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Unraveling the hemolytic toxicity tapestry of peptides using chemical space complex networks
(Oxford University Press, 2024)
Castillo-Mendieta, Kevin
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Agüero-Chapin, Guillermin
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Mora, José R.
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Pérez, Noel
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Contreras-Torres, Ernesto
Peptides have emerged as promising therapeutic agents. However, their potential is hindered by hemotoxicity. Understanding the hemotoxicity of peptides is crucial for developing safe and effective peptide-based therapeutics. Here, we employed chemical space complex networks (CSNs) to unravel the hemotoxicity tapestry of peptides. CSNs are powerful tools for visualizing and analyzing the relationships between peptides based on their physicochemical properties and structural features. We constructed CSNs from the StarPepDB database, encompassing 2,004 hemolytic peptides, and explored the impact of seven different (dis)similarity measures on network topology and cluster (communities) distribution. Our findings revealed that each CSN extracts orthogonal information, enhancing the motif discovery and enrichment process. We identified 12 consensus hemolytic motifs, whose amino acid composition unveiled a high abundance of lysine, leucine, and valine residues, whereas aspartic acid, methionine, histidine, asparagine, and glutamine were depleted. Additionally, physicochemical properties were used to characterize clusters/communities of hemolytic peptides. To predict hemolytic activity directly from peptide sequences, we constructed multi-query similarity searching models, which outperformed cutting-edge machine learning-based models, demonstrating robust hemotoxicity prediction capabilities. Overall, this novel in silico approach uses complex network science as its central strategy to develop robust model classifiers, characterize the chemical space, and discover new motifs from hemolytic peptides. This will help to enhance the design/selection of peptides with potential therapeutic activity and low toxicity. ©2024 Toxicological Sciences ©2024 The authors.
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Theoretical study of the hydrolysis mechanism of β-lactam antibiotics catalysed by a Zn(II) dinuclear biomimetic organometallic complex
(Taylor and Francis Group, 2024)
Zurita, Juan E.
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Mora, José R.
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Barigye, Stephen J.
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Espinoza-Montero, Patricio J.
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Martínez Ríos, Félix Orlando
The degradation and metabolism of antibiotics have attracted the scientific community's attention due to the environmental problems caused by the inappropriate use and disposal of these drugs. Therefore, it is crucial to understand the reaction mechanism involved in the degradation of these compounds. We studied the hydrolysis of nitrocefin and benzylpenicillin, two β-lactam ring antibiotics, mediated by an enzymatic mimetic Zn organometallic compound, using DFT methods. The electronic effects of functional groups adjacent to the β-lactam ring were analysed and good agreement between experimental and theoretical results was found. The reaction involves the nucleophilic attack of the bridging hydroxide group on the Zn atoms towards the β-lactam ring. A stepwise mechanism was found to agree with the experimental results. Chemical hardness profiles were affected by the solvent and reaction synchronicity. Geometric rearrangements dominated the activation barrier, and both antibiotics exhibited late transition states. © Taylor and Francis Group.
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Complex Networks Analyses of Antibiofilm Peptides: An Emerging Tool for Next-Generation Antimicrobials’ Discovery
(MDPI, 2023)
Agüero-Chapin, Guillermin
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Antunes, Agostinho
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Mora, José R.
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Pérez, Noel
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Contreras-Torres, Ernesto
Microbial biofilms cause several environmental and industrial issues, even affecting human health. Although they have long represented a threat due to their resistance to antibiotics, there are currently no approved antibiofilm agents for clinical treatments. The multi-functionality of antimicrobial peptides (AMPs), including their antibiofilm activity and their potential to target multiple microbes, has motivated the synthesis of AMPs and their relatives for developing antibiofilm agents for clinical purposes. Antibiofilm peptides (ABFPs) have been organized in databases that have allowed the building of prediction tools which have assisted in the discovery/design of new antibiofilm agents. However, the complex network approach has not yet been explored as an assistant tool for this aim. Herein, a kind of similarity network called the half-space proximal network (HSPN) is applied to represent/analyze the chemical space of ABFPs, aiming to identify privileged scaffolds for the development of next-generation antimicrobials that are able to target both planktonic and biofilm microbial forms. Such analyses also considered the metadata associated with 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 was extracted, representing the original antibiofilm space. This subset contained the most central to atypical ABFPs, some of them having the desired properties for developing next-generation antimicrobials. Therefore, this subset is advisable for assisting the search for/design of both new antibiofilms and antimicrobial agents. The provided ABFP motifs list, discovered within the HSPN communities, is also useful for the same purpose. © 2023 by the authors.
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