Evidence map›Paper›PMID 33723038›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2021

Computationally designed peptide macrocycle inhibitors of New Delhi metallo-β-lactamase 1.

Vikram Khipple Mulligan, Sean Workman, Tianjun Sun, Stephen Rettie, Xinting Li, Liam J Worrall, Timothy W Craven, Dustin T King, Parisa Hosseinzadeh, Andrew M Watkins and 7 more

Open access · greenAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed
4.4field-weighted citation impact, top 4% of its field
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

37 citing papers in PubMed, 75 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. CyclicMPNN: Stable Cyclic Peptide Sequence Generation.bioRxiv : the preprint server for biology · 2026
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Heuristic energy-based cyclic peptide design.PLoS computational biology · 2025
    Article
  10. Heuristic energy-based cyclic peptide design.bioRxiv : the preprint server for biology · 2025
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. AccuratebioRxiv : the preprint server for biology · 2024
    Article
  16. Review
  17. Article
  18. Machine Learning Models Identify Inhibitors of New Delhi Metallo-β-lactamase.Journal of chemical information and modeling · 2024
    Article
  19. Article
  20. Article
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

17 authors at 8 institutions in 2 countries.

Vikram Khipple MulliganCenter for Computational Biology, Flatiron Institute, New York, NY 10010; vmulligan@flatironinstitute.org.ORCID 0000-0001-6038-8922
Sean WorkmanDepartment of Biochemistry and Molecular Biology and the Centre for Blood Research, University of British Columbia, Life Sciences Centre, Vancouver, BC V6T 1Z3, Canada.ORCID 0000-0001-8807-4466
Tianjun SunDepartment of Biochemistry and Molecular Biology and the Centre for Blood Research, University of British Columbia, Life Sciences Centre, Vancouver, BC V6T 1Z3, Canada.
Stephen RettieInstitute for Protein Design, Department of Biochemistry, Molecular Engineering and Sciences, University of Washington, Seattle, WA 98195.
Xinting LiInstitute for Protein Design, Department of Biochemistry, Molecular Engineering and Sciences, University of Washington, Seattle, WA 98195.
Liam J WorrallDepartment of Biochemistry and Molecular Biology and the Centre for Blood Research, University of British Columbia, Life Sciences Centre, Vancouver, BC V6T 1Z3, Canada.
Timothy W CravenInstitute for Protein Design, Department of Biochemistry, Molecular Engineering and Sciences, University of Washington, Seattle, WA 98195.
Dustin T KingDepartment of Biochemistry and Molecular Biology and the Centre for Blood Research, University of British Columbia, Life Sciences Centre, Vancouver, BC V6T 1Z3, Canada.
Parisa HosseinzadehInstitute for Protein Design, Department of Biochemistry, Molecular Engineering and Sciences, University of Washington, Seattle, WA 98195.ORCID 0000-0002-3128-7433
Andrew M WatkinsDepartment of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305.
P Douglas RenfrewCenter for Computational Biology, Flatiron Institute, New York, NY 10010.
Sharon GuffyDepartment of Biochemistry and Biophysics, University of North Carolina, Chapel Hill, NC 27599.
Jason W LabonteDepartment of Chemistry, Franklin & Marshall College, Lancaster, PA 17604.
Rocco MorettiCenter for Structural Biology, Department of Chemistry, Vanderbilt University, Nashville, TN 37240.
Richard BonneauCenter for Computational Biology, Flatiron Institute, New York, NY 10010.
Natalie C J StrynadkaDepartment of Biochemistry and Molecular Biology and the Centre for Blood Research, University of British Columbia, Life Sciences Centre, Vancouver, BC V6T 1Z3, Canada.
David BakerInstitute for Protein Design, Department of Biochemistry, Molecular Engineering and Sciences, University of Washington, Seattle, WA 98195.ORCID 0000-0001-7896-6217
University of Washington · USUniversity of British Columbia · CACourant Institute of Mathematical Sciences · USFlatiron Health (United States) · USJohns Hopkins University · USStanford University · USUniversity of North Carolina at Chapel Hill · USVanderbilt University · US

Funding

Technologies to predict and probe glycosyl transferR01GM127578 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI GRAY, JEFFREY J · 2018 to 2020
$1.6M
Pilatus 6mS10OD021832 · OD · UNIVERSITY OF CALIFORNIA BERKELEY · PI ADAMS, PAUL DAVID · 2016 to 2016
$980k
Computational tools for understanding chemically modified RNA structure and interactionsR21CA219847 · NCI · STANFORD UNIVERSITY · PI DAS, RHIJU · 2017 to 2018
$334k
Advancing genetic code expansion with Rosetta computational design: improving machinery for bioorthogonal amino acidsF32GM120791 · NIGMS · UNIVERSITY OF WASHINGTON · PI HOSSEINZADEH, PARISA · 2016 to 2018
$170k
Computational Modeling of MUC1 Glycoforms for the Development of Cancer TherapeutF32CA189246 · NCI · JOHNS HOPKINS UNIVERSITY · PI LABONTE, JASON WILLIAM · 2014 to 2016
$169k
CIHRHoward Hughes Medical InstituteNCI NIH HHS F32 CA189246NCI NIH HHS R21 CA219847NIGMS NIH HHS F32 GM120791NIGMS NIH HHS R01 GM127578NIH HHS S10 OD021832
6 · The paper itself

Abstract

The rise of antibiotic resistance calls for new therapeutics targeting resistance factors such as the New Delhi metallo-β-lactamase 1 (NDM-1), a bacterial enzyme that degrades β-lactam antibiotics. We present structure-guided computational methods for designing peptide macrocycles built from mixtures of l- and d-amino acids that are able to bind to and inhibit targets of therapeutic interest. Our methods explicitly consider the propensity of a peptide to favor a binding-competent conformation, which we found to predict rank order of experimentally observed IC

Indexed as

Drug DesignModels, Molecularbeta-Lactamase Inhibitorsbeta-LactamasesBinding SitesDose-Response Relationship, DrugEnzyme ActivationMolecular ConformationMolecular Docking SimulationMolecular StructurePeptidesProtein BindingStructure-Activity Relationshipbeta-Lactamase Inhibitorsbeta-lactamase NDM-1beta-LactamasesPeptidesantibiotic resistancecomputational designdrug designpeptide macrocyclesprotein folding

Identifiers

PMID33723038
PMCPMC8000195
OpenAlexW3138308373

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.