Name
Abstract | ||
|---|---|---|
Self-binding peptides (SBPs) represent those short peptide segments within monomeric proteins to fulfill their biological functions by dynamically binding to/unbinding from their target domains in the same monomers. They are frequently found in disordered or unstructured regions of proteins that are now known to be not simply helices, loops, or linkers and adopt a well-defined structure upon binding. In this study, we systematically explored the structural basis, energy landscape, and thermodynamic properties of SBP-mediated biological mechanisms by dissecting dynamic interactions of SBPs with their cognate targets. In order to identify whether the formation of the SBP-target bound state is naturally a folding or a binding, we carried out atomistic molecular dynamics (MD) simulations to investigate both the native bound state of eight representative SBPs in complex with their cognate domains and the same bound state but where the SBPs were split artificially from the domains in primary sequence. Results showed that the splitting did not influence essentially the interaction behavior of SBPs with their target domains, suggesting that the SBP-domain interaction is almost a binding phenomenon, although the polypeptide linker between the SBP and the domain seems to facilitate the interaction. In addition, the sequence pattern of SBPs is very similar to those of short linear motifs (SLiM) found in many protein-binding peptides where few key residues contribute predominantly to protein-peptide recognition. All of the above comes together to suggest that the SBP is a novel biomolecular phenomenon spanning between folding and binding. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1021/ci500522v | JOURNAL OF CHEMICAL INFORMATION AND MODELING |
Field | DocType | Volume |
Bound state,Peptide,Chemistry,Molecular dynamics,Helix,Bioinformatics,Energy landscape | Journal | 55 |
Issue | ISSN | Citations |
2 | 1549-9596 | 8 |
PageRank | References | Authors |
0.85 | 9 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chao Yang | 1 | 14 | 3.12 |
| Shilei Zhang | 2 | 57 | 9.81 |
| Ping He | 3 | 8 | 0.85 |
| Congcong Wang | 4 | 23 | 2.78 |
| Jian Huang | 5 | 2608 | 200.50 |
| Peng Zhou | 6 | 9 | 1.23 |