@article{ZhaoZhangBhuripanyoetal.2013,
  author    = {Zhao, Bo and Zhang, Keya and Bhuripanyo, Karan and Choi, Chan Hee J. and Villhauer, Eric B. and Li, Heng and Zheng, Ning and Kiyokawa, Hiroaki and Schindelin, Hermann and Yin, Jun},
  title     = {Profiling the Cross Reactivity of Ubiquitin with the Nedd8 Activating Enzyme by Phage Display},
  series = {PLoS ONE},
  volume    = {8},
  journal   = {PLoS ONE},
  number    = {e70312},
  issn      = {1932-6203},
  doi       = {10.1371/journal.pone.0070312},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-128479},
  year      = {2013},
  abstract  = {The C-terminal peptides of ubiquitin (UB) and UB-like proteins (UBLs) play a key role in their recognition by the specific activating enzymes (E1s) to launch their transfer through the respective enzymatic cascades thus modifying cellular proteins. UB and Nedd8, a UBL regulating the activity of cullin-RING UB ligases, only differ by one residue at their C-termini; yet each has its specific E1 for the activation reaction. It has been reported recently that UAE can cross react with Nedd8 to enable its passage through the UB transfer cascade for protein neddylation. To elucidate differences in UB recognition by UAE and NAE, we carried out phage selection of a UB library with randomized C-terminal sequences based on the catalytic formation of UB similar to NAE thioester conjugates. Our results confirmed the previous finding that residue 72 of UB plays a "gate-keeping" role in E1 selectivity. We also found that diverse sequences flanking residue 72 at the UB C-terminus can be accommodated by NAE for activation. Furthermore heptameric peptides derived from the C-terminal sequences of UB variants selected for NAE activation can function as mimics of Nedd8 to form thioester conjugates with NAE and the downstream E2 enzyme Ubc12 in the Nedd8 transfer cascade. Once the peptides are charged onto the cascade enzymes, the full-length Nedd8 protein is effectively blocked from passing through the cascade for the critical modification of cullin. We have thus identified a new class of inhibitors of protein neddylation based on the profiles of the UB C-terminal sequences recognized by NAE.},
  language  = {en}
}
@article{JiangOronClarketal.2016,
  author    = {Jiang, Yuxiang and Oron, Tal Ronnen and Clark, Wyatt T. and Bankapur, Asma R. and D'Andrea, Daniel and Lepore, Rosalba and Funk, Christopher S. and Kahanda, Indika and Verspoor, Karin M. and Ben-Hur, Asa and Koo, Da Chen Emily and Penfold-Brown, Duncan and Shasha, Dennis and Youngs, Noah and Bonneau, Richard and Lin, Alexandra and Sahraeian, Sayed M. E. and Martelli, Pier Luigi and Profiti, Giuseppe and Casadio, Rita and Cao, Renzhi and Zhong, Zhaolong and Cheng, Jianlin and Altenhoff, Adrian and Skunca, Nives and Dessimoz, Christophe and Dogan, Tunca and Hakala, Kai and Kaewphan, Suwisa and Mehryary, Farrokh and Salakoski, Tapio and Ginter, Filip and Fang, Hai and Smithers, Ben and Oates, Matt and Gough, Julian and T{\"o}r{\"o}nen, Petri and Koskinen, Patrik and Holm, Liisa and Chen, Ching-Tai and Hsu, Wen-Lian and Bryson, Kevin and Cozzetto, Domenico and Minneci, Federico and Jones, David T. and Chapman, Samuel and BKC, Dukka and Khan, Ishita K. and Kihara, Daisuke and Ofer, Dan and Rappoport, Nadav and Stern, Amos and Cibrian-Uhalte, Elena and Denny, Paul and Foulger, Rebecca E. and Hieta, Reija and Legge, Duncan and Lovering, Ruth C. and Magrane, Michele and Melidoni, Anna N. and Mutowo-Meullenet, Prudence and Pichler, Klemens and Shypitsyna, Aleksandra and Li, Biao and Zakeri, Pooya and ElShal, Sarah and Tranchevent, L{\´e}on-Charles and Das, Sayoni and Dawson, Natalie L. and Lee, David and Lees, Jonathan G. and Sillitoe, Ian and Bhat, Prajwal and Nepusz, Tam{\´a}s and Romero, Alfonso E. and Sasidharan, Rajkumar and Yang, Haixuan and Paccanaro, Alberto and Gillis, Jesse and Sede{\~n}o-Cort{\´e}s, Adriana E. and Pavlidis, Paul and Feng, Shou and Cejuela, Juan M. and Goldberg, Tatyana and Hamp, Tobias and Richter, Lothar and Salamov, Asaf and Gabaldon, Toni and Marcet-Houben, Marina and Supek, Fran and Gong, Qingtian and Ning, Wei and Zhou, Yuanpeng and Tian, Weidong and Falda, Marco and Fontana, Paolo and Lavezzo, Enrico and Toppo, Stefano and Ferrari, Carlo and Giollo, Manuel and Piovesan, Damiano and Tosatto, Silvio C. E. and del Pozo, Angela and Fern{\´a}ndez, Jos{\´e} M. and Maietta, Paolo and Valencia, Alfonso and Tress, Michael L. and Benso, Alfredo and Di Carlo, Stefano and Politano, Gianfranco and Savino, Alessandro and Rehman, Hafeez Ur and Re, Matteo and Mesiti, Marco and Valentini, Giorgio and Bargsten, Joachim W. and van Dijk, Aalt D. J. and Gemovic, Branislava and Glisic, Sanja and Perovic, Vladmir and Veljkovic, Veljko and Almeida-e-Silva, Danillo C. and Vencio, Ricardo Z. N. and Sharan, Malvika and Vogel, J{\"o}rg and Kansakar, Lakesh and Zhang, Shanshan and Vucetic, Slobodan and Wang, Zheng and Sternberg, Michael J. E. and Wass, Mark N. and Huntley, Rachael P. and Martin, Maria J. and O'Donovan, Claire and Robinson, Peter N. and Moreau, Yves and Tramontano, Anna and Babbitt, Patricia C. and Brenner, Steven E. and Linial, Michal and Orengo, Christine A. and Rost, Burkhard and Greene, Casey S. and Mooney, Sean D. and Friedberg, Iddo and Radivojac, Predrag and Veljkovic, Nevena},
  title     = {An expanded evaluation of protein function prediction methods shows an improvement in accuracy},
  series = {Genome Biology},
  volume    = {17},
  journal   = {Genome Biology},
  number    = {184},
  doi       = {10.1186/s13059-016-1037-6},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-166293},
  year      = {2016},
  abstract  = {Background A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent.},
  language  = {en}
}