Evidence map›Paper›PMID 28966980›Full record

ArticleACS biomaterials science & engineering2017

Predicting Silk Fiber Mechanical Properties through Multiscale Simulation and Protein Design.

Nae-Gyune Rim, Erin G Roberts, Davoud Ebrahimi, Nina Dinjaski, Matthew M Jacobsen, Zaira Martín-Moldes, Markus J Buehler, David L Kaplan, Joyce Y Wong

Abstract read
In one paragraph

Article in ACS biomaterials science & engineering, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Review
  2. Article
  3. Recombinant fibrous protein biomaterials meet skin tissue engineering.Frontiers in bioengineering and biotechnology · 2024
    Review
  4. Article
  5. Article
  6. Review
  7. Article
  8. Review
  9. Review
  10. Article
  11. 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

9 authors.

Nae-Gyune RimDepartment of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston, Massachusetts 02215, United States.
Erin G RobertsDivision of Materials Science and Engineering, Boston University, 44 Cummington Mall, Boston, Massachusetts 02215, United States.
Davoud EbrahimiDepartment of Civil and Environmental Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States.
Nina DinjaskiDepartment of Civil and Environmental Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States.
Matthew M JacobsenDepartment of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston, Massachusetts 02215, United States.
Zaira Martín-MoldesDepartment of Biomedical Engineering, Tufts University, 4 Colby Street, Medford, Massachusetts 02155, United States.
Markus J BuehlerDepartment of Civil and Environmental Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States.
David L KaplanDepartment of Biomedical Engineering, Tufts University, 4 Colby Street, Medford, Massachusetts 02155, United States.
Joyce Y WongDepartment of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston, Massachusetts 02215, United States.

Funding

Models to Predict Protein Biomaterial PerformanceU01EB014976 · NIBIB · TUFTS UNIVERSITY MEDFORD · PI BUEHLER, MARKUS J., KAPLAN, DAVID L. · 2012 to 2020
$5.2M
NIBIB NIH HHS U01 EB014976
6 · The paper itself

Abstract

Silk is a promising material for biomedical applications, and much research is focused on how application-specific, mechanical properties of silk can be designed synthetically through proper amino acid sequences and processing parameters. This protocol describes an iterative process between research disciplines that combines simulation, genetic synthesis, and fiber analysis to better design silk fibers with specific mechanical properties. Computational methods are used to assess the protein polymer structure as it forms an interconnected fiber network through shearing and how this process affects fiber mechanical properties. Model outcomes are validated experimentally with the genetic design of protein polymers that match the simulation structures, fiber fabrication from these polymers, and mechanical testing of these fibers. Through iterative feedback between computation, genetic synthesis, and fiber mechanical testing, this protocol will enable a priori prediction capability of recombinant material mechanical properties via insights from the resulting molecular architecture of the fiber network based entirely on the initial protein monomer composition. This style of protocol may be applied to other fields where a research team seeks to design a biomaterial with biomedical application-specific properties. This protocol highlights when and how the three research groups (simulation, synthesis, and engineering) should be interacting to arrive at the most effective method for predictive design of their material.

Indexed as

computational modelinggenetic synthesisrecombinant silkspinning

Identifiers

PMID28966980
PMCPMC5617357

What OpenQuestion holds

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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.