Point accepted mutation (PAM)or percentage accepted mutation, is a set of matrices used to score sequence alignments. The PAM matrices were introduced by Margaret Dayhoff in 1978 based on 1572 observed mutations in 71 families of closely related proteins. Each PAM matrix has twenty rows and columns, referring to the twenty standard amino acids; the value in a given cell is related to the probability of a substitution of one amino acid for another. This type of matrix is commonly known as a substitution matrix.
This matrix is used in bioinformatics as a scoring matrix to assess the similarity of two aligned protein sequences. For example, an 18% probability of replacing arginine with lysine (in the substitution matrix) is turned into a score of 3 in the scoring matrix. The calculation uses the ratio of the probability value and the frequency of the original amino acid (arginine) in known sequences.
The PAM matrices are derived from a discrete-time Markov chain model of protein mutation, whose transition matrix corresponds to the specific mutation rates observed in homologous sequences that experience one accepted point mutation for every hundred amino acids, i.e. that diverge by "one PAM unit." Generally speaking, a PAM matrix applies to sequences that are PAM units apart. It can be noted that mutations may overlap so that the sequences reflected in the PAM250 matrix have experienced 250 mutation events for every 100 amino acids, yet only 80 out of every 100 amino acids have been affected.
A generic entry of the PAM matrix is defined by:
where is the number of PAM units, is the estimated frequency of amino acid mutating into amino acid during one PAM unit, are the observed substitution frequencies of amino acids.
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