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| title | chunk | source | category | tags | date_saved | instance |
|---|---|---|---|---|---|---|
| BLOSUM | 1/3 | https://en.wikipedia.org/wiki/BLOSUM | reference | science, encyclopedia | 2026-05-05T14:01:55.384613+00:00 | kb-cron |
In bioinformatics, the BLOSUM (BLOcks SUbstitution Matrix) matrix is a substitution matrix used for sequence alignment of proteins. BLOSUM matrices are used to score alignments between evolutionarily divergent protein sequences. They are based on local alignments. BLOSUM matrices were first introduced in a paper by Steven Henikoff and Jorja Henikoff. They scanned the BLOCKS database for very conserved regions of protein families (that do not have gaps in the sequence alignment) and then counted the relative frequencies of amino acids and their substitution probabilities. Then, they calculated a log-odds score for each of the 210 possible substitution pairs of the 20 standard amino acids. All BLOSUM matrices are based on observed alignments; they are not extrapolated from comparisons of closely related proteins like the PAM Matrices.
== Biological background == The genetic instructions of every replicating cell in a living organism are contained within its DNA. Throughout the cell's lifetime, this information is transcribed and replicated by cellular mechanisms to produce proteins or to provide instructions for daughter cells during cell division, and the possibility exists that the DNA may be altered during these processes. This is known as a mutation. At the molecular level, there are regulatory systems that correct most — but not all — of these changes to the DNA before it is replicated. The functionality of a protein is highly dependent on its structure. Changing a single amino acid in a protein may reduce its ability to carry out this function, or the mutation may even change the function that the protein carries out. Changes like these may severely impact a crucial function in a cell, potentially causing the cell — and in extreme cases, the organism — to die. Conversely, the change may allow the cell to continue functioning albeit differently, and the mutation can be passed on to the organism's offspring. If this change does not result in any significant physical disadvantage to the offspring, the possibility exists that this mutation will persist within the population. The possibility also exists that the change in function becomes advantageous. The 20 amino acids translated by the genetic code vary greatly by the physical and chemical properties of their side chains. However, these amino acids can be categorised into groups with similar physicochemical properties. Substituting an amino acid with another from the same category is more likely to have a smaller impact on the structure and function of a protein than replacement with an amino acid from a different category. Sequence alignment is a fundamental research method for modern biology. The most common sequence alignment for protein is to look for similarity between different sequences in order to infer function or establish evolutionary relationships. This helps researchers better understand the origin and function of genes through the nature of homology and conservation. Substitution matrices are utilized in algorithms to calculate the similarity of different sequences of proteins; however, the utility of Dayhoff PAM Matrix has decreased over time due to the requirement of sequences with a similarity more than 85%. In order to fill in this gap, Henikoff and Henikoff introduced BLOSUM (BLOcks SUbstitution Matrix) matrix which led to marked improvements in alignments and in searches using queries from each of the groups of related proteins.
== Terminology == BLOSUM Blocks Substitution Matrix, a substitution matrix used for sequence alignment of proteins. Scoring metrics (statistical versus biological) When evaluating a sequence alignment, one would like to know how meaningful it is. This requires a scoring matrix, or a table of values that describes the probability of a biologically meaningful amino-acid or nucleotide residue-pair occurring in an alignment. Scores for each position are obtained frequencies of substitutions in blocks of local alignments of protein sequences. BLOSUM r
The matrix built from blocks with less than r% of similarity E.g., BLOSUM62 is the matrix built using sequences with less than 62% similarity (sequences with ≥ 62% identity were clustered together). Note: BLOSUM 62 is the default matrix for protein BLAST. Experimentation has shown that the BLOSUM-62 matrix is among the best for detecting most weak protein similarities. Several sets of BLOSUM matrices exist using different alignment databases, named with numbers. BLOSUM matrices with high numbers are designed for comparing closely related sequences, while those with low numbers are designed for comparing distant related sequences. For example, BLOSUM80 is used for closely related alignments, and BLOSUM45 is used for more distantly related alignments. The matrices were created by merging (clustering) all sequences that were more similar than a given percentage into one single sequence and then comparing those sequences (that were all more divergent than the given percentage value) only; thus reducing the contribution of closely related sequences. The percentage used was appended to the name, giving BLOSUM80 for example where sequences that were more than 80% identical were clustered.
== Construction of BLOSUM matrices == BLOSUM matrices are obtained by using blocks of similar amino acid sequences as data, then applying statistical methods to the data to obtain the similarity scores. Statistical Methods Steps:
=== Eliminating Sequences === Eliminate the sequences that are more than r% identical. There are two ways to eliminate the sequences. It can be done either by removing sequences from the block or just by finding similar sequences and replace them by new sequences which could represent the cluster. Elimination is done to remove protein sequences that are more similar than the specified threshold.
=== Calculating Frequency & Probability === A database storing the sequence alignments of the most conserved regions of protein families. These alignments are used to derive the BLOSUM matrices. Only the sequences with a percentage of identity lower than the threshold are used. By using the block, counting the pairs of amino acids in each column of the multiple alignment.
=== Log odds ratio === It gives the ratio of the occurrence each amino acid combination in the observed data to the expected value of occurrence of the pair. It is rounded off and used in the substitution matrix.