Evidence map›Paper›PMID 31978103›Full record

ArticlePloS one2020

Predicting antibacterial activity from snake venom proteomes.

Justin L Rheubert, Michael F Meyer, Raeshelle M Strobel, Megan A Pasternak, Robert A Charvat

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.8field-weighted citation impact, top 15% 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

4 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. 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

5 authors at 2 institutions in 1 country.

Justin L RheubertDepartment of Biology, University of Findlay, Findlay, Ohio, United States of America.ORCID 0000-0002-6354-7164
Michael F MeyerSchool of the Environment, Washington State University, Pullman, Washington, United States of America.ORCID 0000-0002-8034-9434
Raeshelle M StrobelDepartment of Biology, University of Findlay, Findlay, Ohio, United States of America.
Megan A PasternakDepartment of Biology, University of Findlay, Findlay, Ohio, United States of America.ORCID 0000-0002-1885-1490
Robert A CharvatDepartment of Biology, University of Findlay, Findlay, Ohio, United States of America.
University of Findlay · USWashington State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The continued evolution of antibiotic resistance has increased the urgency for new antibiotic development, leading to exploration of non-traditional sources. In particular, snake venom has garnered attention for its potent antibacterial properties. Numerous studies describing snake venom proteomic composition as well as antibiotic efficacy have created an opportunity to synthesize relationships between venom proteomes and their antibacterial properties. Using literature reported values from peer-reviewed studies, our study generated models to predict efficacy given venom protein family composition, snake taxonomic family, bacterial Gram stain, bacterial morphology, and bacterial respiration strategy. We then applied our predictive models to untested snake species with known venom proteomic compositions. Overall, our results provide potential protein families that serve as accurate predictors of efficacy as well as promising organisms in terms of antibacterial properties of venom. The results from this study suggest potential future research trajectories for antibacterial properties in snake venom by offering hypotheses for a variety of taxa.

Indexed as

AnimalsAnti-Bacterial AgentsAntiveninsBacteriaProteomeSnakesSnake VenomsAnti-Bacterial AgentsAntiveninsProteomeSnake Venoms

Identifiers

PMID31978103
PMCPMC6980403
OpenAlexW3001828056

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.