L
Lauren Wickstrom
Researcher at City University of New York
Publications - 27
Citations - 7368
Lauren Wickstrom is an academic researcher from City University of New York. The author has contributed to research in topics: Solvation & Solvent models. The author has an hindex of 16, co-authored 26 publications receiving 5041 citations. Previous affiliations of Lauren Wickstrom include Borough of Manhattan Community College & Brookhaven National Laboratory.
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Journal ArticleDOI
ff14SB: Improving the Accuracy of Protein Side Chain and Backbone Parameters from ff99SB
James Maier,Carmenza Martinez,Koushik Kasavajhala,Lauren Wickstrom,Kevin Hauser,Carlos Simmerling +5 more
TL;DR: Together, these backbone and side chain modifications (hereafter called ff14SB) not only better reproduced their benchmarks, but also improved secondary structure content in small peptides and reproduction of NMR χ1 scalar coupling measurements for proteins in solution.
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Evaluating the performance of the ff99SB force field based on NMR scalar coupling data.
TL;DR: This work performs extensive replica-exchange molecular-dynamics simulations on Ala(3) and Ala(5) in TIP3P and TIP4P-Ew solvent models and suggests that the performance of ff99SB is among the best of currently available models.
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Improved Efficiency of Replica Exchange Simulations through Use of a Hybrid Explicit/Implicit Solvation Model
Asim Okur,Lauren Wickstrom,Melinda Layten,Raphaël Geney,Kun Song,and Viktor Hornak,Carlos Simmerling +6 more
TL;DR: An REMD variant in which the simulations are performed with a fully explicit solvent, but the calculation of exchange probability is carried out using a hybrid model, with the solvation shells calculated on the fly during the fully solvated simulation providing a dramatic decrease in the computational cost of REMD.
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Secondary structure bias in generalized Born solvent models: comparison of conformational ensembles and free energy of solvent polarization from explicit and implicit solvation.
TL;DR: It is shown that even when perfect radii are used the agreement of GB with TIP3P DeltaDeltaG(pol) values does not improve, suggesting a limit to the optimization of the effective Born radius calculation and that future efforts to improve the accuracy of GB models must extend beyond such optimizations.
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Large scale affinity calculations of cyclodextrin host-guest complexes: Understanding the role of reorganization in the molecular recognition process.
TL;DR: Interestingly, it is found that binding free energies are superior rank order predictors for a large subset containing the most flexible guests, which indicates that, while challenging, accurate modeling of reorganization effects can lead to ligand design models of superior predictive power for rank ordering relative to models based only on ligand-receptor interaction energies.