Exercise interventions offer profound systemic benefits, yet patient adherence remains a major clinical hurdle. Recent reports identify Lac-Phe (N-lactoyl-phenylalanine) as an exercise-induced metabolite driving appetite suppression and fat loss; however, it is entirely absent from every released feature table in the MoTrPAC exercise atlas. Using Claude Science, this project orchestrated the re-analysis of raw metabolomics data to map Lac-Phe dynamics across 19 tissues. The signal was successfully recovered from raw spectra, revealing robust training-induced elevations—including a previously undescribed female-predominant pattern in the heart and white adipose tissue. Crucially, the data demonstrates that Lac-Phe dynamics are governed by upstream substrate availability (lactate) rather than the induction of its synthesizing enzyme, CNDP2. Leveraging this mechanistic insight, a modular computational pipeline was designed to predict clinical viability, validating targets, drug relations, ADMET profiles, and side effects using open data. This pipeline successfully identifies hydrolysis-resistant Lac-Phe isosteres as stable, high-potential exercise mimetics. Why it matters: By rescuing "invisible" data from the world's largest exercise atlas, this project resolves a core biological paradox of Lac-Phe kinetics. Furthermore, it delivers an end-to-end predictive computational pipeline to de-risk and engineer next-generation exercise mimetics prior to costly wet-lab synthesis.
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