IGF-dependent dynamic modulation of a protease cleavage site in the intrinsically disordered linker domain of human IGFBP2.

Functional regulation via conformational dynamics is well known in structured proteins but less well characterized in intrinsically disordered proteins and their complexes. Using NMR spectroscopy, we have identified a dynamic regulatory mechanism in the human insulin-like growth factor (IGF) system involving the central, intrinsically disordered linker domain of human IGF-binding protein-2 (hIGFBP2). The bioavailability of IGFs is regulated by the proteolysis of IGF-binding proteins. In the case of hIGFBP2, the linker domain (L-hIGFBP2) retains its intrinsic disorder upon binding IGF-1, but its dynamics are significantly altered, both in the IGF binding region and distantly located protease cleavage sites. The increase in flexibility of the linker domain upon IGF-1 binding may explain the IGF-dependent modulation of proteolysis of IGFBP2 in this domain. As IGF homeostasis is important for cell growth and function, and its dysregulation is a key contributor to several cancers, our findings open up new avenues for the design of IGFBP analogs inhibiting IGF-dependent tumors.

A fast NMR method for resonance assignments: application to metabolomics.

We present a new method for rapid NMR data acquisition and assignments applicable to unlabeled ((12)C) or (13)C-labeled biomolecules/organic molecules in general and metabolomics in particular. The method involves the acquisition of three two dimensional (2D) NMR spectra simultaneously using a dual receiver system. The three spectra, namely: (1) G-matrix Fourier transform (GFT) (3,2)D [(13)C, (1)H] HSQC-TOCSY, (2) 2D (1)H-(1)H TOCSY and (3) 2D (13)C-(1)H HETCOR are acquired in a single experiment and provide mutually complementary information to completely assign individual metabolites in a mixture. The GFT (3,2)D [(13)C, (1)H] HSQC-TOCSY provides 3D correlations in a reduced dimensionality manner facilitating high resolution and unambiguous assignments. The experiments were applied for complete (1)H and (13)C assignments of a mixture of 21 unlabeled metabolites corresponding to a medium used in assisted reproductive technology. Taken together, the experiments provide time gain of order of magnitudes compared to the conventional data acquisition methods and can be combined with other fast NMR techniques such as non-uniform sampling and covariance spectroscopy. This provides new avenues for using multiple receivers and projection NMR techniques for high-throughput approaches in metabolomics.

Amino acid selective labeling and unlabeling for protein resonance assignments.

Structural characterization of proteins by NMR spectroscopy begins with the process of sequence specific resonance assignments in which the (1)H, (13)C and (15)N chemical shifts of all backbone and side-chain nuclei in the polypeptide are assigned. This process requires different isotope labeled forms of the protein together with specific experiments for establishing the sequential connectivity between the neighboring amino acid residues. In the case of spectral overlap, it is useful to identify spin systems corresponding to the different amino acid types selectively. With isotope labeling this can be achieved in two ways: (i) amino acid selective labeling or (ii) amino acid selective 'unlabeling'. This chapter describes both these methods with more emphasis on selective unlabeling describing the various practical aspects. The recent developments involving combinatorial selective labeling and unlabeling are also discussed.

High resolution methyl selective ¹³C-NMR of proteins in solution and solid state.

New ¹³C-detected NMR experiments have been devised for molecules in solution and solid state, which provide chemical shift correlations of methyl groups with high resolution, selectivity and sensitivity. The experiments achieve selective methyl detection by exploiting the one bond J-coupling between the ¹³C-methyl nucleus and its directly attached ¹³C spin in a molecule. In proteins such correlations edit the ¹³C-resonances of different methyl containing residues into distinct spectral regions yielding a high resolution spectrum. This has a range of applications as exemplified for different systems such as large proteins, intrinsically disordered polypeptides and proteins with a paramagnetic centre.

Efficient sequential assignments in proteins with reduced dimensionality 3D HN(CA)NH.

We present reduced dimensionality (RD) 3D HN(CA)NH for efficient sequential assignment in proteins. The experiment correlates the (15)N and (1)H chemical shift of a residue ('i') with those of its immediate N-terminal (i - 1) and C-terminal (i + 1) neighbors and provides four-dimensional chemical shift correlations rapidly with high resolution. An assignment strategy is presented which combines the correlations observed in this experiment with amino acid type information obtained from 3D CBCA(CO)NH. By classifying the 20 amino acid types into seven distinct categories based on (13)C(ß) chemical shifts, it is observed that a stretch of five sequentially connected residues is sufficient to map uniquely on to the polypeptide for sequence specific resonance assignments. This method is exemplified by application to three different systems: maltose binding protein (42 kDa), intrinsically disordered domain of insulin-like growth factor binding protein-2 and Ubiquitin. Fast data acquisition is demonstrated using longitudinal (1)H relaxation optimization. Overall, 3D HN(CA)NH is a powerful tool for high throughput resonance assignment, in particular for unfolded or intrinsically disordered polypeptides.

Amino acid selective unlabeling for sequence specific resonance assignments in proteins.

Sequence specific resonance assignment constitutes an important step towards high-resolution structure determination of proteins by NMR and is aided by selective identification and assignment of amino acid types. The traditional approach to selective labeling yields only the chemical shifts of the particular amino acid being selected and does not help in establishing a link between adjacent residues along the polypeptide chain, which is important for sequential assignments. An alternative approach is the method of amino acid selective 'unlabeling' or reverse labeling, which involves selective unlabeling of specific amino acid types against a uniformly (13)C/(15)N labeled background. Based on this method, we present a novel approach for sequential assignments in proteins. The method involves a new NMR experiment named, {(12)CO( i )-(15)N( i+1)}-filtered HSQC, which aids in linking the (1)H(N)/(15)N resonances of the selectively unlabeled residue, i, and its C-terminal neighbor, i + 1, in HN-detected double and triple resonance spectra. This leads to the assignment of a tri-peptide segment from the knowledge of the amino acid types of residues: i - 1, i and i + 1, thereby speeding up the sequential assignment process. The method has the advantage of being relatively inexpensive, applicable to (2)H labeled protein and can be coupled with cell-free synthesis and/or automated assignment approaches. A detailed survey involving unlabeling of different amino acid types individually or in pairs reveals that the proposed approach is also robust to misincorporation of (14)N at undesired sites. Taken together, this study represents the first application of selective unlabeling for sequence specific resonance assignments and opens up new avenues to using this methodology in protein structural studies.