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Related Experiment Video

Updated: Jul 23, 2026

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions
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AMPSeek: A Workflow for Predicting Antimicrobial Peptide Activity, Three-Dimensional Structure, and Toxicity.

Emily Zhang1, Berke Ucar1, Ali Salehi1

  • 1BC Cancer, Vancouver, BC, Canada.

Current Protocols
|February 19, 2026
PubMed
Summary

Antimicrobial peptides offer a promising alternative to antibiotics. The new AMPSeek protocol uses in silico methods to efficiently predict antimicrobial activity, toxicity, and structure, accelerating drug discovery.

Keywords:
antimicrobial activityantimicrobial peptidesdrug toxicitymachine learning

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Production and Testing of Antimicrobial Peptides and Their Mimics
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Published on: April 10, 2026

Area of Science:

  • Computational Biology
  • Drug Discovery
  • Proteomics

Background:

  • Antimicrobial resistance (AMR) is a critical global health threat, necessitating novel therapeutic strategies.
  • Antimicrobial peptides (AMPs) show potential as alternatives to conventional antibiotics.
  • Traditional wet lab screening for AMPs is resource-intensive; in silico methods are increasingly vital for peptide property prediction.

Purpose of the Study:

  • To introduce AMPSeek, a novel computational protocol for screening peptides.
  • To predict antimicrobial activity, toxicity, and three-dimensional structure of candidate peptides using a single command.
  • To provide a scalable and efficient in silico tool for accelerating the discovery of antimicrobial peptides.

Main Methods:

  • Development of the AMPSeek framework, integrating AMPlify, tAMPer, and LocalColabFold.
  • Implementation of a streamlined protocol for predicting peptide physicochemical, structural, and biological properties.
  • Testing and validation using datasets of varying sizes (n=10, 20, and 100) to demonstrate scalability.

Main Results:

  • AMPSeek enables rapid prediction of antimicrobial activity, toxicity, and 3D structure.
  • The protocol demonstrates near-linear scalability with increasing sample size.
  • An interactive HTML report is generated for user-friendly interpretation of results.

Conclusions:

  • AMPSeek provides an efficient and scalable in silico solution for identifying potential antimicrobial peptides.
  • This protocol facilitates faster drug discovery by reducing reliance on costly and time-consuming experimental screening.
  • AMPSeek is publicly available on GitHub, promoting wider adoption in antimicrobial research.