Evidence map›Paper›PMID 36177630›Full record

ReviewCurrent pharmaceutical design2022

Development of Peptide-based Metallo-β-lactamase Inhibitors as a New Strategy to Combat Antimicrobial Resistance: A Mini-review.

Qipeng Cheng, Ping Zeng, Edward Wai Chi Chan, Sheng Chen

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current pharmaceutical design, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Qipeng ChengAnhui Provincial Key Laboratory of Molecular Enzymology and Mechanism of Major Diseases and Key Laboratory of Biomedicine in Gene Diseases and Health of Anhui Higher Education Institutes, College of Life Sciences, Anhui Normal University, Wuhu, Anhui, China.
Ping ZengSchool of Pharmacy, The Chinese University of Hong Kong, Shatin, Hong Kong.
Edward Wai Chi ChanDepartment of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Kowloon, Hong Kong.
Sheng ChenDepartment of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Kowloon, Hong Kong.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Global dissemination of antimicrobial resistance (AMR) not only poses a significant threat to human health, food security, and social development but also results in millions of deaths each year. In Gram-negative bacteria, the primary mechanism of resistance to β-lactam antibiotics is the production of β-lactamases, one of which is carbapenem-hydrolyzing β-lactamases known as carbapenemases. As a general scheme, these enzymes are divided into Ambler class A, B, C, and D based on their protein sequence homology. Class B β-lactamases are also known as metallo-β-lactamases (MBLs). The incidence of recovery of bacteria expressing metallo-β- lactamases (MBLs) has increased dramatically in recent years, almost reaching a pandemic proportion. MBLs can be further divided into three subclasses (B1, B2, and B3) based on the homology of protein sequences as well as the differences in zinc coordination. The development of inhibitors is one effective strategy to suppress the activities of MBLs and restore the activity of β-lactam antibiotics. Although thousands of MBL inhibitors have been reported, none have been approved for clinical use. This review describes the clinical application potential of peptide-based drugs that exhibit inhibitory activity against MBLs identified in past decades. In this report, peptide-based inhibitors of MBLs are divided into several groups based on the mode of action, highlighting compounds of promising properties that are suitable for further advancement. We discuss how traditional computational tools, such as in silico screening and molecular docking, along with new methods, such as deep learning and machine learning, enable a more accurate and efficient design of peptide-based inhibitors of MBLs.

Indexed as

Anti-Bacterial Agentsbeta-Lactamase Inhibitorsbeta-LactamasesCarbapenemsDrug Resistance, BacterialHumansMolecular Docking SimulationPeptidesAnti-Bacterial Agentsbeta-Lactamase Inhibitorsbeta-LactamasesCarbapenemsPeptidesdeep learningin silico screeningmachine learning.Metallo-β-lactamases (MBLs)molecular dockingpeptide-based inhibitors

Identifiers

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.