Zika virus (ZIKV), a mosquito-borne flavivirus, has emerged as a significant global health concern due to its association with severe neurological complications, including congenital microcephaly and Guillain–Barré syndrome. Despite recurring outbreaks across multiple continents, there are currently no licensed vaccines or specific antiviral therapies available. Previous intrinsic disorder profiling of the ZIKV proteome has revealed that several viral proteins harbour substantial intrinsically disordered regions (IDRs), with particularly high disorder propensity in the non-structural proteins NS4B and NS5, and in the C-terminal tail of the capsid protein. These flexible regions facilitate dynamic interactions with host factors, playing a pivotal role in viral replication, immune modulation, and evasion mechanisms. In this study, we present an open-access, end-to-end in silico antibody design pipeline specifically tailored to target these disordered viral proteins. Consensus IDR prediction was performed using IUPred3, flDPnn, PONDR, and IDPpred, enabling the identification of epitope-rich disordered segments. Structural ensembles for these regions were generated using AlphaFold2 modelling followed by FlexServ sampling to capture conformational heterogeneity. B-cell epitope profiling (BepiPred-3.0, ElliPro) was employed to identify accessible and potentially immunogenic regions, which were then docked to human germline antibody scaffolds sourced from SAbDab using HADDOCK 2.4 and ClusPro. Paratope optimisation was achieved with ABpredict2, while developability and manufacturability assessments were performed using Thera-P. Preliminary docking and scoring indicate that several candidate antibodies display predicted nanomolar-range affinities for the NS4B N-terminal disordered segment and the capsid tail epitopes, with favourable stability and developability profiles. This work demonstrates the feasibility of computational antibody engineering against naturally flexible ZIKV proteins, highlighting the potential of targeting the viral “dark proteome” to develop novel therapeutic interventions.