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Structural elements inserted in proteins are essential to define folding/unfolding mechanisms and partner recognition events governing signaling processes in living organisms. Here, we present an original approach to model the folding mechanism of these structural elements. Our approach is based on the exploitation of local, sequence-dependent structural information encoded in a database of three-residue fragments extracted from a large set of high-resolution experimentally determined protein structures. The computation of conformational transitions leading to the formation of the structural elements is formulated as a discrete path search problem using this database. To solve this problem, we propose a heuristically-guided depth-first search algorithm. The domain-dependent heuristic function aims at minimizing the length of the path in terms of angular distances, while maximizing the local density of the intermediate states, which is related to their probability of existence. We have applied the strategy to two small synthetic polypeptides mimicking two common structural motifs in proteins. The folding mechanisms extracted are very similar to those obtained when using traditional, computationally expensive approaches. These results show that the proposed approach, thanks to its simplicity and computational efficiency, is a promising research direction. [ABSTRACT FROM AUTHOR]

Proline is found in a cis conformation in proteins more often than other proteinogenic amino acids, where it influences structure and modulates function, being the focus of several high-resolution structural studies. However, until now, technical and methodological limitations have hampered the site-specific investigation of the conformational preferences of prolines present in poly proline (poly-P) homorepeats in their protein context. Here, we apply site-specific isotopic labeling to obtain high-resolution NMR data on the cis/trans equilibrium of prolines within the poly-P repeats of huntingtin exon 1, the causative agent of Huntington's disease. Screening prolines in different positions in long (poly-P 11 ) and short (poly-P 3 ) poly-P tracts, we found that, while the first proline of poly-P tracts adopts similar levels of cis conformation as isolated prolines, a length-dependent reduced abundance of cis conformers is observed for terminal prolines. Interestingly, the cis isomer could not be detected in inner prolines, in line with percentages derived from a large database of proline-centered tripeptides extracted from crystallographic structures. These results suggest a strong cooperative effect within poly-Ps that enhances their stiffness by diminishing the stability of the cis conformation. This rigidity is key to rationalizing the protection toward aggregation that the poly-P tract confers to huntingtin. Furthermore, the study provides new avenues to probe the structural properties of poly-P tracts in protein design as scaffolds or nanoscale rulers.

Intrinsically Disordered Proteins (IDPs) are fundamental actors of biological processes. Their inherent plasticity facilitates very specialized tasks in cell regulation and signalling, and their malfunction is linked to severe pathologies. Understanding the functional role of disorder requires the structural characterization of IDPs and the complexes they form. Small-angle Scattering of X-rays (SAXS) and Neutrons (SANS) have notably contributed to this structural understanding. In this review we summarize the most relevant developments in the field of SAS studies of disordered proteins. Emphasis is given to ensemble methods and how SAS data can be combined with computational approaches or other biophysical information such as NMR. The unique capabilities of SAS enable its application to extremely challenging disordered systems such as low-complexity regions, amyloidogenic proteins and transient biomolecular complexes. This reinforces the fundamental role of SAS in the structural and dynamic characterization of this elusive family of proteins.