Reduced dimensionality (3,2)D NMR experiments and their automated analysis: implications to high‐throughput structural studies on proteins

Protein NMR spectroscopy has expanded dramatically over the last decade into a powerful tool for the study of their structure, dynamics, and interactions. The primary requirement for all such investigations is sequence‐specific resonance assignment. The demand now is to obtain this information as rapidly as possible and in all types of protein systems, stable/unstable, soluble/insoluble, small/big, structured/unstructured, and so on. In this context, we introduce here two reduced dimensionality experiments – (3,2)D‐hNCO canH and (3,2)D‐hN coCA nH – which enhance the previously described 2D NMR‐based assignment methods quite significantly. Both the experiments can be recorded in just about 2–3 h each and hence would be of immense value for high‐throughput structural proteomics and drug discovery research. The applicability of the method has been demonstrated using alpha‐helical bovine apo calbindin‐D9k P43M mutant (75 aa) protein. Automated assignment of this data using AUTOBA has been presented, which enhances the utility of these experiments. The backbone resonance assignments so derived are utilized to estimate secondary structures and the backbone fold using Web‐based algorithms. Taken together, we believe that the method and the protocol proposed here can be used for routine high‐throughput structural studies of proteins. Copyright © 2014 John Wiley & Sons, Ltd.     

Facile backbone (1H, 15N, 13Ca,and 13C′) assignment of 13C/15N‐labeled proteins using orthogonal projection planes of HNN and HN(C)N experiments and its automation

Recently, we introduced an efficient high‐throughput protocol for backbone assignment of small folded proteins based on two‐dimensional (2D) projections of HN(C)N suite of experiments and its automation [Borkar et al., J. Biomol. NMR 2011, 50(3), 285–297]. This strategy provides complete sequence‐specific assignment of backbone (¹H, ¹⁵N, ¹³C^α, and ¹³C′) resonances in less than a day; thus, it has great implications for high‐throughput structural proteomics. However, in cases when such small folded protein exhibits substantial amide ¹H shift degeneracy (typically seen in alpha‐helical proteins), the strategy may fail or lead to ambiguities. Another limitation is with respect to the identification of checkpoints from the variants of 2D‐hncNH spectrum. For example, a protein with many GG, GA, AA, SS, TS, TT, and TS types of dipeptide stretches along its sequence, thus the identification of NH cross‐peak corresponding to second G, A, S, or T becomes difficult. In this backdrop, we present here two improvements to enhance the utility of the proposed high‐throughput AUTOmatic Backbone Assignment protocol: (i) use of 2D‐hNnH spectrum and its variants that display additional ¹H–¹⁵N correlations and thus help to resolve ambiguities arising because of amide ¹H shift degeneracy and (ii) optimization of the τ_CN delay in the 2D‐hncNH experiment that, when properly adjusted, is observed to help remove ambiguities in the identification of the checkpoints. These improvements have also been incorporated in the automation program AUTOmatic Backbone Assignment. Finally, the performance of the strategy and the automation has been demonstrated using the chicken SH3 domain protein. Copyright © 2012 John Wiley & Sons, Ltd.