While significant advances have been made in recent years in elucidating the mechanisms and molecular targeting signals involved in the proper sorting of TA proteins, particularly to the endoplasmic reticulum and mitochondria, relatively little is known about the targeting of TA proteins to the plastid outer envelope. Here we show that several known or predicted plastid TA outer envelope proteins (OEPs) in Arabidopsis possess a C-terminal RK/ST sequence motif that serves as a conserved element of their plastid targeting signal. Evidence for this conclusion comes primarily from experiments with OEP7.2, which is a member of the Arabidopsis 7 kDa OEP family. We confirmed that OEP7.2 is localized to the plastid outer envelope and possesses a TA topology, and its C-terminal sequence (CTS), which includes the RK/ST motif, is essential for proper targeting to plastids. The CTS of OEP7.2 is functionally interchangeable with the CTSs of other TA OEPs that possess similar RK/ST motifs, but not with those that lack the motif. Further, a bioinformatics search based on a consensus sequence led to the identification of several new OEP TA proteins. Collectively, this study provides new insight into the mechanisms of TA protein sorting in plant cells, defines a new targeting signal element for a subset of TA OEPs and expands the number and repertoire of TA proteins at the plastid outer envelope.

Development of a Structure-Based, pH-Dependent Lipophilicity Scale of Amino Acids from Continuum Solvation Calculations

Lipophilicity is a fundamental property to characterize the structure and function of proteins, motivating the development of lipophilicity scales. We report a versatile strategy to derive a pH-adapted scale that relies on theoretical estimates of distribution coefficients from conformational ensembles of amino acids. This is accomplished by using an accurately parametrized version of the IEFPCM/MST continuum solvation model as an effective way to describe the partitioning between n-octanol and water, in conjunction with a formalism that combines partition coefficients of neutral and ionic species of residues and the corresponding p K_a values of ionizable groups. Two weighting schemes are considered to derive solvent-like and protein-like scales, which have been calibrated by comparison with other experimental scales developed in different chemical/biological environments and pH conditions as well as by examining properties such as the retention time of small peptides and the recognition of antigenic peptides. A straightforward extension to nonstandard residues is enabled by this efficient methodological strategy.

Production of neutralizing antibodies against the secreted Clostridium chauvoei toxin A (CctA) upon blackleg vaccination

Clostridium chauvoei is the etiologic agent of blackleg in cattle, inducing fever, severe myonecrosis, oedemic lesions and ultimately death of infected animals. The pathogen often results in such rapid death that antibiotic therapy is futile and thus vaccination is the only efficient strategy in order to control the disease. The β-barrel pore forming leucocidin Clostridium chauvoei toxin A (CctA) is one of the best characterised toxins of C. chauvoei and has been shown to be an important virulence factor. It has been reported to induce protective immunity and is conserved across C. chauvoei strains collected from diverse geographical locations for more than 50 years. The aim of this study was to identify the location of the CctA toxin during liquid culture fermentation and to use CctA to develop an in vitro assay to replace the current guinea pig challenge assay for vaccine potency in standard batch release procedures. We report that CctA is fully secreted in C. chauvoei culture and show that it is found abundantly in the supernatant of liquid cultures. Sera from cattle vaccinated with a commercial blackleg vaccine revealed strong haemolysin-neutralizing activity against recombinant CctA which reached titres of 1000 times 28 days post-vaccination. Similarly, guinea pig sera from an official potency control test reached titres of 600 times 14 days post-vaccination. In contrast, ELISA was not able to specifically measure anti-CctA antibodies in cattle serum due to strong cross-reactions with antibodies against other proteins present pre-vaccination. We conclude that haemolysin-neutralizing antibodies are a valuable measurement for protective immunity against blackleg and have the potential to be a suitable replacement of the guinea pig challenge potency test, which would forego the unnecessary challenge of laboratory animals.

Design and Production of a Recombinant Hybrid Toxin to Raise Protective Antibodies Against Loxosceles Spider Venom

Human accidents with spiders of the genus Loxosceles are an important health problem affecting thousands of people worldwide. Patients evolve to severe local injuries and, in many cases, to systemic disturbances as acute renal failure, in which cases antivenoms are considered to be the most effective treatment. However, for antivenom production, the extraction of the venom used in the immunization process is laborious and the yield is very low. Thus, many groups have been exploring the use of recombinant Loxosceles toxins, particularly phospholipases D (PLDs), to produce the antivenom. Nonetheless, some important venom activities are not neutralized by anti-PLD antibodies. Astacin-like metalloproteases (ALMPs) are the second most expressed toxin acting on the extracellular matrix, indicating the importance of its inclusion in the antigen’s formulation to provide a better antivenom. Here we show the construction of a hybrid recombinant immunogen, called LgRec1ALP1, composed of hydrophilic regions of the PLD and the ALMP toxins from Loxosceles gaucho. Although the LgRec1ALP1 was expressed as inclusion bodies, it resulted in good yields and it was effective to produce neutralizing antibodies in mice. The antiserum neutralized fibrinogenolytic, platelet aggregation and dermonecrotic activities elicited by L. gaucho, L. laeta, and L. intermedia venoms, indicating that the hybrid recombinant antigen may be a valuable source for the production of protective antibodies against Loxosceles ssp. venoms. In addition, the hybrid recombinant toxin approach may enrich and expand the alternative antigens for antisera production for other venoms.

Finding an Optimal Corneal Xenograft Using Comparative Analysis of Corneal Matrix Proteins Across Species

Numerous animal species have been proposed as sources of corneal tissue for obtaining decellularized xenografts. The selection of an appropriate animal model must take into consideration the differences in the composition and structure of corneal proteins between humans and other animal species in order to minimize immune response and improve outcome of the xenotransplant. Here, we compared the amino-acid sequences of 16 proteins present in the corneal stromal matrix of 14 different animal species using Basic Local Alignment Search Tool, and calculated a similarity score compared to the respective human sequence. Primary amino acid structures, isoelectric point and grand average of hydropathy (GRAVY) values of the 7 most abundant proteins (i.e. collagen α-1 (I), α-1 (VI), α-2 (I) and α-3 (VI), as well as decorin, lumican, and keratocan) were also extracted and compared to those of human. The pig had the highest similarity score (91.8%). All species showed a lower proline content compared to human. Isoelectric point of pig (7.1) was the closest to the human. Most species have higher GRAVY values compared to human except horse. Our results suggest that porcine cornea has a higher relative suitability for corneal transplantation into humans compared to other studied species.

iHyd-PseAAC (EPSV): Identifying Hydroxylation Sites in Proteins by Extracting Enhanced Position and Sequence Variant Feature via Chou's 5-Step Rule and General Pseudo Amino Acid Composition

BACKGROUND

In various biological processes and cell functions, Post Translational Modifications (PTMs) bear critical significance. Hydroxylation of proline residue is one kind of PTM, which occurs following protein synthesis. The experimental determination of hydroxyproline sites in an uncharacterized protein sequence requires extensive, time-consuming and expensive tests.

METHODS

With the torrential slide of protein sequences produced in the post-genomic age, certain remarkable computational strategies are desired to overwhelm the issue. Keeping in view the composition and sequence order effect within polypeptide chains, an innovative in-silico> predictor via a mathematical model is proposed.

RESULTS

Later, it was stringently verified using self-consistency, cross-validation and jackknife tests on benchmark datasets. It was established after a rigorous jackknife test that the new predictor values are superior to the values predicted by previous methodologies.

CONCLUSION

This new mathematical technique is the most appropriate and encouraging as compared with the existing models.

Predicting protein-protein interactions using high-quality non-interacting pairs

BACKGROUND

Identifying protein-protein interactions (PPIs) is of paramount importance for understanding cellular processes. Machine learning-based approaches have been developed to predict PPIs, but the effectiveness of these approaches is unsatisfactory. One major reason is that they randomly choose non-interacting protein pairs (negative samples) or heuristically select non-interacting pairs with low quality.

RESULTS

To boost the effectiveness of predicting PPIs, we propose two novel approaches (NIP-SS and NIP-RW) to generate high quality non-interacting pairs based on sequence similarity and random walk, respectively. Specifically, the known PPIs collected from public databases are used to generate the positive samples. NIP-SS then selects the top-m dissimilar protein pairs as negative examples and controls the degree distribution of selected proteins to construct the negative dataset. NIP-RW performs random walk on the PPI network to update the adjacency matrix of the network, and then selects protein pairs not connected in the updated network as negative samples. Next, we use auto covariance (AC) descriptor to encode the feature information of amino acid sequences. After that, we employ deep neural networks (DNNs) to predict PPIs based on extracted features, positive and negative examples. Extensive experiments show that NIP-SS and NIP-RW can generate negative samples with higher quality than existing strategies and thus enable more accurate prediction.

CONCLUSIONS

The experimental results prove that negative datasets constructed by NIP-SS and NIP-RW can reduce the bias and have good generalization ability. NIP-SS and NIP-RW can be used as a plugin to boost the effectiveness of PPIs prediction. Codes and datasets are available at http://mlda.swu.edu.cn/codes.php?name=NIP .

A cross-talk on compositional dynamics and codon usage patterns of mitochondrial CYB gene in Echinodermata

Codon usage bias (CUB) refers to a phenomenon in which some synonymous codons are used in mature mRNA at a higher frequency than other members codifying the same amino acid. CUB is mainly determined by mutation pressure and natural selection. We used bioinformatic tools to analyze the protein coding sequences of mitochondrial CYB gene in different classes of Echinodermata to understand the patterns of codon usage. The ENC values of CYB gene in five different classes of Echinodermata were 41.64, 30.33, 43.63, 41.11, and 41.33, which suggested that the CUB of this gene was low. The relative synonymous codon usage (RSCU) values showed that the patterns of over-represented and under-represented codons were different among different classes. Correspondence analysis indicated that the plots of CYB gene were different across classes, suggesting that the pattern of codon usage was also different among five classes under study. Highly significant correlation (p < .01) between overall nucleotide composition and its 3rd codon position indicated that both mutational pressure and natural selection had an influence on the codon usage bias of CYB gene. Furthermore, PR-2 bias plot analysis showed that both mutation pressure and natural selection might have affected the pattern of codon usage in CYB gene of Echinodermata.

Predicting Humoral Alloimmunity from Differences in Donor and Recipient HLA Surface Electrostatic Potential

In transplantation, development of humoral alloimmunity against donor HLA is a major cause of organ transplant failure, but our ability to assess the immunological risk associated with a potential donor–recipient HLA combination is limited. We hypothesized that the capacity of donor HLA to induce a specific alloantibody response depends on their structural and physicochemical dissimilarity compared with recipient HLA. To test this hypothesis, we first developed a novel computational scoring system that enables quantitative assessment of surface electrostatic potential differences between donor and recipient HLA molecules at the tertiary structure level [three-dimensional electrostatic mismatch score (EMS-3D)]. We then examined humoral alloimmune responses in healthy females subjected to a standardized injection of donor lymphocytes from their male partner. This analysis showed a strong association between the EMS-3D of donor HLA and donor-specific alloantibody development; this relationship was strongest for HLA-DQ alloantigens. In the clinical transplantation setting, the immunogenic potential of HLA-DRB1 and -DQ mismatches expressed on donor kidneys, as assessed by their EMS-3D, was an independent predictor of development of donor-specific alloantibody after graft failure. Collectively, these findings demonstrate the translational potential of our approach to improve immunological risk assessment and to decrease the burden of humoral alloimmunity in organ transplantation.

Determination of immunodominant scaffolds of Com1 and OmpH antigens of Coxiella burnetii

Today, there is an increasing emphasis on recombinant vaccines to eliminate the side effects of conventional vaccines such as whole-cell bacteria. Query fever is an emerging disease that causes irreparable complications for both humans and domestic animals. The cause of this disease is Coxiella burnetii, a gram-negative intracellular bacteria. In order to determine the most immunodominant epitopes of Com1 and OmpH antigens of C. burnetii, the most reliable bioinformatics tools with high rates of citation in predicting B cell and T cell epitopes were used. Finally, by comparing the results of all servers, the best overlapped epitopes with the highest antigenicity among different servers were selected. In this regard, epitopes in 18-27and 67-82 amino acids residues were introduced for MHCI and MHCII of T cell, respectively, whereas epitope in 16-25 amino acids residues was introduced for B cell of OmpH antigen. The epitopes in the range of 193-202, 100-108 and 215-223 amino acid residues were preferred for MHCI class of T cell, MHCII class of T cell and B cell of Com1 antigen, respectively. For each antigen, some empirical common epitopic regions were introduced, which included both T and B cells epitopes, 53-65 and 102-111 amino acid residues of OmpH antigen as well as 38-54 range of the amino acid of Com1 antigen. All the predicted epitopes were selected based on their high antigenicity scores and number of non-digestive enzymes. To optimize the application of reported epitopes, various orders of epitopes were arranged in three categories of B cell, T cell and common T and B cells epitopes for each antigen. Then, the best immunodominant scaffolds for each antigen were proposed in these categories. The results demonstrated that the scaffold arranged based on B cell epitopes had the highest antigenicity in both antigens.

Telomeric Repeat-Binding Factor Homologs in Entamoeba histolytica: New Clues for Telomeric Research

Telomeric Repeat Binding Factors (TRFs) are architectural nuclear proteins with critical roles in telomere-length regulation, chromosome end protection and, fusion prevention, DNA damage detection, and senescence regulation. Entamoeba histolytica, the parasite responsible of human amoebiasis, harbors three homologs of human TRFs, based on sequence similarities to their Myb DNA binding domain. These proteins were dubbed EhTRF-like I, II and III. In this work, we revealed that EhTRF-like I and II share similarity with human TRF1, while EhTRF-like III shares similarity with human TRF2 by in silico approach. The analysis of ehtrf-like genes showed they are expressed differentially under basal culture conditions. We also studied the cellular localization of EhTRF-like I and III proteins using subcellular fractionation and western blot assays. EhTRF-like I and III proteins were enriched in the nuclear fraction, but they were also present in the cytoplasm. Indirect immunofluorescence showed that these proteins were located at the nuclear periphery co-localizing with Lamin B1 and trimethylated H4K20, which is a characteristic mark of heterochromatic regions and telomeres. We found by transmission electron microscopy that EhTRF-like III was located in regions of more condensed chromatin. Finally, EMSA assays showed that EhTRF-like III forms specific DNA-protein complexes with telomeric related sequences. Our data suggested that EhTRF-like proteins play a role in the maintenance of the chromosome ends in this parasite.

Computational B-cell epitope identification and production of neutralizing murine antibodies against Atroxlysin-I

Epitope identification is essential for developing effective antibodies that can detect and neutralize bioactive proteins. Computational prediction is a valuable and time-saving alternative for experimental identification. Current computational methods for epitope prediction are underused and undervalued due to their high false positive rate. In this work, we targeted common properties of linear B-cell epitopes identified in an individual protein class (metalloendopeptidases) and introduced an alternative method to reduce the false positive rate and increase accuracy, proposing to restrict predictive models to a single specific protein class. For this purpose, curated epitope sequences from metalloendopeptidases were transformed into frame-shifted Kmers (3 to 15 amino acid residues long). These Kmers were decomposed into a matrix of biochemical attributes and used to train a decision tree classifier. The resulting prediction model showed a lower false positive rate and greater area under the curve when compared to state-of-the-art methods. Our predictions were used for synthesizing peptides mimicking the predicted epitopes for immunization of mice. A predicted linear epitope that was previously undetected by an experimental immunoassay was able to induce neutralizing-antibody production in mice. Therefore, we present an improved prediction alternative and show that computationally identified epitopes can go undetected during experimental mapping.

Use of Synthetic Peptides and Multiple Antigen Blot Assay in the Immunodiagnosis of Hepatitis C Virus Infection

Acute hepatitis C virus (HCV) infection is usually asymptomatic, therefore, early diagnosis is rare. It may remain undiagnosed in individuals who progress to chronic infection, often until serious liver damage has developed. To incorporate the diagnosis of this viral disease in a multiple-diagnostic assay, we first analyzed by immunoinformatics the HCV subtype 1a polyprotein (specifically Core, E2, NS3, NS5A proteins) to select antigenic peptides to be tested initially by the Pepscan technique. Next, we performed the immunodiagnosis of HCV infection, using the Multiple Antigen Blot Assay (MABA). In 22 patients' sera included in this study, a 20-mer linear peptide belonging to the N-terminus of the worldwide conserved Core protein showed 100% sensitivity and specificity; other sequences showed different levels of antibody recognition. The use of MABA in combination with synthetic peptides as a source of multiple, specific, and nonexpensive antigens for other infectious diseases could represent a rapid, integrated, and inexpensive diagnostic methodology.

Cell penetrating peptides: a comparative transport analysis for 474 sequence motifs

Delivering reagents into cells is a key demand in molecular medicine. The vehicle of choice is often cell penetrating peptides (CPPs), which can ferry conjugated cargo across membranes. Although numerous peptides have been shown to promote such uptake events, there has been no comprehensive comparison of individual performance under standardized conditions. We have devised a method to rapidly analyze the ability of a multitude of CPP conjugates to carry a model cargo into HeLa cells. Sequence information for 474 CPPs was collected from literature sources, and the respective peptides were synthesized and modified with carboxyfluorescein (FAM) as model cargo. All candidates were evaluated in an identical uptake test, and transport was quantified using cellular fluorescence intensities. Substantial differences in the ability to carry the fluorophore into the cells were observed, with transport performance differing by a factor of 70 between the best CPP investigated and cargo alone. Strong correlations were observed between uptake efficiency and both sequence length and the presence of positive net charge. A compilation of the 20 top performers with regard to cargo delivery performance and cell compatibility is provided.

Structural Capacitance in Protein Evolution and Human Diseases

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

Structural Basis of Epitope Recognition by Heavy-Chain Camelid Antibodies

Truncated versions of heavy-chain antibodies (HCAbs) from camelids, also termed nanobodies, comprise only one-tenth the mass of conventional antibodies, yet retain similar, high binding affinities for the antigens. Here we analyze a large data set of nanobody-antigen crystal structures and investigate how nanobody-antigen recognition compares to the one by conventional antibodies. We find that nanobody paratopes are enriched in aromatic residues just like conventional antibodies, but additionally, they also bear a more hydrophobic character. Most striking differences were observed in the characteristics of the antigen's epitope. Unlike conventional antibodies, nanobodies bind to more rigid, concave, conserved and structured epitopes enriched with aromatic residues. Nanobodies establish fewer interactions with the antigens compared to conventional antibodies, and we speculate that high binding affinities are achieved due to less unfavorable conformational and more favorable solvation entropy contributions. We observed that interactions with antigen are mediated not only by three CDR loops but also by numerous residues from the nanobody framework. These residues are not distributed uniformly; rather, they are concentrated into four structurally distinct regions and mediate mostly charged interactions. Our findings suggest that in some respects nanobody-antigen interactions are more similar to the general protein-protein interactions rather than antibody-antigen interactions.

An Integrated-OFFT Model for the Prediction of Protein Secondary Structure Class

BACKGROUND

Proteins are the utmost multi-purpose macromolecules, which play a crucial function in many aspects of biological processes. For a long time, sequence arrangement of amino acid has been utilized for the prediction of protein secondary structure. Besides, in major methods for the prediction of protein secondary structure class, the impact of Gaussian noise on sequence representation of amino acids has not been considered until now; which is one of the important constraints for the functionality of a protein.

METHODS

In the present research, the prediction of protein secondary structure class was accomplished by integrated application of Stockwell transformation and Amino Acid Composition (AAC), on equivalent Electron-ion Interaction Potential (EIIP) representation of raw amino acid sequence. The introduced method was evaluated by using 4 benchmark datasets of low sequence homology, namely PDB25, 498, 277, and 204. Furthermore, random forest algorithm together with the out-of-bag error estimate and Support Vector Machine (SVM), using k-fold cross validation demonstrated high feature representation potential of our reported approach.

RESULTS

The overall prediction accuracy for PDB25, 498, 277, and 204 datasets with randomforest classifier was 92.5%, 94.79%, 92.45%, and 88.04% respectively, whereas with SVM, the results were 84.66%, 95.32%, 89.29%, and 84.37% respectively.

CONCLUSION

An integrated-order-function-frequency-time (OFFT) model has been proposed for the prediction of protein secondary structure class. For the first time, we reported the effect of Gaussian noise on the prediction accuracy of protein secondary structure class and proposed a robust integrated- OFFT model, which is effectively noise resistant.

Glycan Masking Focuses Immune Responses to the HIV-1 CD4-Binding Site and Enhances Elicitation of VRC01-Class Precursor Antibodies

An important class of HIV-1 broadly neutralizing antibodies, termed the VRC01 class, targets the conserved CD4-binding site (CD4bs) of the envelope glycoprotein (Env). An engineered Env outer domain (OD) eOD-GT8 60-mer nanoparticle has been developed as a priming immunogen for eliciting VRC01-class precursors and is planned for clinical trials. However, a substantial portion of eOD-GT8-elicited antibodies target non-CD4bs epitopes, potentially limiting its efficacy. We introduced N-linked glycans into non-CD4bs surfaces of eOD-GT8 to mask irrelevant epitopes and evaluated these mutants in a mouse model that expressed diverse immunoglobulin heavy chains containing human IGHV1-2∗02, the germline VRC01 VH segment. Compared to the parental eOD-GT8, a mutant with five added glycans stimulated significantly higher proportions of CD4bs-specific serum responses and CD4bs-specific immunoglobulin G+ B cells including VRC01-class precursors. These results demonstrate that glycan masking can limit elicitation of off-target antibodies and focus immune responses to the CD4bs, a major target of HIV-1 vaccine design.

Solubility and aggregation behavior of protein fractions from the heterotrophically cultivated microalga Chlorella protothecoides

Protein solubility in water is a key property of food proteins. The aim of this work was to study the solubility and microstructural properties as a function of pH of both protein fractions (water-soluble (WSPE) and water-insoluble protein extracts (WISPE)) obtained from the microalga Chlorella protothecoides, which is promising for food use. Protein solubility was determined as the ratio of protein concentration in the supernatant after centrifugation to total protein concentration. An unusually high solubility and only slight gravitational separation across a very broad pH-range (2-12) were observed for the WSPE with a minimum protein solubility of 84.3 ± 2.2% at pH 2. The origin of this high pH-independent protein solubility was attributed to a high degree of glycosylation and a high amount of hydrophilic amino acids. In contrast, the WISPE was found to contain strongly aggregated proteins, and these large aggregates separated rapidly from solution by gravitation independent of the pH. This corresponded to their protein solubility, which was overall low in the pH-range of 2-11, and only increased at pH 12 to a maximum solubility of 26.9 ± 2.8%. These results suggest that the WSPE of Chlorella protothecoides may exhibit unique properties for food formulations, allowing for example for both acidified, neutral or slightly alkaline foods to be formulated, whereas WISPE may be more suited for foods where phase separation is rather slow.

Membrane affinity and fluorescent labelling: comparative study of monolayer interaction, cellular uptake and cytotoxicity profile of carboxyfluorescein-conjugated cationic peptides

Fluorescent labelling is a common approach to reveal the molecular details of cellular uptake, internalisation, transport, distribution processes in biological systems. The conjugation with a fluorescent moiety might affect relevant physico-chemical and in vitro transport properties of the bioactive component. A representative set of seven cationic peptides-including cell-penetrating peptides as well as antimicrobial peptides and synthetic derivatives-was selected for our comparative study. Membrane affinity of the peptides and their 5(6)-carboxyfluorescein (Cf) derivatives was determined quantitatively and compared applying Langmuir monolayer of zwitterionic (DPPC) and negatively charged (DPPC + DPPG) lipids as cell membrane models. The interaction with neutral lipid layer is mainly governed by the overall hydrophobicity of the molecule which is remarkably increased by Cf-conjugation for the most hydrophobic Magainin, Melittin and Transportan. A significantly enhanced membrane affinity was detected in negatively charged lipid model monolayer for all of the peptides since the combination of electrostatic and hydrophobic interaction is active in that case. The Cf-conjugation improved the penetration ability of Penetratin and Dhvar4 suggesting that both the highly charged character (Z/n) and the increased hydrophobicity by Cf-conjugation present important contribution to membrane interaction. This effect might also responsible for the observed high in vitro internalisation rate of Penetratin and Dhvar4, while according to in vitro studies they did not cause damage of cell membrane. From the experiments with the given seven cationic peptides, it can be concluded that the Cf-conjugation alters the degree of membrane interaction of such peptides which are moderately hydrophobic and highly charged.

iBCE-EL: A New Ensemble Learning Framework for Improved Linear B-Cell Epitope Prediction

Identification of B-cell epitopes (BCEs) is a fundamental step for epitope-based vaccine development, antibody production, and disease prevention and diagnosis. Due to the avalanche of protein sequence data discovered in postgenomic age, it is essential to develop an automated computational method to enable fast and accurate identification of novel BCEs within vast number of candidate proteins and peptides. Although several computational methods have been developed, their accuracy is unreliable. Thus, developing a reliable model with significant prediction improvements is highly desirable. In this study, we first constructed a non-redundant data set of 5,550 experimentally validated BCEs and 6,893 non-BCEs from the Immune Epitope Database. We then developed a novel ensemble learning framework for improved linear BCE predictor called iBCE-EL, a fusion of two independent predictors, namely, extremely randomized tree (ERT) and gradient boosting (GB) classifiers, which, respectively, uses a combination of physicochemical properties (PCP) and amino acid composition and a combination of dipeptide and PCP as input features. Cross-validation analysis on a benchmarking data set showed that iBCE-EL performed better than individual classifiers (ERT and GB), with a Matthews correlation coefficient (MCC) of 0.454. Furthermore, we evaluated the performance of iBCE-EL on the independent data set. Results show that iBCE-EL significantly outperformed the state-of-the-art method with an MCC of 0.463. To the best of our knowledge, iBCE-EL is the first ensemble method for linear BCEs prediction. iBCE-EL was implemented in a web-based platform, which is available at http://thegleelab.org/iBCE-EL. iBCE-EL contains two prediction modes. The first one identifying peptide sequences as BCEs or non-BCEs, while later one is aimed at providing users with the option of mining potential BCEs from protein sequences.

A coarse-grained approach to studying the interactions of the antimicrobial peptides aurein 1.2 and maculatin 1.1 with POPG/POPE lipid mixtures

In the present work we investigated the differential interactions of the antimicrobial peptides (AMPs) aurein 1.2 and maculatin 1.1 with a bilayer composed of a mixture of the lipids 1-palmitoyl-2-oleoyl-sn-glycero-3-phospho-(1'-rac-glycerol) (POPG) and 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoethanolamine (POPE). We carried out molecular dynamics (MD) simulations using a coarse-grained approach within the MARTINI force field. The POPE/POPG mixture was used as a simple model of a bacterial (prokaryotic cell) membrane. The results were compared with our previous findings for structures of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC), a representative lipid of mammalian cells. We started the simulations of the peptide-lipid system from two different initial conditions: peptides in water and peptides inside the hydrophobic core of the membrane, employing a pre-assembled lipid bilayer in both cases. Our results show similarities and differences regarding the molecular behavior of the peptides in POPE/POPG in comparison to their behavior in a POPC membrane. For instance, aurein 1.2 molecules can adopt similar pore-like structures on both POPG/POPE and POPC membranes, but the peptides are found deeper in the hydrophobic core in the former. Maculatin 1.1 molecules, in turn, achieve very similar structures in both kinds of bilayers: they have a strong tendency to form clusters and induce curvature. Therefore, the results of this study provide insight into the mechanisms of action of these two peptides in membrane leakage, which allows organisms to protect themselves against potentially harmful bacteria. Graphical Abstract Aurein pore structure (green) in a lipid bilayer composed by POPE (blue) and POPG (red) mixture. It is possible to see water beads (light blue) inside the pore.

Effect of sequential C‐terminal tryptophans on green fluorescent protein fluorescence

The effect of the addition of sequential C‐terminal tryptophan residues on the fluorescence intensity of GFP was investigated. Tandem repeats of six tryptophan residues markedly decreased fluorescence intensity. This phenomenon is likely to occur because of the inhibition of GFP folding, resulting in insolubility. Exploiting this phenomenon, we constructed a cloning vector that facilitates the identification of recombinant colonies of Escherichia coli by the activation of GFP.

Analysis of the Genome Sequence and Prediction of B-Cell Epitopes of the Envelope Protein of Middle East Respiratory Syndrome-Coronavirus

The outbreak of Middle East respiratory syndrome-coronavirus (MERS-CoV) in South Korea in April 2015 led to 186 infections and 37 deaths by the end of October 2015. MERS-CoV was isolated from the imported patient in China. The envelope (E) protein, a small structural protein of MERS-CoV, plays an important role in host recognition and infection. To identify the conserved epitopes of the E protein, sequence analysis was performed by comparing the E proteins from 42 MERS-CoV strains that triggered severe pandemics and infected humans in the past. To predict the potential B cell epitopes of E protein, three most effective online epitope prediction programs, the ABCpred, Bepipred, and Protean programs from the LaserGene software were used. All the nucleotides and amino acids sequences were obtained from the NCBI Database. One potential epitope with a suitable length (amino acids 58-82) was confirmed and predicted to be highly antigenic. This epitope had scores of >0.80 in ABCpred and level 0.35 in Bepipred programs. Due to the lack of X-ray crystal structure of the E protein in the PDB database, the simulated 3D structure of the E protein were also predicted using PHYRE 2 and Pymol programs. In conclusion, using bioinformatics methods, we analyzed the genome sequence of MERS-CoV and identified a potential B-cell epitope of the E protein, which might significantly improve our current MERS vaccine development strategies.

Structural predication and antigenic analysis of Toxoplasma gondii ROP20

Toxoplasma gondii infects almost all the warm-blooded animals. ROP20 protein is expressed in the rhoptry of Toxoplasma gondii. In this study, the secondary structure of ROP20 was analyzed using SMART software. We constructed and analyzed the 3D model of ROP20 protein using SWISS-MODEL online procedure and Visual Molecular Dynamics (VMD) software. The structure analysis fully indicated that ROP20 protein is an important member of the ROP family. Furthermore, We used DNASTAR software and Epitope Database online service to analyze liner-B cell epitopes and T-cell epitopes of ROP20 protein. All the analysis results of ROP20 protein can provide positive information on treatment and vaccine for toxoplasmosis. Moreover, ROP20 gene was obtained from PCR, and a recombinant eukaryotic expression vector (pEGFP-C1-ROP20) was constructed in the following study. After restriction enzyme digestion, the constructed plasmid was transfected into HEK 293-T cells. The RT-PCR result indicated that the recombinant plasmid could transcribe successfully in HEK 293-T cell. The results of western blotting indicated the expressed proteins can be recognized by anti-STAg mouse sera.

Relationship of epitope glycosylation and other properties of blood group proteins to the immunogenicity of blood group antigens

BACKGROUND

The intrinsic properties of polypeptide blood group antigens that determine their relative immunogenicities are unknown. Because size, composition, charge, dose, and epitope glycosylation affect the immunogenicity of other polypeptides, we examined whether similar properties were related to the immunogenicity of blood group antigens.

STUDY DESIGN AND METHODS

Amino acid (AA) sequences of antithetical blood group antigens were searched for N- and O-glycosylation sites. Regression analysis was carried out to determine whether blood group protein properties, including total and ectodomain size, red blood cell (RBC) antigen site density, number of mismatched AAs between an antigen and its closest homolog, and differences in mass, charge, and hydrophobicity of the mismatched AAs, were related to immunogenicity.

RESULTS

The immunogenicities of non-RhD polypeptide antigens were directly related to the total and ectodomain sizes of their carrier proteins. A negative power relationship existed between RBC antigen site density and immunogenicity, such that the most immunogenic antigens had the lowest site density. The strong immunogenicity of RhD was related to the number of AA mismatches between RhD and RhCE, to their cumulative hydrophobicity and electrostatic mismatch scores, and the cumulative AA mass difference. No N- or O-glycosylation differences were predicted for antithetical or homologous antigens, other than a previously known N-glycosylation difference between K and k.

CONCLUSION

Epitope glycosylation appeared not to be a determinant of immunogenicity for blood group antigens, except possibly for K. The immunogenicity of blood group antigens was positively related to total and ectodomain sizes of blood group proteins and negatively related to antigen site density. Such findings should be considered hypothesis generating for future, more definitive studies.

Prediction of HIV Drug Resistance by Combining Sequence and Structural Properties

Drug resistance is a major obstacle faced by therapist in treating HIV infected patients. The reason behind these phenomena is either protein mutation or the changes in gene expression level that induces resistance to drug treatments. These mutations affect the drug binding activity, hence resulting in failure of treatment. Therefore, it is necessary to conduct resistance testing in order to carry out HIV effective therapy. This study combines both sequence and structural features for predicting HIV resistance by applying SVM and Random Forests classifiers. The model was tested on the mutants of HIV-1 protease and reverse transcriptase. Taken together the features we have used in our method, total contact energies among multiple mutations have a strong impact in predicting resistance as they are crucial in understanding the interactions of HIV mutants. The combination of sequence-structure features offers high accuracy with support vector machines as compared to Random Forests classifier. Both single and acquisition of multiple mutations are important in predicting HIV resistance to certain drug treatments. We have discovered the practicality of these features; hence, these can be used in the future to predict resistance for other complex diseases.

Identification of Allergenic Epitopes and Critical Amino Acids of Major Allergens in Chinese Shrimp ( Penaeus chinensis) by Immunoinformatics Coupled with Competitive-Binding Strategy

Chinese shrimp ( Penaeus chinensis) is widely cultured and consumed in Asia but is also a major food allergen locally. Although they may be the foundation for preventing and treating allergies, the allergenic epitopes of the major allergens tropomyosin (TM) and arginine kinase (AK) in Penaeus chinensis have not been identified. Here, we applied Immunoinfo-CB (immunoinformatics coupled with competitive-binding strategy) to address the point. Potential allergenic epitopes of TM and AK were predicted by multiple immunoinformatics tools, followed by validating with inhibitory dot-blot assay, indirect competition ELISA, and mast cell degranulation assay. Furthermore, critical amino acids in allergenic epitopes were also identified by Immunoinfo-CB. Our findings provide new insight into allergenic epitopes and critical amino acids of TM and AK responsible for the anaphylactic response. The Immunoinfo-CB therefore offers promises for characterization of IgE-binding epitopes that might be used as new targets for immunotherapy of food allergy.

Precision compatibilizers for composites: in-between self-aggregation, surfaces recognition and interface stabilization

Peptide-polymer conjugates are applied as interface stabilizers that are precisely tuned to recognize the surfaces of inorganic constituents in composites. A set of peptide sequences is usually selected through phage-display and a strategy is presented for the identification of the most effective sequences through the evaluation of secondary interactions, including not only surface binding but also solubility and self-aggregation tendency.

Proteome-wide mapping of immune features onto Plasmodium protein three-dimensional structures

Humoral immune responses against the malaria parasite are an important component of a protective immune response. Antibodies are often directed towards conformational epitopes, and the native structure of the antigenic region is usually critical for antibody recognition. We examined the structural features of various Plasmodium antigens that may impact on epitope location, by performing a comprehensive analysis of known and modelled structures from P. falciparum. Examining the location of known polymorphisms over all available structures, we observed a strong propensity for polymorphic residues to be exposed on the surface and to occur in particular secondary structure segments such as hydrogen-bonded turns. We also utilised established prediction algorithms for B-cell epitopes and MHC class II binding peptides, examining predicted epitopes in relation to known polymorphic sites within structured regions. Finally, we used the available structures to examine polymorphic hotspots and Tajima's D values using a spatial averaging approach. We identified a region of PfAMA1 involving both domains II and III under a high degree of balancing selection relative to the rest of the protein. In summary, we developed general methods for examining how sequence-based features relate to one another in three-dimensional space and applied these methods to key P. falciparum antigens.

Analysis of Evolutionarily Independent Protein-RNA Complexes Yields a Criterion to Evaluate the Relevance of Prebiotic Scenarios

A central difficulty facing study of the origin of life on Earth is evaluating the relevance of different proposed prebiotic scenarios. Perhaps the most established feature of the origin of life was the progression through an RNA World, a prebiotic stage dominated by functional RNA. We use the appearance of proteins in the RNA World to understand the prebiotic milieu and develop a criterion to evaluate proposed synthetic scenarios. Current consensus suggests that the earliest amino acids of the genetic code were anionic or small hydrophobic or polar amino acids. However, the ability to interact with the RNA World would have been a crucial feature of early proteins. To determine which amino acids would be important for the RNA World, we analyze non-biological protein-aptamer complexes in which the RNA or DNA is the result of in vitro evolution. This approach avoids confounding effects of biological context and evolutionary history. We use bioinformatic analysis and molecular dynamics simulations to characterize these complexes. We find that positively charged and aromatic amino acids are over-represented whereas small hydrophobic amino acids are under-represented. Binding enthalpy is found to be primarily electrostatic, with positively charged amino acids contributing cooperatively to binding enthalpy. Arginine dominates all modes of interaction at the interface. These results suggest that proposed prebiotic syntheses must be compatible with cationic amino acids, particularly arginine or a biophysically similar amino acid, in order to be relevant to the invention of protein by the RNA World.

S-FLN: A sequence-based hierarchical approach for functional linkage network construction

The functional linkage network (FLN) construction is a primary and important step in drug discovery and disease gene prioritization methods. In order to construct FLN, several methods have been introduced based on integration of various biological data. Although, there are impressive ideas behind these methods, they suffer from low quality of the biological data. In this paper, a hierarchical sequence-based approach is proposed to construct FLN. The proposed approach, denoted as S-FLN (Sequence-based Functional Linkage Network), uses the sequence of proteins as the primary data in three main steps. Firstly, the physicochemical properties of amino-acids are employed to describe the functionality of proteins. As the sequence of proteins is a more comprehensive and accurate primary data, more reliable relations are achieved. Secondly, seven different descriptor methods are used to extract feature vectors from the proteins sequences. Advantage of different descriptor methods lead to obtain diverse ensemble learners in the next step. Finally, a two-layer ensemble learning structure is proposed to calculated the score of protein pairs. The proposed approach has been evaluated using two biological datasets, S.Cerevisiae and H.Pylori, and resulted in 93.9% and 91.15% precision rates, respectively. The results of various experiments indicate the efficiency and validity of the proposed approach.