Evidence map›Paper›PMID 37066177›Full record

ArticlebioRxiv : the preprint server for biology2023

Epistasis meets pleiotropy in shaping biophysical protein subspaces associated with antimicrobial resistance.

C Brandon Ogbunugafor, Rafael F Guerrero, Eugene I Shakhnovich, Matthew D Shoulders

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

C Brandon OgbunugaforDepartment of Ecology and Evolutionary Biology, Yale University, New Haven, CT.
Rafael F GuerreroDepartment of Biological Sciences, North Carolina State University, Raleigh, NC.
Eugene I ShakhnovichDepartment of Chemistry and Chemical Biology, Harvard University, Cambridge MA.
Matthew D ShouldersDepartment of Chemistry, Massachusetts Institute of Technology, Cambridge, MA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Protein space is a rich analogy for genotype-phenotype maps, where amino acid sequence is organized into a high-dimensional space that highlights the connectivity between protein variants. It is a useful abstraction for understanding the process of evolution, and for efforts to engineer proteins towards desirable phenotypes. Few framings of protein space consider how higher-level protein phenotypes can be described in terms of their biophysical dimensions, nor do they rigorously interrogate how forces like epistasis-describing the nonlinear interaction between mutations and their phenotypic consequences-manifest across these dimensions. In this study, we deconstruct a low-dimensional protein space of a bacterial enzyme (dihydrofolate reductase; DHFR) into "subspaces" corresponding to a set of kinetic and thermodynamic traits [(

Indexed as

antimicrobial resistancebiophysicsepistasisfitness landscapepleiotropyprotein space

Identifiers

PMID37066177
PMCPMC10104174

What OpenQuestion holds

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Registered trials

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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.