Detecting hidden sequence propensity for amyloid fibril formation

The preponderance of evidence implicates protein misfolding in many unrelated human diseases. In all cases, normal correctly folded proteins transform from their proper native structure into an abnormal beta-rich structure known as amyloid fibril. Here we introduce a computational algorithm to detect nonnative (hidden) sequence propensity for amyloid fibril formation. Analyzing sequence-structure relationships in terms of tertiary contact (TC), we find that the hidden beta-strand propensity of a query local sequence can be quantitatively estimated from the secondary structure preferences of template sequences of known secondary structure found in regions of high TC. The present method correctly pinpoints the minimal peptide fragment shown experimentally as the likely local mediator of amyloid fibril formation in beta-amyloid peptide, islet amyloid polypeptide (hIAPP), alpha-synuclein, and human acetylcholinesterase (AChE). It also found previously unrecognized beta-strand propensities in the prototypical helical protein myoglobin that has been reported as amyloidogenic. Analysis of 2358 nonhomologous protein domains provides compelling evidence that most proteins contain sequences with significant hidden beta-strand propensity. The present method may find utility in many medically relevant applications, such as the engineering of protein sequences and the discovery of therapeutic agents that specifically target these sequences for the prevention and treatment of amyloid diseases.