ReviewACS omega2021
Understanding the Antibacterial Resistance: Computational Explorations in Bacterial Membranes.
Review in ACS omega, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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.
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.
Who cites it
20 citing papers in PubMed, 35 citations in OpenAlex.
- Article
- Reimagining antimicrobial resistance: AI-driven predictive epidemiology and the C-AMRE framework for next-generation antibiotic discovery.The Journal of antibiotics · 2026Review
- Green-synthesized gold nanoparticles: as emerging tools to combat antimicrobial resistance and therapeutic applications in poultry.Veterinary research communications · 2026Review
- Computational Identification of Potential Novel Allosteric IHF Inhibitors Using QSAR Modeling to Inhibit Plasmid-Mediated Antibiotic Resistance.International journal of molecular sciences · 2026Article
- The Perspectives of Combining Antibiotics with Saponins-Herbal Excipients.Molecules (Basel, Switzerland) · 2025Review
- Novel Anti-MRSA Peptide from Mangrove-DerivedMarine drugs · 2025Article
- Newly developed antibiotics against multidrug-resistant and carbapenem-resistant Gram-negative bacteria: action and resistance mechanisms.Archives of microbiology · 2025Review
- Gut-bone axis perturbation: Mechanisms and interventions via gut microbiota as a primary driver of osteoporosis.Journal of orthopaedic translation · 2025Review
- Simulating Bacterial Membrane Models at the Atomistic Level: A Force Field Comparison.Journal of chemical theory and computation · 2024Article
- Drivers of antimicrobial resistance in layer poultry farming: Evidence from high prevalence of multidrug-resistantVeterinary world · 2023Article
- The role of efflux pumps ın antıbıotıc resıstance of gram negatıve rods.Archives of microbiology · 2023Review
- Antimicrobial Potential of Betulinic Acid and Investigation of the Mechanism of Action against Nuclear and Metabolic Enzymes with Molecular Modeling.Pathogens (Basel, Switzerland) · 2023Article
- Methicillin ResistantInfection and drug resistance · 2023Review
- Lipid-A-dependent and cholesterol-dependent dynamics properties of liposomes from gram-negative bacteria in ESKAPE.Scientific reports · 2022Article
- The Role of Outer Membrane Proteins in UPEC Antimicrobial Resistance: A Systematic Review.Membranes · 2022Review
- Harnessing the Role of Bacterial Plasma Membrane Modifications for the Development of Sustainable Membranotropic Phytotherapeutics.Membranes · 2022Review
- A comprehensive review on genomics, systems biology and structural biology approaches for combating antimicrobial resistance in ESKAPE pathogens: computational tools and recent advancements.World journal of microbiology & biotechnology · 2022Review
- Model architectures for bacterial membranes.Biophysical reviews · 2022Review
- Machine Learning in Antibacterial Drug Design.Frontiers in pharmacology · 2022Review
- Lipid Flip-Flop-Inducing Antimicrobial Phytochemicals fromACS omega · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Antimicrobial resistance (AMR) represents a major threat to global public health in the 21st century, dramatically increasing the pandemic expectations in the coming years. The ongoing need to develop new antimicrobial treatments that are effective against multi-drug-resistant pathogens has led the research community to investigate innovative strategies to tackle AMR. The bacterial cell envelope has been identified as one of the key molecular players responsible for antibiotic resistance, attracting considerable interest as a potential target for novel antimicrobials effective against AMR, to be used alone or in combination with other drugs. However, the multicomponent complexity of bacterial membranes provides a heterogeneous morphology, which is typically difficult to study at the molecular level by experimental techniques, in spite of the significant development of fast and efficient experimental protocols. In recent years, computational modeling, in particular, molecular dynamics simulations, has proven to be an effective tool to reveal key aspects in the architecture and membrane organization of bacterial cell walls. Here, after a general overview about bacterial membranes, AMR mechanisms, and experimental approaches to study AMR, we review the state-of-the-art computational approaches to investigate bacterial AMR envelopes, including their limitations and challenges ahead. Representative examples illustrate how these techniques improve our understanding of bacterial membrane resistance mechanisms, hopefully leading to the development of novel antimicrobial drugs escaping from bacterial resistance strategies.
Identifiers
What OpenQuestion holds
Registered trials
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.