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Institute
Photolabile protecting groups are widely used to trigger oligonucleotide activity. The ON/OFF‐amplitude is a critical parameter. An experimental setup has been developed to identify protecting group derivatives with superior caging properties. Bulky rests are attached to the cage moiety via Cu‐catalyzed azide–alkyne cycloaddition post‐synthetically on DNA. Interestingly, the decrease in melting temperature upon introducing o‐nitrobenzyl‐caged (NPBY‐) and diethylaminocoumarin‐cages (DEACM‐) in DNA duplexes reaches a limiting value. NMR spectroscopy was used to characterize individual base‐pair stabilities and determine experimental structures of a selected number of photocaged DNA molecules. The experimental structures agree well with structures predicted by MD simulations. Combined, the structural data indicate that once a sterically demanding group is added to generate a tri‐substituted carbon, the sterically less demanding cage moiety points towards the neighboring nucleoside and the bulkier substituents remain in the major groove.
The structure and flexibility of RNA depends sensitively on the microenvironment. Using pulsed electron-electron double-resonance (PELDOR)/double electron-electron resonance (DEER) spectroscopy combined with advanced labeling techniques, we show that the structure of double-stranded RNA (dsRNA) changes upon internalization into Xenopus lævis oocytes. Compared to dilute solution, the dsRNA A-helix is more compact in cells. We recapitulate this compaction in a densely crowded protein solution. Atomic-resolution molecular dynamics simulations of dsRNA semi-quantitatively capture the compaction, and identify non-specific electrostatic interactions between proteins and dsRNA as a possible driver of this effect.
Disordered proteins and nucleic acids can condense into droplets that resemble the membraneless organelles observed in living cells. MD simulations offer a unique tool to characterize the molecular interactions governing the formation of these biomolecular condensates, their physicochemical properties, and the factors controlling their composition and size. However, biopolymer condensation depends sensitively on the balance between different energetic and entropic contributions. Here, we develop a general strategy to fine-tune the potential energy function for molecular dynamics simulations of biopolymer phase separation. We rebalance protein–protein interactions against solvation and entropic contributions to match the excess free energy of transferring proteins between dilute solution and condensate. We illustrate this formalism by simulating liquid droplet formation of the FUS low-complexity domain (LCD) with a rebalanced MARTINI model. By scaling the strength of the nonbonded interactions in the coarse-grained MARTINI potential energy function, we map out a phase diagram in the plane of protein concentration and interaction strength. Above a critical scaling factor of αc ≈ 0.6, FUS-LCD condensation is observed, where α = 1 and 0 correspond to full and repulsive interactions in the MARTINI model. For a scaling factor α = 0.65, we recover experimental densities of the dilute and dense phases, and thus the excess protein transfer free energy into the droplet and the saturation concentration where FUS-LCD condenses. In the region of phase separation, we simulate FUS-LCD droplets of four different sizes in stable equilibrium with the dilute phase and slabs of condensed FUS-LCD for tens of microseconds, and over one millisecond in aggregate. We determine surface tensions in the range of 0.01–0.4 mN/m from the fluctuations of the droplet shape and from the capillary-wave-like broadening of the interface between the two phases. From the dynamics of the protein end-to-end distance, we estimate shear viscosities from 0.001 to 0.02 Pa s for the FUS-LCD droplets with scaling factors α in the range of 0.625–0.75, where we observe liquid droplets. Significant hydration of the interior of the droplets keeps the proteins mobile and the droplets fluid.
Highlights
• Sampling the large conformational space of disordered proteins requires extensive molecular dynamics (MD) simulations.
• Fragment assembly complements MD simulations to produce extensive ensembles of disordered proteins with atomic detail.
• Hierarchical chain growth (HCG) ensembles capture key experimental descriptors “out of the box”.
• HCG has revealed local structural characteristics associated with protein dysfunction in neurodegeneration.
Abstract
Disordered proteins and nucleic acids play key roles in cellular function and disease. Here, we review recent advances in the computational exploration of the conformational dynamics of flexible biomolecules. While atomistic molecular dynamics (MD) simulation has seen a lot of improvement in recent years, large-scale computing resources and careful validation are required to simulate full-length disordered biopolymers in solution. As a computationally efficient alternative, hierarchical chain growth (HCG) combines pre-sampled chain fragments in a statistically reproducible manner into ensembles of full-length atomically detailed biomolecular structures. Experimental data can be integrated during and after chain assembly. Applications to the neurodegeneration-linked proteins α-synuclein, tau, and TDP-43, including as condensate, illustrate the use of HCG. We conclude by highlighting the emerging connections to AI-based structural modeling including AlphaFold2.