Improvements of network approach for analysis of the folding free‐energy surface of peptides and proteins

Jiang, Xuewei; Chen, Changjun; Xiao, Yi

doi:10.1002/jcc.21544

Cited by 11 publications

(5 citation statements)

References 49 publications

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“…The former mainly emphasizes energy, whereas the latter focuses more on conformation. Recently, Jiang et al (49) applied a Markov cluster algorithm to a folding analysis of the trpzip2 peptide. A simplified network with five basins was constructed and the relative free energy and interbasin transitions were clearly demonstrated.…”

Section: Comparison With Other Representations Of Protein Foldingmentioning

confidence: 99%

Folding Network of Villin Headpiece Subdomain

Lei

Jin

et al. 2010

Biophysical Journal

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Protein folding is a complex multidimensional process that is difficult to illustrate by the traditional analyses based on one- or two-dimensional profiles. Analyses based on transition networks have become an alternative approach that has the potential to reveal detailed features of protein folding dynamics. However, due to the lack of successful reversible folding of proteins from conventional molecular-dynamics simulations, this approach has rarely been utilized. Here, we analyzed the folding network from several 10 μs conventional molecular-dynamics reversible folding trajectories of villin headpiece subdomain (HP35). The folding network revealed more complexity than the traditional two-dimensional map and demonstrated a variety of conformations in the unfolded state, intermediate states, and the native state. Of note, deep enthalpic traps at the unfolded state were observed on the folding landscape. Furthermore, in contrast to the clear separation of the native state and the primary intermediate state shown on the two-dimensional map, the two states were mingled on the folding network, and prevalent interstate transitions were observed between these two states. A more complete picture of the folding mechanism of HP35 emerged when the traditional and network analyses were considered together.

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Section: Comparison With Other Representations Of Protein Foldingmentioning

confidence: 99%

Folding Network of Villin Headpiece Subdomain

Lei

Jin

et al. 2010

Biophysical Journal

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“…Understanding peptide folding has attracted significant attention in recent years [1]–[4], with published results covering the whole range from experimental [5]–[8] to theoretical and computational approaches [9]–[12]. The recent advances in simulation algorithms (especially PME-based full electrostatics [13] and multiple time-stepping methods [14]) together with the ever-increasing availability of computing power, has made possible the application of high quality (explicit solvent, full electrostatics) simulations in the µs regime and higher.…”

Section: Introductionmentioning

confidence: 99%

Order through Disorder: Hyper-Mobile C-Terminal Residues Stabilize the Folded State of a Helical Peptide. A Molecular Dynamics Study

Patapati

Glykos

2010

PLoS ONE

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Conventional wisdom has it that the presence of disordered regions in the three-dimensional structures of polypeptides not only does not contribute significantly to the thermodynamic stability of their folded state, but, on the contrary, that the presence of disorder leads to a decrease of the corresponding proteins' stability. We have performed extensive 3.4 µs long folding simulations (in explicit solvent and with full electrostatics) of an undecamer peptide of experimentally known helical structure, both with and without its disordered (four residue long) C-terminal tail. Our simulations clearly indicate that the presence of the apparently disordered (in structural terms) C-terminal tail, increases the thermodynamic stability of the peptide's folded (helical) state. These results show that at least for the case of relatively short peptides, the interplay between thermodynamic stability and the apparent structural stability can be rather subtle, with even disordered regions contributing significantly to the stability of the folded state. Our results have clear implications for the understanding of peptide energetics and the design of foldable peptides.

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“…Another instance is community network analysis (CNA) which is used to study the dynamics of enzymes and protein/DNA (and/or RNA) complexes for understanding their allosteric mechanisms [5] [6]. Similarly, the folding rate of protein has also been modelled using network properties based on only graph-theoretic approach [7].…”

Section: Introductionmentioning

confidence: 99%