Tidying up the conformational ensemble of a disordered peptide by computational prediction of spectroscopic fingerprints

The most advanced structure prediction methods are powerless in exploring the conformational ensemble of disordered peptides and proteins and for this reason the "protein folding problem" remains unsolved. We present a novel methodology that enables the accurate prediction of spectroscopic fingerprints (circular dichroism, infrared, Raman, and Raman optical activity), and by this allows for "tidying up" the conformational ensembles of disordered peptides and disordered regions in proteins. This concept is elaborated for and applied to a dodecapeptide, whose spectroscopic fingerprint is measured and theoretically predicted by means of enhanced-sampling molecular dynamics coupled with quantum mechanical calculations. Following this approach, we demonstrate that peptides lacking a clear propensity for ordered secondary-structure motifs are not randomly, but only conditionally disordered. This means that their conformational landscape, or phase-space, can be well represented by a basis-set of conformers including about 10 to 100 structures. The implications of this finding have profound consequences both for the interpretation of experimental electronic and vibrational spectral features of peptides in solution and for the theoretical prediction of these features using accurate and computationally expensive techniques. The here-derived methods and conclusions are expected to fundamentally impact the rationalization of so-far elusive structure-spectra relationships for disordered peptides and proteins, towards improved and versatile structure prediction methods. Pairing experiments with simulations, we predict spectroscopic fingerprints, enhancing understanding of disordered peptides' conformational ensembles. This helps rationalize elusive structure-spectra relationships for these peptides and proteins.