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Published on: August 20, 2014
Nascent Hairpins in Proteins: Identifying Turn Loci and Quantitating Turn Contributions to Hairpin Stability
Jordan M Anderson1, Brice Jurban1, Kelly N L Huggins1
1Department of Chemistry, University of Washington , Seattle, Washington 98105, United States.
Abstract:
Many factors influence the stability of hairpins that could appear as foldons in partially folded states of proteins; of these, the propensity of certain amino acid sequences to favor conformations that serve to align potential β-strands for antiparallel association is likely the dominant feature. Quantitating turn propensities is viewed as the first step in developing an algorithm for locating nascent hairpins in protein sequences. Such nascent hairpins can serve to accelerate protein folding or, if they represent structural elements that differ from the final folded state, as kinetic traps. We have measured these "turn propensities" for the two most common turn types using a series of model peptide hairpins with four- and six-residue loops connecting the associated β-strands. Loops of four to six residues with specific turn sequences containing only natural l-amino acids and glycine can provide as much as 15 kJ/mol of hairpin stabilization versus loops lacking the defined turn loci. Single-site mutations within some of the optimal connecting loops can have ΔΔG effects as large as 9-10 kJ/mol on hairpin stability. In contrast to the near universal II'/I' turns of model hairpins, a number of hairpin-supporting XZZG sequence β-turns with αR and/or γR configurations at the ZZ unit were found. A series of turn replacements (four-residue β-turns replaced by sequences that favor five- and six-residue reversing loops) using identical strands in our model systems have confirmed that several sequences have intrinsic turn propensities that could favor β-strand association in a non-native strand register and thus serve as kinetic traps. These studies also indicate that aryl residues immediately flanking a turn sequence can alter relative turn propensities by as much as 9-11 kJ/mol and will need to be a part of any nascent hairpin recognition algorithm.
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