Eukaryotes have several highly conserved actin-binding proteins that crosslink filamentous actin into compact ordered bundles present in distinct cytoskeletal processes, including microvilli, stereocilia and filopodia. Fascin is an actin-binding protein that is present predominantly in filopodia, which are believed to play a central role in normal and aberrant cell migration. An important outstanding question regards the molecular basis for the unique localization and functional properties of fascin compared with other actin crosslinking proteins. Here, we present the crystal structure of full-length Homo sapiens fascin-1, and examine its packing, conformational flexibility, and evolutionary sequence conservation. The structure reveals a novel arrangement of four tandem beta-trefoil domains that form a bi-lobed structure with approximate pseudo 2-fold symmetry. Each lobe has internal approximate pseudo 2-fold and pseudo 3-fold symmetry axes that are approximately perpendicular, with beta-hairpin triplets located symmetrically on opposite sides of each lobe that mutational data suggest are actin-binding domains. Sequence conservation analysis confirms the importance of hydrophobic core residues that stabilize the beta-trefoil fold, as well as interfacial residues that are likely to stabilize the overall fascin molecule. Sequence conservation also indicates highly conserved surface patches near the putative actin-binding domains of fascin, which conformational dynamics analysis suggests to be coupled via an allosteric mechanism that might have important functional implications for F-actin crosslinking by fascin.

Synthetic nucleic acids can be programmed to form precise three-dimensional structures on the nanometer-scale. These thermodynamically stable complexes can serve as structural scaffolds to spatially organize functional molecules including multiple enzymes, chromophores, and force-sensing elements with internal dynamics that include substrate reaction-diffusion, excitonic energy transfer, and force-displacement response that often depend critically on both the local and global conformational dynamics of the nucleic acid assembly. However, high molecular weight assemblies exhibit long time-scale and large length-scale motions that cannot easily be sampled using all-atom computational procedures such as molecular dynamics. As an alternative, here we present a computational framework to compute the overdamped conformational dynamics of structured nucleic acid assemblies and apply it to a DNA-based tweezer, a nine-layer DNA origami ring, and a pointer-shaped DNA origami object, which consist of 204, 3,600, and over 7,000 basepairs, respectively. The framework employs a mechanical finite element model for the DNA nanostructure combined with an implicit solvent model to either simulate the Brownian dynamics of the assembly or alternatively compute its Brownian modes. Computational results are compared with an all-atom molecular dynamics simulation of the DNA-based tweezer. Several hundred microseconds of Brownian dynamics are simulated for the nine-layer ring origami object to reveal its long time-scale conformational dynamics, and the first ten Brownian modes of the pointer-shaped structure are predicted.

Normal mode analysis plays an important role in relating the conformational dynamics of proteins to their biological function. The subspace iteration method is a numerical procedure for normal mode analysis that has enjoyed widespread success in the structural mechanics community due to its numerical stability and computational efficiency in calculating the lowest normal modes of large systems. Here, we apply the subspace iteration method to proteins to demonstrate its advantageous properties in this area of computational protein science. An effective algorithm for choosing the number of iteration vectors in the method is established, offering a considerable improvement over the original implementation. In the present application, computational time scales linearly with the number of normal modes computed. Additionally, the method lends itself naturally to normal mode analyses of multiple neighboring macromolecular conformations, as demonstrated in a conformational change pathway analysis of adenylate kinase. These properties, together with its computational robustness and intrinsic scalability to multiple processors, render the subspace iteration method an effective and reliable computational approach to protein normal mode analysis.

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