Evidence map›Paper›PMID 36656852›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2023

De novo protein fold design through sequence-independent fragment assembly simulations.

Robin Pearce, Xiaoqiang Huang, Gilbert S Omenn, Yang Zhang

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2023. 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. Review
  2. Review
  3. Article
  4. Article
  5. Article
  6. Review
  7. Sticking to the Subject: Multifunctionality in Microbial Adhesins.Journal of fungi (Basel, Switzerland) · 2023
    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.

Robin PearceDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109.ORCID 0000-0001-6402-734X
Xiaoqiang HuangDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109.ORCID 0000-0002-1005-848X
Gilbert S OmennDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109.ORCID 0000-0002-8976-6074
Yang ZhangDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109.ORCID 0000-0002-2739-1916

Funding

Strategic Vision & Impact on Environmental HealthP30ES017885 · NIEHS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Dana Dolinoy · 2011 to 2026
$21.3M
Structure-based functional annotation of microbial genomesR01AI134678 · NIAID · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Lydia Petra Freddolino, SCOTT J. HULTGREN · 2018 to 2026
$6.5M
University of Michigan Proteogenomics Data Analysis CenterU24CA210967 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI CHINNAIYAN, ARUL M, DHANASEKARAN, SARAVANA M · 2016 to 2020
$4.1M
Proteogenomics of Cancer Training ProgramT32CA140044 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI RAO, ARVIND, SARTOR, MAUREEN AGNES · 2010 to 2024
$3.9M
Advanced approaches to protein structure predictionR35GM136422 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ZHANG, YANG · 2020 to 2021
$946k
High-Performance Computing Cluster for Biomedical ResearchS10OD026825 · OD · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ATHEY, BRIAN DAVID · 2020 to 2020
$600k
NCI NIH HHS T32 CA140044NCI NIH HHS U24 CA210967NIAID NIH HHS R01 AI134678NIEHS NIH HHS P30 ES017885NIGMS NIH HHS R35 GM136422NIH HHS S10 OD026825
6 · The paper itself

Abstract

De novo protein design generally consists of two steps, including structure and sequence design. Many protein design studies have focused on sequence design with scaffolds adapted from native structures in the PDB, which renders novel areas of protein structure and function space unexplored. We developed FoldDesign to create novel protein folds from specific secondary structure (SS) assignments through sequence-independent replica-exchange Monte Carlo (REMC) simulations. The method was tested on 354 non-redundant topologies, where FoldDesign consistently created stable structural folds, while recapitulating on average 87.7% of the SS elements. Meanwhile, the FoldDesign scaffolds had well-formed structures with buried residues and solvent-exposed areas closely matching their native counterparts. Despite the high fidelity to the input SS restraints and local structural characteristics of native proteins, a large portion of the designed scaffolds possessed global folds completely different from natural proteins in the PDB, highlighting the ability of FoldDesign to explore novel areas of protein fold space. Detailed data analyses revealed that the major contributions to the successful structure design lay in the optimal energy force field, which contains a balanced set of SS packing terms, and REMC simulations, which were coupled with multiple auxiliary movements to efficiently search the conformational space. Additionally, the ability to recognize and assemble uncommon super-SS geometries, rather than the unique arrangement of common SS motifs, was the key to generating novel folds. These results demonstrate a strong potential to explore both structural and functional spaces through computational design simulations that natural proteins have not reached through evolution.

Indexed as

Protein FoldingProteinsMonte Carlo MethodProtein ConformationProtein Structure, SecondaryProteinsde novo protein designnovel fold of proteinreplica-exchange Monte Carlo simulationstructural designstructural motif

Identifiers

PMID36656852
PMCPMC9942881

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.