Concurrent Identification and Characterization of Protein Structure and Continuous Internal Dynamics with REDCRAFT

Abstract

Internal dynamics of proteins can play a critical role in the biological function of some proteins. Several well documented instances have been reported such as MBP, DHFR, hTS, DGCR8, and NSP1 of the SARS-CoV family of viruses. Despite the importance of internal dynamics of proteins, there currently are very few approaches that allow for meaningful separation of internal dynamics from structural aspects using experimental data. Here we present a computational approach named REDCRAFT that allows for concurrent characterization of protein structure and dynamics. Here, we have subjected DHFR (PDB-ID 1RX2), a 159-residue protein, to a fictitious, mixed mode model of internal dynamics. In this simulation, DHFR was segmented into 7 regions where 4 of the fragments were fixed with respect to each other, two regions underwent rigid-body dynamics, and one region experienced uncorrelated and melting event. The two dynamical and rigid-body segments experienced an average orientational modification of 7° and 12° respectively. Observable RDC data for backbone C′-N, N-HN, and C′-HN were generated from 102 uniformly sampled frames that described the molecular trajectory. The structure calculation of DHFR with REDCRAFT by using traditional Ramachandran restraint produced a structure with 29 Å of structural difference measured over the backbone atoms (bb-rmsd) over the entire length of the protein and an average bb-rmsd of more than 4.7 Å over each of the dynamical fragments. The same exercise repeated with context-specific dihedral restraints generated by PDBMine produced a structure with bb-rmsd of 21 Å over the entire length of the protein but with bb-rmsd of less than 3 Å over each of the fragments. Finally, utilization of the Dynamic Profile generated by REDCRAFT allowed for the identification of different dynamical regions of the protein and the recovery of individual fragments with bb-rmsd of less than 1 Å. Following the recovery of the fragments, our assembly procedure of domains (larger segments consisting of multiple fragments with a common dynamical profile) correctly assembled the four fragments that are rigid with respect to each other, categorized the two domains that underwent rigid-body dynamics, and identified one dynamical region for which no conserved structure could be defined. In conclusion, our approach was successful in identifying the dynamical domains, recovery of structure where it is meaningful, and relative assembly of the domains when possible.

Representing structures of the multiple conformational states of proteins

“…Chemical shift refocusing experiments like Carr-Purcell-Meiboom-Gill (CPMG) relaxation dispersion and T1rho relaxation experiments, and saturation transfer experiments (e.g., chemical exchange by saturation transfer, CEST), can provide quantitative information about conformational exchange on the intermediate or slow chemical shift timescale [34] and can be used to characterize sparsely-populated states that cannot otherwise be observed in NMR spectra [35]. NOESY and residual dipolar coupling (RDC) data can reveal multiple conformations in fast dynamic equilibrium, and may provide structural restraints for modeling each state [38][39][40][41]. Paramagnetic effects in metal-containing biomolecules provide ensemble-averaged distance restraints and can also determine ensemble-averaged relative orientations of structural domains [42,43].…”

Representing Structures of the Multiple Conformational States of Proteins

“…Chemical shift refocusing experiments like Carr-Purcell-Meiboom-Gill (CPMG) relaxation dispersion and T1rho relaxation experiments, and saturation transfer experiments (e.g., chemical exchange by saturation transfer, CEST), can provide quantitative information about conformational exchange on the intermediate or slow chemical shift timescale [34], and can be used to characterize sparsely-populated states that cannot otherwise be observed in NMR spectra [35]. NOESY and residual dipolar coupling (RDC) data can reveal multiple conformations in fast dynamic equilibrium and provide structural restraints for modeling each state [38][39][40][41]. Paramagnetic effects in metal-containing biomolecules provide ensemble-averaged distance restraints and can also determine ensemble-averaged relative orientations of structural domains [42,43].…”