Detection of key proteins has enormous medical potential, particularly during the initial phase of an outbreak of infectious diseases. For this purpose, we develop a research paradigm based on computational speculation. With the rapid development of computers, it is possible to analyze the structure of key proteins and screen specific fluorescent ligands through computational tools. This process resembles the production of antibodies but is more effective, and the resultant product is significantly cheaper. A proof of concept was demonstrated by studying the S protein of SARS-CoV-2. The structural data of the S protein enabled automated docking with fluorescent molecules. After two rounds of conditional screening and verification, the most effective fluorescent ligand, Protoporphyrin IX (PPIX), was identified. PPIX illuminates the S protein, recovers fluorescence upon binding. The illuminated complex is enriched by a single microsphere, allowing for the quantitative analysis of the proteins through fluorescence intensity. Finally, less than 1000 copies S protein-bearing pseudovirus can be detected in 20 minutes without amplification. Overall, we established a highly sensitive general method for protein detection based on single microsphere enrichment with the aid of computerised simulation. We hope this integrated approach will provide new insights for rapid screening in epidemic populations.