Antibiotic discovery with artificial intelligence for the treatment of Acinetobacter baumannii infections

Global challenges presented by multidrug-resistant Acinetobacter baumannii infections have stimulated the development of new treatment strategies. We reported that outer membrane protein W (OmpW) is a potential therapeutic target in A. baumannii. Here, a library of 11,648 natural compounds was subjected to a primary screening using quantitative structure-activity relationship (QSAR) models generated from a ChEMBL data set with >7,000 compounds with their reported minimal inhibitory concentration (MIC) values against A. baumannii followed by a structure-based virtual screening against OmpW. In silico pharmacokinetic evaluation was conducted to assess the drug-likeness of these compounds. The ten highest-ranking compounds were found to bind with an energy score ranging from -7.8 to -7.0 kcal/mol where most of them belonged to curcuminoids. To validate these findings, one lead compound exhibiting promising binding stability as well as favorable pharmacokinetics properties, namely demethoxycurcumin, was tested against a panel of A. baumannii strains to determine its antibacterial activity using microdilution and time-kill curve assays. To validate whether the compound binds to the selected target, an OmpW-deficient mutant was studied and compared with the wild type. Our results demonstrate that demethoxycurcumin in monotherapy and in combination with colistin is active against all A. baumannii strains. Finally, the compound was found to significantly reduce the A. baumannii interaction with host cells, suggesting its anti-virulence properties. Collectively, this study demonstrates machine learning as a promising strategy for the discovery of curcuminoids as antimicrobial agents for combating A. baumannii infections.

IMPORTANCE

Acinetobacter baumannii presents a severe global health threat, with alarming levels of antimicrobial resistance rates resulting in significant morbidity and mortality in the USA, ranging from 26% to 68%, as reported by the Centers for Disease Control and Prevention (CDC). To address this threat, novel strategies beyond traditional antibiotics are imperative. Computational approaches, such as QSAR models leverage molecular structures to predict biological effects, expediting drug discovery. We identified OmpW as a potential therapeutic target in A. baumannii and screened 11,648 natural compounds. We employed QSAR models from a ChEMBL bioactivity data set and conducted structure-based virtual screening against OmpW. Demethoxycurcumin, a lead compound, exhibited promising antibacterial activity against A. baumannii, including multidrug-resistant strains. Additionally, demethoxycurcumin demonstrated anti-virulence properties by reducing A. baumannii interaction with host cells. The findings highlight the potential of artificial intelligence in discovering curcuminoids as effective antimicrobial agents against A. baumannii infections, offering a promising strategy to address antibiotic resistance.

Arginine Homopeptide of 11 Residues as a Model of Cell-Penetrating Peptides in the Interaction with Bacterial Membranes

Cell-penetrating peptides rich in arginine are good candidates to be considered as antibacterial compounds, since peptides have a lower chance of generating resistance than commonly used antibiotics. Model homopeptides are a useful tool in the study of activity and its correlation with a secondary structure, constituting an initial step in the construction of functional heteropeptides. In this report, the 11-residue arginine homopeptide (R11) was used to determine its antimicrobial activity against Staphylococcus aureus and Escherichia coli and the effect on the secondary structure, caused by the substitution of the arginine residue by the amino acids Ala, Pro, Leu and Trp, using the scanning technique. As a result, most of the substitutions improved the antibacterial activity, and nine peptides were significantly more active than R11 against the two tested bacteria. The cell-penetrating characteristic of the peptides was verified by SYTOX green assay, with no disruption to the bacterial membranes. Regarding the secondary structure in four different media-PBS, TFE, E. coli membrane extracts and DMPG vesicles-the polyproline II structure, the one of the parent R11, was not altered by unique substitutions, although the secondary structure of the peptides was best defined in E. coli membrane extract. This work aimed to shed light on the behavior of the interaction model of penetrating peptides and bacterial membranes to enhance the development of functional heteropeptides.

Kinnow peel extract as a reducing and capping agent for the fabrication of silver NPs and their biological applications

An effective approach used for the synthesis of silver nanoparticles (AgNPs) through green chemistry by using Kinnow peel extract as a reducing and capping agent is presented. Two different approaches, diluted and concentrated peel extracts, were used for the synthesis of AgNPs. Ultraviolet-visible spectroscopy exhibits characteristic absorption peaks at 425 and 400 nm for nanoparticles (NPs) synthesised by diluted and concentrated extracts, respectively. The X-ray diffraction analysis of nanofabricated silver exhibited a pure face centred cubic structure of 27.4 and 18.1 nm sizes calculated by using Scherrer equation. Scanning electron microscopy analysis showed a uniform morphology of synthesised NPs. Significant antioxidant, phytochemical and antibacterial assays show that both AgNPs can be effectively used in biomedical applications. Furthermore, the use of citrus peel for the synthesis of NPs can be an effective tool in waste management.

In vitro antibacterial activity and physicochemical properties of a crude methanol extract of the larvae of the blow fly Lucilia cuprina

The emergence of multidrug-resistant bacterial strains has prompted the reintroduction of maggot therapy in the treatment of chronic, infected wounds. Many previous studies have demonstrated the potent antibacterial activity of larval excretions/secretions of the blowfly Lucilia sericata (Meigen) (Diptera:Calliphoridae) against bacteria. However, the antibacterial activity of its sibling species, Lucilia cuprina (Wiedemann) (Diptera:Calliphoridae) against a wide range of pathogenic bacteria has never been determined. The aim of this study was to develop a new procedure to produce whole body extract of larvae of L. cuprina via methanol extraction as well as to demonstrate the in vitro antibacterial activity of this extract against seven selected wound pathogens (Staphylococcus aureus, methicillin-resistant S. aureus, S. epidermidis, Streptococcus pyogenes, Klebsiella pneumoniae, Pseudomonas aeruginosa and Escherichia coli). The turbidimetric assay demonstrated that L. cuprina larval extract was significantly potent against all bacteria tested (P < 0.001). Additionally, colony-forming unit (CFU), agar well diffusion and minimum inhibitory concentration assays have confirmed the apparent potency of larval extract against P. aeruginosa. The reconstituted larval extract was highly robust and thermally stable. These observations substantiated the feasibility of the methanol extraction method in the production of larval extract.