Evidence map›Paper›PMID 31699898›Full record

ReviewThe Journal of biological chemistry2019

Designing protein structures and complexes with the molecular modeling program Rosetta.

Brian Kuhlman

Open access · hybridAbstract readReview
In one paragraph

Review in The Journal of biological chemistry, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
5.5field-weighted citation impact, top 5% 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

22 citing papers in PubMed, 36 citations in OpenAlex.

  1. Multifaceted and evolutionarily dynamic interactions betweenbioRxiv : the preprint server for biology · 2026
    Article
  2. Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. How to Design Peptides.Methods in molecular biology (Clifton, N.J.) · 2023
    Article
  14. Molecular Dynamics Methods for Antibody Design.Methods in molecular biology (Clifton, N.J.) · 2023
    Article
  15. Article
  16. Article
  17. Knowledge-Based Unfolded State Model for Protein Design.Methods in molecular biology (Clifton, N.J.) · 2022
    Article
  18. Review
  19. Target-templatedChemical science · 2021
    Article
  20. An enumerative algorithm for de novo design of proteins with diverse pocket structures.Proceedings of the National Academy of Sciences of the United States of America · 2020
    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

1 author at 1 institution in 1 country.

Brian KuhlmanDepartment of Biochemistry and Biophysics, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina 27599-7260 bkuhlman@email.unc.edu.ORCID 0000-0003-4907-9699
University of North Carolina at Chapel Hill · US

Funding

GPU workstation for deep learning-based protein design and cryo-EM data processingR35GM131923 · NIGMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BRIAN A KUHLMAN · 2019 to 2026
$6.1M
NIGMS NIH HHS R35 GM131923
6 · The paper itself

Abstract

Proteins perform an amazingly diverse set of functions in all aspects of life. Critical to the function of many proteins are the highly specific three-dimensional structures they adopt. For this reason, there is strong interest in learning how to rationally design proteins that adopt user-defined structures. Over the last 25 years, there has been significant progress in the field of computational protein design as rotamer-based sequence optimization protocols have enabled accurate design of protein tertiary and quaternary structure. In this award article, I will summarize how the molecular modeling program Rosetta is used to design new protein structures and describe how we have taken advantage of this capability to create proteins that have important applications in research and medicine. I will highlight three protein design stories: the use of protein interface design to create therapeutic bispecific antibodies, the engineering of light-inducible proteins that can be used to recruit proteins to specific locations in the cell, and the

Indexed as

Computational BiologyModels, MolecularSoftwareProtein ConformationProtein EngineeringProteinsProteinsantibody engineeringbispecific antibodycomputational biologycomputational protein designde novo protein designMonte Carlo samplingoptogeneticsphotoswitchprotein designprotein-protein interfaceprotein stabilityRosettasequence optimization

Identifiers

PMID31699898
PMCPMC6916497
OpenAlexW2987982852

What OpenQuestion holds

Textmetadata
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.