2024 AIChE Annual Meeting
Predicting the Nonfouling Properties of Peptides Using Model Ensemble
Nonfouling peptides, which bind specifically to the body, are invaluable in biomedical applications such as drug delivery. However, recognizing nonfouling peptides poses a significant challenge due to the limited number of known peptides and their complex synthesis. The vast array of untested peptides makes the experimental process both costly and time-consuming. To address this, we employ protein language models (PLMs) to facilitate the recognition of nonfouling peptides. This study investigates the impact of a model ensemble on the accuracy of nonfouling peptide predictions and leverages this ensemble to test peptides from natural sources, aiming to discover more biomedically useful peptides.