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Exploring complexity of class-A Beta-lactamase family using physiochemical-based multiplex networks
The Beta-lactamase protein family is vital in countering Beta-lactam antibiotics, a widely used antimicrobial. To enhance our understanding of this family, we adopted a novel approach employing a multiplex network representation of its multiple sequence alignment. Each network layer, derived from th...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10667273/ https://www.ncbi.nlm.nih.gov/pubmed/37996629 http://dx.doi.org/10.1038/s41598-023-48128-y |
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author | Bhadola, Pradeep Deo, Nivedita |
author_facet | Bhadola, Pradeep Deo, Nivedita |
author_sort | Bhadola, Pradeep |
collection | PubMed |
description | The Beta-lactamase protein family is vital in countering Beta-lactam antibiotics, a widely used antimicrobial. To enhance our understanding of this family, we adopted a novel approach employing a multiplex network representation of its multiple sequence alignment. Each network layer, derived from the physiochemical properties of amino acids, unveils distinct insights into the intricate interactions among nodes, thereby enabling the identification of key motifs. Nodes with identical property signs tend to aggregate, providing evidence of the presence of consequential functional and evolutionary constraints shaping the Beta-lactamase family. We further investigate the distribution of evolutionary links across various layers. We observe that polarity manifests the highest number of unique links at lower thresholds, followed by hydrophobicity and polarizability, wherein hydrophobicity exerts dominance at higher thresholds. Further, the combinations of polarizability and volume, exhibit multiple simultaneous connections at all thresholds. The combination of hydrophobicity, polarizability, and volume uncovers shared links exclusive to these layers, implying substantial evolutionary impacts that may have functional or structural implications. By assessing the multi-degree of nodes, we unveil the hierarchical influence of properties at each position, identifying crucial properties responsible for the protein’s functionality and providing valuable insights into potential targets for modulating enzymatic activity. |
format | Online Article Text |
id | pubmed-10667273 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-106672732023-11-23 Exploring complexity of class-A Beta-lactamase family using physiochemical-based multiplex networks Bhadola, Pradeep Deo, Nivedita Sci Rep Article The Beta-lactamase protein family is vital in countering Beta-lactam antibiotics, a widely used antimicrobial. To enhance our understanding of this family, we adopted a novel approach employing a multiplex network representation of its multiple sequence alignment. Each network layer, derived from the physiochemical properties of amino acids, unveils distinct insights into the intricate interactions among nodes, thereby enabling the identification of key motifs. Nodes with identical property signs tend to aggregate, providing evidence of the presence of consequential functional and evolutionary constraints shaping the Beta-lactamase family. We further investigate the distribution of evolutionary links across various layers. We observe that polarity manifests the highest number of unique links at lower thresholds, followed by hydrophobicity and polarizability, wherein hydrophobicity exerts dominance at higher thresholds. Further, the combinations of polarizability and volume, exhibit multiple simultaneous connections at all thresholds. The combination of hydrophobicity, polarizability, and volume uncovers shared links exclusive to these layers, implying substantial evolutionary impacts that may have functional or structural implications. By assessing the multi-degree of nodes, we unveil the hierarchical influence of properties at each position, identifying crucial properties responsible for the protein’s functionality and providing valuable insights into potential targets for modulating enzymatic activity. Nature Publishing Group UK 2023-11-23 /pmc/articles/PMC10667273/ /pubmed/37996629 http://dx.doi.org/10.1038/s41598-023-48128-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Bhadola, Pradeep Deo, Nivedita Exploring complexity of class-A Beta-lactamase family using physiochemical-based multiplex networks |
title | Exploring complexity of class-A Beta-lactamase family using physiochemical-based multiplex networks |
title_full | Exploring complexity of class-A Beta-lactamase family using physiochemical-based multiplex networks |
title_fullStr | Exploring complexity of class-A Beta-lactamase family using physiochemical-based multiplex networks |
title_full_unstemmed | Exploring complexity of class-A Beta-lactamase family using physiochemical-based multiplex networks |
title_short | Exploring complexity of class-A Beta-lactamase family using physiochemical-based multiplex networks |
title_sort | exploring complexity of class-a beta-lactamase family using physiochemical-based multiplex networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10667273/ https://www.ncbi.nlm.nih.gov/pubmed/37996629 http://dx.doi.org/10.1038/s41598-023-48128-y |
work_keys_str_mv | AT bhadolapradeep exploringcomplexityofclassabetalactamasefamilyusingphysiochemicalbasedmultiplexnetworks AT deonivedita exploringcomplexityofclassabetalactamasefamilyusingphysiochemicalbasedmultiplexnetworks |