Amino acids secondary structure

Figure 15.22 The structural hierarchy of proteins. A typical protein s structure can be viewed at different levels. Primary structure (shown as a long string of balls leaving and returning to the picture frame) is the sequence of amino acids. Secondary structure consists of highly ordered regions that occur as an a-helix or a p-sheet. Tertiary structure combines these ordered regions with more random sections. In many proteins, several tertiary units interact to give the quaternary structure.

Primary structure is the order of the amino acids. Secondary structure is characterized by a repetitive organization of the peptide backbone. Tertiary structure refers to the complete three-dimensional structure of the protein. Quaternary structure describes a protein that has multiple polypeptide chains. 

Peptides are formed by the condensation of carboxyl and amino groups in amino acids. Their primary structure is the sequence of amino acids. Secondary structure is determined by the required planarity of the amide group and interactions between side chains. a-Helices and p-pleated sheets are common motifs. Tertiary structure is the full three-dimensional structure of the peptide. 

In addition to the primary structure, proteins also exhibit secondary, tertiary, and quaternary structure. The overall structure of proteins is related to several factors. Primary among these factors is the electrostatic nature of amino acids. The structures displayed in Figure 16.10 do not show the charge distribution displayed by amino acids. In neutral solutions, the carboxyl group tends to donate a proton (hydrogen ion) to the amino group. The transfer of a proton means the amino end of the molecule... 

For larger peptides (—30 amino acids) secondary as well as tertiary structure can be observed. For alanHf+ ( =25-35) two helical sections connected by a loop appear to form an antiparallel helical bundle [80]. 

The common amino acids used in mammalian protein synthesis belong to the L-enantiomeric series. However, fungi also employ the o-enantiomers in the biosynthesis of some secondary metabolites. These are normally formed from the corresponding L-amino acid. Fungi can also make amino acids with structures that differ from those commonly found in mammalian proteins and in higher plants. These unusual amino acids are utilized for the synthesis of secondary metabolites and some peptides. 

A prerequisite for the catalytic function of an enzyme is its native tertiary structure which is determined by the number and sequence of amino acids (primary structure) forming the molecule. Favoured by hydrogen bonds, parts of the polypeptide chain exist in an a-helical or a (3-sheet structure (secondary structure). Most enzymes are globular proteins, the tertiary structure of which may be fixed by disulfide bonds between cysteine residues. A famous example is lysozyme (Fig. 20), consisting of 129 amino acids. A defined three-dimensional structure is... 

We have seen that the forces that maintain the secondary structure of a protein are hydrogen bonds between the amide hydrogen and the carbonyl oxygen of the peptide bond. What are the forces that maintain the tertiary structure of a protein The globular tertiary structure forms spontaneously and is maintained as a result of interactions among the side chains, the R groups, of the amino acids. The structure is maintained by the following molecular interactions ... 

In other words, the sum of functional properties depends on the physicochemical characteristics of the whole system containing the working protein. The determinant properties of the protein itself are the amino acid composition, structure (primary, secondary, tertiary, quaternary), and conformational stability the charge of the molecule and its dimensions, shape, and topography the extent of polarity and hydrophobicity, and the nature of protein-protein interactions. 

Proteins are biopolymers formed by one or more continuous chains of covalently linked amino acids. Hydrogen bonds between non-adjacent amino acids stabilize the so-called elements of secondary structure, a-helices and / —sheets. A number of secondary structure elements then assemble to form a compact unit with a specific fold, a so-called domain. Experience has shown that a number of folds seem to be preferred, maybe because they are especially suited to perform biological protein function. A complete protein may consist of one or more domains. 

The comparison of both data sources qualitatively shows a similar picture. Regions of high mobflity are located especially between the secondary structure elements, which are marked on the abscissa of the plot in Figure 7-17. Please remember that the fluctuations plotted in this example also include the amino acid side chains, not only the protein backbone. This is the reason why the side chains of large and flexible amino acids like lysine or arginine can increase the fluctuations dramatically, although the corresponding backbone remains almost immobile. In these cases, it is useful to analyze the fluctuations of the protein backbone and side chains individually. 

Chou P Y and G D Fasman 1978. Prediction of the Secondary Structure of Proteins from Tlieir Amino Acid Sequence. Advances in Enzymology 47 45-148. 

Rule-based systems try to identify certain subsequences of amino acids that tend to have a particular secondary structure, such as sheets, a-helices, (I-strands,... 

Hydrogen bonding stabilizes some protein molecules in helical forms, and disulfide cross-links stabilize some protein molecules in globular forms. We shall consider helical structures in Sec. 1.11 and shall learn more about ellipsoidal globular proteins in the chapters concerned with the solution properties of polymers, especially Chap. 9. Both secondary and tertiary levels of structure are also influenced by the distribution of polar and nonpolar amino acid molecules relative to the aqueous environment of the protein molecules. Nonpolar amino acids are designated in Table 1.3. 

There is some confusion in using Bayes rule on what are sometimes called explanatory variables. As an example, we can try to use Bayesian statistics to derive the probabilities of each secondary structure type for each amino acid type, that is p( x r), where J. is a, P, or Y (for coil) secondary strucmres and r is one of the 20 amino acids. It is tempting to writep( x r) = p(r x)p( x)lp(r) using Bayes rule. This expression is, of course, correct and can be used on PDB data to relate these probabilities. But this is not Bayesian statistics, which relate parameters that represent underlying properties with (limited) data that are manifestations of those parameters in some way. In this case, the parameters we are after are 0 i(r) = p( x r). The data from the PDB are in the form of counts for y i(r), the number of amino acids of type r in the PDB that have secondary structure J.. There are 60 such numbers (20 amino acid types X 3 secondary structure types). We then have for each amino acid type a Bayesian expression for the posterior distribution for the values of xiiry. 

Use very informative priors, where perhaps the prior could be based on the product of individual probabilities for each secondary structure type and amino acid type. 

A similar formalism is used by Thompson and Goldstein [90] to predict residue accessibilities. What they derive would be a very useful prior distribution based on multiplying out independent probabilities to which data could be added to form a Bayesian posterior distribution. The work of Arnold et al. [87] is also not Bayesian statistics but rather the calculation of conditional distributions based on the simple counting argument that p(G r) = p(a, r)lp(r), where a is some property of interest (secondary structure, accessibility) and r is the amino acid type or some property of the amino acid type (hydro-phobicity) or of an amino acid segment (helical moment, etc). 

Analysis and prediction of side-chain conformation have long been predicated on statistical analysis of data from protein structures. Early rotamer libraries [91-93] ignored backbone conformation and instead gave the proportions of side-chain rotamers for each of the 18 amino acids with side-chain dihedral degrees of freedom. In recent years, it has become possible to take account of the effect of the backbone conformation on the distribution of side-chain rotamers [28,94-96]. McGregor et al. [94] and Schrauber et al. [97] produced rotamer libraries based on secondary structure. Dunbrack and Karplus [95] instead examined the variation in rotamer distributions as a function of the backbone dihedrals ( ) and V /, later providing conformational analysis to justify this choice [96]. Dunbrack and Cohen [28] extended the analysis of protein side-chain conformation by using Bayesian statistics to derive the full backbone-dependent rotamer libraries at all... 

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