Evidence map›Paper›PMID 42883645›Full record

ReviewFoods (Basel, Switzerland)2026

Designer Enzymes: Food-System-Oriented Biocatalysts for Mitigating Mycotoxin Contamination and Reducing Postharvest Grain Loss.

Yiyang Zhang, Miao Long

Abstract readReview
In one paragraph

Review in Foods (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Yiyang ZhangKey Laboratory of Livestock Infectious Diseases, Ministry of Education, College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, 120 Dongling Road, Shenyang 110866, China.
Miao LongKey Laboratory of Livestock Infectious Diseases, Ministry of Education, College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, 120 Dongling Road, Shenyang 110866, China.ORCID 0000-0001-6683-1956

Funding

National Natural Science Foundation of China grant no. 32273074, grant no. 31972746, grant no. 31772809
6 · The paper itself

Abstract

Mycotoxin contamination remains a major challenge to food and feed safety, agricultural productivity, and postharvest resource utilization. Although numerous mycotoxin-transforming enzymes have been discovered and increasingly improved through protein engineering, only a limited number have progressed from laboratory characterization to practical food or feed applications. This translational gap arises because catalytic efficiency alone does not address matrix interference, processing stress, scalable production, formulation, degradation-product safety, and application-specific regulatory requirements. This review critically examines the development of enzyme-based detoxification across major mycotoxin classes, including aflatoxins, deoxynivalenol and related trichothecenes, zearalenone, ochratoxin A, and fumonisins, while explicitly distinguishing the deployment requirements of food and feed systems. Building on evidence from natural enzymes, engineered variants, matrix studies, animal evaluations, and commercially advanced systems, we use the term "Designer Enzymes" to describe a literature-derived, deployment-oriented engineering concept in which intended-use conditions are defined before optimization and used to guide molecular, manufacturing, formulation, safety, and regulatory decisions. A five-dimensional framework encompassing Mechanistic Understanding, Predictive Design Integration, Multi-Objective Optimization, Deployment Readiness, and Safety and Regulatory Preparedness is used as a qualitative diagnostic tool to identify translational bottlenecks rather than as a formally validated numerical scoring system. Representative systems targeting ZEN, DON, AFB1, OTA, and fumonisins are compared to illustrate their contrasting trajectories from mechanistic discovery to practical deployment. Structure-guided engineering, AI-assisted mutation prioritization, stability optimization, Design-Build-Test-Learn workflows, synthetic biology, multi-enzyme systems, scalable production, formulation, and existing pilot-scale or commercial translation are further evaluated according to the specific bottlenecks they are intended to address. Overall, this review argues that the future of enzymatic mycotoxin detoxification depends less on maximizing technological complexity than on integrating mechanistic evidence, application-specific performance, manufacturability, degradation-product safety, and regulatory readiness. The Designer Enzyme concept therefore provides a structured roadmap for directing promising detoxification enzymes toward credible, safe, and scalable food and feed applications.

Indexed as

artificial intelligenceDesigner Enzymesfood and feed safetygrain loss reductionmulti-enzyme cascadesmycotoxin detoxificationregulatory preparednesssustainable food systems

Identifiers

PMID42883645
PMCPMC13665256

What OpenQuestion holds

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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.