Evidence map›Paper›PMID 42100447›Full record

ReviewRSC advances2026

Towards hybrid MOF@COF and COF@MOF platforms for next-generation biocatalysis.

Mercy Chaparadza, Linia Gedi Marazani, Lendly Moyo, Evernice Chikukwa, Piwai Tshuma, Johannes Hungwe, Gift Mehlana

Abstract readReview
In one paragraph

Review in RSC advances, 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

7 authors.

Mercy ChaparadzaMidlands State University, Department of Chemical Sciences 9055 Senga Road Gweru Zimbabwe mehlanag@staff.msu.ac.zw.
Linia Gedi MarazaniMidlands State University, Department of Chemical Sciences 9055 Senga Road Gweru Zimbabwe mehlanag@staff.msu.ac.zw.ORCID https://orcid.org/0009-0007-9009-1995
Lendly MoyoMidlands State University, Department of Chemical Sciences 9055 Senga Road Gweru Zimbabwe mehlanag@staff.msu.ac.zw.ORCID https://orcid.org/0009-0008-9887-0587
Evernice ChikukwaMidlands State University, Department of Chemical Sciences 9055 Senga Road Gweru Zimbabwe mehlanag@staff.msu.ac.zw.
Piwai TshumaMidlands State University, Department of Chemical Sciences 9055 Senga Road Gweru Zimbabwe mehlanag@staff.msu.ac.zw.ORCID https://orcid.org/0009-0005-1272-6620
Johannes HungweMidlands State University, Department of Chemical Sciences 9055 Senga Road Gweru Zimbabwe mehlanag@staff.msu.ac.zw.
Gift MehlanaMidlands State University, Department of Chemical Sciences 9055 Senga Road Gweru Zimbabwe mehlanag@staff.msu.ac.zw.ORCID https://orcid.org/0000-0003-1294-0895

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Enzyme immobilization is central to advancing sustainable biocatalysis, yet conventional supports often fail to simultaneously provide structural protection, mass transport, and chemical tunability. Traditional support materials often lack the optimal combination of porosity, stability, and surface functionality needed to preserve enzyme activity. Metal-organic frameworks (MOFs) and covalent organic frameworks (COFs) have emerged as promising hosts due to their high surface area, tunable porosity, and chemical versatility. Recent developments in hybrid architectures MOF@COF and COF@MOF offer a synergistic platform that integrates the structural flexibility and catalytic tunability of MOFs with the robustness and stability of COFs. This review highlights the design principles, immobilization strategies, and catalytic behavior of enzyme@MOF@COF and enzyme@COF@MOF systems. We discuss advances

Identifiers

PMID42100447
PMCPMC13146371

What OpenQuestion holds

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LicenceCC BY-NC
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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.