ArticleChemical biology & drug design2013
Discovery of Staphylococcus aureus sortase A inhibitors using virtual screening and the relaxed complex scheme.
Article in Chemical biology & drug design, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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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.
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Who cites it
32 citing papers in PubMed, 57 citations in OpenAlex.
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- Disarming the Pathogenicity of Methicillin-Resistant Staphylococcus aureus via Osmundacetone-Mediated Inhibition of Sortase A.Microbial biotechnology · 2025Article
- Ensemble Docking as a Tool for the Rational Design of PeptidomimeticInternational journal of molecular sciences · 2024Article
- Beyond Antibiotics: What the Future Holds.Antibiotics (Basel, Switzerland) · 2024Review
- A unique binding mode of P1' Leu-containing target sequences forRSC chemical biology · 2024Article
- High-Throughput Screening of Natural Product and Synthetic Molecule Libraries for Antibacterial Drug Discovery.Metabolites · 2023Review
- Selection of Promising Novel Fragment SizedMolecules (Basel, Switzerland) · 2021Article
- Improving Structure-Based Virtual Screening with Ensemble Docking and Machine Learning.Journal of chemical information and modeling · 2021Article
- Accommodating receptor flexibility and free energy calculation to reduce false positive binders in the discovery of natural products blockers of SARS-COV-2 spike RBD-ACE2 interface.Biochemistry and biophysics reports · 2021Article
- Sorting out the Superbugs: Potential of Sortase A Inhibitors among Other Antimicrobial Strategies to Tackle the Problem of Antibiotic Resistance.Antibiotics (Basel, Switzerland) · 2021Article
- Design and Synthesis of Small Molecules as PotentAntibiotics (Basel, Switzerland) · 2020Review
- A Cell-based Screen in Actinomyces oris to Identify Sortase Inhibitors.Scientific reports · 2020Article
- Optimization of sortase A ligation for flexible engineering of complex protein systems.The Journal of biological chemistry · 2020Article
- Predicting and designing therapeutics against the Nipah virus.PLoS neglected tropical diseases · 2019Article
- Methicillin-resistantMedChemComm · 2019Review
- Improving inverse docking target identification with Z-score selection.Chemical biology & drug design · 2019Article
- Conversion of an amide to a high-energy thioester by Staphylococcus aureus sortase A is powered by variable binding affinity for calcium.Scientific reports · 2018Article
- Efficiency of Stratification for Ensemble Docking Using Reduced Ensembles.Journal of chemical information and modeling · 2018Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
Staphylococcus aureus is the leading cause of hospital-acquired infections in the United States. The emergence of multidrug-resistant strains of S. aureus has created an urgent need for new antibiotics. Staphylococcus aureus uses the sortase A enzyme to display surface virulence factors suggesting that compounds that inhibit its activity will function as potent anti-infective agents. Here, we report the identification of several inhibitors of sortase A using virtual screening methods that employ the relaxed complex scheme, an advanced computer-docking methodology that accounts for protein receptor flexibility. Experimental testing validates that several compounds identified in the screen inhibit the activity of sortase A. A lead compound based on the 2-phenyl-2,3-dihydro-1H-perimidine scaffold is particularly promising, and its binding mechanism was further investigated using molecular dynamics simulations and conducting preliminary structure-activity relationship studies.
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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.