Using Reduced Amino-Acid Alphabets and Simulated Annealing to Identify Antimicrobial Peptides

John Healy; Michela Caprani; Orla Slattery; Joan O’Keeffe

doi:10.1007/978-3-030-86258-9_2

Using Reduced Amino-Acid Alphabets and Simulated Annealing to Identify Antimicrobial Peptides

John Healy, Michela Caprani, Orla Slattery, Joan O’Keeffe

Atlantic Technological University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The efficient detection of similarity between biological sequences is a fundamental task in bioinformatics. This paper describes a k-mer approach for identifying and classifying antimicrobial peptide sequences using 64-bit encoded multiple spaced seeds and a suite of reduced amino acid alphabets. We implemented and tested the approach using a total of 74 reduced alphabets that were either published, altered using simulated annealing, or randomly generated. Our results show that the approach is very accurate and that all of the reduced alphabets of sizes between 9 and 16 were equally effective and far more accurate than smaller sized alphabets. Our custom designed alphabets exhibited higher sensitivity for some families of AMP than any of the published reduced alphabets that we tested.

Original language	English
Title of host publication	Practical Applications of Computational Biology and Bioinformatics, 15th International Conference, PACBB 2021
Editors	Miguel Rocha, Florentino Fdez-Riverola, Mohd Saberi Mohamad, Roberto Casado-Vara
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	11-21
Number of pages	11
ISBN (Print)	9783030862572
DOIs	https://doi.org/10.1007/978-3-030-86258-9_2
Publication status	Published - 2022
Event	15th International Conference on Practical Applications of Computational Biology and Bioinformatics, PACBB 2021 - Salamanca, Spain Duration: 6 Oct 2021 → 8 Oct 2021

Publication series

Name	Lecture Notes in Networks and Systems
Volume	325 LNNS
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	15th International Conference on Practical Applications of Computational Biology and Bioinformatics, PACBB 2021
Country/Territory	Spain
City	Salamanca
Period	6/10/21 → 8/10/21

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10.1007/978-3-030-86258-9_2

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Healy, J., Caprani, M., Slattery, O., & O’Keeffe, J. (2022). Using Reduced Amino-Acid Alphabets and Simulated Annealing to Identify Antimicrobial Peptides. In M. Rocha, F. Fdez-Riverola, M. S. Mohamad, & R. Casado-Vara (Eds.), Practical Applications of Computational Biology and Bioinformatics, 15th International Conference, PACBB 2021 (pp. 11-21). (Lecture Notes in Networks and Systems; Vol. 325 LNNS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-86258-9_2

Healy, John ; Caprani, Michela ; Slattery, Orla et al. / Using Reduced Amino-Acid Alphabets and Simulated Annealing to Identify Antimicrobial Peptides. Practical Applications of Computational Biology and Bioinformatics, 15th International Conference, PACBB 2021. editor / Miguel Rocha ; Florentino Fdez-Riverola ; Mohd Saberi Mohamad ; Roberto Casado-Vara. Springer Science and Business Media Deutschland GmbH, 2022. pp. 11-21 (Lecture Notes in Networks and Systems).

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title = "Using Reduced Amino-Acid Alphabets and Simulated Annealing to Identify Antimicrobial Peptides",

abstract = "The efficient detection of similarity between biological sequences is a fundamental task in bioinformatics. This paper describes a k-mer approach for identifying and classifying antimicrobial peptide sequences using 64-bit encoded multiple spaced seeds and a suite of reduced amino acid alphabets. We implemented and tested the approach using a total of 74 reduced alphabets that were either published, altered using simulated annealing, or randomly generated. Our results show that the approach is very accurate and that all of the reduced alphabets of sizes between 9 and 16 were equally effective and far more accurate than smaller sized alphabets. Our custom designed alphabets exhibited higher sensitivity for some families of AMP than any of the published reduced alphabets that we tested.",

author = "John Healy and Michela Caprani and Orla Slattery and Joan O{\textquoteright}Keeffe",

note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 15th International Conference on Practical Applications of Computational Biology and Bioinformatics, PACBB 2021 ; Conference date: 06-10-2021 Through 08-10-2021",

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doi = "10.1007/978-3-030-86258-9_2",

language = "English",

isbn = "9783030862572",

series = "Lecture Notes in Networks and Systems",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "11--21",

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Healy, J, Caprani, M, Slattery, O & O’Keeffe, J 2022, Using Reduced Amino-Acid Alphabets and Simulated Annealing to Identify Antimicrobial Peptides. in M Rocha, F Fdez-Riverola, MS Mohamad & R Casado-Vara (eds), Practical Applications of Computational Biology and Bioinformatics, 15th International Conference, PACBB 2021. Lecture Notes in Networks and Systems, vol. 325 LNNS, Springer Science and Business Media Deutschland GmbH, pp. 11-21, 15th International Conference on Practical Applications of Computational Biology and Bioinformatics, PACBB 2021, Salamanca, Spain, 6/10/21. https://doi.org/10.1007/978-3-030-86258-9_2

Using Reduced Amino-Acid Alphabets and Simulated Annealing to Identify Antimicrobial Peptides. / Healy, John; Caprani, Michela; Slattery, Orla et al.
Practical Applications of Computational Biology and Bioinformatics, 15th International Conference, PACBB 2021. ed. / Miguel Rocha; Florentino Fdez-Riverola; Mohd Saberi Mohamad; Roberto Casado-Vara. Springer Science and Business Media Deutschland GmbH, 2022. p. 11-21 (Lecture Notes in Networks and Systems; Vol. 325 LNNS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Healy, John

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PY - 2022

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AB - The efficient detection of similarity between biological sequences is a fundamental task in bioinformatics. This paper describes a k-mer approach for identifying and classifying antimicrobial peptide sequences using 64-bit encoded multiple spaced seeds and a suite of reduced amino acid alphabets. We implemented and tested the approach using a total of 74 reduced alphabets that were either published, altered using simulated annealing, or randomly generated. Our results show that the approach is very accurate and that all of the reduced alphabets of sizes between 9 and 16 were equally effective and far more accurate than smaller sized alphabets. Our custom designed alphabets exhibited higher sensitivity for some families of AMP than any of the published reduced alphabets that we tested.

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Healy J, Caprani M, Slattery O, O’Keeffe J. Using Reduced Amino-Acid Alphabets and Simulated Annealing to Identify Antimicrobial Peptides. In Rocha M, Fdez-Riverola F, Mohamad MS, Casado-Vara R, editors, Practical Applications of Computational Biology and Bioinformatics, 15th International Conference, PACBB 2021. Springer Science and Business Media Deutschland GmbH. 2022. p. 11-21. (Lecture Notes in Networks and Systems). doi: 10.1007/978-3-030-86258-9_2

Using Reduced Amino-Acid Alphabets and Simulated Annealing to Identify Antimicrobial Peptides

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