Mechanistic Understanding of Protein–MOF Integration Through Surfactant‐Driven Interfacial Design
- 1Department of Chemistry and Biochemistry Texas Tech University Lubbock Texas USA
- 2Texas Tech University
Abstract
Integration of proteins into metal-organic frameworks (Protein@MOF) represents an effective method for protein stabilization, with rising demand across material and biomedical sciences. However, the molecular mechanism of protein-MOF interactions remains unsettled due to challenges in developing a general platform to systematically investigate such interactions, hindering improvements in their chemical and physical properties. Here, we develop a surfactant-guided strategy to modulate the assembly of protein@MOF through interfacial design. We discovered that the interfacial environment between proteins and MOFs is the primary factor determining encapsulation efficiency, structural retention, and functional performance. Lipid-based non-ionic surfactants such as glycerol monooleate (GMO) increase the protein's solvent-accessible surface area (SASA), suggesting partial remodeling of the protein surface and hydration shell. GMO at the interface of protein@MOF results in a 20% improvement in protein encapsulation and a 30% increase in MOF growth rate. All-atom molecular dynamics simulations reveal domain-specific interactions between GMO and flexible surface residues on protein in a concentration-dependent manner, involving both electrostatic and hydrophobic contacts. This work offers new molecular insights into how surfactant-driven interfacial design fine-tunes the stability of protein@MOF, laying the foundation for robust alternatives to lipid nanodiscs for membrane protein stabilization, and protein-based platforms for drug-delivery, biocatalysis, and biosensing.
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BibTeX
@article{rashidniyaghi2026mechanistic,
title = {{Mechanistic Understanding of Protein–MOF Integration Through Surfactant‐Driven Interfacial Design}},
author = {Ehsan Rashidniyaghi and Mohammad Khavani and Carlie Coerver and Ruibin Liang and Raheleh Ravanfar},
journal = {Advanced Science},
year = {2026},
month = jun,
doi = {10.1002/advs.76011},
url = {https://doi.org/10.1002/advs.76011},
note = {CC BY},
}
RIS
TY - JOUR
TI - Mechanistic Understanding of Protein–MOF Integration Through Surfactant‐Driven Interfacial Design
AU - Ehsan Rashidniyaghi
AU - Mohammad Khavani
AU - Carlie Coerver
AU - Ruibin Liang
AU - Raheleh Ravanfar
PY - 2026
DA - 2026/06/09
JO - Advanced Science
DO - 10.1002/advs.76011
UR - https://doi.org/10.1002/advs.76011
AB - Integration of proteins into metal-organic frameworks (Protein@MOF) represents an effective method for protein stabilization, with rising demand across material and biomedical sciences. However, the molecular mechanism of protein-MOF interactions remains unsettled due to challenges in developing a general platform to systematically investigate such interactions, hindering improvements in their chemical and physical properties. Here, we develop a surfactant-guided strategy to modulate the assembly of protein@MOF through interfacial design. We discovered that the interfacial environment between proteins and MOFs is the primary factor determining encapsulation efficiency, structural retention, and functional performance. Lipid-based non-ionic surfactants such as glycerol monooleate (GMO) increase the protein's solvent-accessible surface area (SASA), suggesting partial remodeling of the protein surface and hydration shell. GMO at the interface of protein@MOF results in a 20% improvement in protein encapsulation and a 30% increase in MOF growth rate. All-atom molecular dynamics simulations reveal domain-specific interactions between GMO and flexible surface residues on protein in a concentration-dependent manner, involving both electrostatic and hydrophobic contacts. This work offers new molecular insights into how surfactant-driven interfacial design fine-tunes the stability of protein@MOF, laying the foundation for robust alternatives to lipid nanodiscs for membrane protein stabilization, and protein-based platforms for drug-delivery, biocatalysis, and biosensing.
SN - 2198-3844
ER -