Fix typo in author names

CV.tex

@@ -345,7 +345,7 @@ \section*{Preprints}
 
 \newarticle{hybrid-qm-mm}{Rufa DA, Bruce Macdonald, HE, Fass J, Wieder M, Grinaway PB, Roitberg AE, Isayev O, and \jdc}{Towards chemical accuracy for alchemical free energy calculations with hybrid physics-based machine learning / molecular mechanics potentials}{\emph{Preprint}}{bioR$\chi$iv}{https://doi.org/10.1101/2020.07.29.227959}{In this first use of hybrid machine learning / molecular mechanics (ML/MM) potentials for alchemical free energy calculations, we demonstrate how the improved modeling of intramolecular ligand energetics offered by the quantum machine learning potential ANI-2x can significantly improve the accuracy in predicting kinase inhibitor binding free energy by reducing the error from 0.97~kcal/mol to 0.47~kcal/mol, which could drastically reduce the number of compounds that must be synthesized in lead optimization campaigns for minimal additional computational cost.}
 
-\newarticle{foldingathome-covid-cryptic-pockets}{Zimmerman MI, Porter JR, Ward MD, Singh S, Vithani N, Meller A, Mallimadugula UL, Kuhn CE, Borowsky JH, Wiewiora RP, Hurley, MFD, Harbison AM, Fogarty CA, Coffland JE, EFadda E, Voelz VA$^\ddag$, \jdc$^\ddag$, Bowman GR$^\ddag$}{Citizen scientists create an exascale computer to combat COVID-19}{\emph{Preprint}}{bioR$\chi$iv}{https://doi.org/10.1101/2020.06.27.175430}{To accelerate a multitude of drug development activities to combat the global threat posed by COVID-19, over a million citizen scientists have banded together through the Folding@home distributed computing project to create the world’s first Exascale computer and simulate protein dynamics. An unprecedented 0.1 seconds of simulation of the viral proteome reveal how the spike complex uses conformational masking to evade an immune response, conformational changes implicated in the function of other viral proteins, and cryptic pockets that are absent in experimental structures. These structures and mechanistic insights present new targets for the design of therapeutics.}
+\newarticle{foldingathome-covid-cryptic-pockets}{Zimmerman MI, Porter JR, Ward MD, Singh S, Vithani N, Meller A, Mallimadugula UL, Kuhn CE, Borowsky JH, Wiewiora RP, Hurley, MFD, Harbison AM, Fogarty CA, Coffland JE, Fadda E, Voelz VA$^\ddag$, \jdc$^\ddag$, Bowman GR$^\ddag$}{Citizen scientists create an exascale computer to combat COVID-19}{\emph{Preprint}}{bioR$\chi$iv}{https://doi.org/10.1101/2020.06.27.175430}{To accelerate a multitude of drug development activities to combat the global threat posed by COVID-19, over a million citizen scientists have banded together through the Folding@home distributed computing project to create the world’s first Exascale computer and simulate protein dynamics. An unprecedented 0.1 seconds of simulation of the viral proteome reveal how the spike complex uses conformational masking to evade an immune response, conformational changes implicated in the function of other viral proteins, and cryptic pockets that are absent in experimental structures. These structures and mechanistic insights present new targets for the design of therapeutics.}
 
 \newarticle{kinase-selectivity-paper}{Albanese SK, \jdc, Volkamer A, Keng S, Abel R, and Wang L}{Is structure based drug design ready for selectivity optimization?}{\emph{Preprint}}{bioR$\chi$iv}{https://doi.org/10.1101/2020.07.02.185132}{We asked whether the similarity of binding sites in related kinases might result in a fortuitous cancellation of errors in using alchemical free energy calculations to predict kinase inhibitor selectivities. Surprisingly, we find that even distantly related kinases have sufficient correlation in their errors that predicting changes in selectivity can be much more accurate than predicting changes in potency due to this effect, and show how this could lead to large reductions in the number of molecules that must be synthesized to achieve a desired selectivity goal.}