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Cancer is a common disease and diagnosis frequency correlates with population age. Though many cancers can be cured today, numerous types remain difficult to treat. Treatments can evoke side effects and often don’t reach the clinic due to inefficacy. Thus, better targeted anti-cancer therapies and candidate drugs are required. This thesis focusses on initial stages of drug discovery where we sought to identify ligands specifically targeting SET and MYND domain containing protein 3 (SMYD3), and Cullin3 associated adaptor proteins: Kelch-like protein 12 (KLHL12) and 20 (KLHL20). These targets are all associated with cancer although their biological mechanisms remain elusive. The targets were challenging from a biochemical perspective, nevertheless via robust expression and purification methods, an amalgamation of biochemical techniques and computational methods were used to identify, characterize, and evolve fragment and peptide-based ligands. Sensitive multiplexed screening assays enabled selection of specific hits. A grating coupled interferometry-based biosensor assay implemented a kinetic criterion for fragment hit identification against SMYD3. Four fragments from a library containing 1056 fragments had their binding site and orientation established using X-ray crystallography. Fragment evolution based on the SMYD3 allosteric ligand diperodon encompassed a structure-affinity-relationship (SAR)-based approach, and a deconstruction-and-growth method wherein ligands with K_D of 0.4-180 μM were attained. Structure prediction complemented a surface plasmon resonance (SPR) biosensor-driven approach to develop a stapled peptide ligand against the Kelch domain of KLHL20, derived from zinc finger translocation associated protein (ZFTA). This peptide had K_D of 1.14 mM and alanine scanning revealed aspartate as vital for interaction. Multiplexed fragment-based SPR biosensor screening assays against the Kelch domains of KLHL12 and 20 identified 237 and 266 hits from a library containing 3000+ fragments. Hit selection was based on preference for folded protein and dose-response analysis was conducted for validation and hit reduction to 24 and 21. Hit SAR was probed using modelling and fragment analogues. NMR confirmed fragment-protein binding. All targets studied herein were concluded as poorly druggable, however using multiple experimental approaches alongside computational methodologies permitted hit identification, validation, and a further understanding of poorly druggable targets. The validated hits presented are befitting for evolution by medicinal chemistry.