Evidence map›Paper›PMID 33129066›Full record

ReviewCurrent opinion in structural biology2021

The role of local versus nonlocal physicochemical restraints in determining protein native structure.

Jeffrey Skolnick, Mu Gao

Abstract readReview
In one paragraph

Review in Current opinion in structural biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. High-Performance Deep Learning Toolbox for Genome-Scale Prediction of Protein Structure and Function.Workshop on Machine Learning in HPC Environments. Workshop on Machine Learning in HPC Environments · 2021
    Article
  8. Article
  9. 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.

Jeffrey SkolnickCenter for the Study of Systems Biology, School of Biological Sciences, Georgia Institute of Technology, 950 Atlantic Drive, NW, Atlanta, GA 30332, United States. Electronic address: skolnick@gatech.edu.
Mu GaoCenter for the Study of Systems Biology, School of Biological Sciences, Georgia Institute of Technology, 950 Atlantic Drive, NW, Atlanta, GA 30332, United States. Electronic address: mu.gao@gatech.edu.

Funding

Purchase of a GPU cluster for deep learning applications in protein-protein interaction and supercomplex prediction and biochemical literature annotation.R35GM118039 · NIGMS · GEORGIA INSTITUTE OF TECHNOLOGY · PI JEFFREY SKOLNICK · 2016 to 2026
$5.8M
NIGMS NIH HHS R35 GM118039
6 · The paper itself

Abstract

The tertiary structure of a native protein is dictated by the interplay of local secondary structure propensities, hydrogen bonding, and tertiary interactions. It is argued that the space of known protein topologies covers all single domain folds and results from the compactness of the native structure and excluded volume. Protein compactness combined with the chirality of the protein's side chains also yields native-like Ramachandran plots. It is the many-body, tertiary interactions among residues that collectively select for the global structure that a particular protein sequence adopts. This explains why the recent advances in deep-learning approaches that predict protein side-chain contacts, the distance matrix between residues, and sequence alignments are successful. They succeed because they implicitly learned the many-body interactions among protein residues.

Indexed as

Protein FoldingProteinsModels, MolecularProtein Structure, SecondaryProtein Structure, TertiarySequence AlignmentProteins

Identifiers

PMID33129066
PMCPMC8079554

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.