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The Protein Data Bank (PDB)

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Presentation on theme: "The Protein Data Bank (PDB)"— Presentation transcript:

1 The Protein Data Bank (PDB)
PDB is the principal repository for protein structures Established in 1971 Accessed at or simply Currently contains over 32,000 structure entities Updated 9/05 Page 287

2 PDB content growth (
structures year Fig. 9.6 Page 281

3 PDB holdings (September, 2005)
29,876 proteins, peptides 1,338 protein/nucl. complexes 1,500 nucleic acids 13 carbohydrates 32,727 total Table 9-2 Page 281

4 Protein Data Bank gateways to access PDB files Swiss-Prot, NCBI, EMBL
CATH, Dali, SCOP, FSSP databases that interpret PDB files Fig. 9.10 Page 285

5 Access to PDB through NCBI
You can access PDB data at the NCBI several ways. Go to the Structure site, from the NCBI homepage Use Entrez Perform a BLAST search, restricting the output to the PDB database Page 289

6 Access to PDB through NCBI
Molecular Modeling DataBase (MMDB) Cn3D (“see in 3D” or three dimensions): structure visualization software Vector Alignment Search Tool (VAST): view multiple structures Page 291

7 Fig. 9.15 Page 290

8 Fig. 9.15 Page 290

9 Fig. 9.16 Page 291

10 Fig. 9.16 Page 291

11 Fig. 9.16 Page 291

12 Fig. 9.16 Page 291

13 Fig. 9.16 Page 291

14 Fig. 9.17 Page 292

15 Access to structure data at NCBI: VAST
Vector Alignment Search Tool (VAST) offers a variety of data on protein structures, including -- PDB identifiers -- root-mean-square deviation (RMSD) values to describe structural similarities -- NRES: the number of equivalent pairs of alpha carbon atoms superimposed -- percent identity Page 294

16 Many databases explore protein structures
SCOP CATH Dali Domain Dictionary FSSP Page 293

17 Structural Classification of Proteins (SCOP)
SCOP describes protein structures using a hierarchical classification scheme: Classes Folds Superfamilies (likely evolutionary relationship) Families Domains Individual PDB entries Page 293

18 Class, Architecture, Topology, and
Homologous Superfamily (CATH) database CATH clusters proteins at four levels: C Class (a, b, a&b folds) A Architecture (shape of domain, e.g. jelly roll) T Topology (fold families; not necessarily homologous) H Homologous superfamily Page 293

19 SCOP statistics (September, 2005)
Class # folds # superfamilies # families All a All b a/b a+b Total Table 9-4 Page 298 a/b = parallel b sheets a+b = antiparallel b sheets

20 Fig. 9.23 Page 298

21 Fig. 9.24 Page 299

22 Fig. 9.25 Page 300

23 Fig. 9.25 Page 300

24 Fig. 9.26 Page 301

25 Fig. 9.27 Page 302

26 Fig. 9.28 Page 303

27 Dali Domain Dictionary
Dali contains a numerical taxonomy of all known structures in PDB. Dali integrates additional data for entries within a domain class, such as secondary structure predictions and solvent accessibility. Page 302

28 Fig. 9.29 Page 303

29 Fig. 9.30 Page 304

30 Fig. 9.30 Page 304

31 Fig. 9.30 Page 304

32 Fold classification based on structure-structure
alignment of proteins (FSSP) FSSP is based on a comprehensive comparison of PDB proteins (greater than 30 amino acids in length). Representative sets exclude sequence homologs sharing > 25% amino acid identity. The output includes a “fold tree.” Page 293

33 Fig. 9.31 Page 305

34 FSSP: fold tree Fig. 9.32 Page 306

35 Fig. 9.33 Page 307

36 Fig. 9.34 Page 307

37 Approaches to predicting protein structures
There are about >20,000 structures in PDB, and about 1 million protein sequences in SwissProt/ TrEMBL. For most proteins, structural models derive from computational biology approaches, rather than experimental methods. The most reliable method of modeling and evaluating new structures is by comparison to previously known structures. This is comparative modeling. An alternative is ab initio modeling. Page

38 Approaches to predicting protein structures
obtain sequence (target) fold assignment comparative modeling ab initio modeling Fig. 9.35 Page 308 build, assess model

39 Comparative modeling of protein structures
[1] Perform fold assignment (e.g. BLAST, CATH, SCOP); identify structurally conserved regions [2] Align the target (unknown protein) with the template. This is performed for >30% amino acid identity over a sufficient length [3] Build a model [4] Evaluate the model Page 305

40 Errors in comparative modeling
Errors may occur for many reasons [1] Errors in side-chain packing [2] Distortions within correctly aligned regions [3] Errors in regions of target that do not match template [4] Errors in sequence alignment [5] Use of incorrect templates Page 306

41 Comparative modeling In general, accuracy of structure prediction depends on the percent amino acid identity shared between target and template. For >50% identity, RMSD is often only 1 Å. Page 306

42 Fig. 9.36 Page 308 Baker and Sali (2000)

43 Comparative modeling Many web servers offer comparative modeling services. Examples are SWISS-MODEL (ExPASy) Predict Protein server (Columbia) WHAT IF (CMBI, Netherlands) Page 309

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