Discovery of beta-lactamase CMY-10 inhibitors for combination therapy against multi-drug resistant Enterobacteriaceae

Tackling the Antimicrobial Resistance "Pandemic" with Machine Learning Tools: A Summary of Available Evidence

Antimicrobial resistance is recognised as one of the top threats healthcare is bound to face in the future. There have been various attempts to preserve the efficacy of existing antimicrobials, develop new and efficient antimicrobials, manage infections with multi-drug resistant strains, and improve patient outcomes, resulting in a growing mass of routinely available data, including electronic health records and microbiological information that can be employed to develop individualised antimicrobial stewardship. Machine learning methods have been developed to predict antimicrobial resistance from whole-genome sequencing data, forecast medication susceptibility, recognise epidemic patterns for surveillance purposes, or propose new antibacterial treatments and accelerate scientific discovery. Unfortunately, there is an evident gap between the number of machine learning applications in science and the effective implementation of these systems. This narrative review highlights some of the outstanding opportunities that machine learning offers when applied in research related to antimicrobial resistance. In the future, machine learning tools may prove to be superbugs' kryptonite. This review aims to provide an overview of available publications to aid researchers that are looking to expand their work with new approaches and to acquaint them with the current application of machine learning techniques in this field.

Identification of Phytochemicals with Inhibitory Potential Against Beta-lactamase Enzymes via Computer-aided Approach

INTRODUCTION

Antibacterial drugs have been widely used for the past century to treat diseases, but their efficacy has been limited by multi-resistant pathogens, particularly those that utilize beta-lactamase enzymes. The inhibition of beta-lactamase enzymes holds great promise for reducing the influence of such pathogens.

OBJECTIVE

This study aims to evaluate the mechanism of inhibition of phytochemicals with antibacterial activity against two classes of beta-lactamases using computational methods.

METHODS

To achieve this objective, a total of thirty phytochemicals were docked against SHV-1 beta-lactamase and AmpC beta-lactamase after procurement from Protein Data Bank. The pharmacokinetics (ADMET) and density functional theory (DFT) analysis study were also conducted to unravel the nature of the top six most promising compounds on each protein.

RESULTS

The results showed that a significant percentage of the compounds had binding affinities greater than that of avibactam, the positive control. Quercetin-3-O-rutinoside showed the most promising results against SHV-1 beta-lactamase with an affinity of -9.4 kcal/mol, while luteolin was found to be the most promising candidate against AmpC beta-lactamase with an affinity of -8.5 kcal/mol. DFT analysis demonstrated the reactivity of these compounds, and the ADMET study indicated that they were relatively safe.

CONCLUSION

In conclusion, the study's findings suggest that the selected compounds have significant potential to inhibit beta-lactamase and may be used in combination with antibiotics against organisms that produce beta-lactamase. This study provides a basis for further research in a wet-lab setting to validate the results.

Halogenated Antimicrobial Agents to Combat Drug-Resistant Pathogens

Antimicrobial resistance presents us with a potential global crisis as it undermines the abilities of conventional antibiotics to combat pathogenic microbes. The history of antimicrobial agents is replete with examples of scaffolds containing halogens. In this review, we discuss the impacts of halogen atoms in various antibiotic types and antimicrobial scaffolds and their modes of action, structure-activity relationships, and the contributions of halogen atoms in antimicrobial activity and drug resistance. Other halogenated molecules, including carbohydrates, peptides, lipids, and polymeric complexes, are also reviewed, and the effects of halogenated scaffolds on pharmacokinetics, pharmacodynamics, and factors affecting antimicrobial and antivirulence activities are presented. Furthermore, the potential of halogenation to circumvent antimicrobial resistance and rejuvenate impotent antibiotics is addressed. This review provides an overview of the significance of halogenation, the abilities of halogens to interact in biomolecular settings and enhance pharmacological properties, and their potential therapeutic usages in preventing a postantibiotic era. SIGNIFICANCE STATEMENT: Antimicrobial resistance and the increasing impotence of antibiotics are critical threats to global health. The roles and importance of halogen atoms in antimicrobial drug scaffolds have been established, but comparatively little is known of their pharmacological impacts on drug resistance and antivirulence activities. This review is the first to extensively evaluate the roles of halogen atoms in various antibiotic classes and pharmacological scaffolds and to provide an overview of their ability to overcome antimicrobial resistance.

Non-β Lactam Inhibitors of the Serine β-Lactamase blaCTX-M15 in Drug-Resistant Salmonella typhi

Antibiotic resistance by bacterial pathogens against widely used β-lactam drugs is a major concern to public health worldwide, resulting in high healthcare cost. The present study aimed to extend previous research by investigating the potential activity of reported compounds against the S. typhi β-lactamase protein. 74 compounds from computational screening reported in our previous study against β-lactamase CMY-10 were subjected to docking studies against blaCTX-M15. Site-Identification by Ligand Competitive Saturation (SILCS)-Monte Carlo (SILCS-MC) was applied to the top two ligands selected from molecular docking studies to predict and refine their conformations for binding conformations against blaCTX-M15. The SILCS-MC method predicted affinities of -8.6 and -10.7 kcal/mol for Top1 and Top2, respectively, indicating low micromolar binding to the blaCTX-M15 active site. MD simulations initiated from SILCS-MC docked orientations were carried out to better characterize the dynamics and stability of the complexes. Important interactions anchoring the ligand within the active site include pi-pi stacked, amide-pi, and pi-alkyl interactions. Simulations of the Top2-blaCTX-M15 complex exhibited stability associated with a wide range of hydrogen-bond and aromatic interactions between the protein and the ligand. Experimental β-lactamase (BL) activity assays showed that Top1 has 0.1 u/mg BL activity, and Top2 has a BL activity of 0.038 u/mg with a minimum inhibitory concentration of 1 mg/mL. The inhibitors proposed in this study are non-β-lactam-based β-lactamase inhibitors that exhibit the potential to be used in combination with β-lactam antibiotics against multidrug-resistant clinical isolates. Thus, Top1 and Top2 represent lead compounds that increase the efficacy of β-lactam antibiotics with a low dose concentration.

β-Lactam potentiators to re-sensitize resistant pathogens: Discovery, development, clinical use and the way forward

β-lactam antibiotics are one of the most widely used and diverse classes of antimicrobial agents for treating both Gram-negative and Gram-positive bacterial infections. The β-lactam antibiotics, which include penicillins, cephalosporins, monobactams and carbapenems, exert their antibacterial activity by inhibiting the bacterial cell wall synthesis and have a global positive impact in treating serious bacterial infections. Today, β-lactam antibiotics are the most frequently prescribed antimicrobial across the globe. However, due to the widespread use and misapplication of β-lactam antibiotics in fields such as human medicine and animal agriculture, resistance to this superlative drug class has emerged in the majority of clinically important bacterial pathogens. This heightened antibiotic resistance prompted researchers to explore novel strategies to restore the activity of β-lactam antibiotics, which led to the discovery of β-lactamase inhibitors (BLIs) and other β-lactam potentiators. Although there are several successful β-lactam-β-lactamase inhibitor combinations in use, the emergence of novel resistance mechanisms and variants of β-lactamases have put the quest of new β-lactam potentiators beyond precedence. This review summarizes the success stories of β-lactamase inhibitors in use, prospective β-lactam potentiators in various phases of clinical trials and the different strategies used to identify novel β-lactam potentiators. Furthermore, this review discusses the various challenges in taking these β-lactam potentiators from bench to bedside and expounds other mechanisms that could be investigated to reduce the global antimicrobial resistance (AMR) burden.

Artificial intelligence as a smart approach to develop antimicrobial drug molecules: A paradigm to combat drug-resistant infections

Antimicrobial resistance (AMR) is a silent pandemic with the third highest global mortality. The antibiotic development pipeline is scarce even though AMR has escalated uncontrollably. Artificial intelligence (AI) is a revolutionary approach, accelerating drug discovery because of its fast pace, cost efficiency, lower labor requirements, and fewer chances of failure. AI has been used to discover several beta-lactamase inhibitors and antibiotic alternatives from antimicrobial peptides (AMPs), nonribosomal peptides, bacteriocins, and marine natural products. The significant recent increase in the use of AI platforms by pharmaceutical companies could result in the discovery of efficient antibiotic alternatives with lower chances of resistance generation.

Computer-Aided Drug Design: An Update

Computer-aided drug design (CADD) approaches are playing an increasingly important role in understanding the fundamentals of ligand-receptor interactions and helping medicinal chemists design therapeutics. About 5 years ago, we presented a chapter devoted to an overview of CADD methods and covered typical CADD protocols including structure-based drug design (SBDD) and ligand-based drug design (LBDD) approaches that were frequently used in the antibiotic drug design process. Advances in computational hardware and algorithms and emerging CADD methods are enhancing the accuracy and ability of CADD in drug design and development. In this chapter, an update to our previous chapter is provided with a focus on new CADD approaches from our laboratory and other peers that can be employed to facilitate the development of antibiotic therapeutics.

A Comprehensive Survey of Prospective Structure-Based Virtual Screening for Early Drug Discovery in the Past Fifteen Years

Structure-based virtual screening (SBVS), also known as molecular docking, has been increasingly applied to discover small-molecule ligands based on the protein structures in the early stage of drug discovery. In this review, we comprehensively surveyed the prospective applications of molecular docking judged by solid experimental validations in the literature over the past fifteen years. Herein, we systematically analyzed the novelty of the targets and the docking hits, practical protocols of docking screening, and the following experimental validations. Among the 419 case studies we reviewed, most virtual screenings were carried out on widely studied targets, and only 22% were on less-explored new targets. Regarding docking software, GLIDE is the most popular one used in molecular docking, while the DOCK 3 series showed a strong capacity for large-scale virtual screening. Besides, the majority of identified hits are promising in structural novelty and one-quarter of the hits showed better potency than 1 μM, indicating that the primary advantage of SBVS is to discover new chemotypes rather than highly potent compounds. Furthermore, in most studies, only in vitro bioassays were carried out to validate the docking hits, which might limit the further characterization and development of the identified active compounds. Finally, several successful stories of SBVS with extensive experimental validations have been highlighted, which provide unique insights into future SBVS drug discovery campaigns.

In Silico and In Vitro Screening of Natural Compounds as Broad-Spectrum β-Lactamase Inhibitors against Acinetobacter baumannii New Delhi Metallo-β-lactamase-1 (NDM-1)

Antibiotic resistance is one of the significant problems globally; there is an increase in resistance with introducing every new class of antibiotics. Further, this has become one of the reasons for arising of new resistance mechanisms in Acinetobacter baumannii. In this study, we have screened natural compounds as a possible inhibitor against the NDM-1 β-lactamase enzyme from A. baumannii using a combination of in silico methods and in vitro evaluation. The database of natural compounds was screened against NDM-1 protein, using Glide docking, followed by QM-polarised ligand docking (QPLD). When the screened hits were validated in vitro, withaferin A and mangiferin had good IC₅₀ values in reducing the activity of NDM-1 enzymes, and their fractional inhibitory concentration index (FICI) was ascertained in combination with imipenem. The withaferin A and mangiferin-NDM-1 docking complexes were analyzed for structural stability by molecular dynamic simulation analysis using GROMACS for 100 ns. The molecular properties of the natural compounds were then calculated using density functional theory (DFT). Withaferin A and mangiferin showed promising inhibitory activity and can be a natural compound candidate inhibitor synergistically used along with carbapenems against NDM-1 producing A. baumannii.

Artificial Intelligence and Antibiotic Discovery

Over recent decades, a new antibiotic crisis has been unfolding due to a decreased research in this domain, a low return of investment for the companies that developed the drug, a lengthy and difficult research process, a low success rate for candidate molecules, an increased use of antibiotics in farms and an overall inappropriate use of antibiotics. This has led to a series of pathogens developing antibiotic resistance, which poses severe threats to public health systems while also driving up the costs of hospitalization and treatment. Moreover, without proper action and collaboration between academic and health institutions, a catastrophic trend might develop, with the possibility of returning to a pre-antibiotic era. Nevertheless, new emerging AI-based technologies have started to enter the field of antibiotic and drug development, offering a new perspective to an ever-growing problem. Cheaper and faster research can be achieved through algorithms that identify hit compounds, thereby further accelerating the development of new antibiotics, which represents a vital step in solving the current antibiotic crisis. The aim of this review is to provide an extended overview of the current artificial intelligence-based technologies that are used for antibiotic discovery, together with their technological and economic impact on the industrial sector.

Synthesis and potential antimicrobial activity of novel α-aminophosphonates derivatives bearing substituted quinoline or quinolone and thiazole moieties

To develop novel antimicrobial agents, and based on the biologically active heterocyclic quinoline and thiazole substituted, a series of novel α-aminophosphonates (9a–h) and (10i–l) derivatives that incorporated quinoline or quinolone, and coumarylthiazole or 5-phenylthiazol-2-amine moieties were designed and synthesized via Kabachnik–Fields reaction in the presence of ionic liquid under ultrasound irradiation. All the new compounds were obtained in good yield with a simple workup and were confirmed using various spectroscopic methods. The in vitro antimicrobial activity of all synthesized compounds were screened in terms of MIC values against the selected strains of Gram-negative and Gram-positive bacteria and two fungal strains using the broth micro-dilution method. The results showed that most of the tested compounds showed moderate inhibitory activities against both Gram‐positive and ‐negative bacteria compared with reference drugs. The following compounds 9e, 9g, 9h, 9i and 9f, 9g, 9h, 10k, 10l are the most active against Gram-positive and Gram-negative bacteria strains, respectively, with MIC values ranging between 0.25 and 128 μg/mL. The synthesized compounds 9b, 9c, 9f, 9g, 9h, 10k, and 10l exhibited excellent antifungal inhibition with MIC values ranging between 0.25 and 32 μg/mL. Structure–activity relationship revealed that the presence of coumarylthiazole moiety and hydroxyl in the quinoline group increased the inhibitory activity against microbial strains pathogens. These results confirm that the synthesized compounds can be potential antimicrobial drugs candidate.

Synthesis and potent antimicrobial activity of novel coumarylthiazole α-aminophosphonates derivatives

Herein, we reported a novel series of α-aminophosphonates derivatives (IV)a-m bearing an important pharmacophore coumarylthiazole moiety. All the new compounds have been synthesized via Kabachnik-Fields reaction under ultrasonic irradiation. The products were obtained in good yield with a simple workup and were confirmed using various spectroscopic methods. All these compounds (IV)a-m were screened for their in vitro for antimicrobial activity against thirteen Gram-negative bacteria and five Gram-positive bacteria and Candida albicans strains. The results showed that all the synthesized compounds exhibited moderate antibacterial activities against both references and multidrug-resistant and antifungal strains. The compound (IV)e showed the highest activities against all pathogens of the tested microbial strains with MIC of 0.125 μg/mL. The compounds (IV)h, (IV)f, (IV)b, and (IV)d exhibited moderate and promising activities with MIC of 0.125 μg/mL. Structure-activity relationship revealed that inhibitory activity of the synthesized compounds is related to the type of the substituted group on phenyl rings, and these results showed that the electron-donating groups at ortho and para positions have a high relationship increasing antimicrobial activities than the electron-withdrawing groups. These results confirm that coumarylthiazole α-aminophosphonates compounds can be potential antimicrobial drugs candidate.

Present and Future Perspectives on Therapeutic Options for Carbapenemase-Producing Enterobacterales Infections

Carbapenem-resistant Enterobacterales (CRE) are included in the list of the most threatening antibiotic resistance microorganisms, being responsible for often insurmountable therapeutic issues, especially in hospitalized patients and immunocompromised individuals and patients in intensive care units. The enzymatic resistance to carbapenems is encoded by different β-lactamases belonging to A, B or D Ambler class. Besides compromising the activity of last-resort antibiotics, CRE have spread from the clinical to the environmental sectors, in all geographic regions. The purpose of this review is to present present and future perspectives on CRE-associated infections treatment.