Evidence map›Paper›PMID 41711565›Full record

ArticleCurrent protocols2026

AMPSeek: A Workflow for Predicting Antimicrobial Peptide Activity, Three-Dimensional Structure, and Toxicity.

Emily Zhang, Berke Ucar, Ali Salehi, René L Warren, Inanc Birol

Abstract read
In one paragraph

Article in Current protocols, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Emily ZhangBC Cancer, Vancouver, BC, Canada.ORCID https://orcid.org/0009-0007-7609-8971
Berke UcarBC Cancer, Vancouver, BC, Canada.
Ali SalehiBC Cancer, Vancouver, BC, Canada.
René L WarrenBC Cancer, Vancouver, BC, Canada.
Inanc BirolBC Cancer, Vancouver, BC, Canada.

Funding

Genome Canada 291PEPMichael Smith Health Research BC-Mitacs Industry-Based Opportunity funding IT44733Mitacs Accelerate Program IT43363
6 · The paper itself

Abstract

With antimicrobial resistance emerging as a top global health concern, new approaches to prevent and treat infections are urgently needed. Antimicrobial peptides are recognized as a promising alternative to conventional antibiotics. Considering the costly, labor-intensive, and time-consuming nature of wet lab screening, in recent years, proteomics research has increasingly relied on in silico methods to predict physicochemical, structural, and biological properties of candidate peptides. Here, we present the AMPSeek protocol to enable scientists to screen peptides and predict their potential antimicrobial activity, toxicity, and associated three-dimensional structure with a single command. The AMPSeek framework integrates AMPlify, tAMPer, and LocalColabFold, scales efficiently with increasing sample size, and produces an interactive HyperText Markup Language report to facilitate result interpretation. We provide step-by-step instructions for installing and running AMPSeek on a ten-peptide test set, along with two additional datasets (n = 20 and n = 100; mean peptide length ≈121.3) to demonstrate AMPSeek's near-linear scalability. AMPSeek is available on GitHub under the GPLv3 software license agreement: https://github.com/bcgsc/AMPSeek. © 2026 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol: Prediction of antimicrobial peptide activity, three-dimensional structure, and toxicity.

Indexed as

Anti-Infective AgentsAntimicrobial PeptidesSoftwareHumansPrediction AlgorithmsWorkflowAnti-Infective AgentsAntimicrobial Peptidesantimicrobial activityantimicrobial peptidesdrug toxicitymachine learning

Identifiers

PMID41711565
PMCPMC12919377

What Socratic 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 Socratic graph.