RDC derived protein backbone resonance assignment using fragment assembly

Abstract

Experimental residual dipolar couplings (RDCs) in combination with structural models have the potential for accelerating the protein backbone resonance assignment process because RDCs can be measured accurately and interpreted quantitatively. However, this application has been limited due to the need for very high-resolution structural templates. Here, we introduce a new approach to resonance assignment based on optimal agreement between the experimental and calculated RDCs from a structural template that contains all assignable residues. To overcome the inherent computational complexity of such a global search, we have adopted an efficient two-stage search algorithm and included connectivity data from conventional assignment experiments. In the first stage, a list of strings of resonances (CA-links) is generated via exhaustive searches for short segments of sequentially connected residues in a protein (local templates), and then ranked by the agreement of the experimental (13)C(α) chemical shifts and (15)N-(1)H RDCs to the predicted values for each local template. In the second stage, the top CA-links for different local templates in stage I are combinatorially connected to produce CA-links for all assignable residues. The resulting CA-links are ranked for resonance assignment according to their measured RDCs and predicted values from a tertiary structure. Since the final RDC ranking of CA-links includes all assignable residues and the assignment is derived from a "global minimum", our approach is far less reliant on the quality of experimental data and structural templates. The present approach is validated with the assignments of several proteins, including a 42 kDa maltose binding protein (MBP) using RDCs and structural templates of varying quality. Since backbone resonance assignment is an essential first step for most of biomolecular NMR applications and is often a bottleneck for large systems, we expect that this new approach will improve the efficiency of the assignment process for small and medium size proteins and will extend the size limits assignable by current methods for proteins with structural models.

Fig. 1

Flowchart for RDC derived protein backbone resonance assignment using fragment assembly

Fig. 2

Output for segments II (left) and IV (right) from assignment procedures described in (a) stage I-A and (b) stage I-C for ubiquitin using a 2.3 Å X-ray structure (1AAR). The correct CA-links for assignments are colored in blue. The first six columns in (a) and (b) are resonance numbers. The last column in (a) is the index for CA-links, and in (b) is the RDC deviations sorted in ascending order. The local structure of segments II and IV are shown as ribbons. For simplicity, resonances are numbered according to the ubiquitin residue number

Fig. 3

Assignment results for ubiquitin using the present approach with a 2.7 Å X-ray structure (1F9J), b 2.3 Å X-ray structure (1ARR), and c RDC refined NMR structure (1D3Z) as templates. The last column shows final RDC deviations. Other columns are resonance numbers. For simplicity, resonances are numbered with the ubiquitin residue number. The correct CA-link for assignments appears in blue. Orange and black numbers are inconsistent and consistent assignments in the top ten solutions, respectively

Fig. 4

Overlay of seven predicted PDZ3 structures from residues 16 to 100. Residues from 1 to 15 and 101 to 113 are not shown for clarity. Each residue is colored according to its Q_res value. Q_res is a measurement of the structural similarity of each residue in a set of overlayed structures. In these seven models, more variations are seen in loops than in structured regions and the packing of an α-helix in one model (model 6) appears to be different from others