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TargetDB: a target registration database for structural genomics projects
Open accessAbstract
Summary: TargetDB is a centralized target registration database that includes protein target data from the NIH structural genomics centers and a number of international sites. TargetDB, which is hosted by the Protein Data Bank (RCSB PDB), provides status information on target sequences and tracks their progress through the various stages of protein production and structure determination. A simple search form permits queries based on contributing site, target ID, protein name, sequence, status and other data. The progress of individual targets or entire structural genomics projects may be tracked over time, and target data from all contributing centers may also be downloaded in the XML format. Availability: TagetDB is available at http://targetdb.pdb.org/
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“However, it is important to realize that the majority of sequences in our final dataset stem from TargetDB which con- tains only brief descriptions of experimental results and does not impose standard requirements for annotation.”
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“Models built based on a specific template structure can be also retrieved by entering either PDB accession codes (54) or structural genomics targets identifiers (101).”
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“The RCSB PDB has created an online portal to track the progress of SG efforts (http://sg.pdb.org/ )[ 7]. A target registration database, TargetDB (http://targetdb.pdb.org/) [ 24 ], was founded in 2001 to track the sequence, status and other information about the targets being studied at the SG centers.”
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“As a screening mechanism to avoid duplication of effort, the protein input and associated sequences are searched against the PDB (18) and TargetDB ( 25 ).”
BackgroundMethodInfluentialSolubility-Weighted Index: fast and accurate prediction of protein solubility
Bhandari, B. K., Gardner, P. P., & Lim, C. S. (2020) · Bioinformatics · doi:10.1093/bioinformatics/btaa578 · Cited by 97
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“The Therapeutic Targets Database 291 provides a large volume of data about known therapeutic targets, and TargetDB or TargetTrack focuses on structural information of known targets 292 .”
BackgroundSoluble expression of proteins correlates with a lack of positively-charged surface
Chan, P., Curtis, R., & Warwicker, J. (2013) · Scientific Reports · doi:10.1038/srep03333 · Cited by 92
WormBase: new content and better access
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“Information from the Protein Data Bank’s TargetDB ( 11 ) (http://targetdb.pdb.org/), which provides status and tracking information on the production and solution of structures, is now displayed on Gene pages.”
MethodChang, C. C. H., Song, J., Tey, B. T., & Ramanan, R. N. (2013) · Briefings in Bioinformatics · doi:10.1093/bib/bbt057 · Cited by 90
“TargetDB [30] and Protein Data Bank [31] as their 956 Ching Han Chang et al.”
MethodWang, C., & Zou, Q. (2023) · BMC Biology · doi:10.1186/s12915-023-01510-8 · Cited by 94
“The remaining eight predictors were built based on three comprehensive databases, namely, TargetDB [27], PepcDB [27], and TargetTrack [28].”
BackgroundMethodCRYSTALP2: sequence-based protein crystallization propensity prediction
Kurgan, L., Razib, A., Aghakhani, S., Dick, S., Mizianty, M. J., & Jahandideh, S. S. (2009) · BMC Structural Biology · doi:10.1186/1472-6807-9-50 · Cited by 83
“XtalPred compares nine biochemical and biophysical features of an input protein with probability distributions estimated from data from the TargetDB data-base http://targetdb.pdb.org/ [25].”
MethodTowards Fully Automated Structure-based Function Prediction in Structural Genomics: A Case Study
Watson, J. D., Sanderson, S., Ezersky, A., Savchenko, A. V., Edwards, A. M., Orengo, C. A., Joachimiak, A., Laskowski, R. A., & Thornton, J. M. (2007) · Journal of Molecular Biology · doi:10.1016/j.jmb.2007.01.063 · Cited by 80
Sequence-based prediction of protein crystallization, purification and production propensity
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Will my protein crystallize? A sequence‐based predictor
Smialowski, P., Schmidt, T., Cox, J., Kirschner, A., & Frishman, D. (2005) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.20789 · Cited by 78
“Most of the structures deposited in the Protein Data Bank(14) (PDB) so far are based on the X-ray method.(14,15) Use of the NMR technique, however, dominates in the field of protein dynamics,(16) protein–protein interactions, and protein–ligand interactions.”
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“The SBKB has also established additional portals (Table 1) to capture data produced by the PSI including protein selection and status (TargetDB [7]), their trial history and protocols (PepcDB [8]), homology models (Protein Model Portal [9]), developed technologies (PSI Technology Portal), and…”
BackgroundMethodSelf-citationStructural genomics is the largest contributor of novel structural leverage
Nair, R. P., Liu, J., Soong, T.-T., Acton, T., Everett, J. K., Kouranov, A., Fiser, A., Godzik, A., Jaroszewski, L., Orengo, C. A., et al. (2009) · Journal of Structural and Functional Genomics · doi:10.1007/s10969-008-9055-6 · Cited by 77
“All data about the status of structural genomics targets were taken from TargetDB [9].”
MethodInfluentialSmall angle X‐ray scattering as a complementary tool for high‐throughput structural studies
Grant, T. D., Luft, J. R., Wolfley, J. R., Tsuruta, H., Martel, A., Montelione, G. T., & Snell, E. H. (2011) · Biopolymers · doi:10.1002/bip.21630 · Cited by 75
Luft, J. R., Wolfley, J. R., & Snell, E. H. (2011) · Crystal Growth & Design · doi:10.1021/cg1013945 · Cited by 67
Habibi, N., Hashim, S. Z. M., Norouzi, A., & Samian, M. R. (2014) · BMC Bioinformatics · doi:10.1186/1471-2105-15-134 · Cited by 68
“Random forest [45] SVM recursive feature elimination (SvmRfe) [46] One attribute rule [47] integrating different search results of TargetDB, Protein Data Bank (PDB), and Swiss-Prot database.”
BackgroundThe impact of structural genomics: the first quindecennial
Grabowski, M., Niedzialkowska, E., Zimmerman, M., & Minor, W. (2016) · Journal of Structural and Functional Genomics · doi:10.1007/s10969-016-9201-5 · Cited by 67
“Many SG centers developed their own systems for aggregating and reporting experimental data to the TargetTrack system via XML-formatted reports.”
BackgroundInfluentialUtilization of protein intrinsic disorder knowledge in structural proteomics
Oldfield, C. J., Xue, B., Van, Y.-Y. J., Ulrich, E. L., Markley, J. L., Dunker, A. K., & Uversky, V. N. (2012) · Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics · doi:10.1016/j.bbapap.2012.12.003 · Cited by 63
“…all the proteins currently available at the PSI Structural Biology Knowledgebase (http://sbkb.org), namely at its target progress tracking module (TargetTrack: http://sbkb.org/tt/), which provides status and tracking information on the production protein targets and their structure solution [31].”
BackgroundHalperin, I., Glazer, D. S., Wu, S., & Altman, R. B. (2008) · BMC Genomics · doi:10.1186/1471-2164-9-s2-s2 · Cited by 65
“With this in mind, we scanned all of the SG targets in Tar-getDB [55] associated with unknown function through October 2007 using the SeqFEATURE library, filtered for the highest confidence predictions (based on model-dependent score cutoffs), and compared them to predictions made by a number of…”
MethodOverton, I. M., Padovani, G., Girolami, M., & Barton, G. J. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btn055 · Cited by 65
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Target-Pathogen: a structural bioinformatic approach to prioritize drug targets in pathogens
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“Another database that includes data of known targets is TargetDB/TargetTrack (40), but only focuses on structural information.”
BackgroundCormier, C. Y., Mohr, S. E., Zuo, D., Hu, Y., Rolfs, A., Kramer, J., Taycher, E., Kelley, F., Fiacco, M., Turnbull, G., et al. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp999 · Cited by 61
“truncations or mutations), and the reasons for stopping work on a particular target (23,24).”
Automated protein structure calculation from NMR data
Williamson, M. P., & Craven, C. J. (2009) · Journal of Biomolecular NMR · doi:10.1007/s10858-008-9295-6 · Cited by 61
“The first is improvements to current methods, for example using methods for predicting or matching expected chemical shift values (Fiorito et al. 2008; Hitchens et al. 2003; Malmodin et al. 2003; Moseley et al. 2004a ), and combining J-coupling-based spectra with NOE-based spectra in conjunction with databases that gi…”
BackgroundMethodInfluentialPSI:Biology-materials repository: a biologist’s resource for protein expression plasmids
Cormier, C. Y., Park, J. G., Fiacco, M., Steel, J., Hunter, P. D., Kramer, J., Singla, R. K., & LaBaer, J. (2011) · Journal of Structural and Functional Genomics · doi:10.1007/s10969-011-9100-8 · Cited by 57
A normalised scale for structural genomics target ranking: The OB‐Score
Overton, I. M., & Barton, G. J. (2006) · FEBS Letters · doi:10.1016/j.febslet.2006.06.015 · Cited by 57
“Test data for proteins expected to produce diffraction-quality crystals were taken from 1212 TargetDB [20] entries for which diffraction-quality crystals had been indicated (TDB_DIF).”
PubNet: a flexible system for visualizing literature derived networks
Douglas, S. M., Montelione, G. T., & Gerstein, M. (2005) · Genome biology · doi:10.1186/gb-2005-6-9-r80 · Cited by 54
“The structural genomics PDB IDs were extracted from TargetDB [21], and sets of 300 regular PDB IDs were selected randomly from a total of 3,112 unique structures released in 2001-2002 that included a primary citation available in PubMed.”
MethodFrom Genome to Drugs: New Approaches in Antimicrobial Discovery
Serral, F., Castello, F. A., Sosa, E. J., Pardo, A., Palumbo, M. C., Modenutti, C. P., Palomino, M. M., Lazarowski, A., Auzmendi, J., Ramos, P. I. P., et al. (2021) · Frontiers in Pharmacology · doi:10.3389/fphar.2021.647060 · Cited by 53
Improving the chances of successful protein structure determination with a random forest classifier
Jahandideh, S. S., Jaroszewski, L., & Godzik, A. (2014) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s1399004713032070 · Cited by 53
“These data were collected in the PSI TargetDB database (Chen et al. , 2004), which enabled large-scale data-mining for protein crystallization (Christendat et al. , 2000; Canaves et al. , 2004; Goh et al. , 2004; Smialowski et al. , 2006).”
MethodThe accurate assessment of small-angle X-ray scattering data
Grant, T. D., Luft, J. R., Carter, L. G., Matsui, T., Weiss, T. M., Martel, A., & Snell, E. H. (2014) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s1399004714010876 · Cited by 52
“Success and failure, tracked at each stage of the process, showed that 12% of soluble purified proteins from the initiative resulted in structures deposited in the Protein Data Bank (PDB; Chen et al., 2004).”
BackgroundLessons from high-throughput protein crystallization screening: 10 years of practical experience
Luft, J. R., Snell, E. H., & DeTitta, G. T. (2011) · Expert Opinion on Drug Discovery · doi:10.1517/17460441.2011.566857 · Cited by 51
“[6] While these numbers are impressive, of immediate note is the loss associated with the process.”
BackgroundInfluentialPrice, W. N., Handelman, S. K., Everett, J. K., Tong, S. N., Bracic, A., Luff, J. D., Naumov, V., Acton, T., Manor, P. C., Xiao, R., et al. (2011) · Microbial Informatics and Experimentation · doi:10.1186/2042-5783-1-6 · Cited by 52
“, not progressing past the “expressed” stage in TargetDB [44], which tracks the progress of structural genomics projects).”
BackgroundInfluentialComprehensive Structural Classification of Ligand-Binding Motifs in Proteins
Kinjo, A. R., & Nakamura, H. (2009) · Structure · doi:10.1016/j.str.2008.11.009 · Cited by 45
“In this way, we are currently annotating all structural genomics targets (Chen et al., 2004).”
MethodStructural genomics: from genes to structures with valuable materials and many questions in between
Fox, B. G., Goulding, C. W., Malkowski, M. G., Stewart, L. J., & Deacon, A. M. (2008) · Nature Methods · doi:10.1038/nmeth0208-129 · Cited by 45
Seeing is believing: the impact of structural genomics on antimicrobial drug discovery
Schmid, M. B. (2004) · Nature Reviews Microbiology · doi:10.1038/nrmicro978 · Cited by 42
Johnson, D. E., Xue, B., Sickmeier, M. D., Meng, J., Cortese, M. S., Oldfield, C. J., LeGall, T., Dunker, A. K., & Uversky, V. N. (2012) · Journal of Structural Biology · doi:10.1016/j.jsb.2012.05.013 · Cited by 41
“…(TargetDB: http://targetdb.rcsb.org), which provided status and tracking information on the production protein targets and their structure solution (Chen et al., 2004), and the experimental protocol tracking database (Protein Expression, Purification, and Crystallization Database (PepcDB):…”
MethodLearning to predict expression efficacy of vectors in recombinant protein production
Chan, W.-C., Liang, P., Shih, Y., Yang, U., Lin, W., & Hsu, C.-N. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-s1-s21 · Cited by 38
“utilized random forest and decisiontree based methods on about 27, 000 protein targets in TargetDB [16] to conclude that the most significant protein feature was serine percentage composition [17].”
MethodA pipeline for structure determination ofin vivo-grown crystals usingin cellulodiffraction
Boudes, M., Garriga, D., Fryga, A., Caradoc-Davies, T. T., & Coulibaly, F. (2016) · Acta Crystallographica Section D Structural Biology · doi:10.1107/s2059798316002369 · Cited by 41
“For instance, the success rate in generating crystals suitable for an X-ray diffraction experiment is estimated at only 27% by the Protein Structure Initiative (data from the TargetTrack database; Chen et al., 2004; http://sbkb.org/tt/).”
MethodWang, H., Wang, M., Tan, H., Li, Y., Zhang, Z., & Song, J. (2014) · PLoS ONE · doi:10.1371/journal.pone.0105902 · Cited by 40
Structural genomics: keeping up with expanding knowledge of the protein universe
Grabowski, M., Joachimiak, A., Otwinowski, Z., & Minor, W. (2007) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2007.06.003 · Cited by 40
“The families of these sequences were largely covered by the set of SG targets selected during the pilot phase of PSI [15,16].”
BackgroundAnnotating the human proteome: Beyond establishing a parts list
Mueller, M., Martens, L., & Apweiler, R. (2006) · Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics · doi:10.1016/j.bbapap.2006.11.011 · Cited by 37
Mirković, N., Li, Z., Parnassa, A., & Murray, D. (2006) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.21191 · Cited by 37
“19 The NESG target list is publicly accessible via an NESG Web site called ZebaView, 17 which links to TargetDB, 20 the official compilation of structural genomics targets.”
MethodData Management in the Modern Structural Biology and Biomedical Research Environment
Zimmerman, M. D., Grabowski, M., Domagalski, M. J., MacLean, E., Chruszcz, M., & Minor, W. (2014) · Methods in molecular biology · doi:10.1007/978-1-4939-0354-2_1 · Cited by 37
“In the specific case of the centers funded by NIGMS and NIAID, the NIH established the target registration database, TargetDB [11], and required that all member consortia deposit data on the progress of their targets.”
BackgroundMethodTISIGNER.com: web services for improving recombinant protein production
Bhandari, B. K., Lim, C. S., & Gardner, P. P. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab175 · Cited by 38
Data Deposition and Annotation at the Worldwide Protein Data Bank
Dutta, S., Burkhardt, K., Swaminathan, G. J., Kosada, T., Henrick, K., Nakamura, H., & Berman, H. M. (2008) · Methods in molecular biology · doi:10.1007/978-1-60327-058-8_5 · Cited by 35
“org/) [24], was founded in 2001 to track the sequence, status and other information about the targets being studied at the SG centers.”
BackgroundSelf-citationBuilding a drug–target network and its applications
Lee, S., Park, K., & Kim, D. (2009) · Expert Opinion on Drug Discovery · doi:10.1517/17460440903322234 · Cited by 37
“TargetDB [17] provides the status information on target sequences and tracks their progress through the various stages of protein production and structure determination.”
BackgroundCovering complete proteomes with X-ray structures: a current snapshot
Mizianty, M. J., Fan, X., Yan, J. R., Chalmers, E., Woloschuk, C., Joachimiak, A., & Kurgan, L. (2014) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s1399004714019427 · Cited by 35
“These resources were combined into centralized databases, including TargetDB (Chen et al., 2004) and PepcDB (Protein Expression Purification and Crystallization DataBase; Kouranov et al., 2006), which were recently combined in the TargetTrack knowledgebase (Berman et al., 2009; Gabanyi et al., 2011).”
Methodvon Grotthuss, M., Plewczyński, D., Ginalski, K., Rychlewski, L., & Shakhnovich, E. I. (2006) · BMC Bioinformatics · doi:10.1186/1471-2105-7-53 · Cited by 35
“Over 30 structural genomics centers have been established worldwide with the common goal of large-scale, highthroughput structure determination using X-ray crystallography and NMR[1].”
BackgroundFold recognition by combining profile-profile alignment and support vector machine
Han, S., Lee, B., Yu, S. T., Jeong, C.-S., Lee, S., & Kim, D. (2005) · Computer applications in the biosciences · doi:10.1093/bioinformatics/bti384 · Cited by 35
Structural genomics plucks high-hanging membrane proteins
Kloppmann, E., Punta, M., & Rost, B. (2012) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2012.05.002 · Cited by 34
Polymer‐driven crystallization
Nauli, S., Farr, S., Lee, Y., Kim, H., Faham, S., & Bowie, J. U. (2007) · Protein Science · doi:10.1110/ps.073074207 · Cited by 34
“For example, a search of the TargetDB (Chen et al. 2004) database shows that diffraction-quality crystals were obtained for only 12% of the ;28,000 soluble proteins that were expressed by structural genomics centers worldwide.”
BackgroundStructure Comparison and Alignment
Bourne, P. E., & Shindyalov, I. N. (2003) · Methods of biochemical analysis · doi:10.1002/0471721204.ch16 · Cited by 34
Benefits of Structural Genomics for Drug Discovery Research
Grabowski, M., Chruszcz, M., Zimmerman, M. D., Kirillova, O., & Minor, W. (2009) · Infectious Disorders - Drug Targets · doi:10.2174/187152609789105704 · Cited by 31
Protein Function Analysis through Machine Learning
Avery, C., Patterson, J., Grear, T. J., Frater, T. D., & Jacobs, D. J. (2022) · Biomolecules · doi:10.3390/biom12091246 · Cited by 30
Target Selection for Structural Genomics: An Overview
Marsden, R. L., & Orengo, C. A. (2008) · Methods in molecular biology · doi:10.1007/978-1-60327-058-8_1 · Cited by 29
Target selection and deselection at the Berkeley Structural Genomics Center
Chandonia, J., Kim, S., & Brenner, S. E. (2005) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.20674 · Cited by 28
Current methods in structural proteomics and its applications in biological sciences
Manjasetty, B. A., Büssow, K., Panjikar, S., & Turnbull, A. P. (2011) · 3 Biotech · doi:10.1007/s13205-011-0037-1 · Cited by 27
“Sub-sequently, the Protein Structure Initiative Knowledgebase (PSIKB) was created by integrating TargetDB and PepcDB to turn the products of the SP effort into knowledge that can be accessed by the life sciences community (Berman et al. 2009).”
BackgroundA Novel Structure of an Antikinase and its Inhibitor
Jacques, D. A., Langley, D. B., Hynson, R. M. G., Whitten, A. E., Kwan, A. H., Guss, J. M., & Trewhella, J. (2010) · Journal of Molecular Biology · doi:10.1016/j.jmb.2010.10.047 · Cited by 27
Meta prediction of protein crystallization propensity
Mizianty, M. J., & Kurgan, L. (2009) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2009.09.036 · Cited by 27
“Analysis of data published in the TargetDB database [9], a world-wide repository for information on the experimental progress and status of targets selected for structure determination, shows that only about 8.”
BackgroundCritical evaluation of bioinformatics tools for the prediction of protein crystallization propensity
Wang, H., Feng, L., Webb, G. I., Kurgan, L., Song, J., & Lin, D. (2017) · Briefings in Bioinformatics · doi:10.1093/bib/bbx018 · Cited by 27
Derewenda, Z. S., & Godzik, A. (2017) · Methods in molecular biology · doi:10.1007/978-1-4939-7000-1_4 · Cited by 26
“Availability of such data, collected in the databases of individual PSI centers and, with some caveats, in the TargetDB database [84], enabled development of a first generation of algorithms for evaluation of probability of crystallization of proteins [85–88].”
BackgroundDiscrimination of soluble and aggregation-prone proteins based on sequence information
Fang, Y., & Fang, J. (2013) · Molecular BioSystems · doi:10.1039/c3mb70033j · Cited by 25
Analysis of crystallization data in the Protein Data Bank
Kirkwood, J., Hargreaves, D., O’Keefe, S., & Wilson, J. C. (2015) · Acta Crystallographica Section F Structural Biology Communications · doi:10.1107/s2053230x15014892 · Cited by 25
“Overton et al. (2008) formed the FEAT data set using 1456 sequences obtained from TargetDB (now TargetTrack; TargetTrack, 2015; Chen et al., 2004).”
MethodBhandari, B. K., Lim, C. S., Remus, D. M., Chen, A., van Dolleweerd, C. J., & Gardner, P. P. (2021) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1009461 · Cited by 26
The Research Collaboratory for Structural Bioinformatics Protein Data Bank
Bourne, P. E., Bluhm, W. F., Deshpande, N., Zhang, Q., Berman, H. M., & Flippen-Anderson, J. L. (2007) · Elsevier eBooks · doi:10.1016/b0-08-045044-x/00090-0 · Cited by 24
Self-citationXANNpred: Neural nets that predict the propensity of a protein to yield diffraction‐quality crystals
Overton, I. M., van Niekerk, C. A. J., & Barton, G. J. (2010) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.22914 · Cited by 23
Kurgan, L., & Mizianty, M. J. (2009) · Natural Science · doi:10.4236/ns.2009.12012 · Cited by 22
“The annotations from TargetDB were stripped from the input sequences, which in turn were inputted into the corresponding predictors.”
BackgroundMethodInfluentialA statistical model for improved membrane protein expression using sequence-derived features
Saladi, S. M., Javed, N. M., Müller, A., & Clemons, W. (2018) · Journal of Biological Chemistry · doi:10.1074/jbc.ra117.001052 · Cited by 24
“Such predictors are primarily based on available experimental results from the Protein Structure Initiative (26, 27).”
BackgroundMethodInfluentialWu, S., Liang, M., & Altman, R. B. (2008) · Genome biology · doi:10.1186/gb-2008-9-1-r8 · Cited by 22
“Structural genomics data and targets from almost all structural genomics centers are stored centrally in TargetDB [4], a database accessible from the PDB.”
BackgroundSPINE bioinformatics and data-management aspects of high-throughput structural biology
Albeck, S., Alzari, P. M., Andreini, C., Banci, L., Berry, I. M., Bertini, I., Cambillau, C., Canard, B., Carter, L. G., Cohen, S. X., et al. (2006) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s090744490602991x · Cited by 22
“The different colours indicate different sources of information, e.g. yellow, PDB entries; orange, domain definitions; magenta, SCOP definitions; white, TargetDB entries.”
BackgroundMethodInfluentialStructural genomics and the Protein Data Bank
Michalska, K., & Joachimiak, A. (2021) · Journal of Biological Chemistry · doi:10.1016/j.jbc.2021.100747 · Cited by 24
“SG-created resources included Target Registration Database (TargetDB) (44, 45) and PepcDB (Protein Expression Purification and Crystallization Data Base; (46)), which were eventually merged in the TargetTrack knowledgebase (47) and Structural Biology Knowledgebase (41, 48).”
MethodFusco, D., Barnum, T., Bruno, A. E., Luft, J. R., Snell, E. H., Mukherjee, S., & Charbonneau, P. (2014) · PLoS ONE · doi:10.1371/journal.pone.0101123 · Cited by 21
Mizianty, M. J., & Kurgan, L. (2012) · Protein and Peptide Letters · doi:10.2174/092986612798472910 · Cited by 21
Eswar, N., & Šali, A. (2009) · NATO science for peace and security series. A, Chemistry and biology · doi:10.1007/978-90-481-2339-1_9 · Cited by 21
Understanding the cell in terms of structure and function: insights from structural genomics
Rigden, D. J. (2006) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2006.07.004 · Cited by 21
Controlling aggregation propensity in A53T mutant of alpha-synuclein causing Parkinson’s disease
Kumar, S., Sarkar, A., & Sundar, D. (2009) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2009.07.008 · Cited by 21
Larson, E. T., Mudeppa, D. G., Gillespie, J. R., Mueller, N. R., Napuli, A. J., Arif, J. A., Ross, J., Arakaki, T. L., Lauricella, A. M., DeTitta, G. T., et al. (2010) · Journal of Molecular Biology · doi:10.1016/j.jmb.2010.01.013 · Cited by 19
Machine learning applications in macromolecular X-ray crystallography
Vollmar, M., & Evans, G. (2021) · Crystallography Reviews · doi:10.1080/0889311x.2021.1982914 · Cited by 20
“They used PepcDB, an extension of TargetDB [126], as data source, which is a further extension to the data used for the development of XtalPred .”
MethodCase-controlled structure validation
Read, R. J., & Kleywegt, G. J. (2009) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444908041085 · Cited by 19
“Structures determined as part of publicly funded structural genomics efforts (with entries in TargetDB; Chen et al., 2004) or the Structural Genomics Consortium (SGC; http://www.thesgc.com) are compared with structures determined outside of these projects (non-SG).”
BackgroundInfluentialA protein sequence meta-functional signature for calcium binding residue prediction
Horst, J. A., & Samudrala, R. (2010) · Pattern Recognition Letters · doi:10.1016/j.patrec.2010.04.012 · Cited by 18
“For example 7,179 structures have been successfully characterized by the structural genomics initiatives, but work on 28,090 targets has ceased [10,11].”
Background
Metadata
- Authors
- Chen, L., Oughtred, R., Berman, H. M., & Westbrook, J.
- Affiliations
- Rutgers, The State University of New Jersey (US)
- Corresponding author
- Chen, Li
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2004-05-06
- Volume
- 20
- Issue
- 16
- Pages
- 2860-2862
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2151430326
- Cited by
- 176
- References
- 5
- Citations by year
- 2026: 1 · 2024: 2 · 2023: 7 · 2022: 2 · 2021: 6 · 2020: 3 · 2019: 6 · 2018: 3 · 2017: 5 · 2016: 6 · 2015: 4 · 2014: 12 · 2013: 7 · 2012: 10
- FWCI
- 8.10
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Bioinformatics (publishedVersion)
- PubMed (publishedVersion)
- Rutgers University Community Repository (Rutgers University) (submittedVersion)
- Funders
- National Science Foundation
- U.S. Department of Energy
- National Institutes of Health
- National Institute of Standards and Technology
- University of California, San Diego
- National Cancer Institute
- National Institute of General Medical Sciences
- National Institute of Neurological Disorders and Stroke
- National Institute of Biomedical Imaging and Bioengineering
- National Center for Research Resources
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Enzyme Structure and Function
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
- Keywords
- structural genomics, protein targets, protein structure determination, Protein Data Bank
- MeSH terms
- Amino Acid Sequence, Database Management Systems, Molecular Sequence Data, Proteins, Research, Information Storage and Retrieval, Sequence Analysis, Protein, Genomics, Databases, Protein
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