While many inhibitors of the Human Immunodeficiency Virus (HIV), the causative agent of Acquired Immunodeficiency Syndrome (AIDS), have been developed, the problem of drug resistance has continued to plague the fight against the disease. The ability of computers to aid in the drug discovery process, and by default the resistance problem, has increased dramatically as the speed of computers and sophistication of associated calculation programs has grown. In particular, the capability of predicting a compound's ability to combat resistance prior to synthesis of drug candidates has proven particularly desirable. Since resistance can develop against a specific drug designed to inhibit only one stage of the viral cycle, combinations of drugs directed at more than one step have proven to be more effective than a single drug given alone. While the introduction of this combination therapy (termed highly active antiretroviral therapy (HAART)) has significantly decreased the death rate from HIV infections, resistance problems still arise. This paper will review previous approaches and address current and future computational strategies used in the design of second-generation and beyond drugs.