The bioactive constituents found in natural products (NPs) are crucial in protein-ligand interactions and drug discovery. However, it is difficult to identify ligand molecules from complex NPs that specifically bind to target protein, which often requires time-consuming and labor-intensive processes such as isolation and enrichment. To address this issue, in this study we developed a method that combines ultra-high performance liquid chromatography-electrospray ionization-mass spectrometry (UHPLC-ESI-MS) with molecular dynamics (MD) simulation to identify and observe, rapidly and efficiently, the bioactive components in NPs that bind to specific protein target. In this method, a specific protein target was introduced online using a three-way valve to form a protein-ligand complex. The complex was then detected in real time using high-resolution MS to identify potential ligands. Based on our method, only 10 molecules from green tea (a representative natural product), including the commonly reported epigallocatechin gallate (EGCG) and epicatechin gallate (ECG), as well as the previously unreported eepicatechin (4β→8)-epigallocatechin 3-O-gallate (EC-EGCG) and eepiafzelechin 3-O-gallate-(4β→8)-epigallocatechin 3-O-gallate (EFG-EGCG), were screened out, which could form complexes with Aβ1-42 (a representative protein target), and could be potential ligands of Aβ1-42. Among of them, EC-EGCG demonstrated the highest binding free energy with Aβ1-42 (−68.54 ± 3.82 kcal/mol). On the other side, even though the caffeine had the highest signal among green tea extracts, it was not observed to form a complex with Aβ1-42. Compared to other methods such as affinity selection mass spectrometry (ASMS) and native MS, our method is easy to operate and interpret the data. Undoubtedly, it provides a new methodology for potential drug discovery in NPs, and will accelerate the research on screening ligands for specific proteins from complex NPs.