Evidence map›Paper›PMID 36512534›Full record

ArticlePloS one2022

Rosetta FlexPepDock to predict peptide-MHC binding: An approach for non-canonical amino acids.

Nathaniel Bloodworth, Natália Ruggeri Barbaro, Rocco Moretti, David G Harrison, Jens Meiler

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.8field-weighted citation impact, top 14% 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

9 citing papers in PubMed, 21 citations in OpenAlex.

  1. Article
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  6. AbAMPdb: a database of Acinetobacter baumannii specific antimicrobial peptides.Database : the journal of biological databases and curation · 2024
    Article
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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

5 authors at 2 institutions in 2 countries.

Nathaniel BloodworthDivision of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America.ORCID 0000-0002-5758-003X
Natália Ruggeri BarbaroDepartment of Chemistry and Center for Structural Biology, Vanderbilt University, Nashville, Tennessee, United States of America.
Rocco MorettiDepartment of Chemistry and Center for Structural Biology, Vanderbilt University, Nashville, Tennessee, United States of America.
David G HarrisonDivision of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America.
Jens MeilerDepartment of Chemistry and Center for Structural Biology, Vanderbilt University, Nashville, Tennessee, United States of America.ORCID 0000-0001-8945-193X
Vanderbilt University · USVanderbilt University Medical Center · US

Funding

Mechanisms of Immune Activation in HypertensionR35HL140016 · NHLBI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI HARRISON, DAVID G · 2018 to 2024
$5.3M
Structural Determinants of Allosteric Modulation of Brain GPCRsR01DA046138 · NIDA · VANDERBILT UNIVERSITY · PI MEILER, JENS · 2019 to 2023
$2.0M
Vanderbilt Hypertension and Blood Pressure Regulation ProgramT32HL144446 · NHLBI · VANDERBILT UNIVERSITY · PI HARRISON, DAVID G · 2019 to 2023
$1.7M
NHLBI NIH HHS R35 HL140016NHLBI NIH HHS T32 HL144446NIDA NIH HHS R01 DA046138
6 · The paper itself

Abstract

Computation methods that predict the binding of peptides to MHC-I are important tools for screening and identifying immunogenic antigens and have the potential to accelerate vaccine and drug development. However, most available tools are sequence-based and optimized only for peptides containing the twenty canonical amino acids. This omits a large number of peptides containing non-canonical amino acids (NCAA), or residues that undergo varied post-translational modifications such as glycosylation or phosphorylation. These modifications fundamentally alter peptide immunogenicity. Similarly, existing structure-based methods are biased towards canonical peptide backbone structures, which may or may not be preserved when NCAAs are present. Rosetta FlexPepDock ab-initio is a structure-based computational protocol able to evaluate peptide-receptor interaction where no prior information of the peptide backbone is known. We benchmarked FlexPepDock ab-initio for docking canonical peptides to MHC-I, and illustrate for the first time the method's ability to accurately model MHC-I bound epitopes containing NCAAs. FlexPepDock ab-initio protocol was able to recapitulate near-native structures (≤1.5Å) in the top lowest-energy models for 20 out of 25 cases in our initial benchmark. Using known experimental binding affinities of twenty peptides derived from an influenza-derived peptide, we showed that FlexPepDock protocol is able to predict relative binding affinity as Rosetta energies correlate well with experimental values (r = 0.59, p = 0.006). ROC analysis revealed 80% true positive and a 40% false positive rate, with a prediction power of 93%. Finally, we demonstrate the protocol's ability to accurately recapitulate HLA-A*02:01 bound phosphopeptide backbone structures and relative binding affinity changes, the theoretical structure of the lymphocytic choriomeningitis derived glycosylated peptide GP392 bound to MHC-I H-2Db, and isolevuglandin-adducted peptides. The ability to use non-canonical amino acids in the Rosetta FlexPepDock protocol may provide useful insight into critical amino acid positions where the post-translational modification modulates immunologic responses.

Indexed as

Amino AcidsPeptidesProtein BindingAmino AcidsPeptides

Identifiers

PMID36512534
PMCPMC9746977
OpenAlexW4311328158

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.