Selecting an appropriate antigen with optimal immunogenicity and physicochemical properties is a pivotal factor to develop a protein based subunit vaccine. Despite rapid progress in modern molecular cloning and recombinant protein technology, there remains a huge challenge for purifying and using protein antigens rich in hydrophobic domains, such as membrane associated proteins. To overcome current limitations using hydrophobic proteins as vaccine antigens, we adopted in silico analyses which included bioinformatic prediction and sequence-based protein 3D structure modeling, to develop a novel periodontitis subunit vaccine against the outer membrane protein FomA of Fusobacterium nucleatum. To generate an optimal antigen candidate, we predicted hydrophilicity and B cell epitope parameter by querying to web-based databases, and designed a truncated FomA (tFomA) candidate with better solubility and preserved B cell epitopes. The truncated recombinant protein was engineered to expose epitopes on the surface through simulating amino acid sequence-based 3D folding in aqueous environment. The recombinant tFomA was further expressed and purified, and its immunological properties were evaluated. In the mice intranasal vaccination study, tFomA significantly induced antigen-specific IgG and sIgA responses in both systemic and oral-mucosal compartments, respectively. Our results testify that intelligent in silico designing of antigens provide amenable vaccine epitopes from hard-to-manufacture hydrophobic domain rich microbial antigens.