Candidiasis is a fungal infection that has a high burden of morbidity and mortality in hospitalized and immunocompromised patients. It occurs in more than a quarter of a million patients every year with incidence rates for candidemia of 2–14 per 100000 [
Fba1 is a yeast cell wall protein which presents in multiple species of Candida, e.g.,
The incidence of fungal infection has been increasing in the last few years, due to several factors such as misuse of broad-spectrum antibiotics, cytotoxic chemotherapy, immunocompromised patients, and transplantations [
The aim of this study is to predict the most conserved and immunogenic B- and T-cell epitopes from the Fba1 protein of
In this study, we have used a variety of bioinformatics databases and tools for the prediction of the most promising peptides, through three phases shown in Figure
Schematic representation of the methodology phases.
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Multiple sequence alignment (MSA) was used to determine the conserved regions; the retrieved sequences were aligned by MSA using Clustal W as applied in the BioEdit [
The reference sequence of fructose bisphosphate aldolase protein was submitted to the following B-cell tests [
A collection of methods to predict linear B-cell epitopes based on protein sequence characteristics of the antigen using amino acid scales and HMMs was used.
The Bepipred tool from IEDB (
Emini surface accessibility prediction tool of the Immune Epitope Database (IEDB) (
The Kolaskar and Tongaonkar antigenicity method was used to detect the antigenic sites with a default threshold value of 1.025 (
This method predicts epitopes based upon solvent-accessibility and flexibility. The methods are for modeling, docking of antibody, and protein 3D structures (
The modeled 3D structure was submitted to the ElliPro (
The peptides’ binding affinity to MHC I molecules was defined by the IEDB MHC I prediction tool at
Prediction of peptide binding affinity to MHC II molecules was defined by the IEDB MHC II prediction tool at
The candidate epitopes of MHC I and MHC II and combined binding of MHC I and MHC II alleles from
The reference sequence of
The function of vaccines is to enhance the immunogenic response once introduced to the immune system. Thus, it is essential to recognize the physicochemical parameters of the protein using the protein protogram and BioEdit [
Molecular docking was performed using Moe 2007. The 3D structures of the promiscuous epitopes were predicted by PEP-FOLD. The crystal structures of HLA-A
The reference sequence of fructose bisphosphate aldolase from
Bepipred linear epitope prediction: the red line is the threshold; above (the yellow part) is proposed to be part of the B-cell epitope.
In Emini’s surface accessibility prediction test, for a potent B-cell epitope, the average surface accessibility area of the Fba1 protein was scored as 1.000, with a maximum of 7.725 and a minimum of 0.113; all values equal or greater than the default threshold 1.000 were potentially in the surface shown in Figure
Emini’s surface accessibility prediction test: the red line is the threshold; above (the yellow part) is proposed to be part of the B-cell epitope.
For the Kolaskar and Tongaonkar antigenicity prediction test, the average of antigenicity was 1.025, with a maximum of 1.223 and a minimum of 0.853; all values equal to or greater than the default threshold 1.025 are potential antigenic determinants (see Figure
Kolaskar and Tongaonkar antigenicity prediction test: the red line is the threshold; above (the yellow part) is proposed to be part of the B-cell epitope.
The proposed predicted antigenic B-cell epitopes; 9 antigenic sites were identified from fructose bisphosphate aldolase of
Start | End | Peptide | Length |
---|---|---|---|
63 | 70 | 8 | |
73 | 84 | 12 | |
129 | 134 | 6 | |
147 | 155 | 9 | |
178 | 199 | 22 | |
247 | 260 | 14 | |
269 | 280 | 12 | |
318 | 331 | 14 | |
336 | 345 | 10 |
List of the most promising B-cell epitopes and their surface and antigenicity.
Start | End | Peptide | Length | Surface score ( | Antigenicity score ( |
---|---|---|---|---|---|
129 | 134 | 6 | 1.502 | 1.034 | |
191 | 199 | 9 | 2.48 | 1.032 | |
190 | 199 | 10 | 2.648 | 1.04 |
The modeled 3D structure of the Fba1 protein was submitted to the ElliPro prediction tool to filter out the antigenic residues. The minimum score and maximum distance (Angstrom) were calibrated in the default mode with a score of 0.5 and 6, respectively (see Table
List of the promising discontinuous B-cell epitopes.
No. | Residues | Number of residues | Score |
---|---|---|---|
1 | T300, G301, I302, R303, D304, Y305, V306, L307, N308, K309, K310, D311, Y312, I313, M314, S315, M316, V317, G318, N319, P320, E321, G322, A323, D324, K325, P326, N327, K328, K329, F330, F331, E339, K342 | 34 | 0.867 |
2 | D332, P333, R334, V335, W336 | 5 | 0.749 |
3 | V3, Q4, E5, V6, L7, K8, Y25, E28, H29, K30, F31, K55, S56, A156, T157, V159, K160, K163, G177, I178, T179, G180, G181, E182, E183, D184, G185, V186, N187, N188, E189, H190, V191, D192, K193, E194, S195, L196, Y197, T198, K199, P200, E201, F204, A205, E208, A209, A211, P212, I213, S214, P215, A222, F223, G224, Q231, A232, G233, N234, V235, V236, L237, S238, P239, E240, A243, D244, K247, Y248, A249, A250, E251, K252, T253, G254, A255, P256, A257, G258, S259, K260, P261, S272, T273, Q274, E275, N278, T279, N282, N283, T357, K358, N359, T360, L361 | 95 | 0.669 |
4 | V15, G16, A71, G72, K73, G74, V75, S76, N77, D78, G79, Q80, N81, A82, I84, R85, C112, A113, K114, L117, P118, D121, G122, L124, E125, A126, E128, A129, Y130, F131, K132, E133, H134, G135, E136, P137, L138, R164, A166, A167, M168, N169, Q170 | 43 | 0.668 |
5 | L146, S147, E148,E149, T150, D151, D152, E153 | 8 | 0.582 |
6 | R9, K10, T11, G12, I14, R52, D53, A98, P99, A100, Y101, G102, I103 | 13 | 0.514 |
114 epitopes were anticipated to interact with different MHC I alleles. The core epitopes KYFKRMAAM and QTSNGGAAY were noticed to be the dominant binders with 7 alleles for each (HLA-A
Promising T-cell epitopes (class MHC I alleles) with their position and IC50 value.
Core epitope | Start | End | Allele | IC50 |
---|---|---|---|---|
KYFKRMAAM | 160 | 168 | HLA-A | 451.84 |
160 | 168 | HLA-A | 232.12 | |
160 | 168 | HLA-A | 131.22 | |
160 | 168 | HLA-B | 427.02 | |
160 | 168 | HLA-C | 149.13 | |
160 | 168 | HLA-C | 240.46 | |
160 | 168 | HLA-C | 6.27 | |
AVHEALAPI | 205 | 213 | HLA-A | 154.37 |
205 | 213 | HLA-A | 9.78 | |
205 | 213 | HLA-A | 20.96 | |
205 | 213 | HLA-A | 122.32 | |
205 | 213 | HLA-A | 55.22 | |
RMAAMNQWL | 164 | 172 | HLA-A | 52.44 |
164 | 172 | HLA-A | 237.09 | |
164 | 172 | HLA-A | 79.39 | |
164 | 172 | HLA-B | 258 | |
164 | 172 | HLA-C | 482 | |
QTSNGGAAY | 61 | 69 | HLA-A | 54.18 |
61 | 69 | HLA-A | 89.37 | |
61 | 69 | HLA-A | 56.68 | |
61 | 69 | HLA-A | 47.89 | |
61 | 69 | HLA-B | 111.57 | |
61 | 69 | HLA-B | 82.52 | |
61 | 69 | HLA-B | 99.45 | |
YFKEHGEPL | 130 | 138 | HLA-B | 295.97 |
130 | 138 | HLA-C | 42.03 | |
130 | 138 | HLA-C | 319.29 | |
130 | 138 | HLA-C | 26.8 | |
130 | 138 | HLA-C | 18.47 |
102 conserved predicted epitopes were found to interact with MHC II alleles. The core epitope LFSSHMLDL is thought to be the top binder as it interacts with 9 alleles (HLA-DRB1
Promising T-cell epitope (class MHC II alleles) with their position and peptide sequence and IC50 value and rank.
Core sequence | Allele | Start | End | Peptide sequence | IC50 | Rank |
---|---|---|---|---|---|---|
HLA-DRB1 | 132 | 146 | KEHGEPLFSSHMLDL | 17.8 | 3.37 | |
HLA-DPA1 | 135 | 149 | GEPLFSSHMLDLSEE | 93.6 | 5.05 | |
HLA-DPB1 | 135 | 149 | GEPLFSSHMLDLSEE | 93.6 | 5.05 | |
HLA-DPA1 | 133 | 147 | EHGEPLFSSHMLDLS | 46 | 4.82 | |
HLA-DPB1 | 133 | 147 | EHGEPLFSSHMLDLS | 46 | 4.82 | |
HLA-DPA1 | 134 | 148 | HGEPLFSSHMLDLSE | 59 | 6.3 | |
HLA-DPB1 | 134 | 148 | HGEPLFSSHMLDLSE | 59 | 6.3 | |
HLA-DPA1 | 135 | 149 | GEPLFSSHMLDLSEE | 12 | 1.14 | |
HLA-DPB1 | 135 | 149 | GEPLFSSHMLDLSEE | 12 | 1.14 | |
HLA-DRB1 | 81 | 95 | NASIRGSIAAAHYIR | 31.5 | 15.98 | |
HLA-DRB1 | 81 | 95 | NASIRGSIAAAHYIR | 86.5 | 7.02 | |
HLA-DRB5 | 81 | 95 | NASIRGSIAAAHYIR | 7.3 | 1.55 | |
HLA-DQA1 | 80 | 94 | QNASIRGSIAAAHYI | 59.3 | 3.74 | |
HLA-DQB1 | 80 | 94 | QNASIRGSIAAAHYI | 59.3 | 3.74 | |
HLA-DQA1 | 81 | 95 | NASIRGSIAAAHYIR | 4.6 | 0.27 | |
HLA-DQB1 | 81 | 95 | NASIRGSIAAAHYIR | 4.6 | 0.27 | |
HLA-DRB1 | 227 | 241 | HGVYQAGNVVLSPEI | 19.7 | 11.15 | |
HLA-DRB1 | 227 | 241 | HGVYQAGNVVLSPEI | 80.9 | 5.58 | |
HLA-DQA1 | 227 | 241 | HGVYQAGNVVLSPEI | 91.3 | 6.42 | |
HLA-DQB1 | 227 | 241 | HGVYQAGNVVLSPEI | 91.3 | 6.42 | |
HLA-DQA1 | 224 | 238 | GNVHGVYQAGNVVLS | 7.9 | 0.96 | |
HLA-DQB1 | 224 | 238 | GNVHGVYQAGNVVLS | 7.9 | 0.96 | |
HLA-DRB1 | 41 | 55 | SSTVVAALEAARDAK | 50.9 | 2.91 | |
HLA-DRB1 | 41 | 55 | SSTVVAALEAARDAK | 95.1 | 6.59 | |
HLA-DRB5 | 41 | 55 | SSTVVAALEAARDAK | 15 | 3.71 | |
HLA-DQA1 | 40 | 54 | SSSTVVAALEAARDA | 38.1 | 1.93 | |
HLA-DQB1 | 40 | 54 | SSSTVVAALEAARDA | 38.1 | 1.93 | |
HLA-DQA1 | 42 | 56 | STVVAALEAARDAKS | 16.2 | 2.87 | |
HLA-DQB1 | 42 | 56 | STVVAALEAARDAKS | 16.2 | 2.87 | |
HLA-DRB1 | 94 | 108 | IRSIAPAYGIPVVLH | 12.1 | 6.74 | |
HLA-DRB1 | 91 | 105 | AHYIRSIAPAYGIPV | 34.1 | 6.37 | |
HLA-DRB1 | 94 | 108 | IRSIAPAYGIPVVLH | 79.2 | 8.07 | |
HLA-DQA1 | 94 | 108 | IRSIAPAYGIPVVLH | 16.5 | 2.94 | |
HLA-DQB1 | 94 | 108 | IRSIAPAYGIPVVLH | 16.5 | 2.94 |
The most interesting findings in this test is the population coverage analysis result for the most common binders to MHC I and MHC II alleles each and combined among the world, exhibiting an exceptional coverage with percentages 92.54%, 99.58%, and 98.5%, respectively.
Five epitopes are given to interact with the most frequent MHC class I alleles:
Global coverage for the top five MHC I peptides (AVHEALAPI, KYFKRMAAM, QTSNGGAAY, RMAAMNQWL, and YFKEHGEPL). Note: in the graph, the line (-o-) represents the cumulative percentage of population coverage of the epitopes; the bars represent the population coverage for each epitope.
Three epitopes were assumed to interact with the most frequent MHC class II alleles (IRGSIAAAH, LFSSHMLDL, and VVAALEAAR) with a percentage of 99.58%. The
Global proportion for the top five MHC II IRGSIAAAH, LFSSHMLDL, and VVAALEAAR. Notes: in the graph, the line (-o-) represents the cumulative percentage of population coverage of the epitopes; the bars represent the population coverage for each epitope.
Regarding the combined MHC I and MHC II alleles, five epitopes were supposed to interact with the most predominant MHC class I and MHC class II alleles (IAPAYGIPV, AAFGNVHGV, VVAALEAAR, YIRSTIAPAY, and YQAGMVVLS), representing a significant global coverage by the IEDB population coverage tool which revealed coverage with percentage of 98.50% as shown in Figure
Global population proportion for the top five MHC I and II epitopes in combined mode (IAPAYGIPV, AAFGNVHGV, VVAALEAAR, YIRSTIAPAY, and YQAGMVVLS). Notes: in the graphs, the line (-o-) represents the cumulative percentage of population coverage of the epitopes; the bars represent the population coverage for each epitope.
The 3-dimentional structure of the fructose bisphosphate aldolase protein from C
Structural position of the promising B-cell epitope (AYFKEH (in purple color), VDKESLYTK (in yellow color), and HVDKESLYTK (in red color)) in 3-dimensional structure of the fructose bisphosphate aldolase protein from
The length of fructose bisphosphate aldolase protein is 361 amino acids, and its molecular weight is 39356.3. Theoretical pI is 5.49 which explain the pH of the protein. Total numbers of negatively and positively charged residues that contain the fructose bisphosphate aldolase protein are (Asp+Glu): 47 and (Arg+Lys): 35, respectively. Also, the number of atoms that compose this protein is 5488 which presented as flowing: carbon 1752, hydrogen 2716, nitrogen 470, oxygen 538, and sulfur 12. N-terminal of the sequence considered is M (Met). The half-life of the fructose bisphosphate aldolase protein estimate is 30 hours (mammalian reticulocytes, in vitro) and more than 20 hours (yeast, in vivo). The aliphatic index and the grand average of hydropathicity (GRAVY) value of vaccine were determined as 80.55 and −0.264, respectively. Instability of the fructose bisphosphate aldolase protein is computed to be 29.93, meaning the protein is stable [
Amino acid composition of the protein (fructose bisphosphate aldolase) with their number and molecular weight (Mol%) using BioEdit software version 7.0.5.3.
Amino acid | Number | Mol% | Amino acid | Number | Mol% |
---|---|---|---|---|---|
Ala A | 39 | 10.80 | Leu L | 23 | 6.37 |
Cys C | 3 | 0.83 | Met M | 9 | 2.49 |
Asp D | 21 | 5.82 | Asn N | 19 | 5.26 |
Glu E | 26 | 7.20 | Pro P | 15 | 4.16 |
Phe F | 14 | 3.88 | Gln Q | 8 | 2.22 |
Gly G | 30 | 8.31 | Arg R | 10 | 2.77 |
His H | 12 | 3.32 | Ser S | 23 | 6.37 |
Ile I | 20 | 5.54 | Thr T | 17 | 4.71 |
Lys K | 25 | 6.93 | Val V | 29 | 8.03 |
Trp W | 3 | 0.83 | Tyr Y | 15 | 4.16 |
Graph showing amino acid composition of fructose bisphosphate aldolase protein and their molecular weights using BioEdit software 7.0.5.3.
The best epitopes that displayed the lowest binding energies visualized by using UCSF chimera 1.13.1 software are shown in Table
Docking results of the most promiscuous epitopes that show the best binding affinity.
Epitope | Binding MHC molecule | Binding energy ( |
---|---|---|
HLA-A | -15.8010 | |
HLA-A | -20.5935 | |
HLA-A | -30.5467 | |
HLA-A | -20.6392 | |
HLA-A | -16.7505 | |
HLA-DRB1 | -20.6557 | |
HLA-DRB1 | -25.5732 | |
HLA-DRB1 | -19.8404 |
Illustration of the 2D interaction of the best docking poses of AVHEALAPI in the binding sites of HLA-A
Illustration of the 3D interaction of the best docking poses of AVHEALAPI in the binding sites of HLA-A
Illustration of the 3D interaction of the best docking poses of KYFKRMAAM in the binding sites of HLA-A
Illustration of the 3D interaction of the best docking poses of KYFKRMAAM in the binding sites of HLA-A
Illustration of the 2D interaction of the best docking poses of QTSNGGAAY in the binding sites of HLA-A
Illustrate the 2D interaction of the best docking poses of QTSNGGAAY in the binding sites of HLA-A
Illustration of the 2D interaction of the best docking poses of RMAAMNQWL in the binding sites of HLA-A
Illustration of the 2D interaction of the best docking poses of RMAAMNQWL in the binding sites of HLA-A
Illustration of the 3D interaction of the best docking poses of YFKEHGEPL in the binding sites of HLA-A
Illustration of the 3D interaction of the best docking poses of YFKEHGEPL in the binding sites of HLA-A
Illustration of the 3D interaction of the best docking poses of IRGSIAAAH in the binding sites of HLA-DRB1
Illustration of the 3D interaction of the best docking poses of IRGSIAAAH in the binding sites of HLA-DRB1
Illustration of the 3D interaction of the best docking poses of LFSSHMLDL in the binding sites of HLA-DRB1
Illustration of the 3D interaction of the best docking poses of LFSSHMLDL in the binding sites of HLA-DRB1
Illustration of the 2D interaction of the best docking poses of VVAALEAAR in the binding sites of HLA-DRB1
Illustration of the 2D interaction of the best docking poses of VVAALEAAR in the binding sites of HLA-DRB1
In the present study, we predicted the most conserved and immunogenic B- and T-cell epitopes from Fba1 protein of
The principle of using a cocktail of B- and T-cell epitopes in the epitope-based vaccine to trigger humoral as well as cellular mediated immune response is very promising to clear infection instead of humoral or cellular immunity alone, and it was applied before to enhance protection against different kinds of infectious diseases [
However, the molecular docking, which evaluates the binding affinity to MHC molecules [
After retrieving the various sequences of
The epitope-based vaccines predicted by using immunoinformatics tools have remarkable advantages over the conventional vaccines in that they are more specific, less time consuming, safe, less allergic, and more antigenic. Further in vivo and in vitro experiments are needed to prove the effectiveness of the best candidate’s epitopes QTSNGGAAY and LFSSHMLDL. To the best of our knowledge, this is the first study that has predicted B- and T-cell epitopes from the Fba1 protein by using in silico tools in order to design an effective epitope-based vaccine against
The data used to support the findings of this study are available from the corresponding author upon request.
The authors declare that there are no conflicts of interest.
The authors are grateful to Africa City of Technology, Khartoum, Sudan.