Computational diagnosis of protein conformational diseases: short molecular dynamics simulations reveal a fast unfolding of r-LDL mutants that cause familial hypercholesterolemia.
The molecular basis of conformational diseases frequently resides in mutant proteins constituting a subset of the vast mutational space. While the subtleties of protein structure point to molecular dynamics (MD) techniques as promising tools for an efficient exploration of such a space, the average size of proteins and the time scale of unfolding events make this goal difficult with present computational capabilities. We show here, nevertheless, that an efficient approach is already feasible for modular proteins. Familial hypercholesterolemia (FH) is a conformational disease linked to mutations in the gene encoding the low density lipoprotein receptor. A high percentage of these mutations has been found in the seven small modular binding repeats of the receptor. Taking advantage of its small size, we have performed an in depth MD study of the fifth binding repeat. Fast unfolding dynamics have been observed in the absence of a structural bound calcium ion, which agrees with its reported essential role in the stability of the module. In addition, several mutations detected in FH patients have been analyzed, starting from the native conformation. Our results indicate that in contrast with the wild type protein and an innocuous control mutant, disease-related mutants experience, in short simulation times (2-8 ns), gross departures from the native state that lead to unfolded conformations and, in some cases, to binding site desorganization deriving in calcium release. Computational diagnosis of mutations leading to conformational diseases seems thus feasible, at least for small or modular pathogenic proteins.