Sequential structure alignment program: Difference between revisions

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{{contextTechnical|date=NovemberOctober 20092021}}

The '''sequential structure alignment program (SSAP)''' in [[chemistry]], [[physics]], and [[biology]] is a method that uses double [[dynamic programming]] to produce a structural alignment based on atom-to-atom [[Vector (geometric)|vectors]] in structure space.<ref>{{Cite journal

The SSAP (Sequential Structure Alignment Program) method uses double [[dynamic programming]] to produce a structural alignment based on atom-to-atom [[Vector (geometric)|vectors]] in structure space. Instead of the alpha carbons typically used in structural alignment, SSAP constructs its vectors from the [[beta carbon]]s for all residues except glycine, a method which thus takes into account the rotameric state of each residue as well as its ___location along the backbone. SSAP works by first constructing a series of inter-residue distance vectors between each residue and its nearest non-contiguous neighbors on each protein. A series of matrices are then constructed containing the vector differences between neighbors for each pair of residues for which vectors were constructed. Dynamic programming applied to each resulting matrix determines a series of optimal local alignments which are then summed into a "summary" matrix to which dynamic programming is applied again to determine the overall structural alignment.

| last1 = Taylor | first1 = W. R.

| last2 = Orengo | first2 = C. A.

| title = Protein structure alignment

| journal = Journal of Molecular Biology

| volume = 208

| issue = 1

| pages = 1–22

| year = 1989

| pmid = 2769748

| doi=10.1016/0022-2836(89)90084-3

}}</ref><ref>{{Cite book

| last1 = Orengo | first1 = C. A.

| last2 = Taylor | first2 = W. R.

| chapter = SSAP: Sequential structure alignment program for protein structure comparison

| title = Computer Methods for Macromolecular Sequence Analysis

| series = Methods in Enzymology

| volume = 266

| pages = 617–635

| year = 1996

| pmid = 8743709

| doi=10.1016/s0076-6879(96)66038-8

| isbn = 9780121821678

The SSAP (Sequential Structure Alignment Program) method uses double [[dynamic programming]] to produce a structural alignment based on atom-to-atom [[Vector (geometric)|vectors]] in structure space.}}</ref> Instead of the alpha carbons typically used in structural alignment, SSAP constructs its vectors from the [[beta carbon]]s for all residues except glycine, a method which thus takes into account the [[wikt:rotamer|rotameric state]] of each residue as well as its ___location along the backbone. SSAP works by first constructing a series of inter-residue distance vectors between each residue and its nearest non-contiguous neighbors on each protein. A series of matrices are then constructed containing the vector differences between neighbors for each pair of residues for which vectors were constructed. Dynamic programming applied to each resulting matrix determines a series of optimal local alignments which are then summed into a "summary" matrix to which dynamic programming is applied again to determine the overall structural alignment.

SSAP originally produced only pairwise alignments but has since been extended to multiple alignments as well.<ref name="taylor">{{Cite journal

SSAP originally produced only pairwise alignments but has since been extended to multiple alignments as well.<ref name="taylor">Taylor WR, Flores TP, Orengo CA. (1994). Multiple protein structure alignment. ''Protein Sci'' 3(10):1858-70.</ref> It has been applied in an all-to-all fashion to produce a hierarchical fold classification scheme known as [[CATH]] (Class, Architecture, Topology, Homology),<ref name="orengo">Orengo CA, Michie AD, Jones S, Jones DT, Swindells MB, Thornton JM. (1997) CATH: A hierarchical classification of protein ___domain structures. ''Structure'' 5(8): 1093-1108.</ref> which has been used to construct the [http://www.cathdb.info/latest/index.html CATH Protein Structure Classification] database.

| last1 = Taylor | first1 = W. R.

| last2 = Flores | first2 = T. P.

| last3 = Orengo | first3 = C. A.

| doi = 10.1002/pro.5560031025

| title = Multiple protein structure alignment

| journal = Protein Science

| volume = 3

| issue = 10

| pages = 1858–1870

| year = 1994

| pmid = 7849601

| pmc =2142613

SSAP originally produced only pairwise alignments but has since been extended to multiple alignments as well.<ref name="taylor">Taylor WR, Flores TP, Orengo CA. (1994). Multiple protein structure alignment. ''Protein Sci'' 3(10):1858-70.}}</ref> It has been applied in an all-to-all fashion to produce a hierarchical fold classification scheme known as [[CATH]] (Class, Architecture, Topology, Homology),.<ref name="orengoOrengo1997">{{cite journal |author1=Orengo CA, |author2=Michie AD, |author3=Jones S, |author4=Jones DT, |author5=Swindells MB, |author6=Thornton JM. (1997)|title=CATH—a CATH: A hierarchicalhierarchic classification of protein ___domain structures. ''|journal=Structure'' |volume=5 |issue=8 |pages=1093–1108 |year=1997 |pmid=9309224 |doi=10.1016/S0969-2126(897): 109300260-1108.8|doi-access=free }}</ref> which has been used to construct the [https://web.archive.org/web/20070517161248/http://www.cathdb.info/latest/index.html CATH Protein Structure Classification] database.

Generally, SSAP scores above 80 are associated with highly similar structures. Scores between 70 and 80 indicate a similar fold with minor variations. Structures yielding a score between 60 and 70 do not generally contain the same fold, but usually belong to the same protein class with common structural motifs.<ref name="porwal">Porwal{{Cite G,journal Jain
| S,last1 Babu= SD,Porwal Singh| D,first1 Nanavati= H,G. Noronha
| S.last2 (2007)= ProteinJain Structure| Predictionfirst2 Aided= byS. Geometrical
| andlast3 Probabilistic= Constraints.Babu ''J.| Comput.first3 Chem= S.'' 28(12):D. 1943-1952.</ref>.

| last4 = Singh | first4 = D.

| last5 = Nanavati | first5 = H.

| last6 = Noronha | first6 = S.

| doi = 10.1002/jcc.20736

| title = Protein structure prediction aided by geometrical and probabilistic constraints

| journal = Journal of Computational Chemistry

| volume = 28

| issue = 12

| pages = 1943–1952

| year = 2007

| pmid = 17450548

| pmc =

| s2cid = 5710322

}}</ref>

==See also==

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*[[CATH|Class, Architecture, Topology, Homology (CATH)]]

*[[Root mean square deviation (bioinformatics)|RMSD]] &mdash; A different structure comparison measure

*[[Template Modelingmodeling Score (bioinformatics)score|TM-Scorescore]] &mdash; A different structure comparison measure

*[[Global distance test|GDT]] &mdash; A different structure comparison measure

*[[Longest Continuous Segment (bioinformatics)|LCS]] &mdash; A different structure comparison measure