Large-scale genomics efforts led to the identification of an increasing number of mutations in various cancers. However, the functional role of a vast majority of these mutations in disease pathogenesis remains unknown. For enzymes whose activity can be blocked by approved drugs, knowledge regarding the effect of novel or uncommon mutations on inhibitor sensitivity helps in opting for effective treatment strategies. However, it is impossible to experimentally evaluate pathogenic effect and drug sensitivity for all mutations that are being identified in multiple diseases. Therefore, computational predictions of pathogenicity and drug sensitivity can potentially help in the design of an individualized treatment approach. This article includes computational methods to: (a) predict the pathogenicity of mutations based on primary and tertiary structures of the target enzyme, (b) study the effect of mutations on protein conformation, and (c) predict the binding affinity of mutant structures towards targeted therapeutics. All the methods utilize freely available computational tools and have considerable translational value in improving patient outcomes with targeted therapy. © 2025 Wiley Periodicals LLC. Basic Protocol 1: Pathogenicity prediction of mutations based on primary and tertiary structures Basic Protocol 2: Homology modeling of mutant protein structures Basic Protocol 3: Understanding the effect of mutations on protein conformation Basic Protocol 4: Predicting the binding affinities of mutant proteins towards specific inhibitors.