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MOF-LENS: Bio-inspired lotus effect optimization for accelerated discovery of metal–organic framework nanocarriers for doxorubicin delivery in cancer therapy

Jalali, Mehrdad ORCID iD icon 1; Vu, Binh; Mehraeen, Sina; Chandna, Swati; Jalali, Farzad
1 Institut für Funktionelle Grenzflächen (IFG), Karlsruher Institut für Technologie (KIT)

Abstract (englisch):

Metal–organic frameworks (MOFs) are crystalline materials characterized by adjustable porosity and chemical properties, rendering them effective carriers for doxorubicin (DOX) in the treatment of hepatocellular carcinoma (HCC). The extensive design space complicates the identification of metal-organic frameworks (MOFs) that simultaneously optimize doxorubicin (DOX) loading, pH-responsive release, and biocompatibility. We introduce MOF-LENS (Latent Evolutionary Navigation System), a bio-inspired framework that integrates structural descriptors (pore size, surface area, void fraction) and SMILES-based fingerprints into a unified latent space. This framework employs the previously published Lotus Effect Algorithm (LEA) to identify high-quality MOF nanocarriers. In benchmarks comparing particle swarm optimization, genetic algorithms, random search, and a deterministic filter baseline across 30 independent runs, MOF-LENS achieves comparable or superior best fitness with significantly reduced variance, resulting in a consistent set of top candidates rather than isolated outliers. The chosen MOFs demonstrate pore-limiting diameters within the DOX-compatible range (12–16 Å) and exhibit a strong chemical affinity for DOX. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000189159
Veröffentlicht am 19.12.2025
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Funktionelle Grenzflächen (IFG)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 12.2025
Sprache Englisch
Identifikator ISSN: 2352-4928
KITopen-ID: 1000189159
Erschienen in Materials Today Communications
Verlag Elsevier
Band 49
Seiten 114448
Schlagwörter Metal–Organic Frameworks (MOFs), Doxorubicin (DOX), Drug delivery, Lotus Effect Algorithm (LEA), Multi-objective optimization, Tanimoto similarity, Pore limiting diameter (PLD), Materials informatics
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