Accepted Point Mutations Research Articles

Implementing Protein Sequence Alignment using PAM-250 Matrices

Multiple Protein Sequence is one of the most important problems in modern computational biology. The emphasis here is on the use of computers because most of the tasks involved in genomic data analysis are highly repetitive or mathematically complex. One of the largest areas of Bioinformatics and Data mining has been in the Protein Domain. These efforts have included protein Structure prediction, folding Pathway prediction, Sequence alignment, Substructure Detection and many others. Data storage became easier as the accessibility of large amount of computing power at low cost. The research in bioinformatics has accumulated large amount of data. As the hardware technology advancing, the cost of storing is decreasing. The biological data is available in different formats and is comparatively more complex. In the present work, data mining solution is provided for the problem of protein sequence alignment. Different formats of sequences are studied and plain text format is chosen for the problem under consideration. Clustering methods are based on expressing similarity or dissimilarity of such sequences. The similarity of two protein sequences can be assessed by score of the best alignment of the sequences. Scoring matrix accesses the replacement of one amino acid by another, by natural selection. The replacement can be due the result of two distinct processes: i) occurrence of mutation in the portion of the gene template producing one amino acid of a protein. ii) acceptance of the mutation by the species (similar function). PAM (Accepted Point Mutations) is the scoring matrice that is used for the different computations. PAM-250 matrix is used for the problem under consideration. The matrix is frequently used to score aligned peptide sequences to determine the similarity of those sequences. The numbers given above were derived from comparing aligned sequences of proteins with known homology and determining the accepted point mutations (PAM) observed. Global and Local alignments are predicted along with the alignment score.

PSeq-Gen: an application for the Monte Carlo simulation of protein sequence evolution along phylogenetic trees.

PSeq-Gen will simulate the evolution of protein sequences along evolutionary trees following the procedures previously reported for the DNA sequence simulator Seq-Gen (Sequence-Generator, Rambaut and Grassly, 1997). Statistics calculated from these sequences can be used to give expectations under specific null hypotheses of protein evolution. This Monte Carlo simulation approach to testing hypotheses is often termed 'parametric bootstrapping' (see, for example, Efron, 1985; Huelsenbeck et al., 19%; Huelsenbeck and Rannala, 1997), and has many powerful applications, such as testing the molecular clock (Goldman, 1993), detecting recombination (Grassly and Holmes, 1997), and evaluating competing phylogenetic hypotheses (Hillis et al., 19%). Three common models of amino acid substitution are implemented (PAM: Dayhoff et al., 1978; JTT: Jones et al., 1992; mtREV: Adachi and Hasegawa, 1995). These models use instantaneous rate matrices derived from observed patterns of accepted point mutations for aligned nuclear (PAM, JTT) and mitochondrial (mtREV) genes. The amino acid frequencies found for these alignments are the default in each model, but it is also possible to specify their frequencies independently in the implementation here [following Adachi (1995), but see also Kishino et al. (1990)]. In addition, sitespecific rate heterogeneity following a gamma distribution is allowed (as described in Rambaut and Grassly, 1997; Yang, 1993). As with Seq-Gen, any number of trees may be read in and any number of data sets can be simulated for each tree, allowing large sets of replicate simulations to be created easily. Maximum-likelihood algorithms exist which will reconstruct phylogenies from protein sequences using the PAM, JTT and mtREV substitution models (e.g. Adachi and Hasegawa, 1995; Yang, 1996), and hence bootstrapping to obtain confidence limits about phylogenetic parameters is easily achieved.

Alcohol dehydrogenase of class III: consistent patterns of structural and functional conservation in relation to class I and other proteins

Class III alcohol dehydrogenase from the lizard Uromastix hardwickii has been characterized. This non-mammalian, gnathostomatous vertebrate class III form allows correlations of structures and functions of this class, the traditional class I alcohol dehydrogenase, and other well-studied proteins. Catalytically, results show similar recoveries and activities of all vertebrate class III forms independent of source, similar activities also in invertebrates but in lower amounts, and considerably higher specific activities in microorganisms. Structurally, variability patterns are consistent throughout the vertebrate system with a ratio in accepted point mutations versus class I of 0.4. This ratio between different classes of a zinc enzyme is comparable to that between different heme proteins (cytochrome c and myoglobin), suggesting defined but non-identical functions also for the alcohol dehydrogenase classes.

Empirical and Structural Models for Insertions and Deletions in the Divergent Evolution of Proteins

The exhaustive matching of the protein sequence database makes possible a broadly based study of insertions and deletions (indels) during divergent evolution. In this study, the probability of a gap in an alignment of a pair of homologous protein sequences was found to increase with the evolutionary distance measured in PAM units (number of accepted point mutations per 100 amino acid residues). A relationship between the average number of amino acid residues between indels and evolutionary distance suggests that a unit 30 to 40 amino acid residues in length remains, on average, undisrupted by indels during divergent evolution. Further, the probability of a gap was found to be inversely proportional to gap length raised to the 1·7 power. This empirical law fits closely over the entire range of gap lengths examined. Gap length distribution is largely independent of evolutionary distance. These results rule out the widely used linear gap penalty as a satisfactory formula for scoring gaps when constructing alignments. Further, the observed gap length distribution can be explained by a simple model of selective pressures governing the acceptance of indels during divergent evolution. Finally, this model provides theoretical support for using indels as part of "parsing algorithms", important in the de novo prediction of the folded structure of proteins form the sequence data.

Predicting isomorphic residue replacements for protein design

The replaceability of amino acids as reflected in their neighbourhood selectivity is analyzed in this paper. Neighbourhood selectivity was found to be more characteristic of the individual amino acids than the other commonly used parameters. The residue replacement rank obtained was compared with other proposed ranks and was tested on naturally accepted point mutations in homologous proteins.

Stochastic traits of molecular evolution—Acceptance of point mutations in native actin genes

A stochastic matrix of nucleotide mutation probabilities is derived by counting differences and identities in alignments of native actin genes, with the aim of obtaining a more reliable data base for regular modes of molecular evolution. The evolution of DNA sequences is thereby considered as a Markov process consisting of events (point mutations) characterized by a stochastic matrix for codon-codon interchanges. The genetic distance is set to 1 PAM (percentage of accepted point mutations). The results can be reproduced by Monte Carlo simulations which are subjected to selective constraints. The latter are observed as nonrandom codon usage and ratios of silent to recognizable point mutations. Specific patterns within the matrix of mutation probabilities attest to preferences of natural selection in the evolution of a specific protein.

An estimate on the effect of point mutation and natural selection on the rate of amino acid replacement in proteins.

We outline a method for estimating quantitatively the influence of point mutations and selection on the frequencies of codons and amino acids. We show how the mutation rate, i.e., the rate of amino acid replacement due to point mutation, can be affected by the codon usage as well as by the rates of the involved base exchanges. A comparison of the mutation rates calculated from reliable values of codon usage and base exchange probabilities with those that would be expected on the basis of chance reveals a notable suppression of replacements leading to tryptophan, glutamate, lysine, and methionine, and particularly of those leading to the termination codons. If selection constraints are neglected and only mutations are taken into account, the best agreement between expected and observed frequencies of both codons and amino acids is obtained for alpha = 1.13-1.15, where (Formula: see text). The "selection values" of codons and amino acids derived by our method show a pattern that partially deviates from others in the literature. For example, the selection pressure on methionine and cysteine turns out to be much more pronounced than expected if only the discrepancies between their observed and expected occurrences in proteins are considered. To estimate to what extent randomly occurring amino acid replacements are accepted by selection, we constructed an "acceptability matrix" from the well-established matrix of accepted point mutations. On the basis of this matrix "acceptability values" of the amino acids can be defined that correlate with their selection values. We also examine the significance of mutations and selection of amino acids with respect to their physicochemical properties and functions in proteins. The conservatism of amino acid replacements with respect to certain properties such as polarity can be brought about by the mutational process alone, whereas the conservatism with respect to other relevant properties--among them all measures of bulkiness--obviously is the result of additional selectional constraints on the evolution of protein structures.

Evolutionary changes in protein composition — evidence for an optimal strategy

The information contained in the composition of different proteins of the same family is analyzed. It is found that within each family the gain in information per amino acid replacement is constant. This finding is interpreted to imply that evolutionary changes in proteins follow an "optimal" path in the sense that they maximize the number of potentially functional sequences that can be generated by T accepted point mutations from a given protein, subject to restrictions due to biological function.

Different degrees of interspecies homology in immunoglobulin lamda chain constant domain correlated with three-dimensional structure.

IT is generally accepted that evolution of proteins is a consequence of duplications and point mutations occurring in genes coding for them. Palaeogenetics of Pauling and Zuckerkandl1 as well as protein phylogenetics introduced by Fitch and Margoliash2 (and subsequently modified by other workers) assume that comparative analyses of amino acid sequence data in terms of mutational distances (be it minimal mutational distances, corrected mutational distances or accepted point mutations per 100 amino acids), inferred to exist among genes coding for them, yield a realistic image of evolution; thus, genealogical trees of proteins (that is, dendrograms of mutational distances) can be constructed which relate to main evolutionary events thought to occur in the past.