Infection with HIV is still a global pandemic. Since the discovery of this highly mutagenic virus, nearly 40 million people have passed away as a result of HIV-related health problems. Currently, 38.4 million people are HIV-positive. Following infection, the viral genome gets integrated into the host cell genome. The infected person carries the virus for the rest of their life and can spread it to others through bodily fluids. Because there is no treatment for HIV, the World Health Organization recommends that infected people be diagnosed early through comprehensive screening to restrict the virus's spread. As a result, there is still a need to create practical, sensitive diagnostic tools, particularly for use in the field of HIV infection testing. In this study, the interaction between HIV-1 capsid protein, the first antigen found in the blood during the acute phase of HIV infection, and a nanobody (Nb, a single domain antibody) known to bind to capsid is investigated at the molecular level through computational methods. Because the structure of HIV-1 CA binding-Nb is unknown, all-atom models of the Nb structure were constructed using comparative methods, deep-learning-based methods, and hybrid methods (SwissModel, trRosetta, Robetta, AlphaFold2), and promising models were chosen. In the second stage, molecular docking was used to produce HIV-1 capsidnanobody complex structures, which were then tested for stability and native-likeness using standard molecular dynamics simulations. Understanding the molecular details of the HIV-1 capsid-nanobody complex, we believe, will provide essential data for using this antigen-antibody pair inan immunosensor system for HIV-1 infection diagnosis.