Search Results - "Hurley, Matthew F. D"

SARS-CoV-2 simulations go exascale to predict dramatic spike opening and cryptic pockets across the proteome by Zimmerman, Maxwell I., Porter, Justin R., Ward, Michael D., Singh, Sukrit, Vithani, Neha, Meller, Artur, Mallimadugula, Upasana L., Kuhn, Catherine E., Borowsky, Jonathan H., Wiewiora, Rafal P., Hurley, Matthew F. D., Harbison, Aoife M., Fogarty, Carl A., Coffland, Joseph E., Fadda, Elisa, Voelz, Vincent A., Chodera, John D., Bowman, Gregory R.

“…SARS-CoV-2 has intricate mechanisms for initiating infection, immune evasion/suppression and replication that depend on the structure and dynamics of its…”
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Fluorinated Aromatic Monomers as Building Blocks To Control α‑Peptoid Conformation and Structure by Gimenez, Diana, Zhou, Guangfeng, Hurley, Matthew F. D, Aguilar, Juan A, Voelz, Vincent A, Cobb, Steven L

“…Peptoids are peptidomimetics of interest in the fields of drug development and biomaterials. However, obtaining stable secondary structures is challenging, and…”
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Metal Cation-Binding Mechanisms of Q‑Proline Peptoid Macrocycles in Solution by Hurley, Matthew F. D, Northrup, Justin D, Ge, Yunhui, Schafmeister, Christian E, Voelz, Vincent A

“…The rational design of foldable and functionalizable peptidomimetic scaffolds requires the concerted application of both computational and experimental…”
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Metal-Binding Q‑Proline Macrocycles by Northrup, Justin D, Wiener, Jesse A, Hurley, Matthew F. D, Hou, Chun-Feng David, Keller, Taylor M, Baxter, Richard H. G, Zdilla, Michael J, Voelz, Vincent A, Schafmeister, Christian E

“…We introduce the efficient Fmoc-SPPS and peptoid synthesis of Q-proline-based, metal-binding macrocycles (QPMs), which bind metal cations and display nine…”
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Assigning confidence to molecular property prediction by Nigam, AkshatKumar, Pollice, Robert, Hurley, Matthew F D, Hickman, Riley J, Aldeghi, Matteo, Yoshikawa, Naruki, Chithrananda, Seyone, Voelz, Vincent A, Aspuru-Guzik, Alán

“…: Computational modeling has rapidly advanced over the last decades. Recently, machine learning has emerged as a powerful and cost-effective strategy to learn…”
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Application of established computational techniques to identify potential SARS-CoV-2 Nsp14-MTase inhibitors in low data regimes by Nigam, AkshatKumar, Hurley, Matthew F. D, Li, Fengling, Konko ová, Eva, Klíma, Martin, Tryl ová, Jana, Pollice, Robert, Çinaro lu, Sleyman Selim, Levin-Konigsberg, Roni, Handjaya, Jasemine, Schapira, Matthieu, Chau, Irene, Perveen, Sumera, Ng, Ho-Leung, Kaniskan, H. Ümit, Han, Yulin, Singh, Sukrit, Gorgulla, Christoph, Kundaje, Anshul, Jin, Jian, Voelz, Vincent A, Weber, Jan, Nencka, Radim, Boura, Evzen, Vedadi, Masoud, Aspuru-Guzik, Alán

“…The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has led to significant global morbidity and mortality. A crucial viral protein, the non-structural…”
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Open science discovery of potent noncovalent SARS-CoV-2 main protease inhibitors by Boby, Melissa L, Fearon, Daren, Ferla, Matteo, Filep, Mihajlo, Koekemoer, Lizbé, Robinson, Matthew C, Chodera, John D, Lee, Alpha A, London, Nir, von Delft, Annette, von Delft, Frank, Achdout, Hagit, Aimon, Anthony, Alonzi, Dominic S, Arbon, Robert, Aschenbrenner, Jasmin C, Balcomb, Blake H, Bar-David, Elad, Barr, Haim, Ben-Shmuel, Amir, Bennett, James, Bilenko, Vitaliy A, Borden, Bruce, Boulet, Pascale, Bowman, Gregory R, Brewitz, Lennart, Brun, Juliane, Bvnbs, Sarma, Calmiano, Mark, Carbery, Anna, Carney, Daniel W, Cattermole, Emma, Chang, Edcon, Chernyshenko, Eugene, Clyde, Austin, Coffland, Joseph E, Cohen, Galit, Cole, Jason C, Contini, Alessandro, Cox, Lisa, Croll, Tristan Ian, Cvitkovic, Milan, De Jonghe, Steven, Dias, Alex, Donckers, Kim, Dotson, David L, Douangamath, Alice, Duberstein, Shirly, Dudgeon, Tim, Dunnett, Louise E, Eastman, Peter, Erez, Noam, Eyermann, Charles J, Fairhead, Michael, Fate, Gwen, Fedorov, Oleg, Fernandes, Rafaela S, Ferrins, Lori, Foster, Richard, Foster, Holly, Fraisse, Laurent, Gabizon, Ronen, García-Sastre, Adolfo, Gawriljuk, Victor O, Gehrtz, Paul, Gileadi, Carina, Giroud, Charline, Glass, William G, Glen, Robert C, Glinert, Itai, Godoy, Andre S, Gorichko, Marian, Gorrie-Stone, Tyler, Griffen, Ed J, Haneef, Amna, Hassell Hart, Storm, Heer, Jag, Henry, Michael, Hill, Michelle, Horrell, Sam, Huang, Qiu Yu Judy, Huliak, Victor D, Hurley, Matthew F D, Israely, Tomer, Jajack, Andrew, Jansen, Jitske, Jnoff, Eric, Jochmans, Dirk, John, Tobias, Kaminow, Benjamin, Kang, Lulu, Kantsadi, Anastassia L, Kenny, Peter W, Kiappes, J L, Kinakh, Serhii O, Kovar, Boris, Krojer, Tobias, La, Van Ngoc Thuy, Laghnimi-Hahn, Sophie, Lefker, Bruce A

“…We report the results of the COVID Moonshot, a fully open-science, crowdsourced, and structure-enabled drug discovery campaign targeting the severe acute…”
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SARS-CoV-2 Simulations Go Exascale to Capture Spike Opening and Reveal Cryptic Pockets Across the Proteome by Zimmerman, Maxwell I., Porter, Justin R., Ward, Michael D., Singh, Sukrit, Vithani, Neha, Meller, Artur, Mallimadugula, Upasana L., Kuhn, Catherine E., Borowsky, Jonathan H., Wiewiora, Rafal P., Hurley, Matthew F. D., Harbison, Aoife M, Fogarty, Carl A, Coffland, Joseph E., Fadda, Elisa, Voelz, Vincent A., Chodera, John D., Bowman, Gregory R.

“…SARS-CoV-2 has intricate mechanisms for initiating infection, immune evasion/suppression, and replication, which depend on the structure and dynamics of its…”
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Assigning Confidence to Molecular Property Prediction by Nigam, AkshatKumar, Pollice, Robert, Hurley, Matthew F. D, Hickman, Riley J, Aldeghi, Matteo, Yoshikawa, Naruki, Chithrananda, Seyone, Voelz, Vincent A, Aspuru-Guzik, Alán

“…Introduction: Computational modeling has rapidly advanced over the last decades, especially to predict molecular properties for chemistry, material science and…”
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