Characterizing the fragmentation of AlphaFold predictions

Abstract

The Nobel prize winning program AlphaFold2 computes plausible structures of (well) folded proteins. The main quality assessment is based on the predicted Local Distance Difference Test (pLDDT), a per amino acid confidence score. To enhance quality assessment, we provide novel quantitative measures to identify coherent amino acid (a.a.) stretches along the sequence in terms of pLDDT values. These constructions, grounded in standard techniques from topological data analysis and combinatorics, provide a canonical framework for identifying regions along the protein backbone and analyzing their properties, such as their propensity for disorder and their consistency with a null model. The outcome of our analysis can readily be used to select reliable regions/domains within proteins whose pLDDT values span the entire pLDDT range.