It is a challenge for the traditional affinity methods to capture transient interactions of enzyme-post-translational modification (PTM) substrates in vivo. Herein we presented a strategy termed proximity labeling-based orthogonal trap approach (ProLORT), relying upon APEX2-catalysed proximity labeling and an orthogonal trap pipeline as well as quantitative proteomics to directly investigate the transient interactome of enzyme-PTM substrates in living cells. As a proof of concept, ProLORT allows for robust evaluation of a known HDAC8 substrate, histone H3K9ac. By leveraging this approach, we identified numerous of putative acetylated proteins targeted by HDAC8, and further confirmed CTTN as a bona fide substrate in vivo. Next, we demonstrated that HDAC8 facilitates cell motility via deacetylation of CTTN at lysine 144 that attenuates its interaction with F-actin, expanding the underlying regulatory mechanisms of HDAC8. We developed a general strategy to profile the transient enzyme-substrate interactions mediated by PTMs, providing a powerful tool for identifying the spatiotemporal PTM-network regulated by enzymes in living cells.

Cytochrome P450 1A1 (CYP1A1) has served as a known metabolic enzyme that mediates the carcinogenesis of polycyclic aromatic hydrocarbons (PAHs). However, the structural mechanism involved in the metabolic capacity remains unclear. In this study, thirty-three calculated properties representing the physicochemical and electronic properties of PAH and PAH-CYP1A1 interactions were utilized to identify the key structural properties that affect metabolic processes, including binding ability, metabolic clearance, and mutagenicity, using a quantitative structure-activity relationship (QSAR) strategy combined with docking methods, QM/MM calculations and ab initio calculations. van der Waals interactions (glide vdw) appeared to be important for PAH binding to CYP1A1 and were mainly affected by the molecular weight and hydrophobic structures of PAHs. Interaction features between PAHs and heme, including the distance between iron and carbons of PAHs (Fe_Cmin) and heme vdw, coordinately influence the metabolic clearance of PAHs. Furthermore, the electronic properties (ESP neg variance) appeared to be critical for the mutagenicity of PAHs by CYP1A1 through influencing epoxide metabolite formation. The QSAR models with these key properties provide a new perspective on the structural mechanism of PAH metabolism and provide a useful in silico tool for screening, classifying and predicting PAHs for their metabolism-related toxicities and risk assessment in the environment.