Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Complex Networks Analyses of Antibiofilm Peptides: An Emerging Tool for Next Generation Antimicrobials Discovery

Version 1 : Received: 10 March 2023 / Approved: 10 March 2023 / Online: 10 March 2023 (09:36:30 CET)

A peer-reviewed article of this Preprint also exists.

Agüero-Chapin, G.; Antunes, A.; Mora, J.R.; Pérez, N.; Contreras-Torres, E.; Valdes-Martini, J.R.; Martinez-Rios, F.; Zambrano, C.H.; Marrero-Ponce, Y. Complex Networks Analyses of Antibiofilm Peptides: An Emerging Tool for Next-Generation Antimicrobials’ Discovery. Antibiotics 2023, 12, 747. Agüero-Chapin, G.; Antunes, A.; Mora, J.R.; Pérez, N.; Contreras-Torres, E.; Valdes-Martini, J.R.; Martinez-Rios, F.; Zambrano, C.H.; Marrero-Ponce, Y. Complex Networks Analyses of Antibiofilm Peptides: An Emerging Tool for Next-Generation Antimicrobials’ Discovery. Antibiotics 2023, 12, 747.

Abstract

Microbial biofilms cause several environmental and industrial issues, even on the human health. Although they have represented a threaten due to their resistance to antibiotics, there are currently no approved antibiofilm agents for clinical treatments. The multi-functionality of antimicrobial peptides (AMPs) including the antibiofilm activity and their potentialities to target multiple mi-crobes motivated the synthesis of AMP relatives for developing antibiofilm agents for clinical purposes. Antibiofilm peptides (ABFPs) have been organized in databases that allowed the building of prediction tools which have assisted in the discovery/design of new antibiofilm agents. However, the complex network approach has been explored yet as an assistant tool for this aim. Herein, a kind of similarity networks, called the Half-Space Proximal Network (HSPN) is applied to represent/analyse the chemical space of the ABFPs aimed to identify promising scaf-folds for the development of next generation antimicrobials, able to target both planktonic and biofilm microbial forms. Such analyses also considered the metadata associated to the ABFPs such as origin, other activities, targets, etc. in which the relationships were projected by multilayer networks called metadata networks (METNs). From the complex networks mining, a reduced but informative set of 66 ABFPs representing the original antibiofilm space was extracted. This subset retained from the most central to atypical ABFPs, having some of them, desired properties for developing next generation antimicrobials. So, this subset is advisable for assisting the search/design both new antibiofilm/antimicrobial agents. The provided ABFP motifs list, dis-covered within the HSPN communities, is also useful for the same purpose.

Keywords

Antibiofilm peptide; chemical space; StarPep toolbox; complex network; centrality measure; motif discovery

Subject

Medicine and Pharmacology, Pharmacology and Toxicology

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