Abstract
Solvent accessibility has been extensively used to characterize and predict the chemical properties of the surface residues of soluble proteins. However, there is not yet a widely accepted quantity of the same dimension for the study of lipid-accessible residues of membrane proteins. In this study, we propose that lipid accessibility, defined in a similar way to solvent accessibility, can be used to characterize the lipid-accessible residues of membrane proteins. Moreover, we developed a deep learning-based method, ProtRAP (Protein Relative Accessibility Predictor), to predict the relative lipid accessibility and relative solvent accessibility of residues from a given protein sequence, which can infer which residues are likely accessible to lipids, accessible to solvent, or buried in the protein interior in one run.
Published Version
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