TY - JOUR
T1 - Computational Modeling of Supramolecular Metallo-organic Cages-Challenges and Opportunities
AU - Piskorz, Tomasz K.
AU - Martí-Centelles, Vicente
AU - Young, Tom A.
AU - Lusby, Paul J.
AU - Duarte, Fernanda
N1 - Funding Information:
T.K.P., P.J.L., and F.D. acknowledge the financial support from EPSRC (EP/W010666/1 and EP/W009803/1). T.K.P. and F.D. acknowledge the financial support from the John Fell Fund (ref 0006752). V.M.-C. acknowledges the financial support from Generalitat Valenciana (CIDEGENT/2020/031). T.A.Y. acknowledges the impact acceleration account (IAA) grant (EP/R511742/1).
Publisher Copyright:
© 2022 The Authors. Published by American Chemical Society.
PY - 2022/5/20
Y1 - 2022/5/20
N2 - Self-assembled metallo-organic cages have emerged as promising biomimetic platforms that can encapsulate whole substrates akin to an enzyme active site. Extensive experimental work has enabled access to a variety of structures, with a few notable examples showing catalytic behavior. However, computational investigations of metallo-organic cages are scarce, not least due to the challenges associated with their modeling and the lack of accurate and efficient protocols to evaluate these systems. In this review, we discuss key molecular principles governing the design of functional metallo-organic cages, from the assembly of building blocks through binding and catalysis. For each of these processes, computational protocols will be reviewed, considering their inherent strengths and weaknesses. We will demonstrate that while each approach may have its own specific pitfalls, they can be a powerful tool for rationalizing experimental observables and to guide synthetic efforts. To illustrate this point, we present several examples where modeling has helped to elucidate fundamental principles behind molecular recognition and reactivity. We highlight the importance of combining computational and experimental efforts to speed up supramolecular catalyst design while reducing time and resources.
AB - Self-assembled metallo-organic cages have emerged as promising biomimetic platforms that can encapsulate whole substrates akin to an enzyme active site. Extensive experimental work has enabled access to a variety of structures, with a few notable examples showing catalytic behavior. However, computational investigations of metallo-organic cages are scarce, not least due to the challenges associated with their modeling and the lack of accurate and efficient protocols to evaluate these systems. In this review, we discuss key molecular principles governing the design of functional metallo-organic cages, from the assembly of building blocks through binding and catalysis. For each of these processes, computational protocols will be reviewed, considering their inherent strengths and weaknesses. We will demonstrate that while each approach may have its own specific pitfalls, they can be a powerful tool for rationalizing experimental observables and to guide synthetic efforts. To illustrate this point, we present several examples where modeling has helped to elucidate fundamental principles behind molecular recognition and reactivity. We highlight the importance of combining computational and experimental efforts to speed up supramolecular catalyst design while reducing time and resources.
KW - biomimetic catalysis
KW - computational modeling
KW - metallo-organic cages
KW - supramolecular chemistry
U2 - 10.1021/acscatal.2c00837
DO - 10.1021/acscatal.2c00837
M3 - Review article
C2 - 35633896
AN - SCOPUS:85130026985
SN - 2155-5435
VL - 12
SP - 5806
EP - 5826
JO - ACS Catalysis
JF - ACS Catalysis
IS - 10
ER -