James C. Gumbart

Dr. James C. Gumbart

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Research Focus & Metrics

Academic Career Length

18Years (2009-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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2 September 2013 in Journal of Computational Chemistry
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Journal Article
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CMChristopher G. Mayne
Christopher G. Mayne
JSJan Saam
Jan Saam
KSKlaus Schulten
Klaus Schulten
Emad TajkhorshidEmad Tajkhorshid
Emad Tajkhorshid
JGJames C. Gumbart
James C. Gumbart

4 April 2016 in Journal of Chemical Information and Modeling
Verified
Journal Article
Closed access
CLChristopher T. Lee
Christopher T. Lee
JCJeffrey Comer
Jeffrey Comer
CHConner Herndon
Conner Herndon
NLNelson Leung
Nelson Leung
APAnna Pavlova
Anna Pavlova
JGJames C. Gumbart
James C. Gumbart

16 December 2020 in Journal of Chemical Information and Modeling
Verified
Journal Article
Closed access
AAA. Acharya
A. Acharya
RARupesh Agarwal
Rupesh Agarwal
MBM. B. Baker
M. B. Baker
JBJerome Baudry
Jerome Baudry
DBDebsindhu Bhowmik
Debsindhu Bhowmik
LZL. Zanetti-Polzi
L. Zanetti-Polzi

2 July 2019 in Journal of Chemical Theory and Computation
Verified
Journal Article
Closed access
CBCurtis Balusek
Curtis Balusek
HHHyea Hwang
Hyea Hwang
CLChun Hon Lau
Chun Hon Lau
KLKarl Lundquist
Karl Lundquist
AHAnthony Hazel
Anthony Hazel
JGJames C. Gumbart
James C. Gumbart

28 November 2022 in Nature Materials
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Journal Article
Open access
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LRLaura Rotolo
Laura Rotolo
DVDaryll Vanover
Daryll Vanover
NBNicholas C. Bruno
Nicholas C. Bruno
HPHannah E. Peck
Hannah E. Peck
CZChiara Zurla
Chiara Zurla
PSPhilip J. Santangelo
Philip J. Santangelo
Messenger RNA has now been used to vaccinate millions of people. However, the diversity of pulmonary pathologies, including infections, genetic disorders, asthma and others, reveals the lung as an important organ to directly target for future RNA therapeutics and preventatives. Here we report the screening of 166 polymeric nanoparticle formulations for functional delivery to the lungs, obtained from a combinatorial synthesis approach combined with a low-dead-volume nose-only inhalation system for mice. We identify P76, a poly-β-amino-thio-ester polymer, that exhibits increased expression over formulations lacking the thiol component, delivery to different animal species with varying RNA cargos and low toxicity. P76 allows for dose sparing when delivering an mRNA-expressed Cas13a-mediated treatment in a SARS-CoV-2 challenge model, resulting in similar efficacy to a 20-fold higher dose of a neutralizing antibody. Overall, the combinatorial synthesis approach allowed for the discovery of promising polymeric formulations for future RNA pharmaceutical development for the lungs.

20 February 2014 in PLOS Computational Biology
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Journal Article
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JGJames C. Gumbart
James C. Gumbart
MBMorgan Beeby
Morgan Beeby
GJGrant J Jensen
Grant J Jensen
BRBenoît Roux
Benoît Roux
Bacteria face the challenging requirement to maintain their shape and avoid rupture due to the high internal turgor pressure, but simultaneously permit the import and export of nutrients, chemical signals, and virulence factors. The bacterial cell wall, a mesh-like structure composed of cross-linked strands of peptidoglycan, fulfills both needs by being semi-rigid, yet sufficiently porous to allow diffusion through it. How the mechanical properties of the cell wall are determined by the molecular features and the spatial arrangement of the relatively thin strands in the larger cellular-scale structure is not known. To examine this issue, we have developed and simulated atomic-scale models of Escherichia coli cell walls in a disordered circumferential arrangement. The cell-wall models are found to possess an anisotropic elasticity, as known experimentally, arising from the orthogonal orientation of the glycan strands and of the peptide cross-links. Other features such as thickness, pore size, and disorder are also found to generally agree with experiments, further supporting the disordered circumferential model of peptidoglycan. The validated constructs illustrate how mesoscopic structure and behavior emerge naturally from the underlying atomic-scale properties and, furthermore, demonstrate the ability of all-atom simulations to reproduce a range of macroscopic observables for extended polymer meshes. The structure of the bacterial cell wall has been a point of controversy and contention since it was first discovered. Although the basic chemical composition of peptidoglycan, the key constituent of the cell wall, is now well established, its long-range organization is not. This dearth of information at the mesoscopic scale is a result of the inability of experimental imaging techniques to simultaneously visualize both the atomic-level detail of the peptidoglycan network and its macroscopic arrangement around the bacterium. Now, using molecular dynamics (MD) simulations, we have carefully constructed and validated models of sections of the Escherichia coli cell wall in full atomic detail. By comparing various properties of these models, including elasticity, pore size, and thickness with experiments, we can discriminate between them, resolving which best represents the native wall structure. In doing so, our study provides approaches for connecting measurements made in atomic-scale MD simulations with large-scale and even macroscopic properties.