Inverse design of multicomponent assemblies

Piñeros, William D.; Lindquist, Beth A.; Jadrich, Ryan B.; Truskett, Thomas M.

doi:10.1063/1.5021648

Cited by 39 publications

(30 citation statements)

References 81 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In order to design colloidal systems which self-assemble into crystals of arbitrary complexity, the interparticle interactions between colloids are typically treated as degrees of freedom to be optimized 1–3 . In practice, this tuning can be achieved through various means, including particle charge, shape, and functionalization 4–10 .…”

Section: Introductionmentioning

confidence: 99%

Using symmetry to elucidate the importance of stoichiometry in colloidal crystal assembly

et al. 2019

View full text Add to dashboard Cite

We demonstrate a method based on symmetry to predict the structure of self-assembling, multicomponent colloidal mixtures. This method allows us to feasibly enumerate candidate structures from all symmetry groups and is many orders of magnitude more computationally efficient than combinatorial enumeration of these candidates. In turn, this permits us to compute ground-state phase diagrams for multicomponent systems. While tuning the interparticle potentials to produce potentially complex interactions represents the conventional route to designing exotic lattices, we use this scheme to demonstrate that simple potentials can also give rise to such structures which are thermodynamically stable at moderate to low temperatures. Furthermore, for a model two-dimensional colloidal system, we illustrate that lattices forming a complete set of 2-, 3-, 4-, and 6-fold rotational symmetries can be rationally designed from certain systems by tuning the mixture composition alone, demonstrating that stoichiometric control can be a tool as powerful as directly tuning the interparticle potentials themselves.

show abstract

Section: Introductionmentioning

confidence: 99%

Using symmetry to elucidate the importance of stoichiometry in colloidal crystal assembly

et al. 2019

View full text Add to dashboard Cite

show abstract

“…To resolve this issue, one may use semi-grand canonical ensembles (total N is constant, but particle number of specific species fluctuates), which is especially important for studying phase separation of multi-component mixtures. However, there still remains the issue of setting the correct chemical potentials for each particle species that produces the correct stoichiometry or relative abundance 16,17 . Another way is to identify the constraint of mean particle numbers through a "chemical potential" in a grand canonical ensemble, thus allowing the N to fluctuate (Fig 1b).…”

Section: Fig 1 (A)mentioning

confidence: 99%

Understanding protein-complex assembly through grand canonical maximum entropy modeling

Gasic

Sarkar

Cheung

2021

Phys. Rev. Research

View full text Add to dashboard Cite

Inside a cell, heterotypic proteins assemble in inhomogeneous, crowded systems where the abundance of these proteins vary with cell types. While some protein complexes form putative structures that can be visualized with imaging, there are far more protein complexes that are yet to be solved because of their dynamic associations with one another. Yet, it is possible to infer these protein complexes through a physical model. However, it is often not clear to physicists what kind of data from biology is necessary for such a modeling endeavor. Here, we aim to model these clusters of coarse-grained protein assemblies from multiple subunits through the constraints of interactions among the subunits and the chemical potential of each subunit. We obtained the constraints on the interactions among subunits from the known protein structures. We inferred the chemical potential, that dictates the particle number distribution of each protein subunit, from the knowledge of protein abundance from experimental data. Guided by the maximum entropy principle, we formulate an inverse statistical mechanical method to infer the distribution of particle numbers from the data of protein abundance as chemical potentials for a grand canonical multicomponent mixture. Using grand canonical Monte Carlo simulations, we captured a distribution of high-order clusters in a protein complex of Succinate Dehydrogenase (SDH) with four known subunits. The complexity of hierarchical clusters varies with the relative protein abundance of each subunit in distinctive cell types such as lung, heart, and brain. When the crowding content increases, we observed that crowding stabilizes emergent clusters that do not exist in dilute conditions. We, therefore, proposed a testable hypothesis that the hierarchical complexity of protein clusters on a molecular scale is a plausible biomarker of predicting the phenotypes of a cell.

show abstract

“…The implementation of this technique for determining pair interactions led to the formation of several two-dimensional target lattices, including rectangular Kagome, triangular honeycomb, and octadecagonal star binary [ 108 ], and three-dimensional lattices, like diamond and simple cubic [ 109 ].…”

Section: Entropic Contributions In Self-assembly Processesmentioning

confidence: 99%

Role of Entropy in Colloidal Self-Assembly

Rocha

Paul

Vashisth

2020

Entropy

View full text Add to dashboard Cite

Entropy plays a key role in the self-assembly of colloidal particles. Specifically, in the case of hard particles, which do not interact or overlap with each other during the process of self-assembly, the free energy is minimized due to an increase in the entropy of the system. Understanding the contribution of entropy and engineering it is increasingly becoming central to modern colloidal self-assembly research, because the entropy serves as a guide to design a wide variety of self-assembled structures for many technological and biomedical applications. In this work, we highlight the importance of entropy in different theoretical and experimental self-assembly studies. We discuss the role of shape entropy and depletion interactions in colloidal self-assembly. We also highlight the effect of entropy in the formation of open and closed crystalline structures, as well as describe recent advances in engineering entropy to achieve targeted self-assembled structures.

show abstract

Inverse design of multicomponent assemblies

Cited by 39 publications

References 81 publications

Using symmetry to elucidate the importance of stoichiometry in colloidal crystal assembly

Using symmetry to elucidate the importance of stoichiometry in colloidal crystal assembly

Understanding protein-complex assembly through grand canonical maximum entropy modeling

Role of Entropy in Colloidal Self-Assembly

Contact Info

Product

Resources

About