Design of Highly Potent Antibiofilm, Antimicrobial Peptides Using Explainable Artificial Intelligence.

Pikalyova, Karina et al.·Journal of chemical information and modeling·2026·
RPEP-159022026RETHINKTHC RESEARCH DATABASErethinkthc.com/research

Quick Facts

Study Type
Not classified
Evidence
Not graded
Sample
Not reported

What This Study Found

Key Numbers

How They Did This

Why This Research Matters

What This Study Doesn't Tell Us

Trust & Context

Original Title:
Design of Highly Potent Antibiofilm, Antimicrobial Peptides Using Explainable Artificial Intelligence.
Published In:
Journal of chemical information and modeling, 66(1), 744-755 (2026)
Database ID:
RPEP-15902

Evidence Hierarchy

Meta-Analysis / Systematic Review
Randomized Controlled Trial
Cohort / Case-Control
Cross-Sectional / ObservationalSnapshot without intervening
This study
Case Report / Animal Study
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Cite This Study

RPEP-15902·https://rethinkpeptides.com/research/RPEP-15902

APA

Pikalyova, Karina; Akhmetshin, Tagir; Orlov, Alexey; Haney, Evan F; Akhoundsadegh, Noushin; You, Jiaying; Hancock, Robert E W; Horvath, Dragos; Marcou, Gilles Gérard; Cherkasov, Artem; Varnek, Alexandre. (2026). Design of Highly Potent Antibiofilm, Antimicrobial Peptides Using Explainable Artificial Intelligence.. Journal of chemical information and modeling, 66(1), 744-755. https://doi.org/10.1021/acs.jcim.5c01992

MLA

Pikalyova, Karina, et al. "Design of Highly Potent Antibiofilm, Antimicrobial Peptides Using Explainable Artificial Intelligence.." Journal of chemical information and modeling, 2026. https://doi.org/10.1021/acs.jcim.5c01992

RethinkPeptides

RethinkPeptides Research Database. "Design of Highly Potent Antibiofilm, Antimicrobial Peptides ..." RPEP-15902. Retrieved from https://rethinkpeptides.com/research/pikalyova-2026-design-of-highly-potent

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Study data sourced from PubMed, a service of the U.S. National Library of Medicine, National Institutes of Health.

This study breakdown was produced by the RethinkPeptides research team. We analyze and report published research findings without making health recommendations. All interpretations are based solely on the published abstract and study data.