Evidence map›Paper›PMID 40460077›Full record

ArticlePloS one2025

Discovery of novel targets for important human and plant fungal pathogens via an automated computational pipeline HitList.

David E Condon, Brenda K Schroeder, Paul A Rowley, F Marty Ytreberg

Erratum issuedAbstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Computational Approaches for Discovering Virulence Factors inJournal of fungi (Basel, Switzerland) · 2025
    Review
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

David E CondonInstitute for Modeling Collaboration and Innovation, University of Idaho, Moscow, Idaho, United States of America.
Brenda K SchroederInstitute for Modeling Collaboration and Innovation, University of Idaho, Moscow, Idaho, United States of America.
Paul A RowleyInstitute for Modeling Collaboration and Innovation, University of Idaho, Moscow, Idaho, United States of America.
F Marty YtrebergInstitute for Modeling Collaboration and Innovation, University of Idaho, Moscow, Idaho, United States of America.ORCID https://orcid.org/0000-0001-7439-8224

Funding

Sequence-structure-function relationships in human visual photopigmentsP20GM104420 · NIGMS · UNIVERSITY OF IDAHO · PI MILLER, CRAIG R · 2015 to 2024
$22.9M
NIGMS NIH HHS P20 GM104420
6 · The paper itself

Abstract

Fungi are a major threat to human health and agricultural productivity, causing 1.7 million human deaths and billions of dollars in crop losses and spoilage annually. While various antifungal compounds have been developed to combat these fungi in medical and agricultural settings, there are concerns that effectiveness is waning due to the emergence of acquired drug resistance and novel pathogens. Effectiveness is further hampered due to the limited number of modes of action for available antifungal compounds. To develop new strategies for the control and mitigation of fungal disease and spoilage, new antifungals are needed with novel fungal-specific protein targets that can overcome resistance, prevent host toxicity, and can target fungi that have no effective control measures. The increasing availability of complete genomes of pathogenic and spoilage fungi has enabled identification of novel protein targets essential for viability and not found in host plants or humans. In this study, an automated bioinformatics pipeline utilizing BLAST, Clustal [Formula: see text], and subtractive genomics was created and used to identify potential new targets for any combination of hosts and pathogens with available genomic or proteomic data. This pipeline called HitList allows in silico screening of thousands of possible targets. HitList was then used to generate a list of potential antifungal targets for the World Health Organization fungal priority pathogens list and the top 10 agricultural fungal pathogens. Known antifungal targets were found, validating the approach, and an additional eight novel protein targets were discovered that could be used for the rational design of antifungal compounds.

Indexed as

Antifungal AgentsComputational BiologyFungal ProteinsFungiDrug DiscoveryHumansPlant DiseasesAntifungal AgentsFungal Proteins

Identifiers

PMID40460077
PMCPMC12132981

What OpenQuestion holds

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LicenceCC BY
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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.