A hybrid, bottom-up, structurally accurate, Go¯-like coarse-grained protein model.

ABSTRACT: Coarse-grained (CG) protein models in the structural biology literature have improved over the years from being simple tools to understand general folding and aggregation driving forces to capturing detailed structures achieved by actual folding sequences. Here, we ask whether such models can be developed systematically from recent advances in bottom-up coarse-graining methods without relying on bioinformatic data (e.g., protein data bank statistics). We use relative entropy coarse-graining to develop a hybrid CG but Go¯-like CG peptide model, hypothesizing that the landscape of proteinlike folds is encoded by the backbone interactions, while the sidechain interactions define which of these structures globally minimizes the free energy in a unique native fold. To construct a model capable

SUBMITTER: Sanyal T 

PROVIDER: S-EPMC6663515 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature