Secondary Structures, Protein Identification

The 140-residue protein AS is able to form amyloid fibrils and as such is the main component of protein inclusions involved in Parkinson s disease. Full-length 13C/15N-labelled AS fibrils and AS reverse-labelled for two of the most abundant amino acids, K and V, were examined by homonuclear and heteronuclear 2D and 3D NMR.147 Two different types of fibrils display chemical shift differences of up to 13 ppm in the l5N dimension and up to 5 ppm for the backbone and side-chain 13C chemical shifts. Selection of regions with different mobility indicates the existence of monomers in the sample and allows the identification of mobile segments of the protein within the fibril in the presence of monomeric protein. At least 35 C-terminal residues are mobile and lack a defined secondary structure, whereas the N terminus is rigid starting from residue 22. In addition, temperature-dependent sensitivity enhancement is also noted for the AS fibrils due to both the CP efficiency and motional interference with proton decoupling.148... 

Altogether, the identification of the coordinating residues in the endogenous hDAT Zn2+ binding site followed by the engineering artificial sites have defined an important series of structural constraints in this transporter. This includes not only a series of proximity relationships in the tertiary structure, but also secondary structure relationships. The data also provided information about the orientation of TM7 relative to TM8. A model of the TM7/8 microdomain that incorporates all these structural constraints is shown in Fig. 4 (36). The model is an important example of how structural inferences derived from a series of Zn2+ binding sites can provide sufficient information for at least an initial structural mapping of a selected protein domain. 

ExPASy Proteomics tools (http //expasy.org/tools/), tools and online programs for protein identification and characterization, similarity searches, pattern and profile searches, posttranslational modification prediction, topology prediction, primary structure analysis, or secondary and tertiary structure prediction. 

However, if side-chain carbon assignments are wanted, C(CC)(CO)NH experiments [33] that start directly with carbon magnetization and transfer it further to the amide proton for detection are available. If protonated substituents, for example methyl groups, have been introduced into the otherwise perdeuterated protein, the usual HC(C)(CO)NH-TOCSY pulse sequence can be used to obtain the proton chemical shifts. These protons can provide a small number of NOEs that, together with residual dipolar couplings and the secondary structure identification from chemical shifts, make the determination of the global fold of large proteins possible. 

Figure 11,4. ExPASy Proteomic tools. ExPASy server provides various tools for proteomic analysis which can be accessed from ExPASy Proteomic tools. These tools (locals or hyperlinks) include Protein identification and characterization, Translation from DNA sequences to protein sequences. Similarity searches, Pattern and profile searches, Post-translational modification prediction, Primary structure analysis, Secondary structure prediction, Tertiary structure inference, Transmembrane region detection, and Sequence alignment.

A widely used approach to extract information on protein secondary structure from infrared spectra is linked to computational techniques of Fourier deconvolution. These methods decrease the widths of infrared bands, allowing for increased separation and thus better identification of overlapping component bands present under the composite wide contour in the measured spectra [705]. Increased separation can also be achieved by calculating the nth derivative of the absorption spectrum, either in the frequency domain or though mathematical manipulations in the Fourier domain [114], An example is the method of Susi [775] which uses second derivative FT-IR spectra recorded in D20 for comparison with similar spectra derived from proteins with known structure. These methods have not yielded quantitative results that are more accurate than those obtained with methods that do not use deconvolution. 

Identification of structural units. This involves the search for secondary structural units (more precisely, for units that are superposable on standard units to within a specified error), or for combinations of them. The operator will want to specify the range of the search — within a certain molecule, or over a class of proteins, or over the entire available set of coordinates. He or she will also need to be able to qualify the object of the search, specifying perhaps a range of lengths of... 

The first step, as alluded to above, is the development of possible loop conformations which connect the regions of secondary structure The loops which do not fit into the well-defined category of a-helices or (1-sheets have been fairly well characterized using the data base of proteins for which the three-dimensional structure is known [15,16], The identification of specific loop conformations provides insight into the possible orientations, or at least provides limitations on the possible orientations, of the various secondary structural elements. The second step is then analysis of the array of amino acids within the secondary structural elements with attention to the environment in which the amino acids would be found. It is clear that a cluster of hydrophobic amino acids would not likely be projecting into the aqueous solution, and more likely projecting into the core of the protein. This analysis provides additional restrictions to the number of possible arrangements in which the secondary structural elements may be found. 

One advantage is that the template and test protein do not need to be of similar lengths. A very good fit could be identified for the N-terminal portion of a very long test sequence by a much shorter template Large proteins often adopt different structural domains with identifiable folds. Likewise, a short test sequence could adopt a fold that utilizes only a small portion of the template. This rather straightforward sounding method avoids the problems associated with the identification of secondary structure elements. The assumptions are that most protein folds have already been identified and therefore the unknown structure of the test protein will most likely resemble a fold within the database. It is clear that a novel protein fold will not be identified by this method. 

In RmL the analysis of the structural features of the lid is simplified by the availability of structures of both native and complexed molecules this allows for clear identification of the mobile fragments. The lid is created by a long surface loop made up by residues 80—109. This fragment defies a classical definition of an H loop (Leszczynski and Rose, 1986) in that it exhibits well-defined secondary structure in its central helical fragment. Residues 82-96 (which include a short helix) directly obscure the entrance to the active site in the native enzyme. It is notable that between Arg-80 and Val-95 this fragment is not involved in any hydrogen bonds with any other parts of the molecule. Thus, the lid interacts with the main body of the protein only through hydrophobic interactions. 

Although homonuclear resonance assignment is almost exclusively carried out using the sequential assignment method, one other approach has found use in some applications. The main-chain-directed (MCD) method46 is based on the identification of cyclic patterns of NOEs, which are characteristic of the different types of secondary structure. Because of this, it is less suitable for the assignment of unstructured or irregularly structured sections of a protein. 

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