Computational protein design and engineering have emerged as powerful tools in the field of molecular biology, enabling the generation of novel protein sequences and structures with tailored functionalities. By harnessing computational algorithms and modeling techniques, researchers can optimize protein properties, such as charge distribution, stability, and activity, to meet specific design objectives. The integration of computational approaches with experimental characterization offers unprecedented opportunities to create functional proteins for diverse applications in biotechnology, medicine, and materials science. In this thesis, we present the design and characterization of peptides and enzymes, with a focus on their charge features and electrostatic interactions, highlighting the potential of computational protein design in advancing the field of molecular engineering. We first introduce the design of a tetrahelical peptide bundle motif with tunable net charge, where a series of 17 peptides were designed covering each distinct charge state from -8 to +8. The peptides were further polymerized into rigid, micron-scale fibers, providing nanometer-scale building blocks with tunable charge and the potential for applications as rigid-rod polyelectrolytes. The second example concerns the design of a superpositively charged variant of an enzyme for encapsulation within a protein nanocage. A computationally designed variant of the zinc metalloenzyme human carbonic anhydrase II (hCAII) was engineered with positively charged residues on its surface. This hCAII variant (+21 net charge) demonstrated encapsulation within the Archaeoglobus fulgidus thermophilic ferritin (AfFtn) without the need for fusion partners or additional reagents. The variant retained esterase activity and facilitated the assembly of AfFtn 24mers around itself. The resulting AfFtn-hCAII(+21) host-guest complex exhibited enhanced activity and thermal stability compared to the variant alone. Lastly, we investigate the role of electrostatics in the encapsulation of green fluorescent protein (GFP) within AfFtn cages. Different variants of GFP with positive charges on specific regions were designed, and their effects on the encapsulation process were studied. The GFP variant with positive charges on both ends (GFP+16BE) successfully triggered encapsulation at neutral pH. Lowering the pH to 5.8 improved the encapsulation process, suggesting reduced electrostatic repulsion. The study also explored the thermal stability of encapsulated GFPs and their interactions with AfFtn. Overall, these examples demonstrate the power of computational design in creating peptides and proteins with tunable properties and desired assemblies. These findings contribute to the understanding and optimization of protein encapsulation for various biomedical and biotechnological applications.