Recognizing misfolded and distorted protein structures by the assumption-based similarity score.

Abstract

A new similarity score (sigma-score) is proposed which is able to find the correct protein structure among the very close alternatives and to distinguish between correct and deliberately misfolded structures. This score is based on the general principle 'similar likes similar', and it favors hydrophobic and hydrophilic contacts, and disfavors hydrophobic-to-hydrophilic contacts in proteins. The values of sigma-scores calculated for the high-resolution protein structures from the representative set are compared with those of alternatives: (i) very close alternatives which are only slightly distorted by conformational energy minimization in vacuo; (ii) alternatives with subsequently growing distortions, generated by molecular dynamics simulations in vacuo; (iii) structures derived by molecular dynamics simulation in solvent at 300 K; (iv) deliberately misfolded protein models. In nearly all tested cases the similarity score can successfully distinguish between experimental structure and its alternatives, even if the root mean square displacement of all heavy atoms is less than 1 A. The confidence interval of the similarity score was estimated using the high-resolution X-ray structures of domain pairs related by non-crystallographic symmetry. The similarity score can be used for the evaluation of the general quality of the protein models, choosing the correct structures among the very close alternatives, characterization of models simulating folding/unfolding, etc.