Evidence map›Paper›PMID 33393786›Full record

ArticleJournal of proteome research2021

Functions of Essential Genes and a Scale-Free Protein Interaction Network Revealed by Structure-Based Function and Interaction Prediction for a Minimal Genome.

Chengxin Zhang, Wei Zheng, Micah Cheng, Gilbert S Omenn, Peter L Freddolino, Yang Zhang

Open access · greenAbstract read
In one paragraph

Article in Journal of proteome research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.0field-weighted citation impact, top 13% 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

17 citing papers in PubMed, 26 citations in OpenAlex.

  1. Article
  2. Whole-proteome structure/function prediction in UropathogenicbioRxiv : the preprint server for biology · 2026
    Article
  3. Design biology and mind-body health.Journal, genetic engineering & biotechnology · 2025
    Review
  4. Improving the Annotations of JCVI-Syn3a Proteins.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  5. Recent Progress of Protein Tertiary Structure Prediction.Molecules (Basel, Switzerland) · 2024
    Review
  6. Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Review
  13. Protein-protein interaction prediction with deep learning: A comprehensive review.Computational and structural biotechnology journal · 2022
    Review
  14. Article
  15. Article
  16. Toward the solution of the protein structure prediction problem.The Journal of biological chemistry · 2021
    Review
  17. 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

6 authors at 1 institution in 1 country.

Chengxin ZhangDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, United States.ORCID 0000-0001-7290-1324
Wei ZhengDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, United States.ORCID 0000-0002-2984-9003
Micah ChengDepartment of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, Michigan 48109, United States.ORCID 0000-0002-2086-5752
Gilbert S OmennDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, United States.ORCID 0000-0002-8976-6074
Peter L FreddolinoDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, United States.ORCID 0000-0002-5821-4226
Yang ZhangDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, United States.ORCID 0000-0002-2739-1916
University of Michigan · US

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
Building a unified framework for understanding bacterial gene regulation and chromosomal architectureR35GM128637 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Lydia Petra Freddolino · 2018 to 2026
$3.6M
I-TASSER based atomic-level protein structure predictionR01GM083107 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ZHANG, YANG · 2008 to 2019
$3.5M
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 U24 CA210967NIAID NIH HHS R01 AI134678NIEHS NIH HHS P30 ES017885NIGMS NIH HHS R01 GM083107NIGMS NIH HHS R35 GM128637NIGMS NIH HHS R35 GM136422NIH HHS S10 OD026825
6 · The paper itself

Abstract

When the JCVI-syn3.0 genome was designed and implemented in 2016 as the minimal genome of a free-living organism, approximately one-third of the 438 protein-coding genes had no known function. Subsequent refinement into JCVI-syn3A led to inclusion of 16 additional protein-coding genes, including several unknown functions, resulting in an improved growth phenotype. Here, we seek to unveil the biological roles and protein-protein interaction (PPI) networks for these poorly characterized proteins using state-of-the-art deep learning contact-assisted structure prediction, followed by structure-based annotation of functions and PPI predictions. Our pipeline is able to confidently assign functions for many previously unannotated proteins such as putative vitamin transporters, which suggest the importance of nutrient uptake even in a minimized genome. Remarkably, despite the artificial selection of genes in the minimal syn3 genome, our reconstructed PPI network still shows a power law distribution of node degrees typical of naturally evolved bacterial PPI networks. Making use of our framework for combined structure/function/interaction modeling, we are able to identify both fundamental aspects of network biology that are retained in a minimal proteome and additional essential functions not yet recognized among the poorly annotated components of the syn3.0 and syn3A proteomes.

Indexed as

Genes, EssentialProtein Interaction MapsComputational BiologyProteomeProteomecomputational function annotationdeep learningessential proteinsJCVI-syn3.0 minimal genomeJCVI-syn3Aprotein−protein interactionstructure prediction

Identifiers

PMID33393786
PMCPMC7867644
OpenAlexW3119833134

What OpenQuestion holds

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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.