Traditional Chinese medicine (TCM) is a valuable drug discovery resource known for its therapeutic effects. However, the mechanisms of action (MOAs) of TCM prescriptions are often unknown due to limited target information and the complexity of multiple ingredients and targets. This study introduces TCM-CMap (Connecting Map from Gene Perturbation to Therapeutical Targets for TCM), a framework designed to prioritize active ingredients and targets within TCM prescriptions by integrating transcriptomics-based gene perturbation data with a random walk algorithm. This methodology bridges the gap between gene perturbation in TCM prescriptions and their therapeutic target. Using the Suhuang antitussive capsule (Suhuang) for treating cough variant asthma (CVA) as a case study, we identify and experimentally verify that quercetin and luteolin directly interact with Il17a, Pik3cb, Pik3cd, Akt1, and Tnf. These interactions inhibit the IL-17 signaling pathway and inactivate PI3K, Akt, and NF-κB, preventing lung inflammation and treating CVA. Our findings demonstrate the potential of the TCM-CMap methodology to provide insights into the molecular MOAs of TCM prescriptions, advancing TCM drug discovery.