http://www.gopubmed.org/web/gopubmed/ Protein sequence databases 19,328 documents semantically analyzed top author statistics 1 2 Top Years Publications 2009 2,091 2005 1,915 2007 1,817 2008 1,735 2006 1,733 2004 1,695 2003 1,465 2002 1,169 2001 960 2000 751 2010 682 1999 671 1998 559 1997 465 1996 435 1995 337 1994 294 1993 166 1992 122 1991 116 1 2 1 2 3 ... 6 Top Countries Publications USA 6,835 United Kingdom 1,820 Germany 1,471 Japan 1,062 China 842 France 837 Canada 599 Italy 527 Australia 441 Spain 399 India 377 Switzerland 351 Sweden 306 Netherlands 268 Israel 243 South Korea 223 Denmark 218 Belgium 205 Singapore 201 Taiwan 176 1 2 3 ... 6 1 2 3 ... 62 Top Cities Publications Cambridge 471 London 409 Bethesda 363 New York 308 Heidelberg 295 Beijing 268 San Diego 262 Tokyo 248 Seattle 245 Boston 237 Singapur 201 Paris 198 Berlin 194 San Francisco 159 Toronto 158 Baltimore 151 Cambridge, USA 149 Shanghai 148 Philadelphia 147 Madrid 140 1 2 3 ... 62 1 2 3 ... 85 Top Journals Publications Nucleic Acids Res 1,444 Bioinformatics 1,170 Bmc Bioinformatics 795 Proteins 758 Proteomics 489 J Mol Biol 488 Protein Sci 309 J Proteome Res 280 J Biol Chem 278 Methods Mol Biol 268 Bmc Genomics 246 Electrophoresis 243 P Natl Acad Sci Usa 226 Gene 212 J Med Chem 185 Genome Res 183 Protein Eng 172 Biochem Bioph Res Co 161 Genomics 159 Febs Lett 150 1 2 3 ... 85 1 2 3 ... 1230 Top Terms Publications Proteins 15,821 Humans 7,459 Genes 6,961 Amino Acid Sequence 6,141 Animals 6,026 Genomics 5,139 Genome 5,089 Computational Biology 4,579 Algorithms 4,133 Amino Acids 3,644 Sequence Alignment 3,265 Models, Molecular 3,213 Peptides 2,979 Proteomics 2,969 Base Sequence 2,920 Proteome 2,773 Protein Conformation 2,740 Sequence Homology, Amino Acid 2,412 DNA 2,397 Protein Structure, Tertiary 2,351 1 2 3 ... 1230 1 2 3 ... 3424 Top Authors Publications Thornton J 100 Apweiler R 97 Bairoch A 80 Orengo C 63 Bork P 62 Rost B 62 Koonin E 60 Sander C 60 Gerstein M 59 Chou K 59 Mewes H 50 Valencia A 48 Nussinov R 47 Bourne P 46 Skolnick J 44 Mann M 44 Godzik A 43 Attwood T 42 Hochstrasser D 41 Appel R 40 1 2 3 ... 3424 最新研究报道 Methods Mol Biol. 2010;609:45-57. Protein sequence databases. Rebhan M . Head Bioinformatics Support, Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland. Abstract Protein sequence databases do not contain just the sequence of the protein itself but also annotation that reflects our knowledge of its function and contributing residues. In this chapter, we will discuss various public protein sequence databases, with a focus on those that are generally applicable. Special attention is paid to issues related to the reliability of both sequence and annotation, as those are fundamental to many questions researchers will ask. Using both well-annotated and scarcely annotated human proteins as examples, it will be shown what information about the targets can be collected from freely available Internet resources and how this information can be used. The results are shown to be summarized in a simple graphical model of the protein's sequence architecture highlighting its structural and functional modules. PMID: 20221912 MeSH Terms, Substances MeSH Terms: Amino Acid Sequence Animals Computer Graphics Data Mining* Databases, Protein* Humans Internet Models, Molecular Molecular Sequence Data Protein Conformation Protein Folding Protein Interaction Mapping Proteins/chemistry* Software Structure-Activity Relationship Systems Biology* Systems Integration User-Computer Interface Substances: Proteins LinkOut - more resources Full Text Sources: Springer
http://www.gopubmed.org/web/gopubmed/ Protein structure databases 19,328 documents semantically analyzed top author statistics 1 2 Top Years Publications 2009 2,091 2005 1,915 2007 1,817 2008 1,735 2006 1,733 2004 1,695 2003 1,465 2002 1,169 2001 960 2000 751 2010 682 1999 671 1998 559 1997 465 1996 435 1995 337 1994 294 1993 166 1992 122 1991 116 1 2 1 2 3 ... 6 Top Countries Publications USA 6,835 United Kingdom 1,820 Germany 1,471 Japan 1,062 China 842 France 837 Canada 599 Italy 527 Australia 441 Spain 399 India 377 Switzerland 351 Sweden 306 Netherlands 268 Israel 243 South Korea 223 Denmark 218 Belgium 205 Singapore 201 Taiwan 176 1 2 3 ... 6 1 2 3 ... 62 Top Cities Publications Cambridge 471 London 409 Bethesda 363 New York 308 Heidelberg 295 Beijing 268 San Diego 262 Tokyo 248 Seattle 245 Boston 237 Singapur 201 Paris 198 Berlin 194 San Francisco 159 Toronto 158 Baltimore 151 Cambridge, USA 149 Shanghai 148 Philadelphia 147 Madrid 140 1 2 3 ... 62 1 2 3 ... 85 Top Journals Publications Nucleic Acids Res 1,444 Bioinformatics 1,170 Bmc Bioinformatics 795 Proteins 758 Proteomics 489 J Mol Biol 488 Protein Sci 309 J Proteome Res 280 J Biol Chem 278 Methods Mol Biol 268 Bmc Genomics 246 Electrophoresis 243 P Natl Acad Sci Usa 226 Gene 212 J Med Chem 185 Genome Res 183 Protein Eng 172 Biochem Bioph Res Co 161 Genomics 159 Febs Lett 150 1 2 3 ... 85 1 2 3 ... 1230 Top Terms Publications Proteins 15,821 Humans 7,459 Genes 6,961 Amino Acid Sequence 6,141 Animals 6,026 Genomics 5,139 Genome 5,089 Computational Biology 4,579 Algorithms 4,133 Amino Acids 3,644 Sequence Alignment 3,265 Models, Molecular 3,213 Peptides 2,979 Proteomics 2,969 Base Sequence 2,920 Proteome 2,773 Protein Conformation 2,740 Sequence Homology, Amino Acid 2,412 DNA 2,397 Protein Structure, Tertiary 2,351 1 2 3 ... 1230 1 2 3 ... 3424 Top Authors Publications Thornton J 100 Apweiler R 97 Bairoch A 80 Orengo C 63 Bork P 62 Rost B 62 Koonin E 60 Sander C 60 Gerstein M 59 Chou K 59 Mewes H 50 Valencia A 48 Nussinov R 47 Bourne P 46 Skolnick J 44 Mann M 44 Godzik A 43 Attwood T 42 Hochstrasser D 41 Appel R 40 1 2 3 ... 3424 最新研究报道 Methods Mol Biol. 2010;609:59-82. Protein structure databases. Laskowski RA . EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. Abstract Web-based protein structure databases come in a wide variety of types and levels of information content. Those having the most general interest are the various atlases that describe each experimentally determined protein structure and provide useful links, analyses, and schematic diagrams relating to its 3D structure and biological function. Also of great interest are the databases that classify 3D structures by their folds as these can reveal evolutionary relationships which may be hard to detect from sequence comparison alone. Related to these are the numerous servers that compare folds--particularly useful for newly solved structures, and especially those of unknown function. Beyond these there are a vast number of databases for the more specialized user, dealing with specific families, diseases, structural features, and so on. PMID: 20221913 MeSH Terms, Substances MeSH Terms: Amino Acid Sequence Animals Computer Graphics Data Mining* Databases, Protein* Humans Internet Models, Molecular Molecular Sequence Data Protein Conformation Protein Folding Protein Interaction Mapping Proteins/chemistry* Software Structure-Activity Relationship Systems Biology* Systems Integration User-Computer Interface Substances: Proteins LinkOut - more resources Full Text Sources: Springer
http://www.gopubmed.org/web/gopubmed/ Databases and protein-protein interactions 734 documents semantically analyzed top author statistics Top Years Publications 2009 138 2007 95 2008 94 2006 92 2005 76 2004 60 2003 51 2010 34 2002 28 2001 26 2000 10 1999 9 1998 9 1997 2 1996 2 1995 2 1994 2 1993 2 1991 1 1 2 3 Top Countries Publications USA 282 United Kingdom 55 Germany 54 China 38 Japan 36 Canada 28 France 25 Spain 22 Singapore 21 India 19 Israel 18 Italy 17 Taiwan 17 South Korea 15 Australia 9 Finland 8 Belgium 8 Russia 7 Turkey 6 Colombia 6 1 2 3 1 2 3 ... 12 Top Cities Publications Beijing 22 Singapur 21 Boston 20 Berlin 19 Toronto 18 New York 17 Cambridge 15 Los Angeles 15 Tokyo 13 Bethesda 13 San Diego 11 Seattle 10 Bangalore 10 London 10 Heidelberg 10 New Haven 10 Tel Aviv-Yafo 9 Cambridge, USA 9 Daejeon 8 San Francisco 8 1 2 3 ... 12 1 2 3 ... 11 Top Journals Publications Bmc Bioinformatics 82 Bioinformatics 73 Nucleic Acids Res 63 Proteins 44 J Mol Biol 24 Bmc Genomics 18 Proteomics 15 Methods Mol Biol 15 Plos Comput Biol 14 Genome Biol 14 Plos One 13 Genome Res 11 J Proteome Res 10 Protein Sci 10 Pac Symp Biocomput 10 Mol Cell Proteomics 8 Bmc Syst Biol 6 In Silico Biol 6 Mol Biosyst 6 P Natl Acad Sci Usa 6 1 2 3 ... 11 1 2 3 ... 121 Top Terms Publications Proteins 660 Protein Interaction Mapping 359 Computational Biology 307 Humans 267 Genes 245 Protein Binding 236 Algorithms 211 Proteomics 191 Genomics 191 Animals 188 Genome 183 Proteome 152 Binding Sites 140 Models, Molecular 131 Protein Structure, Tertiary 127 protein complex 123 Amino Acid Sequence 122 Protein Conformation 112 signal transduction 97 Evaluation Studies as Topic 97 1 2 3 ... 121 1 2 3 ... 153 Top Authors Publications Eisenberg D 11 Nussinov R 8 Bader G 8 Gerstein M 8 Janin J 7 Xenarios I 7 Salwiński L 7 Vidal M 7 Schroeder M 6 Wojcik J 6 Pandey A 5 Bahadur R 5 Cesareni G 5 Stuempflen V 5 Dunker A 5 Uversky V 5 Hogue C 5 Ng S 5 Wolfson H 5 Winter C 4 1 2 3 ... 153 最新文献综述 Methods Mol Biol. 2010;609:145-59. Databases of protein-protein interactions and complexes. Ooi HS , Schneider G , Chan YL , Lim TT , Eisenhaber B , Eisenhaber F . Bioinformatics Institute, Agency for science, Technology, and Research, Singapore. Abstract In the current understanding, translation of genomic sequences into proteins is the most important path for realization of genome information. In exercising their intended function, proteins work together through various forms of direct (physical) or indirect interaction mechanisms. For a variety of basic functions, many proteins form a large complex representing a molecular machine or a macromolecular super-structural building block. After several high-throughput techniques for detection of protein-protein interactions had matured, protein interaction data became available in a large scale and curated databases for protein-protein interactions (PPIs) are a new necessity for efficient research. Here, their scope, annotation quality, and retrieval tools are reviewed. In addition, attention is paid to portals that provide unified access to a variety of such databases with added annotation value. PMID: 20221918 Publication Types, MeSH Terms, Substances Publication Types: Review MeSH Terms: Animals Data Mining* Databases, Protein* Humans Internet Multiprotein Complexes Protein Interaction Domains and Motifs* Protein Interaction Mapping* Proteins/chemistry* Software Systems Biology* Systems Integration Terminology as Topic Substances: Multiprotein Complexes Proteins LinkOut - more resources Full Text Sources: Springer
http://www.gopubmed.org/web/gopubmed/ Protein secondary structure prediction 3,355 documents semantically analyzed top author Rost, B New York, USA 18 highly cited papers in open-access literature. Senior author (60 last author) URL to this profile Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY, USA. Protein Design Group, EMBL, Heidelberg, Germany. statistics 1 2 Top Years Publications 2006 242 2005 236 2009 231 2007 229 2008 220 2003 191 2004 189 2001 169 2002 166 1999 142 1997 134 1998 132 1996 119 2000 114 1993 110 1995 106 1994 95 2010 77 1992 56 1991 54 1 2 1 2 3 4 Top Countries Publications USA 1,092 United Kingdom 307 Germany 246 China 190 Japan 159 France 140 Italy 103 Canada 92 India 91 Sweden 61 Spain 58 Switzerland 49 Australia 46 Denmark 43 Taiwan 38 Israel 37 Belgium 36 Poland 35 Russia 35 Netherlands 34 1 2 3 4 1 2 3 ... 29 Top Cities Publications London 110 New York 77 Heidelberg 57 Bethesda 52 San Francisco 44 Seattle 44 Beijing 43 Cambridge 42 Shanghai 39 Tokyo 39 Boston 38 Paris 34 Philadelphia 34 Stockholm 32 Oxford 30 Chicago 29 Berlin 28 Zrich 28 Irvine 27 Cambridge, USA 27 1 2 3 ... 29 1 2 3 ... 26 Top Journals Publications Proteins 339 J Mol Biol 203 Protein Sci 138 Bioinformatics 131 Nucleic Acids Res 119 Bmc Bioinformatics 108 J Biol Chem 107 Protein Eng 97 Biochemistry-us 94 P Natl Acad Sci Usa 83 Febs Lett 75 Biochim Biophys Acta 66 Eur J Biochem 54 Biochem Bioph Res Co 44 Biophys J 39 Comput Appl Biosci 30 Biochem J 27 J Protein Chem 27 Biopolymers 26 J Biomol Struct Dyn 24 1 2 3 ... 26 1 2 3 ... 438 Top Terms Publications Proteins 2,868 Protein Structure, Secondary 1,859 Amino Acid Sequence 1,805 Models, Molecular 1,239 Amino Acids 1,231 Protein Conformation 1,085 Algorithms 1,071 Animals 844 Humans 817 Sequence Alignment 777 Peptides 699 Protein Folding 697 Computational Biology 621 Protein Structure, Tertiary 603 Binding Sites 557 Genes 468 protein folding 435 Base Sequence 430 Sequence Homology, Amino Acid 423 Hydrophobicity 408 1 2 3 ... 438 1 2 3 ... 511 Top Authors Publications Rost B 44 Skolnick J 35 Sternberg M 33 Koliński A 29 Sander C 23 Gromiha M 22 Chou K 21 Cohen F 20 Brunak S 18 Baldi P 17 Barton G 17 Rychlewski L 17 Thornton J 17 Benner S 17 Blundell T 15 Raghava G 14 Casadio R 14 Gerloff D 14 Koonin E 13 Simon I 13 1 2 3 ... 511 最新文献综述 Methods Mol Biol. 2010;609:327-48. Protein secondary structure prediction. Pirovano W , Heringa J . Centre for Integrative Bioinformatics VU, VU University, Amsterdam, The Netherlands. Abstract While the prediction of a native protein structure from sequence continues to remain a challenging problem, over the past decades computational methods have become quite successful in exploiting the mechanisms behind secondary structure formation. The great effort expended in this area has resulted in the development of a vast number of secondary structure prediction methods. Especially the combination of well-optimized/sensitive machine-learning algorithms and inclusion of homologous sequence information has led to increased prediction accuracies of up to 80%. In this chapter, we will first introduce some basic notions and provide a brief history of secondary structure prediction advances. Then a comprehensive overview of state-of-the-art prediction methods will be given. Finally, we will discuss open questions and challenges in this field and provide some practical recommendations for the user. PMID: 20221928 Publication Types, MeSH Terms, Substances Publication Types: Review MeSH Terms: Algorithms Animals Artificial Intelligence Computational Biology* Data Mining* Databases, Protein* Humans Models, Molecular Neural Networks (Computer) Protein Structure, Secondary Proteins/chemistry* Reproducibility of Results Sequence Alignment Sequence Analysis, Protein Sequence Homology Structure-Activity Relationship Substances: Proteins LinkOut - more resources Full Text Sources: Springer Other Literature Sources: COS Scholar Universe
由欧洲生物信息学中心组织的国际蛋白质-蛋白质相互作用预测竞赛，于2010年1月4日至31日举行第20轮。这轮竞赛的两个题目T43和T44均来自美国Washington University的David Baker实验室。这次的题目与以往19轮的题目形式不一样，以往都是在给定已知会相互作用的2个单体的基础上预测复合物结构，而这次是给出了众多人工计算设计的复合物，不确定是否真正相互作用，也不确定复合物三维结构是否正确。 这次的2个题目简介如下： T43有21个A、B两链蛋白质复合物三维结构。其中有20个是人工计算设计的，与天然晶体结构偏差较大。另一个是晶体解析的天然结构。21个复合物的A链实际上是6个不同的蛋白质，B是18个不同蛋白质，所以总共涉及24个蛋白质。我们的任务就是把这其中唯一的天然结构挑出来。 T44也有21个A、B两链蛋白质复合物三维结构，这里的所有复合物都是人工计算设计的，有待进一步做生化和晶体衍射实验确认是否有复合物中的A、B两个蛋白质真正相互作用，甚至结构预测是否正确。21个复合物的A链实际上是3个不同的蛋白质，B是21个不同蛋白质，所以总共也涉及24个蛋白质，只不过与T43的蛋白质不一样。我们的任务是挑出其中有可能真正相互作用的复合物结构，具体数目不确定，可能一个都没有，也可能有多个。 我们昨天提交了预测结果，但最终正确与否还需要等待Baker小组和CAPRI委员会的评判。待评判结果下来后，我将具体分析我们自己预测方法的长、短处。 T43的结果： Normal07.8 磅02falsefalsefalseMicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:普通表格; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman"; mso-fareast-font-family:"Times New Roman"; mso-ansi-language:#0400; mso-fareast-language:#0400; mso-bidi-language:#0400;} All the 21 models of Target 43 have been evaluated as the following steps: 1. Divide the 21 models into 6 groups according to chain A in the models. Models in one group have the similar chain A. G1: 1-4; G2: 5,6,7; G3: 8,9,10; G4: 11,12,13; G5: 14-18; G6: 19,20,21. 2. Predict binding site patch residues for all the monomers A and B. At the same time, search the homologue protein sequences for all the chains A and extract experimental literatures to analyze the related pdb 3D structures. At this step, we want to make clear the aim of every designed model and to compare the designed models with the experimental 3D structures. We think one of the aims is to design an protein inhibitor for the chain A of G1 (models 1-4), which is the protein interleukin 23. 3. Remove the models with an complex interface area less than 1200 Å 2 . 7, 9, 12, 15, 16, 17, 19, 21 4. Remove the models with a gaussian correlation facotr between the chains A and B less than -0.22. 6, 8, 10, 11, 13, 18, 20 5. Remove the models with wrong binding site patch residues according to prediction and experimental information. 5 6. Remove the models with wrong axes orientation between the chains A and B. 1, 4, 14 7. Remove the models with wrong correspondence between the binding site patches compared with the experimental pdb structure 3DUH. 2 At last, we obtain the model 3. So we submit model 3 as the result. T44的结果： Normal07.8 磅02falsefalsefalseMicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:普通表格; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman"; mso-fareast-font-family:"Times New Roman"; mso-ansi-language:#0400; mso-fareast-language:#0400; mso-bidi-language:#0400;} All the 21 models of Target 44 have been evaluated as the following steps: 1. Divide the 21 models into 3 groups according to chain A in the models. Models in one group have the similar chain A. G1: 1, 2, 3; G2: 4-7, 15-21; G3: 8-14. 2. Predict binding site patch residues for all the monomer chains A and B. At the same time, search the homologue protein sequences for all the chains A and extract experimental literatures to analyze the related pdb 3D structures. At this step, we want to make clear the aim of every designed model and to compare the designed models with the experimental 3D structures. We think one of the aims is to design an protein inhibitor for the chain A of G3 (models 8-14), which is the protein hemagglutinin. 3. Remove the models with an complex interface area less than 1200 Å 2 . 9, 10, 12, 14, 15, 16, 17, 19, 20, 21 4. Remove the models with a gaussian correlation facotr between the chains A and B less than -0.22. 7, 11, 18 5. Remove the models with wrong binding site patch residues according to prediction and experimental information. 1, 2, 3, 4, 5, 6 6. Remove the models with wrong axes orientation between the chains A and B according to the pdb structure 3GBM. 8 At last, we obtain the model 13. So we submit model 13 as the result.
标签: 蛋白质
