Evidence map›Paper›PMID 27914055›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2017

An Evolution-Based Approach to De Novo Protein Design.

Jeffrey R Brender, David Shultis, Naureen Aslam Khattak, Yang Zhang

Abstract read
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Multiobjective heuristic algorithm forComputational and structural biotechnology journal · 2021
    Article
  4. Article
  5. Article
  6. A general-purpose protein design framework based on mining sequence-structure relationships in known protein structures.Proceedings of the National Academy of Sciences of the United States of America · 2020
    Article
  7. Review
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

4 authors.

Jeffrey R BrenderDepartment of Computational Medicine and Bioinformatics, University of Michigan, 100 Washtenaw Avenue, Ann Arbor, MI, 48109-2218, USA.
David ShultisDepartment of Computational Medicine and Bioinformatics, University of Michigan, 100 Washtenaw Avenue, Ann Arbor, MI, 48109-2218, USA.
Naureen Aslam KhattakDepartment of Computational Medicine and Bioinformatics, University of Michigan, 100 Washtenaw Avenue, Ann Arbor, MI, 48109-2218, USA.
Yang ZhangDepartment of Computational Medicine and Bioinformatics, University of Michigan, 100 Washtenaw Avenue, Ann Arbor, MI, 48109-2218, USA. zhng@umich.edu.

Funding

I-TASSER based atomic-level protein structure predictionR01GM083107 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ZHANG, YANG · 2008 to 2019
$3.5M
Template-based docking refinement approach to protein-protein structure modelingR01GM116960 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ZHANG, YANG · 2016 to 2019
$1.4M
NIGMS NIH HHS R01 GM083107NIGMS NIH HHS R01 GM116960
6 · The paper itself

Abstract

EvoDesign is a computational algorithm that allows the rapid creation of new protein sequences that are compatible with specific protein structures. As such, it can be used to optimize protein stability, to resculpt the protein surface to eliminate undesired protein-protein interactions, and to optimize protein-protein binding. A major distinguishing feature of EvoDesign in comparison to other protein design programs is the use of evolutionary information in the design process to guide the sequence search toward native-like sequences known to adopt structurally similar folds as the target. The observed frequencies of amino acids in specific positions in the structure in the form of structural profiles collected from proteins with similar folds and complexes with similar interfaces can implicitly capture many subtle effects that are essential for correct folding and protein-binding interactions. As a result of the inclusion of evolutionary information, the sequences designed by EvoDesign have native-like folding and binding properties not seen by other physics-based design methods. In this chapter, we describe how EvoDesign can be used to redesign proteins with a focus on the computational and experimental procedures that can be used to validate the designs.

Indexed as

Models, MolecularProteinsSoftwareAlgorithmsAmino Acid SequenceComputer SimulationDatabases, ProteinEvolution, MolecularMolecular Docking SimulationMolecular Dynamics SimulationProtein BindingProtein ConformationProtein EngineeringProtein FoldingReproducibility of ResultsSolubilityProteinsCircular dichroismEvolutionary profileExperimental protein validationNuclear magnetic resonanceProtein designProtein structure modelingRecombinant expression

Identifiers

PMID27914055
PMCPMC5667548

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.