Amino acid properties

Like the differences in composition, the sequence attribute differences between ordered and disordered sequences are exactly as would be expected if disorder were encoded by the sequence. Attribute values, of course, depend on amino acid compositions, so the composition and attribute results are not independent. Nevertheless, the attribute analysis is useful because it provides a biophysical perspective, allowing insight into the amino acid properties that are important for promoting order or disorder. 

Keywords 3d-4f cluster compounds Amino acids Properties Self-assembly ... 

Web search sites allow the user to choose among several. Their easy interchangeability means that substitution and gap score combinations are readily compared in performance. Over the past several years, results of numerous comprehensive tests have appeared. Some of these evaluation studies have confined themselves to log-odds matrices made from alignment data, whereas others have included matrices that are based on amino acid properties. 

A large number of chemical and physical properties, manifest in the amino acid side chains, have been thoroughly examined by many investigators. Attempts have been made to correlate these properties with their relatedness among protein sequences. What is most relevant is how these side chains interact with the backbone and with one another and what roles they each play within particular types of secondary and tertiary structure. The parametric description of residue environments with the help of solvent accessibility, secondary structure, backbone torsion angles, pairwise residue-residue distances, or Ca positions is the comparison between amino acid types at protein sequence positions and residue locations in structural templates. A recent review has evaluated and quantified the extent to which the amino acid type-specific distributions of commonly used environment parameters discriminate with respect to the 20 amino acid types (Sunyaev et al., 1998). Some of the important amino acid properties and residue environments are discussed below. 

When the similar approach was applied to discriminate members of a given folding class from members of all other classes in the more comprehensive SCOP database, it was shown that specific amino acid properties work differently on different folding classes... 

In these studies, the input sequence was represented by seven non-orthogonal physicochemical properties, namely, hydrophobicity, volume, surface area, hydrophilicity, bulkiness, refractivity, and polarity, with normalized values of (-1, 1). Thirteen-amino acid sequence windows were used, resulting in an input vector of 91 (i.e., 13 x 7) units. With the small number of training examples, the input units were only partially connected to the hidden layer in order to reduce the number of free parameters and avoid overtraining the network. The constraint was to connect each first hidden layer unit to one amino acid property exclusively, and that the size of the second hidden layer size was no larger than the first hidden layer. The output layer had exactly one unit to indicate whether the middle residue was in a membrane/non-membrane boarder. The process of development started with randomly generated architectures and resulted in 18 and 8 units in the first and second hidden layers, with a total number of free parameters of... 

A compelling case can be made for replacing empirically-derived scales of amino acid properties with parameters either measured directly (e.g., chemical shift data or infrared spectra) or calculated from basic principles. The goal would be to develop all-electronic expressions for the physico-chemical properties of amino acids based on computational methods that include QM calculations. A start in this direction was provided by the successful description of steric effects in terms of polarizability and hydrophUicity as a function of electron density (32). Application of more sophisticated computational approaches wiU speed progress toward this objective. 

Jones DD. Amino acid properties and side-chain orientation in proteins a cross correlation approach. J. Theor. Biol. 1975 50 167-183. 

Analysis of the relationship between amino acid properties and protein stability showed that hydrophobicity is the major factor for the stability of proteins during substitution of amino acids in the interior of the protein. The stability of protein mutants is attributed to the number of carbon atoms, which shows the direct relationship between hydrophobicity and stability. 

For the mutations on the surface of the protein, the classifications based on the chemical nature of amino acids, such as hydrophobic amino acids (Ala, Cys, Phe, Gly, He, Leu, Met, Val, Trp, and Tyr), amino acid side chains that can form hydrogen bonds (Asp, Cys, Glu, His, Lys, Met, Asn, Gin, Arg, Ser, Thr, Trp, and Tyr), and so forth, improved the correlation between amino acid properties and protein mutant stability. Furthermore, the inclusion of neighboring and surrounding residues remarkably improved the correlation in all the subgroups of mutations. This result indicates that the information from nearby polar/charged amino acid residues and/or the aliphatic and aromatic residues that are close in space is important for the stability of exposed mutations. 

Gromiha MM, Oobatake M, Sarai A. Important amino acid properties for enhanced thermostability from mesophilic to thermophilic proteins. Biophys. Chem. 1999 82 51-67. 

Musumarra and co-workers [144,145] demonstrated the application of PCA of thin-layer chromatographic (TLC) data for predicting the toxicity of xenobiotics. Wold and co-workers [146,147] reported their multivariate parameterization of amino acid properties based on TLC data obtained in diversified separation systems. These authors were able to explain about 709c of the variance in the literature data on pharmacological activity of a series of oligopeptides. 

One of the most comprehensive resources of amino acid properties freely available on line is the amino acid index database (AAindex), which includes numerical indices representing various physico-chemical, biochemical, and statistical properties of amino acids and pairs of amino acids. AAindex database has been made publicly available by the Japanese GenomeNet database service (http //www.genome.jp/aaindex/). 

Side chains of amino acids are responsible for the packing of the regular elements of secondary structure and then for the tertiary structure of a protein. As a consequence, the structure of a protein can be expressed quantitatively by means of side chain amino acid properties. Several —> amino acid descriptors have been proposed, which contain information about properties of side chains of amino acids. 

A simple approach to protein description consists of representing a protein by a sequence of properties of its constituent amino acids. Each amino acid is described by one ore more properties and therefore the total number of protein descriptors is given by the product of the number of amino acids in the protein and the number of selected amino acid properties. As this number of descriptors increases very fast with the size of proteins, this approach is usually applied to small- and medium-size peptides. Moreover, in QSAR studies that require uniform-length descriptors, it can be used only to describe a series of peptide analogues, vhich are peptide sequences with the same length. To enable QSAR studies of peptide sequences with different length, some method is required that is able to translate the peptide sequences into vectorial descriptors with the same number of variables. For example, ACC transforms were applied to compress information about principal properties of amino acids into peptide sequences with different length. 

For instance, several protein descriptors both topological and geometric were calculated by weighting amino acids with the WHIM descriptors related to size (Am), shape (Km), and atom distribution density (Dm) of the single amino acids [Mauri, Ballabio et al, 2008]. These amino acid properties were calculated on the isolated 3D structure of amino acids and are... 

Jones, D. D. (1975) Amino-Acid Properties and Side-Chain Orientation in Proteins - Cross-Correlation Approach, J. 

G284A <4> (<4> isozyme PDK2, site-directed mutagenesis, mutation of conserved amino acid, properties similar to wild-type [24]) [24]... 

Definition Mixture of sodium and triethanolamine salts of the condensation prod, of undecylenic acid chloride and collagen amino acids Properties Anionic... 

Table 4.7 Pseudo-poly(amino acid) properties...

Properties of Amino Acids Structures of Common Amino Acids Properties of Purine and Pyrimidine Bases The Genetic Code Properties of Fatty Acids Carbohydrate Names and Symbols... 

Li, Y. and Li, B. (2013) Characterization of structure-antioxidant activity relationship of peptides in free radical systems using QSAR models Key sequence positions and their amino acid properties. J Theor Biol 318, 29-43. 

Features Provides a rich source of short chain peptides and amino acids Properties Cream-colored fne spray-dried powd. si. bitter flavor sol. in water (not a cl. sol n.) pH 6.4-6.8 86% protein Storage Store in cool, dry place below 25 C HCO-5 [Nikko Chems. Co. Ltd]... 

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