Functional units, protein patterns

Proteins are the functional units of a cell. They have constantly changing expression levels, locations, and PTMs that may be associated with the onset, progression, and remission of disease. Proteomic technologies (as described in Section 2) are used to detect patterns of differentially expressed proteins that have numerous potential clinical applications. Techniques such as 2D-PAGE and HPLC combined with MS can be used to identify proteins for early detection, diagnosis, prognosis, and response to treatment. 

The quadrupolar contribution is mostly expected in membranes with a high protein concentration, where ordered arrays of integral proteins exist. Examples of this type include the purple membranes of Halobacterium halo-hium, the inner mitochondrial membrane, etc. The presence in biomembranes of extended domains of tightly packed globular proteins in a doubletiered pattern is a basic idea in the structure-function unitization model of biomembranes. The estimated flexocoefScient of an array of identical double-tiered quadrupolar proteins is substantial > 4.5 X 10- ° C as... 

The isomorphous replacement method requires attachment of heavy atoms to protein molecules in the crystal. In this method, atoms of high atomic number are attached to the protein, and the coordinates of these heavy atoms in the unit cell are determined. The X-ray diffraction pattern of both the native protein and its heavy atom derivative(s) are determined. Application of the so-called Patterson function determines the heavy atom coordinates. Following the refinement of heavy atom parameters, the calculation of protein phase angles proceeds. In the final step the electron density of the protein is calculated. 

Structural and Functional Relationships in Fibrous Proteins William Astbury discovered that the x-ray pattern of wool shows a repeating structural unit spaced about 5.2 A along the length of the wool fiber. When he steamed and... 

Equation (5.15) describes one structure factor in terms of diffractive contributions from all atoms in the unit cell. Equation (5.16) describes one structure factor in terms of diffractive contributions from all volume elements of electron density in the unit cell. These equations suggest that we can calculate all of the structure factors either from an atomic model of the protein or from an electron density function. In short, if we know the structure, we can calculate the diffraction pattern, including the phases of all reflections. This computation, of course, appears to go in just the opposite direction that the crystallographer desires. It turns out, however, that computing structure factors from a model of the unit cell (back-transforming the model) is an essential part of crystallography, for several reasons. 

As I described earlier, this entails extracting the relatively simple diffraction signature of the heavy atom from the far more complicated diffraction pattern of the heavy-atom derivative, and then solving a simpler "structure," that of one heavy atom (or a few) in the unit cell of the protein. The most powerful tool in determining the heavy-atom coordinates is a Fourier series called the Pattersonfunction P(u,v,w), a variation on the Fourier series used to compute p(x,y,z) from structure factors. The coordinates (u,v,w) locate a point in a Patterson map, in the same way that coordinates (x,y,z) locate a point in an electron-density map. The Patterson function or Patterson synthesis is a Fourier series without phases. The amplitude of each term is the square of one structure factor, which is proportional to the measured reflection intensity. Thus we can construct this series from intensity measurements, even though we have no phase information. Here is the Patterson function in general form... 

The conditio sine qua non for structure-based drug design is the identification and functional annotation of the relevant binding site(s) in a target protein. A number of methods, closely related to the characteristics of binding sites and the restraints imposed on the formation of functional structural units, are discussed in Section 4.2. The most commonly used methods can be classified into geometry-based methods for cavity detection, methods for identifying specific patterns, and evolutionary methods. 

To explore the feasibility of such an approach for the design of active catalysts, we have systematically replaced the secondary structural elements in the homodimeric helical bundle chorismate mutase (Fig. 3.18) with binary-patterned units of random sequence. Genetic selection was then used to assess the catalytic capabilities of the proteins in the resulting libraries, providing quantitative information about the robustness of this particular protein scaffold and insight into the subtle interactions needed to form a functional active site [119]. 

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