9,988 research outputs found

    Dissecting Ubiquitin Folding Using the Self-Organized Polymer Model

    Full text link
    Folding of Ubiquitin (Ub) is investigated at low and neutral pH at different temperatures using simulations of the coarse-grained Self-Organized-Polymer model with side chains. The calculated radius of gyration, showing dramatic variations with pH, is in excellent agreement with scattering experiments. At TmT_m Ub folds in a two-state manner at low and neutral pH. Clustering analysis of the conformations sampled in equilibrium folding trajectories at TmT_m, with multiple transitions between the folded and unfolded states, show a network of metastable states connecting the native and unfolded states. At low and neutral pH, Ub folds with high probability through a preferred set of conformations resulting in a pH-dependent dominant folding pathway. Folding kinetics reveal that Ub assembly at low pH occurs by multiple pathways involving a combination of nucleation-collapse and diffusion collision mechanism. The mechanism by which Ub folds is dictated by the stability of the key secondary structural elements responsible for establishing long range contacts and collapse of Ub. Nucleation collapse mechanism holds if the stability of these elements are marginal, as would be the case at elevated temperatures. If the lifetimes associated with these structured microdomains are on the order of hundreds of μsec\mu sec then Ub folding follows the diffusion-collision mechanism with intermediates many of which coincide with those found in equilibrium. Folding at neutral pH is a sequential process with a populated intermediate resembling that sampled at equilibrium. The transition state structures, obtained using a PfoldP_{fold} analysis, are homogeneous and globular with most of the secondary and tertiary structures being native-like. Many of our findings are not only in agreement with experiments but also provide missing details not resolvable in standard experiments

    Assessing the effect of dynamics on the closed-loop protein-folding hypothesis

    Get PDF
    The closed-loop (loop-n-lock) hypothesis of protein folding suggests that loops of about 25 residues, closed through interactions between the loop ends (locks), play an important role in protein structure. Coarse-grain elastic network simulations, and examination of loop lengths in a diverse set of proteins, each supports a bias towards loops of close to 25 residues in length between residues of high stability. Previous studies have established a correlation between total contact distance (TCD), a metric of sequence distances between contacting residues (cf. contact order), and the log-folding rate of a protein. In a set of 43 proteins, we identify an improved correlation ( r 2 = 0.76), when the metric is restricted to residues contacting the locks, compared to the equivalent result when all residues are considered ( r 2 = 0.65). This provides qualified support for the hypothesis, albeit with an increased emphasis upon the importance of a much larger set of residues surrounding the locks. Evidence of a similar-sized protein core/extended nucleus (with significant overlap) was obtained from TCD calculations in which residues were successively eliminated according to their hydrophobicity and connectivity, and from molecular dynamics simulations. Our results suggest that while folding is determined by a subset of residues that can be predicted by application of the closed-loop hypothesis, the original hypothesis is too simplistic; efficient protein folding is dependent on a considerably larger subset of residues than those involved in lock formation. </jats:p

    Protein secondary structure: Entropy, correlations and prediction

    Get PDF
    Is protein secondary structure primarily determined by local interactions between residues closely spaced along the amino acid backbone, or by non-local tertiary interactions? To answer this question we have measured the entropy densities of primary structure and secondary structure sequences, and the local inter-sequence mutual information density. We find that the important inter-sequence interactions are short ranged, that correlations between neighboring amino acids are essentially uninformative, and that only 1/4 of the total information needed to determine the secondary structure is available from local inter-sequence correlations. Since the remaining information must come from non-local interactions, this observation supports the view that the majority of most proteins fold via a cooperative process where secondary and tertiary structure form concurrently. To provide a more direct comparison to existing secondary structure prediction methods, we construct a simple hidden Markov model (HMM) of the sequences. This HMM achieves a prediction accuracy comparable to other single sequence secondary structure prediction algorithms, and can extract almost all of the inter-sequence mutual information. This suggests that these algorithms are almost optimal, and that we should not expect a dramatic improvement in prediction accuracy. However, local correlations between secondary and primary structure are probably of under-appreciated importance in many tertiary structure prediction methods, such as threading.Comment: 8 pages, 5 figure
    corecore