AlphaFold pLDDT and expected distance error: Difference between revisions

AlphaFold provides two measures of coordinate error. The residue-by-residue pLDDT value are stored directly in the coordinate file, and the pairwise residue distance error stored in a separate file. Here, we use the bacterial methionine synthase as [https://alphafold.ebi.ac.uk/entry/A0A485DTP7 an example for a predicted structure].

The pLDDT value is assigned to each individual residue and stored in coordinate files instead of temperature factors. Different from temperature factors, high values indicate high confidence in atomic positions, and low values low confidence (scale of 0 to 100). This value is named pLDDT because it predicts the so-called LDDT value (Local Distance Difference Test, <ref>PMID: 23986568</ref>), a way to characterize the difference of two related conformations without aligning the structures.

The LDDT was designed to measure model consistency (or confidence) within a domain. To create a measure of inter-domain confidence, this is an alternate algorithm. 1) For each residue, find other residues with a center-of-mass distance of between 10 and 15 Angstroms. 2) Take the 10 worst distance differences (or estimates) and average them. Calculating this measure for the structure prediction of methionine synthase gives an <scene name='92/920232/Mid_distance_difference_test/2'>estimate of ill-defined domain boundaries</scene>. For this structure, about 40 neighbors were found on average at the chosen distance cutoff.