AIM: To employ proteome-wide Mendelian randomization (MR) to explore novel protein and drug targets for retinal neurodegenerative diseases (RND) in individuals of European ancestry. METHODS: This study used summary data-based MR to analyze the correlation between plasma protein levels and three RND, with protein data derived from two independent large-scale proteomics datasets. Potential drug targets were identified using Bayesian colocalization, followed by MR analysis, sensitivity testing, and external validation. Drug prediction and molecular docking were conducted to evaluate the druggability of the target proteins. RESULTS: The study identified six promising protein targets, each successfully replicated at least twice. The results included three proteins related to diabetic retinopathy (ICAM1, GCKR, WARS), two proteins related to age-related macular degeneration (WARS, BRD2), and two proteins related to glaucoma (SVEP1, NPTXR). Additionally, drug prediction and molecular docking indicated that five drugs (fenofibrate, trofinetide, ticagrelor, lifitegrast, acetaminophen) effectively bound to the target proteins. CONCLUSION: This study identified six potential protein targets for RND and five existing drugs with therapeutic potential. By integrating plasma proteomics with genetic data, it provides a cost-effective framework for drug discovery.