Abstract
Background:
Neisseria meningitidis, a life-threatening human pathogen with the potential to cause large epidemics, can be isolated from the nasopharynx of 5–15% of adults. The aim of the current study was to evaluate biophysical and biochemical properties and immunological aspects of chimeric acyl-carrier protein-macrophage infectivity potentiator protein-type IV pilus biogenesis protein antigen (ACP-MIP-PilQ) from N. meningitidis serogroup B strain.
Methods:
Biochemical properties and multiple alignments were predicted by appropriate web servers. Secondary molecular structures were predicted based on Chou and Fasman, Garnier-Osguthorpe-Robson, and Neural Network methods. Tertiary modeling elucidated conformational properties of the chimeric protein. Proteasome cleavage and transporter associated with antigen processing (TAP) binding sites, and T- and B-cell antigenic epitopes, were predicted using bioinformatic web servers.
Results:
Based on our in silico and immunoinformatics analyses, the ACP-MIP-PilQ protein (AMP) can induce high-level cross-strain bactericidal activity. In addition, several immune proteasomal cleavage sites were detected. The 22 epitopes associated with MHC class I and class II (DR) alleles were confirmed in the AMP. Thirty linear B-cell epitopes as antigenic regions were predicted from the full-length protein.
Conclusion:
All predicted properties of the AMP indicate it could be a good candidate for further immunological
in vitro and in vivo studies.
Key Words: Chimeric protein, In silico, Neisseria meningitides, serogroup B, Vaccine
Introduction
Neisseria meningitidis (N. meningitidis) is an airborne, life-threatening pathogen that infects humans with an infectivity rate of approximately 1%. Thirteen serogroups of N. meningitidis have been classified based on the capsular immunologic reactivity (1). Five serotypes, including A, B, C, W-135, and Y are responsible for most clinical cases with significant morbidity and mortality (2, 3). Humans are the only host of N. meningitidis. Conjugate vaccines using two purified proteins target serogroups A, C, W-135, and Y. No vaccine against serogroup B presently exists, although two vaccines are in developmental stages (4, 5). The recently described 13-kDa adhesion complex protein (ACP) from N. meningitidis serogroup B strain MC58 has been proposed as a potential vaccine candidate (6). Based on amino acid sequence analysis from 13 meningococcal strains, three distinct ACP molecule types, dubbed I, II, and III, have been distinguished. The APC molecules in the 13 strains share >98% similarity, and induce cross-strain bactericidal activity and high levels of serum bactericidal activity. In addition, ACP as an adhesin plays a critical role during host-pathogen interactions, making it a good vaccine candidate (6). Macrophage infectivity potentiator protein (MIP) is a highly-expressed 29-kDa outer membrane protein in N. meningitidis serogroup B strain MC58 and is contributes to cross-strain serum bactericidal activity in N. meningitidis infections (7, 8). The N. meningitidis PilQ as Type IV pilus biogenesis protein is antigenically-conserved and abundant outer membrane protein (9, 10).
The aim of our study was to evaluate biophysical and biochemical properies and immunological aspects of the ACP-MIP-PilQ (AMP) from N. meningitidis serogroup B strain using in silico and immune informatic studies.
Materials and Methods
Sequence analysis
In this study three protein candidates; ACP with accession number NP_275083.1, MIP with accession number NP_274574.1, and PilQ with accession number NP_274809.1, from N. meningitidis serogroup B strain MC58, were selected. The nucleotide and amino acid sequences of the three candidates were retrieved in FASTA format from the gene bank (http://www.ncbi.nlm.nih.gov) for further analyses. Multiple sequences were aligned using ClustalW2 software (www.ebi.ac.uk/Tools/msa) and each sequence was BLASTed on the (http://www.ncbi.nlm.nih.gov/BLAST/) server. In protein drug development, the purpose of creating chimeric proteins is to impart several properties and target multiple platforms together; hence, we integrated three separate functional exposed domains using four helix-forming peptides Glutamic acid- Alanine- Alanine- Alanine- Lysine sequence, (EAAAK)4 as linker (11).
Primary structure and physico-chemical parameters of AMP
In this study AMP was analyzed using the Expasy ProtParam server (http://web.expasy.org/protparam/) (12). Physico-chemical parameters such as theoretical isoelectric point (pI), molecular weight, and the numbers of positively- (KRH) and negatively- (DE) charged amino acids were determined. Hydrophobic, hydrophilic, aromatic, and hydroxyl amino acids were identified, and the instability and aliphatic indexes, estimated charges at pH 7.00, and grand average of hydropathy (GRAVY) were predicted. All physico-chemical predictions were evaluated using the PBIL-IBCP Lyon-Gerland server (http://pbil.ibcp.fr/htm/index.php) and ExPASy's prediction tools (http://web.expasy.org/). Conserved domains were predicted by NCBI's Conserved Domain Database (http://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi).
Secondary and tertiary molecular structure of AMP
Institute for Genomics Bioinformatics (IGB) (http://www.igb.uci.edu) and Center of Informational Biology (http://cib.cf.ocha.ac.jp/index-e.xml) servers based on Chou and Fasman(13), Garnier-Osguthorpe-Robson (14), and neural network methods (15). The alpha helix, beta sheet, and random coil structure of AMP was predicted by the MINNOU server (16). The solubility of AMP was predicted with 94% accuracy. The alpha, beta, and gamma turns were predicted based on the neural network training on PSI-BLAST
(http://www.imtech.res.in/). Transmembrane helices were predicted on the TMHMM data bank (17). Possible presence of transmembrane regions, a signal peptide, and phosphorylation and N-glycosylation sites were predicted using the Protter web server (http://wlab.ethz.ch/protter) (18). The three-dimensional (3D) structure of AMP was predicted by the I-TASSER web server (http://zhanglab.ccmb.med.umich.edu/I-TASSER/). The prediction of the protein’s tertiary molecular structure was based on the sequence homology comparison (19, 20).
Proteasome cleavage sites and TAP binding predictions
Proteasome (model 1-SE 0.874, SP 0.534) cleavage of the chimeric protein was predicted by the (http://imed.med.ucm.es) server (21). The transporter associated with antigen processing (TAP) binding affinity was predicted by the TAPPred online server (http://www.imtech.res.in/raghava/tappred/service) (22).
Epitope Mapping
The ProPred-I server
(http://www.imtech.res.in/raghava/propred1/) predicted 53 alleles of MHC class I binding sites (23) and the ProPred server (http://www.imtech.res.in/raghava/propred/) predicted 51 alleles of MHC class II HLA-DR binding sites associated with the AMP (24). The AMP dependent B-cell epitopes were predicted by the IEDB-AR server (http://tools.immuneepitope.org).
Results
The sequences retrieved from the BLASTp program were associated with N. meningitidis. Tables 1, 2, and 3 summarize BLASTp results of APC, MIP, and PilQ, respectively. The NCBI BLASTp software indicated that the retrieved MIP sequence was related to peptidyl prolyl isomerase, a fraction of the high-abundance N. meningitidis MIP. The MIP amino acid sequences were 99 to 100% identical between N. meningitidis strains.
Table 1.
Summary of BLASTp of ACP from N. meningitides
| Sequence ID | Length | Max score | Total score | Query cover | E value | Identities | Positive | Gap |
|---|---|---|---|---|---|---|---|---|
| NP_275083.1 | 124 | 254 | 254 | 100% | 2e-87 | 100% | 100% | 0% |
| WP_002215074.1 | 124 | 252 | 252 | 100% | 1e-86 | 99% | 100% | 0% |
| WP_012222154.1 | 186 | 253 | 253 | 100% | 5e-86 | 100% | 100% | 0% |
| WP_011799040.1 | 186 | 251 | 251 | 100% | 2e-85 | 99% | 100% | 0% |
Table 2.
Summary of BLASTp of MIP from N. meningitides
| Sequence ID | Length | Max score | Total score | Query cover | E value | Identities | Positive | Gap |
|---|---|---|---|---|---|---|---|---|
| CBA04183.1 | 302 | 549 | 549 | 100% | 0.0 | 100% | 100% | 0% |
| WP_002212827.1 | 272 | 548 | 548 | 100% | 0.0 | 100% | 100% | 0% |
| WP_002239187.1 | 272 | 547 | 547 | 100% | 0.0 | 99% | 100% | 0% |
| WP_002236000.1 | 272 | 546 | 546 | 100% | 0.0 | 99% | 100% | 0% |
Table 3.
Summary of BLASTp of PilQ from N. meningitides
| Sequence ID | Max score | Total score | Query cover | E value | Identities | Positive | Gap |
|---|---|---|---|---|---|---|---|
| WP_002249070.1 | 709 | 709 | 100% | 0.0 | 100% | 100% | 0% |
| WP_009348000.1 | 709 | 709 | 100% | 0.0 | 100% | 100% | 0% |
| WP_002225652.1 | 710 | 710 | 100% | 0.0 | 100% | 100% | 0% |
| EOC56528.1 | 709 | 709 | 100% | 0.0 | 100% | 100% | 0% |
| WP_002249070.1 | 709 | 709 | 100% | 0.0 | 100% | 100% | 0% |
Fig. 1.
Schematic of antigenic chimera of AMP genes with (EAAAK)4 linkers
The multiple alignments using ClustalW2 software revealed many conserved regions within the selected regions of ACP, MIP, and PilQ among most N. meningitidis serogroups. The multiple alignments of each protein are shown in supplementary Figs. S1, S2, and S3.
Primary structure analysis
The AMP contained 786 amino acids. Of these, 100 are positively-charged, and 89 are negatively charged.
Its molecular weight is 83558.3 Daltons and the theoretical pI is 8.94. The in vitro the estimated half-life in mammalian reticulocytes is about 30 hours, whereas the in vivo estimated half-life in Escherichia coli was predicted as less than 10 hours. The AMP also contains 277 hydrophobic (ALIVMW), 327 hydrophilic (DEKNQRST), 41 aromatic (FYW), and 126 hydroxyl (STY) residues. The amino acid composition is summarized in Table 4.
Table 4.
The amino acid composition of AMP
| Amino acid | No. of residues | % of residues | Amino acid | No. of residues | % of residues |
|---|---|---|---|---|---|
| Ala (A) | 100 | 12.7% | Lys (K) | 78 | 9.9% |
| Arg (R) | 22 | 2.8% | Met (M) | 17 | 2.2% |
| Asn (N) | 39 | 5.0% | Phe (F) | 21 | 2.7% |
| Asp (D) | 38 | 4.8% | Pro (P) | 27 | 3.4% |
| Cys (C) | 5 | 0.6% | Ser (S) | 50 | 6.4% |
| Gln (Q) | 35 | 4.5% | Thr (T) | 59 | 7.5% |
| Glu (E) | 51 | 6.5% | Trp (W) | 3 | 0.4% |
| Gly (G) | 66 | 8.4% | Tyr (Y) | 17 | 2.2% |
| His (H) | 1 | 0.1% | Val (V) | 48 | 6.1% |
| Ile (I) | 49 | 6.2% | Pyll (O) | 0 | 0.0% |
| Leu (L) | 60 | 7.6% | Sec (U) | 0 | 0.0% |
The conserved domains of the AMP were predicted using PRS-BLAST. The protein contains six distinct functional regions. The first and forth domains were identical to bacterial type II and III secretionsystems. The second, third, and fifth domains belonged to the isomerase family. The predicted domains are given in Table 5.
Table 5.
Predicted domain of the recombinant protein by PRS-PLAST
| Name | Accession number | Description | Interval | E-value |
|---|---|---|---|---|
| Secretin | pfam00263 | Bacterial type II and III secretion system protein | 617-778 | 2.11e-53 |
| FKBP_N | pfam01346 | FKBP-type peptidyl-prolylisomerase | 187-299 | 1.34e-37 |
| FKBP_C | pfam00254 | FKBP-type peptidyl-prolylcis-trans isomerase | 306-394 | 2.15e-32 |
| Secretin_N | pfam03958 | Bacterial type II/III secretion system short domain | 460-529 | 1.01e-11 |
| FkpA | COG0545 | FKBP-type peptidyl-prolylcis-trans isomerases | 186-396 | 8.09e-76 |
| pilus_MshL | TIGR02519 | Pilus (MSHA type) biogenesis protein MshL | 498-777 | 3.47e-34 |
Secondary structure prediction
The secondary structure prediction showed that the AMP contains 15 alpha helixes, 33 beta strands, and 48 random coils. The secondary structure was predicted using the MINNNOU server (Fig. 3). The joint results from both the IGB server (Fig. 2) and the MINNNOU web site were identical.
Fig. 3.
The secondary structure prediction of chimeric AMP based on relative solvent accessibility
Fig. 2.
The Joint result of secondary structure prediction based on Chou and Fasman, Garnier-Osguthorpe-Robson, and neural network methods
The secondary structure profile of AMP, according to the position and number of each structure, is shown in Table 6. No transmembrane helix topology was identified in the sequence using the TMHMM data bank. The sequence of AMP also was analyzed for putative signal peptide, N-glycosylation, and phosphorylation sites using the Protter web server. The Protter analysis predicted an N-terminal signal peptide region (red) from amino acids 1 to 21, and five N-linked glycosylation sites (green) at positions 26, 384, 564, 682, and 703. No phosphorylation sites or transmembrane regions were identified. The results are illustrated on supplement S4.
Table 6.
The secondary structure profile of AMP according to the position of each conformation
| Secondary structure | Position |
|---|---|
| Alpha helix (Hh) | 2-21,29-32,124-164,195-214,222-234,242-282,348-355,435-455,470-479,513-525,531-539,603-619,750-755,775-776,783-786 |
| Extended strand (Ee) | 44-48,68-73,81-83,91,107-110,116-118,289-290,295-301,313=322,327-328,338-341,345,361-366,387-392,426-428,460-466,497-500,506-510,540-542,552-555,600-602,625-628,632-634,640-644,647-654,662-679,684-692,707-709,714-720,725-729,731-732,743-745,767-772 |
| Random coil (Cc) | 22-28,33-43,49-67,74-80,84-90.92-106,111-115,119-123,165-194,215-221,235-241,283-288,291-294,302-312,323-326,329-337,342-344,346-347,356-360,367-386,393-425,429-434,456-459,467-469,480-496,501-505,511-512,526-530,543-551,556-599,620-624,629-631,635-639,645-646,655-661,680-683,693-706,710-713,721-724,730,733-742,746-749,756-766,773-774, 777-782 |
| Alpha turn (Aa) | 21-30,76-80,96-105,171-190,306-310,331-335,356-360,371-385,421-430,481-495,561-565,581-600,656-660,736-745,761-765,781-785 |
| Beta turn (Tt) | 1-2,17-33,36-42,46-56,63-67,73-90,94-107,111-116,129-141,168-192,210-219,232-240,265-270,283-294,300-312,322-326,330-345,356-360,368-385,396-406,415-436,448-454,464-468,477-496,501-505,525-529,547-550,556-600,606-611,619-629,635-639,643-651,655-660,679-683,691-704,707-716,720-724,733-750,755-765,771-786 |
| Gamma turn (Gg) | 1-3,15-17,19-33,39-42,51-57,64-66,74-81,85-89,94-106,111-115,120-127,131-134,136-141,167-193,212-221,234-241,266-271,282-288,290-294,301-311,323-326,330-337,341-346,356-360,371-385,397-407,417-436,448-454,465-469,479-496,502-505,527-529,557-568,572-574,576-600,607-609,621-624,636-638,656-660,680-683,692-696,698-704,721-724,734-750,757-765,778-786 |
Hydropathy prediction
Hydropathy was predicted by two Kyte-Doolittle and Hopp-Woods hydropathy plots, which can indicate potential transmembrane and surface regions.
The positive values in the Kyte-Doolittle plot indicate hydrophobic amino acids, which may be parts of alpha helixes spanning lipid bilayers, whereas the Hopp-Woods scale (25) indicates hydrophilic, residues and use to identify potential antigenic sites in protein sequences.
The Kyte-Doolittle plot of the AMP (Fig. 4) showed six short significant hydrophobic regions (gray) around amino acids 150, 390, 500, 600, 670, and 760. In the Hopp-Woods scale, the negative values assigned to apolar residues; thus, antigenic sites are likely to be in the positive region. In Fig. 5, the Hopp-Woods plot illustrates nine potentially antigenic areas in the chimer.
Fig. 4.
The Kyte-Doolittle plot of the AMP
Fig. 5.
The Hopp-Woods plot of AMP
In proteomics studies, tertiary structure refers to geometric shape, and is symbolic of single-, double-, or triple-bonded protein molecules. The I-TASSER server is an on-line platform for protein structure predictions. The 3D model is based on multiple-threading alignments and iterative template fragment assembly simulations with the goal to provide the most accurate structural and functional predictions using state-of-the-art algorithms. The 3D structure of the AMP is shown in Fig. 6.
Fig. 6.
The 3D structure of the AMP
Proteasome cleavage sites and TAP binding predictions
Proteasome degradation is critical to the function of the adaptive immune system. Antigenic peptides are displayed by the major histocompatibility complex (MHC) class I proteins on the surface of antigen-presenting cells. The analysis predicted 203 proteasome and 367 immunoproteasome cleavage sites in the AMP; of these, 192 sites were identified as both proteasome and immunoproteasome cleavage sites. The TAP transporter is found in the endoplasmic reticulum (ER) organelle, associated with the peptide-loading complex (PLC). The ten high affinity TAP-binding sequences associated with the AMP are shown in Table 7.
Table 7.
TAP transporter binding affinity of AMP
| Rank | Sequence | Position | Score | Predicted Affinity |
|---|---|---|---|---|
| 1 | AKMNTIFKI | 143-152 | 8.395 | High |
| 2 | EEFRSILRL | 471-479 | 8.130 | High |
| 3 | AQEVMMKFL | 245-253 | 7.585 | High |
| 4 | AAAKMNTIF | 141-149 | 7.430 | High |
| 5 | TVAKKTVSY | 28-36 | 7.398 | High |
| 6 | KRVQMPVNL | 66-74 | 7.327 | High |
| 7 | GTAGNSLRY | 778-786 | 7.135 | High |
| 8 | KEAKIESGY | 638-646 | 7.102 | High |
| 9 | AEIDLKVFT | 218-226 | 7.035 | High |
| 10 | ATFYIPSNL | 362-370 | 7.002 | High |
Prediction of T-cell, B-cell, and antigenic epitopes
The ProPred-I server predicted 22 epitopes in the full length of AMP which recognized by MHC I alleles with a cutoff of 0.05. The 53 unique human MHC I alleles were involved in the prediction. The prediction was based on the level of binding affinity for the most frequent human MHC I alleles. Among the 53 MHC I alleles, SALTLSAAL, VTVEYEGRL, WGAETKINL, NTLTKVPLL, SVIEKFRKL were the most important epitopes recognized by the most number of human MHC I alleles.
In addition analysis of binding affinity of the AMP for most frequent human DR MHC II alleles reveal that 22 AMP epitopes bind to some of human DR MHC II alleles with a cutoff of 0.04. Table 8 shows conformational high affinity epitopes in the AMP sorted by matching position.
Table 8.
Prediction of conformational high affinity epitopes in the AMP recognized by human MHC alleles
|
Predicted epitopes
51 human DR MHC II alleles (Cutoff 0.04) |
Number of MHC class II
binding alleles |
Matching Position |
Predicted epitopes
53 unique MHC I alleles (Cutoff 0.05) |
Number of MHC class I binding alleles | Matching Position |
|---|---|---|---|---|---|
| MKLLTTAIL | 34 | 1-9 | AILSSAIAL | 13 | 7-15 |
| ILSSAIALS | 19 | 8-16 | YGKEGGYVL | 13 | 84-92 |
| VNLDKSDNV | 12 | 72-80 | KEAAAKEAA | 7 | 421-429 |
| YVLGTGVMD | 11 | 90-98 | SALTLSAAL | 26 | 152-160 |
| YRKQPIMIT | 18 | 102-110 | APASASEPA | 12 | 171-179 |
| IVFKDCSPR | 16 | 116-124 | KEQGAEIDL | 11 | 214-222 |
| MNTIFKISAL | 15 | 145-154 | AQEVMMKFL | 10 | 245-252 |
| IFKISALTLS | 33 | 148-157 | EAFLKENAA | 14 | 276-284 |
| VMMKFLQEQ | 21 | 248-256 | VTVEYEGRL | 16 | 314-322 |
| LQYKITKQG | 17 | 295-303 | ELLAKDKAL | 14 | 437-445 |
| LVFDVKLVK | 27 | 387-395 | LISGRGSVL | 8 | 491-499 |
| LAKDKALLQ | 21 | 439-447 | SVIEKFRKL | 15 | 514-522 |
| FQLKYKNVEE | 18 | 463-472 | AADGFSRDL | 12 | 542-550 |
| FRSILRLDN | 35 | 473-481 | FSRDLGVKF | 9 | 546-554 |
| VLIDPATNT | 11 | 498-506 | FGATGKKKL | 12 | 554-562 |
| IVTDTRSVI | 20 | 508-516 | WGAETKINL | 16 | 583-592 |
| LKNDTSAFG | 11 | 562-570 | AANSISLVR | 14 | 596-604 |
| LVRAISSGAL | 30 | 602-611 | ESLSKTKTL | 13 | 619-627 |
| YEIPFTVTS | 14 | 646-654 | KTLANPRVL | 13 | 625-633 |
| IIMTVKINK | 24 | 685-693 | GGSSTNTEL | 9 | 658-666 |
| ILCISTKNL | 15 | 706-714 | ILCISTKNL | 8 | 706-714 |
| LLIFITPRIMG | 45 | 768-778 | NTLTKVPLL | 16 | 738-746 |
B-cell epitopes are antigenic regions that can induce B-cell responses. They generally consist of groups of amino acids that lie close together on the protein surface and determine antigenicity. B-cell receptors (antibodies) exclusively recognize these regions. Predicted linear B-cell epitopes are presented in Table 9.
Table 9.
Predicted linear epitopes in the AMP
| No | Position | Peptide | Length | No. | Position | Peptide | Length |
|---|---|---|---|---|---|---|---|
| 1 | 20-31 | AAAGTDNPTVAK | 12 | 16 | 423-441 | DIKKVNEAAAEAAAKE | 19 |
| 2 | 74-92 | VNLDKSDNVETFYGKEGGY | 19 | 17 | 489-497 | SILRLD N | 9 |
| 3 | 97-105 | GVMDGKSYR | 9 | 18 | 552-556 | EARIV | 5 |
| 4 | 123-145 | CSPREAAAKEAAAKEAAAKEA | 23 | 19 | 564-579 | FSRDLGVKFGATGKKK | 16 |
| 5 | 168-200 | ACGKKEAAPASASEPAAASSAQGDTSSIGST | 33 | 20 | 583-595 | DTSAFGWGVNSGF | 13 |
| 6 | 216-222 | LKQMKEQ | 7 | 21 | 628-633 | SGALNL | 6 |
| 7 | 241-249 | GKEIKM T | 9 | 22 | 635-638 | LSAS | 4 |
| 8 | 261-282 | LQEQQAKAVEKHKADAKANKEK | 22 | 23 | 642-655 | SKTKTLANPRVLTQ | 14 |
| 9 | 286-298 | FLKENAAKDGVKT | 13 | 24 | 665-676 | GYEIPFTVTSIA | 12 |
| 10 | 304-318 | QYKIT KQGEGKQP | 15 | 25 | 687-693 | ELKKAVL | 7 |
| 11 | 333-345 | IDGTVFDSSKANG | 13 | 26 | 703-713 | PDGQIIMTVKI | 11 |
| 12 | 352-356 | LSQVI | 5 | 27 | 730-733 | CIST | 4 |
| 13 | 363-368 | VQLLKE | 6 | 28 | 744-752 | ENGGTLIV | 9 |
| 14 | 377-390 | YIPSNLAYREQGAG | 14 | 29 | 771-776 | GDIPVI | 6 |
| 15 | 403-417 | VKLVKIGAPENAPAK | 15 | 30 | 790- 795 | RELLIF | 6 |
Discussion
Drug discovery is an expensive process involving high research and development costs and extensive clinical testing. Typical development time is estimated to be 10-15 years. Modern powerful computers and appropriate software can perform in silico analyses faster and more economically and predict the relative success of drug development more reliably than traditional methods (26). Currently no meningococcal vaccines against N. meningitidis serogroup B are available; therefore, on-hand vaccines are generally used during serogroup B outbreaks (30). Presently, most of in silico studies have focused on reverse vaccinology and genomic in silico analysis (27, 28), or concentrated on other components of bacteria such as the factor H binding protein (29) or detergent-derived outer membrane vesicles (30). The three dimensional structure shown that two helix-forming peptide linkers (EAAAK)4 well separated the three segment of the AMP. According to our results conformational turns, which represent likely antigenic sites, were found throughout the entire sequence of the AMP which can be used as a good stimulator of the immune system. The absence of a transmembrane lipophilic alpha helix introduces the AMP as a water-soluble protein. The presence of several high-affinity TAP-binding regions within the AMP may make it a good inducer of both the humoral and the cellular immune response. For this reason it is thought the AMP can be a good candidate for immunological in vitro and in vivo studies.
Acknowledgment
The current research was supported by Iran University of Medical Sciences, Tehran, Iran. The authors declare no competing interest.
References
- 1.Pace D, Pollard AJ, Messonier NE. Quadrivalent meningococcal conjugate vaccines. Vaccine. 2009;27 (Suppl 2):B30–41. doi: 10.1016/j.vaccine.2009.05.003. [DOI] [PubMed] [Google Scholar]
- 2.Brigham KS, Sandora TJ. Neisseria meningitidis: epidemiology, treatment and prevention in adolescents. Current opinion in pediatrics. 2009;21(4):437–43. doi: 10.1097/MOP.0b013e32832c9668. [DOI] [PubMed] [Google Scholar]
- 3.Woodard JL, Berman DM. Prevention of meningococcal disease. Fetal and pediatric pathology. 2006;25(6):311–9. doi: 10.1080/15513810701209538. [DOI] [PubMed] [Google Scholar]
- 4.Panatto D, Amicizia D, Lai PL, Gasparini R. Neisseria meningitidis B vaccines. Expert review of vaccines. 2011;10(9):1337–51. doi: 10.1586/erv.11.103. [DOI] [PubMed] [Google Scholar]
- 5.Safadi MA, Barros AP. Meningococcal conjugate vaccines: efficacy and new combinations. Jornal de pediatria. 2006;82(3 Suppl):S35–44. doi: 10.2223/JPED.1495. [DOI] [PubMed] [Google Scholar]
- 6.Hung M-C, Heckels JE, Christodoulides M. The adhesin complex protein (ACP) of Neisseria meningitidis is a new adhesin with vaccine potential. mBio. 2013;4(2) doi: 10.1128/mBio.00041-13. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Hung MC, Salim O, Williams JN, Heckels JE, Christodoulides M. The Neisseria meningitidis macrophage infectivity potentiator protein induces cross-strain serum bactericidal activity and is a potential serogroup B vaccine candidate. Infection and immunity. 2011;79(9):3784–91. doi: 10.1128/IAI.05019-11. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Christodoulides M, McGuinness BT, Heckels JE. Immunization with synthetic peptides containing epitopes of the class 1 outer-membrane protein of Neisseria meningitidis: production of bactericidal antibodies on immunization with a cyclic peptide. Journal of General Microbiology. 1993;139(8):1729–38. doi: 10.1099/00221287-139-8-1729. [DOI] [PubMed] [Google Scholar]
- 9.Collins RF, Frye SA, Kitmitto A, Ford RC, Tønjum T, Derrick JP. Structure of the Neisseria meningitidis outer membrane PilQ secretin complex at 12 Å resolution. Journal of Biological Chemistry. 2004;279(38):39750–6. doi: 10.1074/jbc.M405971200. [DOI] [PubMed] [Google Scholar]
- 10.Frye SA, Assalkhou R, Collins RF, Ford RC, Petersson C, Derrick JP, et al. Topology of the outer-membrane secretin PilQ from Neisseria meningitidis. Microbiology (Reading, England) 2006;152(Pt 12):3751–64. doi: 10.1099/mic.0.2006/000315-0. [DOI] [PubMed] [Google Scholar]
- 11.Wu YJ, Fan CY, Li YK. Protein purification involving a unique auto-cleavage feature of a repeated EAAAK peptide. Journal of chromatography B, Analytical technologies in the biomedical and life sciences. 2009;877(31):4015–21. doi: 10.1016/j.jchromb.2009.10.009. [DOI] [PubMed] [Google Scholar]
- 12.Gasteiger E, Hoogland C, Gattiker A, Wilkins MR, Appel RD, Bairoch A. Protein identification and analysis tools on the ExPASy server. In: Walker JM, editor. The Proteomics Protocols Handbook. Springer; 2005. pp. 571–607. [Google Scholar]
- 13.Chou PY, Fasman GD. Prediction of the secondary structure of proteins from their amino acid sequence. Advances in enzymology and related areas of molecular biology. 1978;47:45–148. doi: 10.1002/9780470122921.ch2. [DOI] [PubMed] [Google Scholar]
- 14.Garnier J, Osguthorpe DJ, Robson B. Analysis of the accuracy and implications of simple methods for predicting the secondary structure of globular proteins. Journal of molecular biology. 1978;120(1):97–120. doi: 10.1016/0022-2836(78)90297-8. [DOI] [PubMed] [Google Scholar]
- 15.Qian N, Sejnowski TJ. Predicting the secondary structure of globular proteins using neural network models. Journal of molecular biology. 1988;202(4):865–84. doi: 10.1016/0022-2836(88)90564-5. [DOI] [PubMed] [Google Scholar]
- 16.Cao B, Porollo A, Adamczak R, Jarrell M, Meller J. Enhanced recognition of protein transmembrane domains with prediction-based structural profiles. Bioinformatics (Oxford, England) 2006;22(3):303–9. doi: 10.1093/bioinformatics/bti784. [DOI] [PubMed] [Google Scholar]
- 17.Moller S, Croning MD, Apweiler R. Evaluation of methods for the prediction of membrane spanning regions. Bioinformatics (Oxford, England) 2001;17(7):646–53. doi: 10.1093/bioinformatics/17.7.646. [DOI] [PubMed] [Google Scholar]
- 18.Omasits U, Ahrens CH, Muller S, Wollscheid B. Protter: interactive protein feature visualization and integration with experimental proteomic data. Bioinformatics (Oxford, England) 2014;30(6):884–6. doi: 10.1093/bioinformatics/btt607. [DOI] [PubMed] [Google Scholar]
- 19.Roy A, Yang J, Zhang Y. COFACTOR: an accurate comparative algorithm for structure-based protein function annotation. Nucleic acids research. 2012;40(Web Server issue):W471–7. doi: 10.1093/nar/gks372. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Roy A, Kucukural A, Zhang Y. I-TASSER: a unified platform for automated protein structure and function prediction. Nature protocols. 2010;5(4):725–38. doi: 10.1038/nprot.2010.5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Diez-Rivero CM, Lafuente EM, Reche PA. Computational analysis and modeling of cleavage by the immunoproteasome and the constitutive proteasome. BMC bioinformatics. 2010;11 doi: 10.1186/1471-2105-11-479. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Bhasin M, Raghava GP. Analysis and prediction of affinity of TAP binding peptides using cascade SVM. Protein science : a publication of the Protein Society. 2004;13(3):596–607. doi: 10.1110/ps.03373104. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Singh H, Raghava GPS. ProPred1: prediction of promiscuous MHC Class-I binding sites. Bioinformatics (Oxford, England) 2003;19(8):1009–14. doi: 10.1093/bioinformatics/btg108. [DOI] [PubMed] [Google Scholar]
- 24.Singh H, Raghava GP. ProPred: prediction of HLA-DR binding sites. Bioinformatics (Oxford, England) 2001;17(12):1236–7. doi: 10.1093/bioinformatics/17.12.1236. [DOI] [PubMed] [Google Scholar]
- 25.Hopp TP, Woods KR. Prediction of protein antigenic determinants from amino acid sequences. Proceedings of the National Academy of Sciences of the United States of America. 1981;78(6):3824–8. doi: 10.1073/pnas.78.6.3824. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Ekins S, Mestres J, Testa B. In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling. British journal of pharmacology. 2007;152(1):9–20. doi: 10.1038/sj.bjp.0707305. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Kelly DF, Rappuoli R. Reverse vaccinology and vaccines for serogroup B Neisseria meningitidis. Advances in experimental medicine and biology. 2005;568:217–23. doi: 10.1007/0-387-25342-4_15. [DOI] [PubMed] [Google Scholar]
- 28.Pizza M, Scarlato V, Masignani V, Giuliani MM, Arico B, Comanducci M, et al. Identification of vaccine candidates against serogroup B meningococcus by whole-genome sequencing. Science (New York, NY) 2000;287(5459):1816–20. doi: 10.1126/science.287.5459.1816. [DOI] [PubMed] [Google Scholar]
- 29.McNeil LK, Zagursky RJ, Lin SL, Murphy E, Zlotnick GW, Hoiseth SK, et al. Role of Factor H Binding Protein in Neisseria meningitidis Virulence and Its Potential as a Vaccine Candidate To Broadly Protect against Meningococcal Disease. Microbiology and Molecular Biology Reviews. 2013;77(2):234–52. doi: 10.1128/MMBR.00056-12. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Ferrari G, Garaguso I, Adu-Bobie J, Doro F, Taddei AR, Biolchi A, et al. Outer membrane vesicles from group B Neisseria meningitidis delta gna33 mutant: proteomic and immunological comparison with detergent-derived outer membrane vesicles. Proteomics. 2006;6(6):1856–66. doi: 10.1002/pmic.200500164. [DOI] [PubMed] [Google Scholar]