Publications by authors named "Huifen Nie"

Discrete molecular dynamics (DMD) is a rapid sampling method used in protein folding and aggregation studies. Until now, DMD was used to perform simulations of simplified protein models in conjunction with structure-based force fields. Here, we develop an all-atom protein model and a transferable force field featuring packing, solvation, and environment-dependent hydrogen bond interactions.

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Lipid aggregation into fluid bilayers is an essential process for sustaining life. Simplified models of lipid structure, which allow for long time scales or large length scales not obtainable with all-atom simulations, have recently been developed and show promise for describing lipid dynamics in biological systems. Here, we describe two simplified models, a reduced-lipid model and a bola-lipid model for thermophilic bacterial membranes, developed for use with the rapid discrete molecular dynamics simulation method.

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Over the past three decades the protein folding field has undergone monumental changes. Originally a purely academic question, how a protein folds has now become vital in understanding diseases and our abilities to rationally manipulate cellular life by engineering protein folding pathways. We review and contrast past and recent developments in the protein folding field.

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Unlabelled: We built a novel web-based platform for performing discrete molecular dynamics simulations of proteins. In silico protein folding involves searching for minimal frustration in the vast conformational landscape. Conventional approaches for simulating protein folding insufficiently address the problem of simulations in relevant time and length scales necessary for a mechanistic understanding of underlying biomolecular phenomena.

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Time-resolved small-angle x-ray scattering measurements reveal that a long-lived intermediate bcc state forms when a poly(styrene-b-isoprene) diblock copolymer solution in an isoprene selective solvent is rapidly cooled from the disordered micellar fluid at high temperature to an equilibrium fcc state. The kinetics of the epitaxial growth of the [111] fcc peak from the [110] bcc peak was obtained by fitting the scattering data to a simple model of the transformation. The growth of the [111] fcc peak agrees with the Avrami model of nucleation and growth kinetics with an exponent n=1.

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