Machine learning predicts the functional composition of the protein corona and the cellular recognition of nanoparticles.

ABSTRACT: Protein corona formation is critical for the design of ideal and safe nanoparticles (NPs) for nanomedicine, biosensing, organ targeting, and other applications, but methods to quantitatively predict the formation of the protein corona, especially for functional compositions, remain unavailable. The traditional linear regression model performs poorly for the protein corona, as measured by R² (less than 0.40). Here, the performance with R² over 0.75 in the prediction of the protein corona was achieved by integrating a machine learning model and meta-analysis. NPs without modification and surface modification were identified as the two most important factors determining protein corona formation. According to experimental verification, the functional protein

SUBMITTER: Ban Z 

PROVIDER: S-EPMC7229677 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature