Over the past century, nearly half of the FDA-approved drugs were sourced from natural products, with plants representing a prolific reservoir of chemotherapeutics. Among these, cyclic peptides have emerged as promising scaffolds for cancer drug discovery, offering the metabolic stability and target specificity of biologics alongside the oral bioavailability and membrane permeability of small molecules. Despite their promise, plant natural product drug discovery has been deprioritized by the pharmaceutical industry due to three persistent bottlenecks: (1) lowyield isolation from source plant material, (2) chemical rediscovery in bioactivity-guided fractionation, and (3) synthetic barriers to macrocyclic complexity and lead diversification. This dissertation addresses these challenges through an integrated multi-omics strategy that combines metabolomics, genome mining, proteomics, and metabolic engineering to identify novel cyclic peptides from plant sequencing data. Additionally, a high-content screening (HCS) platform was developed to evaluate the cytotoxicity profiles of these peptides in cell-based cancer models. The integrated multi-omics and HCS approach led to the discovery of cyclic peptides from three distinct classes of ribosomally synthesized and post-translationally modified peptides (RiPPs): a cyclopeptide alkaloid, multiple stephanotic acid peptides, and two cysteine-rich peptides. These peptides, collectively termed burpitides, are cyclized by copper-dependent BURP-domain-containing proteins (burpitide cyclases) encoded within the same precursor gene as their peptide substrates. This genomic architecture enables discovery via sequence-based mining of plant genomes and transcriptomes. Proteome database search tools facilitated the detection of post-translationally modified peptides from tandem mass spectrometry data, while expression of BURP-domain precursor genes in Nicotiana benthamiana enabled source-plantindependent biosynthesis. Finally, multiplexed fluorescence imaging of peptide-treated cancer cells provided morphological information to assess cytotoxicity and infer their mechanism of action. xxii These studies collectively illustrate the power of integrating multi-omic strategies with high-content analysis and establishes a scalable workflow for expanding the chemical space of bioactive cyclic plant peptides.