D
David Shirvanyants
Researcher at University of North Carolina at Chapel Hill
Publications - 34
Citations - 3784
David Shirvanyants is an academic researcher from University of North Carolina at Chapel Hill. The author has contributed to research in topics: Protein aggregation & Covalent bond. The author has an hindex of 23, co-authored 34 publications receiving 3175 citations.
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Journal ArticleDOI
Continuous liquid interface production of 3D objects
John R. Tumbleston,David Shirvanyants,Nikita Ermoshkin,Rima Janusziewicz,Ashley R. Johnson,David L. Kelly,Kai Chen,Robert Pinschmidt,Jason P. Rolland,Alexander Ermoshkin,Edward T. Samulski,Joseph M. DeSimone,Joseph M. DeSimone +12 more
TL;DR: The continuous generation of monolithic polymeric parts up to tens of centimeters in size with feature resolution below 100 micrometers is demonstrated and critical control parameters are delineated and shown that complex solid parts can be drawn out of the resin at rates of hundreds of millimeters per hour.
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Adsorption-induced scission of carbon–carbon bonds
Sergei S. Sheiko,Frank C. Sun,Adrian Randall,David Shirvanyants,Michael Rubinstein,Hyung-il Lee,Krzysztof Matyjaszewski +6 more
TL;DR: It is shown that simple adsorption of brush-like macromolecules with long side chains on a substrate can induce not only conformational deformations, but also spontaneous rupture of covalent bonds in themacromolecular backbone.
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Effect of Initiation Conditions on the Uniformity of Three-Arm Star Molecular Brushes
TL;DR: A series of three-arm star densely grafted molecular brushes with poly(n-butyl acrylate) side chains were prepared by atom transfer radical polymerization (ATRP) as discussed by the authors.
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Engineering extrinsic disorder to control protein activity in living cells.
Onur Dagliyan,Miroslaw Tarnawski,Pei Hsuan Chu,David Shirvanyants,Ilme Schlichting,Nikolay V. Dokholyan,Klaus M. Hahn +6 more
TL;DR: The authors engineered domains into three different classes of proteins involved in cell signaling and found that switching the proteins between active and inactive states could control the shape and movement of living cells.
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Discrete molecular dynamics: an efficient and versatile simulation method for fine protein characterization.
TL;DR: In this article, the authors employ discrete molecular dynamics simulations with an all-atom force field to fold fast-folding proteins and demonstrate that DMD can be used to observe equilibrium folding of villin headpiece and WW domain, and sample near-native states in ab initio folding of proteins of ∼100 residues.