Accurate protein structure modeling using sparse NMR data and homologous structure information

Abstract

While information from homologous structures plays a central role in X-ray structure determination by molecular replacement, such information is rarely used in NMR structure determination because it can be incorrect, both locally and globally, when evolutionary relationships are inferred incorrectly or there has been considerable evolutionary structural divergence. Here we describe a method that allows robust modeling of protein structures of up to 225 residues by combining 1 H N , 13 C, and 15 N backbone and 13 Cβ chemical shift data, distance restraints derived from homologous structures, and a physically realistic all-atom energy function. Accurate models are distinguished from inaccurate models generated using incorrect sequence alignments by requiring that (i) the all-atom energies of models generated using the restraints are lower than models generated in unrestrained calculations and (ii) the low-energy structures converge to within 2.0 Å backbone rmsd over 75% of the protein. Benchmark calculations on known structures and blind targets show that the method can accurately model protein structures, even with very remote homology information, to a backbone rmsd of 1.2-1.9 Å relative to the conventional determined NMR ensembles and of 0.9-1.6 Å relative to X-ray structures for well-defined regions of the protein structures. This approach facilitates the accurate modeling of protein structures using backbone chemical shift data without need for side-chain resonance assignments and extensive analysis of NOESY cross-peak assignments.biochemistry | biophysics | computational biology | nuclear magnetic resonance | structural genomics I n recent years, the application of multidimensional data collection techniques in isotopically enriched proteins (1) as well as development of selective labeling schemes in perdeuterated samples (2-5) and other methodological improvements (6, 7) have allowed the application of NMR methods to larger proteins (8-10). Conventional NMR structure determination relies primarily on the availability of distance restraints from NOESY experiments, which requires time-consuming experiments, including extensive analysis of side-chain resonance assignments and laborious assignments of most of the observed NOESY crosspeak resonances. While automated assignment methods (11-13) have greatly stream-lined the process (14), the assignment of NOE cross-peaks in spectra of larger proteins presents a significant challenge due to increased spectral overlap, line broadening, and low signal-to-noise ratios, rendering existing automated assignment methods ineffective in the absence of a preliminary structural model. Accurate structures can be generated for small proteins (up to 100-120 residues) using chemical shift information to guide structure prediction calculations (15, 16), but additional NMR data, including backbone NOEs and residual dipolar coupling (RDC) data, are required to obtained converged structures for larger proteins (17) and protein oligomers (18). Such data are often hard to collect and a...

Solution NMR refinement of a metal ion bound protein using metal ion inclusive restrained molecular dynamics methods

“…NOE and RDC restraint-based simulations can identify multiple conformations or Markov states that may play a role in biological function (Chennubhotla and Bahar 2006). Indeed, this approach will aid in protein folding studies by presenting additional metal ion based restraints (Lange et al 2012; Thompson et al 2012) and help in the design and structure determination of novel metal-templated proteins (Brodin et al 2010; Salgado et al 2010; Salgado et al 2011). QM/MM MD metal ion NMR-refinement calculations are particularly poised to tackle protein structures with previously undetermined metal-binding conformations (Chakravorty et al 2012a; Lee et al 2012).…”

A Mechanism for the Auto-inhibition of Hyperpolarization-activated Cyclic Nucleotide-gated (HCN) Channel Opening and Its Relief by cAMP

“…In addition to chemical shift and residual dipolar couplings, distance restraints were generated from remote homologous structures using the CS-HM protocol (41,51). Homologous protein structures and their alignment to the target sequence were determined with HHSEARCH (version 2.0.16).…”

Iterative Molecular Dynamics–Rosetta Membrane Protein Structure Refinement Guided by Cryo-EM Densities

“…Experimental data has been used from a broad range of sources including NMR spectroscopy 52–54 , fluorescence resonance energy transfer microscopy (FRET) 55 , electron paramagnetic resonance (EPR) 56, 57 , cryo-EM 58–60 , small angle X-ray scattering (SAXS) 61, 62 , small angle neutron scattering (SANS) 63 and mass spectroscopy 64–66 . These sparse experimental restraints used in combination with computational methods have shown to considerably improve macromolecular structure prediction and refinement 53, 60, 67 . Rosetta allows the use of many types of experimental restraints in its structure prediction and refinement protocols 52, 58, 68 .…”