Folding with a protein's native shortcut network
Susan Khor

TL;DR
This paper introduces a network-based approach to protein folding using native shortcut networks, revealing correlations with folding rates and pathways, and providing insights into the hierarchical nature of folding processes.
Contribution
It proposes a novel network analysis method for protein folding, linking native topology to folding kinetics and pathways, applicable to both native and non-native structures.
Findings
SCN0_lnCO correlates with folding rates.
CSCN0 helps identify folding pathways.
Analysis extends to non-native structures and predicts folding success factors.
Abstract
A complex network approach to protein folding is proposed. The graph object is the network of shortcut edges present in a native-state protein (SCN0). Although SCN0s are found via an intuitive message passing algorithm (S. Milgram, Psychology Today, May 1967 pp. 61-67), they are meaningful enough that the logarithm form of their contact order (SCN0_lnCO) correlates significantly with protein kinetic rates, regardless of protein size. Further, the clustering coefficient of a SCN0 (CSCN0) can be used to combine protein segments iteratively within the Restricted Binary Collision model to form the whole native structure. This simple yet surprisingly effective strategy identified reasonable folding pathways for 12 small single-domain two-state folders, and three non-canonical proteins: ACBP (non-two-state), Top7 (non-cooperative) and DHFR (non-single-domain, > 100 residues). For two-state…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
