Today’s world is gradually getting agitated by Human Immunodeficiency Virus-Type 1 due to its pervasive and death-dealing nature. The virus replicates by exploiting a complex interaction network of HIV-1 and human proteins and destructs human immunity power, gradually leading to AIDS. Anti-HIV drugs are designed to utilize the information on viral-host protein-protein interactions (PPIs), so that the viral replication and infection can be prevented. In this article, we have presented an effective computational approach using pattern-mining based algorithm in order to predict novel interactions between HIV-1 and human proteins based on the experimentally validated interactions curated in public PPI database. Additionally, we have tried to provide the information on interaction types associated with each of the predicted interactions with an estimated confidence. Further, we have analyzed our predicted interactions by finding overlap with other studies. We believe that this article would enhance the discovery of HIV-1 medications in a way of designing the drug targets.