Ora Schueler-Furman
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Protein–protein docking with simultaneous optimization of rigid-body displacement and side-chain conformations
JJ Gray, S Moughon, C Wang, O Schueler-Furman, B Kuhlman, CA Rohl, ...
Journal of molecular biology 331 (1), 281-299, 2003
Macromolecular modeling and design in Rosetta: recent methods and frameworks
JK Leman, BD Weitzner, SM Lewis, J Adolf-Bryfogle, N Alam, RF Alford, ...
Nature methods 17 (7), 665-680, 2020
Sub‐angstrom modeling of complexes between flexible peptides and globular proteins
B Raveh, N London, O Schueler‐Furman
Proteins: Structure, Function, and Bioinformatics 78 (9), 2029-2040, 2010
The structural basis of peptide-protein binding strategies
N London, D Movshovitz-Attias, O Schueler-Furman
Structure 18 (2), 188-199, 2010
Rosetta FlexPepDock web server—high resolution modeling of peptide–protein interactions
N London, B Raveh, E Cohen, G Fathi, O Schueler-Furman
Nucleic acids research 39 (suppl_2), W249-W253, 2011
Progress in modeling of protein structures and interactions
O Schueler-Furman, C Wang, P Bradley, K Misura, D Baker
science 310 (5748), 638-642, 2005
Rosetta FlexPepDock ab-initio: simultaneous folding, docking and refinement of peptides onto their receptors
B Raveh, N London, L Zimmerman, O Schueler-Furman
PloS one 6 (4), e18934, 2011
Improved side‐chain modeling for protein–protein docking
C Wang, O Schueler‐Furman, D Baker
Protein Science 14 (5), 1328-1339, 2005
Protein–peptide docking: opportunities and challenges
M Ciemny, M Kurcinski, K Kamel, A Kolinski, N Alam, O Schueler-Furman, ...
Drug discovery today 23 (8), 1530-1537, 2018
Druggable protein–protein interactions–from hot spots to hot segments
N London, B Raveh, O Schueler-Furman
Current opinion in chemical biology 17 (6), 952-959, 2013
Rosetta predictions in CASP5: successes, failures, and prospects for complete automation
P Bradley, D Chivian, J Meiler, KMS Misura, CA Rohl, WR Schief, ...
Proteins: Structure, Function, and Bioinformatics 53 (S6), 457-468, 2003
Application of asymmetric statistical potentials to antibody–protein docking
R Brenke, DR Hall, GY Chuang, SR Comeau, T Bohnuud, D Beglov, ...
Bioinformatics 28 (20), 2608-2614, 2012
Structure-based prediction of binding peptides to MHC class I molecules: application to a broad range of MHC alleles
O Schueler-Furman, Y Altuvia, A Sette, H Margalit
Protein Science 9 (9), 1838-1846, 2000
Harnessing protein folding neural networks for peptide–protein docking
T Tsaban, JK Varga, O Avraham, Z Ben-Aharon, A Khramushin, ...
Nature communications 13 (1), 176, 2022
Relacin, a novel antibacterial agent targeting the stringent response
E Wexselblatt, Y Oppenheimer-Shaanan, I Kaspy, N London, ...
Public Library of Science 8 (9), e1002925, 2012
Can self‐inhibitory peptides be derived from the interfaces of globular protein–protein interactions?
N London, B Raveh, D Movshovitz‐Attias, O Schueler‐Furman
Proteins: Structure, Function, and Bioinformatics 78 (15), 3140-3149, 2010
Ubiquitination and degradation of the inhibitors of NF-κB
N Kanarek, N London, O Schueler-Furman, Y Ben-Neriah
Cold Spring Harbor perspectives in biology 2 (2), a000166, 2010
Community-wide assessment of protein-interface modeling suggests improvements to design methodology
SJ Fleishman, TA Whitehead, EM Strauch, JE Corn, S Qin, HX Zhou, ...
Journal of molecular biology 414 (2), 289-302, 2011
Protein–protein docking predictions for the CAPRI experiment
JJ Gray, SE Moughon, T Kortemme, O Schueler‐Furman, KMS Misura, ...
Proteins: Structure, Function, and Bioinformatics 52 (1), 118-122, 2003
High-resolution global peptide-protein docking using fragments-based PIPER-FlexPepDock
N Alam, O Goldstein, B Xia, KA Porter, D Kozakov, O Schueler-Furman
PLoS computational biology 13 (12), e1005905, 2017
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Articles 1–20