Evidence map›Paper›PMID 34170981›Full record

ArticleNature machine intelligence2020

A topology-based network tree for the prediction of protein-protein binding affinity changes following mutation.

Menglun Wang, Zixuan Cang, Guo-Wei Wei

Open access · bronzeAbstract read
In one paragraph

Article in Nature machine intelligence, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 124 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
124citing papers in PubMed, 1 pooled it
17.5field-weighted citation impact, top 1% 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

124 citing papers in PubMed, 1 synthesis or guideline pooled it, 214 citations in OpenAlex.

  1. Pooled it
  2. Article
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  12. Article
  13. Predicting Protein-Protein Interactions from Machine-Learned Representations.Advances in experimental medicine and biology · 2026
    Review
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

64 more citing papers are in PubMed but not listed here.

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

3 authors at 1 institution in 1 country.

Menglun WangDepartment of Mathematics, Michigan State University, East Lansing, MI USA.
Zixuan CangDepartment of Mathematics, Michigan State University, East Lansing, MI USA.ORCID 0000-0002-9951-5586
Guo-Wei WeiDepartment of Mathematics, Michigan State University, East Lansing, MI USA.ORCID 0000-0001-8132-5998
Michigan State University · US

Funding

Synergistic integration of topology and machine learning for the predictions of protein-ligand binding affinities and mutation impactsR01GM126189 · NIGMS · MICHIGAN STATE UNIVERSITY · PI WEI, GUOWEI · 2018 to 2021
$1.4M
NIGMS NIH HHS R01 GM126189
6 · The paper itself

Abstract

The ability to predict protein-protein interactions is crucial to our understanding of a wide range of biological activities and functions in the human body, and for guiding drug discovery. Despite considerable efforts to develop suitable computational methods, predicting protein-protein interaction binding affinity changes following mutation (ΔΔ

Indexed as

BiophysicsComputational biology and bioinformaticsMathematics and computingProtein function predictions

Identifiers

PMID34170981
PMCPMC7223817
OpenAlexW3005822506

What OpenQuestion holds

Textmetadata
LicenceTDM
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.