Evidence map›Paper›PMID 42482556›Full record

ReviewSmall (Weinheim an der Bergstrasse, Germany)2026

Biomacromolecule-MOF Composites for Intracellular Delivery: From Empirical Construction to Rational Design and AI-Assisted Screening.

Lijun Xu, Haiyue Yu, Xiaoyang Li, Jun Ge

Abstract readReview
In one paragraph

Review in Small (Weinheim an der Bergstrasse, Germany), 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

4 authors.

Lijun XuDepartment of Chemical Engineering, Tsinghua University, Beijing, China.
Haiyue YuDepartment of Chemical Engineering, Tsinghua University, Beijing, China.
Xiaoyang LiCollege of Life Science and Technology, Beijing University of Chemical Technology, Beijing, China.
Jun GeDepartment of Chemical Engineering, Tsinghua University, Beijing, China.ORCID 0000-0001-5503-8899

Funding

Beijing Natural Science Foundation Z240030National Natural Science Foundation of China 22425803Shenzhen Science and Technology Program KCXFZ20240903093102004
6 · The paper itself

Abstract

Biomacromolecules, including proteins, peptides, and nucleic acids, hold great promise for disease diagnosis and therapy because they can execute highly specific biological functions, including catalysis, molecular recognition, and gene regulation. Nevertheless, their clinical translation is limited by inefficient intracellular delivery due to poor membrane permeability, endo/lysosomal entrapment, and instability in complex biological environments. Metal-organic frameworks (MOFs), featuring high porosity, tunable structures, mild encapsulation conditions, versatile surface modification, and stimulus-responsive degradation, have emerged as attractive material platforms for biomacromolecule protection and intracellular delivery. This review summarizes the design evolution of biomacromolecule-MOF composites from empirical construction to rational design and AI-assisted screening. Recent advances in AI-assisted enzyme-MOF and drug-delivery MOF design are further discussed as emerging tools for synergistic integration of multiple functions. This review provides an overview of how MOFs can be developed into next-generation intracellular delivery platforms and how emerging design strategies enable the rapid and precise development of biomacromolecule-MOF composites tailored for specific biomedical applications.

Indexed as

Drug Delivery SystemsMetal-Organic FrameworksAnimalsHumansMetal-Organic FrameworksAI‐assisted screeningbiomacromoleculeempirical constructionintracellular deliverymetal–organic frameworksrational design

Identifiers

PMID42482556
PMCPMC13509103

What OpenQuestion holds

Textmetadata
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.