Improvements in lectin-glycan binding arrays and AI predictive models are necessary to expand the scope and reliability of glycan sequencing technology. In this study, we investigated how the deglycosylation of five lectins (DSL, PHA-E RCA-1, SNA, and WGA) may alter the binding signal between lectins and the model protein Fetuin B. We used Protein Deglycosylation Mix II to remove glycans from the lectins, validated deglycosylation by observing mobility shifts in SDS-PAGE gels, and conducted an ELISA to measure differences in lectin-protein binding between deglycosylated and non-deglycosylated lectin samples. We inputted the results from the ELISA into the Lewis Lab’s glycan sequencing AI model GlycoSeq and observed differences in the predicted glycoprofile between the deglycosylated and native lectin variants. However, further controlled experiments, including the purification of the lectins after deglycosylation, and updated model assumptions are required.