Chandipura virus (CHPV), a neurotropic member of the Rhabdoviridae family, has emerged as a significant public health concern in the Indian subcontinent due to its rapid progression to encephalitis and high fatality rates. Recent analysis of its dark proteome revealed a substantial presence of intrinsically disordered proteins (IDPs) and intrinsically disordered protein regions (IDPRs), particularly within the phosphoprotein (P), which exhibited the highest intrinsic disorder propensity among all CHPV proteins. IDPs are characterized by conformational flexibility, enabling them to mediate multiple and transient interactions with host factors, often via molecular recognition features (MoRFs). Such properties make them crucial for viral replication, immune evasion, and host machinery manipulation. In this study, we extend our findings toward an in silico pipeline for IDP-based antibody design targeting the CHPV P protein. Consensus IDR prediction, coupled with MoRF mapping, was integrated with epitope mapping algorithms to identify disordered yet immunogenic regions. Structural ensembles generated using AlphaFold2 and disorder-refined molecular dynamics simulations using Gromacs force field enabled the modeling of conformational variability for antibody docking. This approach facilitates the rational selection of epitope-rich, conformationally adaptable targets for monoclonal antibody engineering. Our findings highlight that targeting IDP regions traditionally overlooked in structure-based vaccine design, offers a novel paradigm for CHPV immunotherapeutics, potentially overcoming antigenic variability and functional plasticity.