Using Markov state models to study self-assembly

Perkett, Matthew R.; Hagan, Michael F.

doi:10.1063/1.4878494

Cited by 51 publications

(53 citation statements)

References 139 publications

(248 reference statements)

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“…[35] In particular, recent millisecond simulations [34] revealed unexpected intermediate stages in the processing of DNA by RNA polymerase. These simulations used a multi-scale approach that extrapolates from conventional sub-microsecond molecular dynamics models using Markov models [36] to approach the real timescale for translocation (at least tens of microseconds). They also represent an important step forward in the state of the art for using modeling to describe features that are important for rational design but which are difficult if not impossible to measure experimentally.…”

Section: Reviewmentioning

confidence: 99%

Nanoscale Engineering of Designer Cellulosomes

et al. 2016

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Biocatalysts showcase the upper limit obtainable for high-speed molecular processing and transformation. Efforts to engineer functionality in synthetic nanostructured materials are guided by the increasing knowledge of evolving architectures, which enable controlled molecular motion and precise molecular recognition. The cellulosome is a biological nanomachine, which, as a fundamental component of the plant-digestion machinery from bacterial cells, has a key potential role in the successful development of environmentally-friendly processes to produce biofuels and fine chemicals from the breakdown of biomass waste. Here, the progress toward so-called "designer cellulosomes", which provide an elegant alternative to enzyme cocktails for lignocellulose breakdown, is reviewed. Particular attention is paid to rational design via computational modeling coupled with nanoscale characterization and engineering tools. Remaining challenges and potential routes to industrial application are put forward.

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Section: Reviewmentioning

confidence: 99%

Nanoscale Engineering of Designer Cellulosomes

et al. 2016

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“…Finally, enhanced sampling methods can focus computational time on critical but rare events, such as crossing nucleation barriers. Methods well-suited for the diverse pathways typical of assembly systems include multiple state transition path sampling [36], Markov state models [37], weighted ensemble dynamics [35], and diffusion maps [38].…”

Section: Coarse-grained Models For Capsid Assemblymentioning

confidence: 99%

Recent advances in coarse-grained modeling of virus assembly

Hagan

Zandi

2016

Current Opinion in Virology

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In many virus families, tens to thousands of proteins assemble spontaneously into a capsid (protein shell) while packaging the genomic nucleic acid. This review summarizes recent advances in computational modeling of these dynamical processes. We present an overview of recent technological and algorithmic developments, which are enabling simulations to describe the large ranges of length-and time-scales relevant to assembly, under conditions more closely matched to experiments than in earlier work. We then describe two examples in which computational modeling has recently provided an important complement to experiments.Comment: 9 pages, 3 figure

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“…Minimizing φ b ij creates an interaction that resists torsion and enforces angular specificity commensurate with a complete capsid. The potentials are given by Eqs (16) [68,89] Conformational dynamics. In our BD simulations with conformational dynamics, free subunits stochastically switch between inactive and active conformations.…”

Section: Brownian Dynamics Model Detailsmentioning

confidence: 99%

Allosteric Control of Icosahedral Capsid Assembly

Lázaro

Hagan

2016

J. Phys. Chem. B

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During the lifecycle of a virus, viral proteins and other components self-assemble to form an ordered protein shell called a capsid. This assembly process is subject to multiple competing constraints, including the need to form a thermostable shell while avoiding kinetic traps. It has been proposed that viral assembly satisfies these constraints through allosteric regulation, including the interconversion of capsid proteins among conformations with different propensities for assembly. In this article we use computational and theoretical modeling to explore how such allostery affects the assembly of icosahedral shells. We simulate assembly under a wide range of protein concentrations, protein binding affinities, and two different mechanisms of allosteric control. We find that, above a threshold strength of allosteric control, assembly becomes robust over a broad range of subunit binding affinities and concentrations, allowing the formation of highly thermostable capsids. Our results suggest that allostery can significantly shift the range of protein binding affinities that lead to successful assembly, and thus should be accounted for in models that are used to estimate interaction parameters from experimental data.

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Using Markov state models to study self-assembly

Cited by 51 publications

References 139 publications

Nanoscale Engineering of Designer Cellulosomes

Nanoscale Engineering of Designer Cellulosomes

Recent advances in coarse-grained modeling of virus assembly

Allosteric Control of Icosahedral Capsid Assembly

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