Human Immunodeficiency Virus (HIV) causes Acquired Immuno-Deficiency Syndrome which is a global health issue infecting 38.4 million people worldwide in 2021 leading to a casualty of around half a million people. HIV protease is an enzyme vital for the replication of HIV and serves as a prime target for antiretroviral therapy. HIV protease is a dimeric protein consisting of two identical subunits of 99 amino acids and the formation of dimer is crucial for its activity and function. Currently there are 10 FDA approved inhibitors for HIV protease designed to act on its catalytic active site. However, prolonged usage has made these inhibitors ineffective due to emergence of drug resistance. Current research on HIV protease mainly focuses on the design of novel active site inhibitors to overcome this drug resistance. Studying the dimerization mechanism of HIV protease can provide novel insights into disrupting this process which could hinder viral replication. This study aims to use computational methods to gain insights on the mechanism of HIV protease dimerization. Markov State Models also called kinetic network models can be developed to capture all of the major conformational states along the dimerization pathway, and also the transitions between those states. Using accelerated molecular dynamics, we also aim to investigate the mechanism of action of the few reported dimerization inhibitors. Elucidating the molecular details of HIV protease dimerization and its inhibition can contribute to developing novel strategies to inhibit HIV protease effectively, potentially overcoming issues like drug resistance that arise with current therapies.