In recent years, the advent of computational techniques to predict the potential activity of a drug interacting with a receptor or to predict the structure of unidentified proteins with aberrant characteristics has significantly impacted the field of drug design. We provide a comprehensive review of the current state of in silico approaches and software for investigating the effects of receptor mutations associated with human diseases, focusing on both frequent and rare mutations. The reported techniques include virtual screening, homology modeling, threading, docking, and molecular dynamics. This review clearly shows that it is common for successful studies to integrate different techniques in drug design, with docking and molecular dynamics being the most frequently used techniques. This trend reflects the current emphasis on developing novel therapies for diseases resulting from receptor mutations with the recently discovered AlphaFold algorithm as the driving force.