The Network Dynamics (ND) model is proposed. ND views protein folding as a partial ordering of contacts in a native-state Protein Residue Network (PRN0). The ND process recreates a PRN0 , which gives rise to edges called shortcuts, named for their backtracking avoidance role in small-world communication between nodes in a PRN0. Clustering of native shortcut edges were previously shown able to identify folding pathways. ND applies two fundamental folding principles: loop-entropy and hydrophobic (and other key folding) interactions, via two model parameters which control the probability of edge creation and the probability of node selection. Correlation between experimental folding rates and ND simulated folding rates is strongest when the probability of edge creation is higher for contacts with smaller sequence separation, and when the probability of node selection is higher for nodes with larger remaining degree within a local neighborhood. These two conditions also induce a wider range of simulated folding rates, which is a sign of cooperative folding for two-state folders; and better correspondence between experimental phi-values and calculated phi-values. The calculated phi-values based on centrality of nodes in ND networks are competitive with phi-values calculated from transition-state ensemble PRNs, but are less so than phi-values calculated as local centrality (a measure introduced in this paper) of nodes in PRN0s. Taken together, the two influences on the ordering of PRN0 contacts , result in more route-like formation of native shortcut networks, and hence more two-state like folding. Of the five ND variants tested, the best results at  the macroscopic, mesoscopic and microscopic levels, were produced by a single variant. These ND results extend the utility of protein structure networks to the investigation of partially folded structures, and to the folding process itself .
The Network Dynamics (ND) model is proposed. ND views protein folding as a partial ordering of contacts in a native-state Protein Residue Network (PRN0). The ND process recreates a PRN0 while keeping nodes fixed at PDB positions. ND applies two fundamental folding principles: loop-entropy and hydrophobic (and other key folding) interactions, via two model parameters which control the probability of edge creation and the probability of node selection. Correlation between experimental folding rates and ND simulated folding rates is strongest when the probability of edge creation is higher for contacts with smaller sequence separation, and when the probability of node selection is higher for nodes with larger remaining degree within a local neighborhood. These two conditions also induce a wider range of simulated folding rates, which is a sign of cooperative folding for two-state folders; and better correspondence between experimental phi-values and calculated phi-values. The calculated phi-values based on centrality of nodes in ND PRNs are competitive with phi-values calculated from transition-state ensemble PRNs, but are less so than phi-values calculated as local centrality (a measure introduced in this paper) of nodes in PRN0s. The two influences on the ordering of PRN0 contacts also result in more route-like formation of native shortcut networks, and hence more two-state like folding. Of the five ND variants tested, the best results at each of the macroscopic, mesoscopic and microscopic levels, is produced by a single ND variant. Further preliminary exploration of mixed ND variants by chain fold type suggests that these results could be improved with context-sensitive model parameters, and that the ND model could be extended to multi-state folders .
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