## 4 Discussion  
As a human pathogen, _N. meningitidis_ is known to cause devastating effect on humans [30]. The expression of several genes in response to iron (e.g., specific virulence factors) was reported to be regulated by the pathogenic _Neisseria_. As all bacteria demands iron for their growth, immunogenicity analysis for vaccine and drug design often sets iron-regulated _N. meningitidis_ protein as the target [31]. To develop new vaccines (or new therapies) for undetectable bacterial agents in the pathogenesis, it is often crucial to find new cell-surface and/or secreted proteins [32]. Outer membrane proteins may have a strong immunogenic property with easy accessibility to antibodies [33; 34]. In the host, the infection and survival of the _N. meningitidis_ is siderophore-dependent [35]. _Neisseria_ species hijack siderophore produced by other bacteria [36]. FrpB is an integral outer membrane protein from _N. meningitidis_. It was demonstrated that this protein should possess antigeic properties as a potential candidate for a vaccine against meningococcal meningitis [37; 38; 39]. This protein has been extensively characterized previously [37; 40]. FrpB promotes the uptake of iron across the outer membrane to work as siderophore receptor [37; 38]. Thus, because of their outer membrane localization, iron-regulated proteins are easily exposed to the host immune system, which responds to the immunogenicity and protection probability by provoking higher antibody production [41; 42]. In other bacterial species, the use of specific antibodies against iron-regulated outer membrane proteins (IROMPs) is for bactericidal purposes to inhibit the uptake of iron. [43]. Nuclear magnetic resonance (NMR) and X-ray crystallography methods have been utilized to determine the 3D structure of proteins [44; 45]. However, these methods are time-consuming and highly expensive. We used comparative homology modeling instead of experimental NMR and X-ray crystallography. Comparative homology modeling is considered as a highly favorable option  
Figure 3: Overall model quality of predicted protein models by ProSA. (**A**) CAM07737. (**B**) CBA03648. (**C**) CBA07476. (**D**). CBA09441. because of its capability for function prediction as well as its application in different research fields (e.g., 3D structure prediction, mutagenesis analysis, and disulfide bridge analysis) [46; 47]. We predicted 3D structures for all four IROMPs and validated them. The continuous decrease of force field energy was realized through energy minimization after the refinement of the protein model. Our data also suggested that, in terms of the Z-score, the G factor value and ERRAT value of all four IROMPs were good, but among them, CBA03648 had the highest score. In the current study, IROMPs from _N. meningitidis_ were chosen to estimate their immunogenicity for the generation of a vaccine. The immunogenicity of an antigen is reported to be affected by several properties, such as mobility of backbone atoms, accessibility, flexibility, hydrophilicity, and topology [48]. All data obtained from Vaxijen, ANTIGENpro, and IEDB were comparable to each other considering the lowest scores for antigenicity. Protein solubility is another important factor used for immunogenicity prediction. Insoluble proteins are not appropriate for an immunogenicity effect. We used SOLpro to predict the solubility of protein. SOLpro provides the corresponding solubility probability (above 0.5) ([[http://scratch.proteomics.ics.uci.edu/explanation.html#SOLpro](http://scratch.proteomics.ics.uci.edu/explanation.html#SOLpro)]([http://scratch.proteomics.ics.uci.edu/explanation.html#SOLpro](http://scratch.proteomics.ics.uci.edu/explanation.html#SOLpro))). Our data suggest that all of the predicted protein models should be water-soluble (Table 2). An essential task in the design of a vaccine is to choose proteins with antibody-binding epitopes (B-cell epitopes) through which the immune response can be induced efficiently [49; 50].