Zobrazeno 1 - 10
of 36
pro vyhledávání: '"Gyu Rie Lee"'
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 21, Iss , Pp 158-167 (2023)
While deep learning (DL) has brought a revolution in the protein structure prediction field, still an important question remains how the revolution can be transferred to advances in structure-based drug discovery. Because the lessons from the recent
Externí odkaz:
https://doaj.org/article/32fafc9741104fbf9782d4e001dedc93
Autor:
Chen Keasar, Liam J. McGuffin, Björn Wallner, Gaurav Chopra, Badri Adhikari, Debswapna Bhattacharya, Lauren Blake, Leandro Oliveira Bortot, Renzhi Cao, B. K. Dhanasekaran, Itzhel Dimas, Rodrigo Antonio Faccioli, Eshel Faraggi, Robert Ganzynkowicz, Sambit Ghosh, Soma Ghosh, Artur Giełdoń, Lukasz Golon, Yi He, Lim Heo, Jie Hou, Main Khan, Firas Khatib, George A. Khoury, Chris Kieslich, David E. Kim, Pawel Krupa, Gyu Rie Lee, Hongbo Li, Jilong Li, Agnieszka Lipska, Adam Liwo, Ali Hassan A. Maghrabi, Milot Mirdita, Shokoufeh Mirzaei, Magdalena A. Mozolewska, Melis Onel, Sergey Ovchinnikov, Anand Shah, Utkarsh Shah, Tomer Sidi, Adam K. Sieradzan, Magdalena Ślusarz, Rafal Ślusarz, James Smadbeck, Phanourios Tamamis, Nicholas Trieber, Tomasz Wirecki, Yanping Yin, Yang Zhang, Jaume Bacardit, Maciej Baranowski, Nicholas Chapman, Seth Cooper, Alexandre Defelicibus, Jeff Flatten, Brian Koepnick, Zoran Popović, Bartlomiej Zaborowski, David Baker, Jianlin Cheng, Cezary Czaplewski, Alexandre Cláudio Botazzo Delbem, Christodoulos Floudas, Andrzej Kloczkowski, Stanislaw Ołdziej, Michael Levitt, Harold Scheraga, Chaok Seok, Johannes Söding, Saraswathi Vishveshwara, Dong Xu, Foldit Players consortium, Silvia N. Crivelli
Publikováno v:
Scientific Reports, Vol 8, Iss 1, Pp 1-18 (2018)
Abstract Every two years groups worldwide participate in the Critical Assessment of Protein Structure Prediction (CASP) experiment to blindly test the strengths and weaknesses of their computational methods. CASP has significantly advanced the field
Externí odkaz:
https://doaj.org/article/b0b847aec1154062a3c86bac14d94e55
Publikováno v:
PLoS ONE, Vol 9, Iss 11, p e113811 (2014)
Protein loop modeling is a tool for predicting protein local structures of particular interest, providing opportunities for applications involving protein structure prediction and de novo protein design. Until recently, the majority of loop modeling
Externí odkaz:
https://doaj.org/article/038353de217e47949be1339280c791c5
Autor:
An, Linna, Said, Meerit, Tran, Long, Majumder, Sagardip, Goreshnik, Inna, Gyu Rie Lee, Juergens, David, Dauparas, Justas, Anishchenko, Ivan, Coventry, Brian, Bera, Asim K., Kang, Alex, Levine, Paul M., Alvarez, Valentina, Pillai, Arvind, Norn, Christoffer, Feldman, David, Zorine, Dmitri, Hicks, Derrick R., Xinting Li
Publikováno v:
Science; 7/19/2024, Vol. 385 Issue 6706, p276-282, 7p, 4 Diagrams
Autor:
Andy Hsien-Wei Yeh, Christoffer Norn, Yakov Kipnis, Doug Tischer, Samuel J. Pellock, Declan Evans, Pengchen Ma, Gyu Rie Lee, Jason Z. Zhang, Ivan Anishchenko, Brian Coventry, Longxing Cao, Justas Dauparas, Samer Halabiya, Michelle DeWitt, Lauren Carter, K. N. Houk, David Baker
Publikováno v:
Nature, vol 614, iss 7949
De novo enzyme design has sought to introduce active sites and substrate-binding pockets that are predicted to catalyse a reaction of interest into geometrically compatible native scaffolds1,2, but has been limited by a lack of suitable protein struc
Autor:
Susana Vázquez Torres, Philip J. Y. Leung, Isaac D. Lutz, Preetham Venkatesh, Joseph L. Watson, Fabian Hink, Huu-Hien Huynh, Andy Hsien-Wei Yeh, David Juergens, Nathaniel R. Bennett, Andrew N. Hoofnagle, Eric Huang, Michael J MacCoss, Marc Expòsit, Gyu Rie Lee, Paul M. Levine, Xinting Li, Mila Lamb, Elif Nihal Korkmaz, Jeff Nivala, Lance Stewart, Joseph M. Rogers, David Baker
Many peptide hormones form an alpha-helix upon binding their receptors1–4, and sensitive detection methods for them could contribute to better clinical management.De novoprotein design can now generate binders with high affinity and specificity to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a1f71e8af52449b591ee281d1a65d41b
https://doi.org/10.1101/2022.12.10.519862
https://doi.org/10.1101/2022.12.10.519862
Publikováno v:
BIODESIGN. 9:47-50
Autor:
Jose Henrique Pereira, Ana C. Ebrecht, Lisa N. Kinch, R. Dustin Schaeffer, Ivan Anishchenko, Justas Dauparas, Udit Dalwadi, Gyu Rie Lee, Christoph Buhlheller, Diederik J. Opperman, David Baker, Tea Pavkov-Keller, Qian Cong, Caleb R. Glassman, Alberdina A. van Dijk, Jue Wang, Andria V. Rodrigues, Theo Sagmeister, Randy J. Read, Andy DeGiovanni, Hahnbeom Park, Paul D. Adams, Calvin K. Yip, Frank DiMaio, John E. Burke, Claudia Millán, K. Christopher Garcia, Carson Adams, Minkyung Baek, Nick V. Grishin, Sergey Ovchinnikov, Manoj K. Rathinaswamy
Publikováno v:
Science. 373:871-876
DeepMind presented notably accurate predictions at the recent 14th Critical Assessment of Structure Prediction (CASP14) conference. We explored network architectures that incorporate related ideas and obtained the best performance with a three-track
Autor:
Nick V. Grishin, Minkyung Baek, Udit Dalwadi, Gyu Rie Lee, Hahnbeom Park, Carson Adams, van Dijk Aa, Manoj K. Rathinaswamy, Theo Sagmeister, Qian Cong, Frank DiMaio, Randy J. Read, David Baker, Paul D. Adams, Sergey Ovchinnikov, Buhlheller C, Calvin K. Yip, Caleb R. Glassman, Ivan Anishchenko, Schaeffer Rd, Claudia Millán, Diederik J. Opperman, Tea Pavkov-Keller, Jose Henrique Pereira, Ana C. Ebrecht, Lisa N. Kinch, Jing Wang, John E. Burke, Kenan Christopher Garcia, Andria V. Rodrigues, Justas Dauparas, Andy DeGiovanni
DeepMind presented remarkably accurate protein structure predictions at the CASP14 conference. We explored network architectures incorporating related ideas and obtained the best performance with a 3-track network in which information at the 1D seque
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0c004bba94029129763bc982a1dcf7f6
https://doi.org/10.1101/2021.06.14.448402
https://doi.org/10.1101/2021.06.14.448402
Publikováno v:
Proteins
Because proteins generally fold to their lowest free energy states, energy-guided refinement in principle should be able to systematically improve the quality of protein structure models generated using homologous structure or co-evolution derived in