Carrimycin is a macrolide antibiotic widely used in the pharmaceutical and clinical fields， with its primary composition consisting of three distinct derivatives of spiramycin. For decades， macrolides like carrimycin have been valued for their efficacy against Gram-positive bacteria and certain atypical pathogens. However， as research has progressed， recent studies have revealed that carrimycin， along with various other structurally modified spiramycin derivatives， exhibits significant antitumor activity in multiple experimental models. This finding suggests that the spiramycin molecular scaffold possesses intrinsic potential beyond its conventional antibacterial role. By strategically modifying the substituents attached to this core structure， it may be feasible to develop novel compounds with enhanced and more selective antitumor properties. Despite this promising outlook， research into the specific targets and comprehensive mechanisms underlying the antitumor effects of spiramycin derivatives remains notably insufficient. A major gap exists in the precise identification of their molecular targets within cancer cells and the detailed signaling pathways they modulate. This lack of mechanistic understanding poses a substantial barrier to the rational design， optimization， and clinical translation of spiramycin-based antitumor therapeutics. To systematically address this knowledge gap and elucidate the antitumor mechanism of this compound class， the present study adopted an activity-based protein profiling （ABPP） strategy. ABPP is a chemoproteomic approach that enables the direct identification of functionally active proteins that interact with small-molecule probes in a native biological context. As a first step， we designed and synthesized a novel， high-activity spiramycin derivative termed n-hexanoyl spiramycin （h-SPM）. Building upon the structure of h-SPM， we subsequently engineered and synthesized a structurally analogous activity-based probe. This probe was specifically functionalized with chemical handles （such as an alkyne group） compatible with ABPP methodologies， allowing for downstream bioorthogonal conjugation and enrichment steps. The experimental workflow began by incubating this active probe with live cancer cells. During this co-incubation period， the probe engaged with and covalently bound to its potential protein targets within the complex cellular environment. Following the interaction， cells were lysed， and the probe-labeled proteins were efficiently isolated and purified using affinity-based enrichment techniques—specifically via copper-catalyzed azide-alkyne cycloaddition （click chemistry） to immobilize them onto a solid support. The enriched protein pool was then subjected to in-depth analysis using liquid chromatography-mass spectrometry （LC-MS）. This analytical phase yielded detailed， proteome-wide information on the identities of proteins that interact with the h-SPM-based probe. To extract biological insights from the list of identified proteins， we performed comprehensive bioinformatic analysis using Gene Ontology （GO） enrichment. This systematic classification provided crucial information regarding the biological processes， molecular functions， and cellular components associated with the captured proteins. The functional annotations derived from GO analysis allowed us to evaluate and prioritize several promising candidate target proteins for further experimental validation. Through this integrated proteomic and bioinformatic approach， we successfully identified multiple potential cellular targets of h-SPM. Notable among these were amyloid precursor protein （APP） and low-density lipoprotein receptor （LDLR）， both of which are implicated in diverse cellular processes such as cell adhesion， signal transduction， and metabolic regulation. To confirm the biological relevance of these interactions， we employed Western Blotting experiments. These studies verified that the expression or post-translational modification states of APP and LDLR were altered in response to h-SPM treatment， thereby confirming their status as responsive molecular targets. After identifying and preliminarily validating APP as a key interactor， we proceeded to investigate its functional role in the drug’s mechanism of action. Using short hairpin RNA （shRNA）-mediated protein knockdown， we generated cancer cell lines with significantly reduced APP expression. Comparative analysis of drug sensitivity between these knockdown cells and their wild-type counterparts revealed a marked attenuation of h-SPM’s antitumor effects in the absence of APP. Complementary to this， cell staining assays， including immunofluorescence， were conducted to visualize morphological changes， alterations in cell viability， and the subcellular localization of relevant biomarkers following h-SPM treatment. Collectively， these functional experiments provided compelling evidence that APP plays a critical and indispensable role in mediating the antitumor activity of h-SPM. Our findings thus outline a preliminary model of the drug’s mechanism， likely involving cellular pathways regulated or influenced by APP. In summary， this study achieves two significant objectives. First， it establishes and validates a robust， generalizable target-screening platform based on ABPP， specifically tailored for the investigation of spiramycin-class compounds. Second， and more importantly， it delivers novel biological insights by pinpointing specific protein targets such as APP. The identification of these targets provides invaluable mechanistic clues and a solid theoretical foundation for the future development of this family of compounds. This work effectively advances spiramycin derivatives from compounds with observed phenotypic activity toward agents with an emerging mechanistic understanding， thereby paving the way for more targeted drug design and informed combination therapy strategies in oncology. Future studies will focus on delineating the detailed downstream consequences of APP engagement by h-SPM and exploring the therapeutic potential of other identified targets in preclinical models.