ABSTRACT Levinthal's paradox is that finding the native folded state of a protein by a random search among all possible configurations can take an enormously long time. Yet proteins can fold in seconds or less. Mathematical analysis of a simple model shows that a small and physically reasonable energy bias against locally unfavorable configurations, of the order of a few kT, can reduce Levinthal's time to a biologically significant size.
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ABSTRACT: How do proteins fold, and why do they fold in that way? This Perspective integrates earlier and more recent advances over the 50-y history of the protein folding problem, emphasizing unambiguously clear structural information. Experimental results show that, contrary to prior belief, proteins are multistate rather than two-state objects. They are composed of separately cooperative foldon building blocks that can be seen to repeatedly unfold and refold as units even under native conditions. Similarly, foldons are lost as units when proteins are destabilized to produce partially unfolded equilibrium molten globules. In kinetic folding, the inherently cooperative nature of foldons predisposes the thermally driven amino acid-level search to form an initial foldon and subsequent foldons in later assisted searches. The small size of foldon units, ∼20 residues, resolves the Levinthal time-scale search problem. These microscopic-level search processes can be identified with the disordered multitrack search envisioned in the "new view" model for protein folding. Emergent macroscopic foldon-foldon interactions then collectively provide the structural guidance and free energy bias for the ordered addition of foldons in a stepwise pathway that sequentially builds the native protein. These conclusions reconcile the seemingly opposed new view and defined pathway models; the two models account for different stages of the protein folding process. Additionally, these observations answer the "how" and the "why" questions. The protein folding pathway depends on the same foldon units and foldon-foldon interactions that construct the native structure.Proceedings of the National Academy of Sciences 10/2014; 111(45). DOI:10.1073/pnas.1411798111 · 9.81 Impact Factor
Article: The Human Genome ProjectAccounts of Chemical Research 04/1994; 27(4):94-100. DOI:10.1021/ar00040a002 · 24.35 Impact Factor
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ABSTRACT: Secondary structure assignment codes were built to explore the regularities associated with the periodic motifs of proteins, such as those in backbone dihedral angles or in hydrogen bonds between backbone atoms. Precise structure assignment is challenging because real-life secondary structures are susceptible to bending, twist, fraying and other deformations that can distance them from their geometrical prototypes. Although results from codes such as DSSP and STRIDE converge in well-ordered structures, the agreement between the secondary structure assignments is known to deteriorate as the conformations become more distorted. Conformationally irregular peptides therefore offer a great opportunity to explore the differences between these codes. This is especially important for unfolded proteins and intrinsically disordered proteins, which are known to exhibit residual and/or transient secondary structure whose characterization is challenging. In this work, we have carried out Molecular Dynamics simulations of (relatively) disordered peptides, specifically gp41659-671 (ELLELDKWASLWN), the homopeptide polyasparagine (N18), and polyasparagine dimers. We have analyzed the resulting conformations with DSSP and STRIDE, based on hydrogen-bond patterns (and dihedral angles for STRIDE), and KAKSI, based on α-Carbon distances; and carefully characterized the differences in structural assignments. The full-sequence Segment Overlap (SOV) scores, that quantify the agreement between two secondary structure assignments, vary from 70% for gp41659-671 (STRIDE as reference) to 49% for N18 (DSSP as reference). Major differences are observed in turns, in the distinction between α and 310 helices, and in short parallel-sheet segments.Journal of Molecular Graphics and Modelling 11/2014; 55. DOI:10.1016/j.jmgm.2014.10.005 · 2.02 Impact Factor