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Nathan R. Kern

Researcher at Lehigh University

Publications -  13
Citations -  1005

Nathan R. Kern is an academic researcher from Lehigh University. The author has contributed to research in topics: Protein structure prediction & Viral membrane. The author has an hindex of 7, co-authored 10 publications receiving 454 citations. Previous affiliations of Nathan R. Kern include University of Kansas.

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CHARMM-GUI Membrane Builder for Complex Biological Membrane Simulations with Glycolipids and Lipoglycans.

TL;DR: These tools are expected to be useful in innovative and novel glycolipid/LPS/LOS modeling and simulation research by easing tedious and intricate steps in modeling complex biological systems and shall provide insight into structures, dynamics, and underlying mechanisms of complex glycolIPid-/ LPS-/LOS-containing biological membrane systems.
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Developing a Fully-glycosylated Full-length SARS-CoV-2 Spike Protein Model in a Viral Membrane.

TL;DR: This technical study describes all-atom modeling and simulation of a fully glycosylated full-length SARS-CoV-2 spike (S) protein in a viral membrane and makes structures available in CHARMM-GUI COVID-19 Archive so that researchers can use these models to carry out innovative and novel modeling andsimulation research for the prevention and treatment of CO VID-19.
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CHARMM-GUI Glycan Modeler for modeling and simulation of carbohydrates and glycoconjugates

TL;DR: A computational tool, Glycan Modeler for in silico N-/O-glycosylation of the target protein and generation of carbohydrate-only systems and the structural properties of modeled glycan structures investigated by running 2-μs molecular dynamics simulations of HIV envelope protein.
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CHARMM-GUI supports the Amber force fields

TL;DR: The development of FF-Converter is presented to prepare Amber simulation inputs with various Amber force fields within the current CHARMM-GUI workflow to support other simulation programs that support the Amber force field.
Posted ContentDOI

Modeling and Simulation of a Fully-glycosylated Full-length SARS-CoV-2 Spike Protein in a Viral Membrane

TL;DR: In this article, a fully-glycosylated full-length SARS-CoV-2 spike (S) protein in a viral membrane was modeled using template-based modeling, de-novo protein structure prediction, and loop modeling techniques in GALAXY.