Amino acids multiple alignment

Fig. 1. The SE family tree. This tree has been constructed using Clustal X and SplitsTrees version 4 programs and is based on a multiple amino acid sequence alignment of the mature form of S. aureus toxins. The bacterial toxins tree can be divided into four distinct groups, the fourth is only composed of TSST-1. 

Figure 20-3 Multiple amino-acid sequence alignment of Dx with Rds from Desulfovibrio sp. and Clostridium pasteurianum. The conserved residues are represented in white in a black frame. C.p., Clostridium pasteurianum D.d, Desulfovibrio desulfuricans D.g., Desulfovibrio gigas D.v., Desulfovibrio vulgaris H, Hildenborough M, Miyasaki.

A prior distribution for sequence profiles can be derived from mixtures of Dirichlet distributions [16,51-54]. The idea is simple Each position in a multiple alignment represents one of a limited number of possible distributions that reflect the important physical forces that determine protein structure and function. In certain core positions, we expect to get a distribution restricted to Val, He, Met, and Leu. Other core positions may include these amino acids plus the large hydrophobic aromatic amino acids Phe and Trp. There will also be positions that are completely conserved, including catalytic residues (often Lys, GIu, Asp, Arg, Ser, and other polar amino acids) and Gly and Pro residues that are important in achieving certain backbone conformations in coil regions. Cys residues that form disulfide bonds or coordinate metal ions are also usually well conserved. 

A prior distribution of the probabilities of the 20 amino acids at a particular position in a multiple alignment can be represented by a Dirichlet distribution, described in Section lI.E. That is, it is an expression of the values of the probabilities of each residue type r, where r ranges from 1 to 20, and E( i0,. = 1 ... 

CX.0 = Z(=iCx.r represents the total number of counts that the prior distribution represents, and the a, the counts for each type of amino acid (not necessarily integers). Because different distributions will occur in multiple sequence alignments, the prior distribution for any position should be represented as a mixture of N Dirichlet distributions ... 

This branch of bioinformatics is concerned with computational approaches to predict and analyse the spatial structure of proteins and nucleic acids. Whereas in many cases the primary sequence uniquely specifies the 3D structure, the specific rules are not well understood, and the protein folding problem remains largely unsolved. Some aspects of protein structure can already be predicted from amino acid content. Secondary structure can be deduced from the primary sequence with statistics or neural networks. When using a multiple sequence alignment, secondary structure can be predicted with an accuracy above 70%. 

Fig. 2a-d. Multiple alignment of primary structures from 36 PHA synthases. A comparison of amino acid sequences derived from PH A synthase genes is shown. Amino acids are specified by the standard one-letter abbreviations. The consensus sequence represents amino acid residues (shaded) which are present in at least 50% of the PHA synthases. Highly conserved amino acids, which are present in at least 70% of the PHA synthases, are additionally underlined in the consensus sequence and the eight amino acid residues, which are present in all PHA synthases, are indicated as bold letters. See Table 1 for references... 

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