FlexSnap: Flexible non-sequential protein structure alignment

Saeed Salem, Mohammed J. Zaki, Chris Bystroff

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Proteins have evolved subject to energetic selection pressure for stability and flexibility. Structural similarity between proteins which have gone through conformational changes can be captured effectively if flexibility is considered. Topologically unrelated proteins that preserve secondary structure packing interactions can be detected if both flexibility and sequence permutations are considered. We propose the FlexSnap algorithm for flexible non-topological protein structural alignment. The effectiveness of FlexSnap is demonstrated by measuring the agreement of its alignments with manually curated non-sequential structural alignments. FlexSnap showed competitive results against state-of-the-art algorithms, like DALI, SARF2, MultiProt, FlexProt, and FATCAT.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages273-285
Number of pages13
Volume5724 LNBI
DOIs
Publication statusPublished - 2 Nov 2009
Externally publishedYes
Event9th International Workshop on Algorithms in Bioinformatics, WABI 2009 - Philadelphia, PA, United States
Duration: 12 Sep 200913 Sep 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5724 LNBI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other9th International Workshop on Algorithms in Bioinformatics, WABI 2009
CountryUnited States
CityPhiladelphia, PA
Period12/9/0913/9/09

Fingerprint

Protein Structure
Alignment
Proteins
Protein
Flexibility
Structural Similarity
Secondary Structure
Packing
Permutation
Interaction

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Salem, S., Zaki, M. J., & Bystroff, C. (2009). FlexSnap: Flexible non-sequential protein structure alignment. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5724 LNBI, pp. 273-285). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5724 LNBI). https://doi.org/10.1007/978-3-642-04241-6_23

FlexSnap : Flexible non-sequential protein structure alignment. / Salem, Saeed; Zaki, Mohammed J.; Bystroff, Chris.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5724 LNBI 2009. p. 273-285 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5724 LNBI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Salem, S, Zaki, MJ & Bystroff, C 2009, FlexSnap: Flexible non-sequential protein structure alignment. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 5724 LNBI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5724 LNBI, pp. 273-285, 9th International Workshop on Algorithms in Bioinformatics, WABI 2009, Philadelphia, PA, United States, 12/9/09. https://doi.org/10.1007/978-3-642-04241-6_23
Salem S, Zaki MJ, Bystroff C. FlexSnap: Flexible non-sequential protein structure alignment. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5724 LNBI. 2009. p. 273-285. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-04241-6_23
Salem, Saeed ; Zaki, Mohammed J. ; Bystroff, Chris. / FlexSnap : Flexible non-sequential protein structure alignment. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5724 LNBI 2009. pp. 273-285 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{260d56867c2b45298edb62af138973b7,
title = "FlexSnap: Flexible non-sequential protein structure alignment",
abstract = "Proteins have evolved subject to energetic selection pressure for stability and flexibility. Structural similarity between proteins which have gone through conformational changes can be captured effectively if flexibility is considered. Topologically unrelated proteins that preserve secondary structure packing interactions can be detected if both flexibility and sequence permutations are considered. We propose the FlexSnap algorithm for flexible non-topological protein structural alignment. The effectiveness of FlexSnap is demonstrated by measuring the agreement of its alignments with manually curated non-sequential structural alignments. FlexSnap showed competitive results against state-of-the-art algorithms, like DALI, SARF2, MultiProt, FlexProt, and FATCAT.",
author = "Saeed Salem and Zaki, {Mohammed J.} and Chris Bystroff",
year = "2009",
month = "11",
day = "2",
doi = "10.1007/978-3-642-04241-6_23",
language = "English",
isbn = "3642042406",
volume = "5724 LNBI",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "273--285",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

}

TY - GEN

T1 - FlexSnap

T2 - Flexible non-sequential protein structure alignment

AU - Salem, Saeed

AU - Zaki, Mohammed J.

AU - Bystroff, Chris

PY - 2009/11/2

Y1 - 2009/11/2

N2 - Proteins have evolved subject to energetic selection pressure for stability and flexibility. Structural similarity between proteins which have gone through conformational changes can be captured effectively if flexibility is considered. Topologically unrelated proteins that preserve secondary structure packing interactions can be detected if both flexibility and sequence permutations are considered. We propose the FlexSnap algorithm for flexible non-topological protein structural alignment. The effectiveness of FlexSnap is demonstrated by measuring the agreement of its alignments with manually curated non-sequential structural alignments. FlexSnap showed competitive results against state-of-the-art algorithms, like DALI, SARF2, MultiProt, FlexProt, and FATCAT.

AB - Proteins have evolved subject to energetic selection pressure for stability and flexibility. Structural similarity between proteins which have gone through conformational changes can be captured effectively if flexibility is considered. Topologically unrelated proteins that preserve secondary structure packing interactions can be detected if both flexibility and sequence permutations are considered. We propose the FlexSnap algorithm for flexible non-topological protein structural alignment. The effectiveness of FlexSnap is demonstrated by measuring the agreement of its alignments with manually curated non-sequential structural alignments. FlexSnap showed competitive results against state-of-the-art algorithms, like DALI, SARF2, MultiProt, FlexProt, and FATCAT.

UR - http://www.scopus.com/inward/record.url?scp=70350365694&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=70350365694&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-04241-6_23

DO - 10.1007/978-3-642-04241-6_23

M3 - Conference contribution

AN - SCOPUS:70350365694

SN - 3642042406

SN - 9783642042409

VL - 5724 LNBI

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 273

EP - 285

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ER -