How the Choice of Force-Field Affects the Stability and Self-Assembly Process of Supramolecular CTA Fibers

[Image: see text] In recent years, computational methods have become an essential element of studies focusing on the self-assembly process. Although they provide unique insights, they face challenges, from which two are the most often mentioned in the literature: the temporal and spatial scale of the self-assembly. A less often mentioned issue, but not less important, is the choice of the force-field. The repetitive nature of the supramolecular structure results in many similar interactions. Consequently, even a small deviation in these interactions can lead to significant energy differences in the whole structure. However, studies comparing different force-fields for self-assembling systems are scarce. In this article, we compare molecular dynamics simulations for trifold hydrogen-bonded fibers performed with different force-fields, namely GROMOS, CHARMM General Force Field (CGenFF), CHARMM Drude, General Amber Force-Field (GAFF), Martini, and polarized Martini. Briefly, we tested the force-fields by simulating: (i) spontaneous self-assembly (none form a fiber within 500 ns), (ii) stability of the fiber (observed for CHARMM Drude, GAFF, MartiniP), (iii) dimerization (observed for GROMOS, GAFF, and MartiniP), and (iv) oligomerization (observed for CHARMM Drude and MartiniP). This system shows that knowledge of the force-field behavior regarding interactions in oligomer and larger self-assembled structures is crucial for designing efficient simulation protocols for self-assembling systems

Computational Modeling of Supramolecular Metallo-organic Cages-Challenges and Opportunities

[Image: see text] 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

Biocatalytic self-assembly of tripeptide gels and emulsions

We report on the biocatalytic activation of a self-assembling (unprotected) tripeptide to stabilize oil-in-water emulsions on-demand. This is achieved by the conversion of a phosphorylated precursor into a hydrogelator using alkaline phosphatase (AP) as the trigger. The rate of conversion, controlled by the amount of enzyme used, is shown to play a key role in dictating the morphology of the nanofibrous networks produced. When these amphiphilic tripeptides are used in biphasic mixtures, nanofibers are shown to self-assemble not only at the aqueous/organic interface but also throughout the surrounding buffer, thereby stabilizing the oil-in-water droplet dispersions. The use of enzymatic activation of tripeptide emulsions gives rise to enhanced control of the emulsification process because emulsions can be stabilized on-demand by simply adding AP. In addition, control over the emulsion stabilization can be achieved by taking advantage of the kinetics of dephosphorylation and consequent formation of different stabilizing nanofibrous networks at the interface and/or in the aqueous environment. This approach can be attractive for various cosmetic, food, or biomedical applications because both tunability of the tripeptide emulsion stability and on-demand stabilization of emulsions can be achieved

Identification of 12 new susceptibility loci for different histotypes of epithelial ovarian cancer.

To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3 and 9q31.1) and one for endometrioid EOC (5q12.3). We then performed meta-analysis on the results for high-grade serous ovarian cancer with the results from analysis of 31,448 BRCA1 and BRCA2 mutation carriers, including 3,887 mutation carriers with EOC. This identified three additional susceptibility loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a new candidate susceptibility gene for low-grade and borderline serous EOC

Picking the lock of coordination cage catalysis

The design principles of metallo-organic assembly reactions have facilitated access to hundreds of coordination cages of varying size and shape. Many of these assemblies possess a well-defined cavity capable of hosting a guest, pictorially mimicking the action of a substrate binding to the active site of an enzyme. While there are now a growing collection of coordination cages that show highly proficient catalysis, exhibiting both excellent activity and efficient turnover, this number is still small compared to the vast library of metal–organic structures that are known. In this review, we will attempt to unpick and discuss the key features that make an effective coordination cage catalyst, linking structure to activity (and selectivity) using lessons learnt from both experimental and computational analysis of the most notable exemplars. We will also provide an outlook for this area, reasoning why coordination cages have the potential to become the gold-standard in (synthetic) non-covalent catalysis

Mechanism of Ostwald Ripening in 2D Physisorbed Assemblies at Molecular Time and Length Scale by Molecular Dynamics Simulations

Ostwald ripening can improve the long-range order of self-assembled monolayers by the growth of large domains and disassembly of smaller ones. Here, coarse-grained molecular dynamics simulations are used to study the dynamics of the stable assembly and the coarsening of defects of physisorbed monolayers of long-chain functionalized alkanes. Our results show that the partial desorption from the surface of one or more adsorbent molecules is the essential process that allows other adsorbent molecules to rearrange on the surface and thereby improve alignment. We also show that the ripening process is faster at higher temperature because the rate of partial desorption is higher.status: publishe

Computational Modeling of Supramolecular Metallo-organic Cages-Challenges and Opportunities

[EN] 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.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).Piskorz, TK.; Martí-Centelles, V.; Young, TA.; Lusby, PJ.; Duarte, F. (2022). Computational Modeling of Supramolecular Metallo-organic Cages-Challenges and Opportunities. ACS Catalysis. 12(10):5806-5826. https://doi.org/10.1021/acscatal.2c0083758065826121

Nucleation Mechanisms of Self-Assembled Physisorbed Monolayers on Graphite

status: publishe