{{Short description|Alignment of more than two molecular sequences}}
[[File:RPLP0 90 ClustalW aln.gif|thumb|upright=1.36|First 90 positions of a protein multiple sequence alignment of instances of the acidic ribosomal protein P0 (L10E) from several organisms. Generated with [[ClustalX]].]]
'''Multiple sequence alignment''' ('''MSA''') is the process or the result of [[sequence alignment]] of three or more [[biological sequence]]s, generally [[protein]], [[DNA]], or [[RNA]]. InThese many cases, the input set of query sequencesalignments are assumedused to have aninfer [[evolutionary]] relationshiprelationships byvia which[[phylogenetic]] they share a linkageanalysis and arecan descended from a common ancestor. From the resulting MSA, sequencehighlight [[homology (biology)|homologyhomologous]] canfeatures be inferred and [[molecular phylogeny|phylogenetic analysis]] can be conducted to assess thebetween sequences' shared evolutionary origins. VisualAlignments depictions of the alignment as in the image at right illustratehighlight [[mutation]] events such as [[point mutations]] (single [[amino acid]] or [[nucleotide]] changes) that appear as differing characters in a single alignment column, and [[insertion ormutation]]s deletionand mutations ([[indeldeletion mutation]]s, orand gaps)alignments that appear as hyphens in one or more of the sequences in the alignment. Multiple sequence alignment is oftenare used to assess sequence [[conservation (genetics)|conservation]] and infer the presence and activity of [[protein ___domain]]s, [[tertiary structure|tertiary]] ands, [[secondary structure|secondary]] structuress, and even individual amino acids or nucleotides.
ComputationalMultiple [[algorithm]]ssequence are used to produce and analyse the MSAs due to the difficulty and intractability of manually processing the sequences given their biologically-relevant length. MSAsalignments require more sophisticated methodologies than [[sequence alignmentSequence_alignment#Pairwise_alignment|pairwise alignmentalignments]], becauseas they are more [[Computational complexity theory|computationally complex]]. Most multiple sequence alignment programs use [[heuristic]] methods rather than [[global optimization]] because identifying the optimal alignment between more than a few sequences of moderate length is prohibitively computationally expensive. On the other handHowever, heuristic methods generally failcannot toguarantee givehigh-quality guaranteessolutions onand thehave solution quality, with heuristic solutionsbeen shown to befail oftento far below theyield near-optimal solutionsolutions on benchmark instancestest cases.<ref name="thompson2011">{{cite journal | doi = 10.1371/journal.pone.0018093|vauthors= Thompson JD, Linard B, Lecompte O, Poch O | year = 2011 | title = A comprehensive benchmark study of multiple sequence alignment methods: current challenges and future perspectives | journal = PLOS ONE | volume = 6 | issue = 3| pages = e18093| pmid = 21483869| pmc = 3069049|bibcode= 2011PLoSO...618093T |doi-access= free }}</ref><ref name="nuin2006" /><ref name="hosseininasab">{{cite journal | doi = 10.1287/ijoc.2019.0937 |vauthors=Hosseininasab A, van Hoeve WJ | year = 2019 | title = Exact Multiple Sequence Alignment by Synchronized Decision Diagrams | journal = INFORMS Journal on Computing |s2cid=109937203 }}</ref>
