Evidence map›Paper›PMID 30676995›Full record

ReviewBiological chemistry2019

Computational design of structured loops for new protein functions.

Kale Kundert, Tanja Kortemme

Abstract readReview
In one paragraph

Review in Biological chemistry, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
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

19 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. bioRxiv : the preprint server for biology · 2023
    Article
  7. Review
  8. Accurate positioning of functional residues with robotics-inspired computational protein design.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  9. Extension of a de novo TIM barrel with a rationally designed secondary structure element.Protein science : a publication of the Protein Society · 2021
    Article
  10. Article
  11. Article
  12. Review
  13. Current approaches to flexible loop modeling.Current research in structural biology · 2021
    Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Advances in protein structure prediction and design.Nature reviews. Molecular cell biology · 2019
    Review
  19. 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

2 authors.

Kale KundertGraduate Group in Biophysics, University of California San Francisco, San Francisco, CA 94158, USA.
Tanja KortemmeGraduate Group in Biophysics, University of California San Francisco, San Francisco, CA 94158, USA.

Funding

Computational design of protein-based small-molecule biosensorsR01GM110089 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KORTEMME, TANJA · 2015 to 2022
$2.3M
NIGMS NIH HHS R01 GM110089
6 · The paper itself

Abstract

The ability to engineer the precise geometries, fine-tuned energetics and subtle dynamics that are characteristic of functional proteins is a major unsolved challenge in the field of computational protein design. In natural proteins, functional sites exhibiting these properties often feature structured loops. However, unlike the elements of secondary structures that comprise idealized protein folds, structured loops have been difficult to design computationally. Addressing this shortcoming in a general way is a necessary first step towards the routine design of protein function. In this perspective, we will describe the progress that has been made on this problem and discuss how recent advances in the field of loop structure prediction can be harnessed and applied to the inverse problem of computational loop design.

Indexed as

Computational BiologyProteinsModels, MolecularProtein ConformationProteinsbinding site designloop modelingpositioning functional residuesprotein designRosetta software

Identifiers

PMID30676995
PMCPMC6530579

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Registered trials

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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.