Sequences PDB

The full Swissprot sequences (25, 26) are searched against the purified unique set of the PDB sequences. Three-dimensional (3D) domains are annotated based on PDB sequence boundaries, and their structures are clustered to 95% sequence identity. 

Distribution of sequence identities between proteins in four genomes and their closest homologues in the Protein Databank for those sequences in genomes with homologues in the PDB. PSI-BLAST was used to search the non-redundant protein sequence database with a representative set of PDB sequences as queries. The program was run for four iterations, with a maximum expectation value of 0.0001 (see Chapter 2 for an... 

Yang and Honig have developed the PrISM package of programs that performs structure alignment, PDB sequence search, fold recognition, se-... 

Another site, Swiss-Model [8] (http //swissmodel.expasy.org/), also uses BLAST to allow users to easily and quickly search PDB sequences for a matches. Currently, however, the matches are presented only in a table, so it is not easy to see where the stmctures match the target sequence. An advantage of Swiss-Model is that it allows the user to then select a stmcture to be used as a template and automatically generates a homology model. Of course, this process can take some time. 

Consider an example in which the sequence ELVISISALIVES is represented in the SEQRES entry of a hypothetical PDB file, but the coordinate information is missing all (x, y, z) locations for the subsequence ISA. Software that reads the implicit sequence will often report the PDB sequence incorrectly from the chemical graph as ELVISLIVES. A test structure to determine whether software looks only at the implicit sequence is 3TS1 (Brick et al., 1989) as shown in the Java three-dimensional structure viewer WebMol in Eigure 5.3. Here, both the implicit and explicit sequences in the PDB file to the last residue with coordinates are correctly displayed. 

When a researcher wishes to hnd a structure related to a new sequence, NCBFs BLAST (Altschul et al., 1990) can be used because the BLAST databases contain a copy of all the validated sequences from MMDB. The BLAST Web interface can be used to perform the query by pasting a sequence in FASTA format into the sequence entry box and then selecting the pdb sequence database. This will yield a search against all the validated sequences in the current public structure database. More information on performing BLAST runs can be found in Chapter 8. 

The PDB contains 20 254 experimentally determined 3D structures (November, 2002) of macromolecules (nucleic adds, proteins, and viruses). In addition, it contains data on complexes of proteins with small-molecule ligands. Besides information on the structure, e.g., sequence details (primary and secondary structure information, etc.), atomic coordinates, crystallization conditions, structure factors. 

The SWISS-PROT database [36] release 40.44 (February, 2003) contains over 120 000 sequences of proteins with more than 44 million amino adds abstracted from about 100 000 references. Besides sequence data, bibHographical references, and taxonomy data, there are highly valuable annotations of information (e.g., protein function), a minimal level of redundancy, and a high level of integration with other databases (EMBL, PDB, PIR, etc.). The database was initiated in 1987 by a partnership between the Department of Medicinal Biochemistry of the University of Geneva, Switzerland, and the EMBL. Now SWISS-PROT is driven as a joint project of the EMBL and the Swiss Institute of Bioinformatics (SIB). 

PDB, NRL3D Protein Data Bank - protein structures (mostly fror X-ray crystallography). NRL3D is a derived sequence database in PIR format... 

For example, Stolorz et al. [88] derived a Bayesian formalism for secondary structure prediction, although their method does not use Bayesian statistics. They attempt to find an expression for / ( j. seq) = / (seq j.)/7( j.)//7(seq), where J. is the secondary structure at the middle position of seq, a sequence window of prescribed length. As described earlier in Section II, this is a use of Bayes rule but is not Bayesian statistics, which depends on the equation p(Q y) = p(y Q)p(Q)lp(y), where y is data that connect the parameters in some way to observables. The data are not sequences alone but the combination of sequence and secondary structure that can be culled from the PDB. The parameters we are after are the probabilities of each secondary structure type as a function of the sequence in the sequence window, based on PDB data. The sequence can be thought of as an explanatory variable. That is, we are looking for... 

In this case, we are looking for counts for each secondary structure type J. for each sequence x, which might be derived from PDB data by... 

Thompson and Goldstein [89] improve on the calculations of Stolorz et al. by including the secondary structure of the entire window rather than just a central position and then sum over all secondary strucmre segment types with a particular secondary structure at the central position to achieve a prediction for this position. They also use information from multiple sequence alignments of proteins to improve secondary structure prediction. They use Bayes rule to fonnulate expressions for the probability of secondary structures, given a multiple alignment. Their work describes what is essentially a sophisticated prior distribution for 6 i(X), where X is a matrix of residue counts in a multiple alignment in a window about a central position. The PDB data are used to form this prior, which is used as the predictive distribution. No posterior is calculated with posterior = prior X likelihood. 

RL Dunbrack Jr. Culling the PDB by resolution and sequence identity. 1999. http // www.fccc.edu/research/labs/dunbrack/culledpdb.html... 

In the protein structure database PDB ( http //www. rcsb.org/pdb), by X-ray crystallography and NMR spectroscopy, experimentally solved 3D-protein structures are available to the public. Homology model building for a query sequence uses protein portions of known 3D-stmctures as structural templates for proteins with high sequence similarity. 

Predicting a likely conformation or fold of a particular region of a protein with less or no sequence similarity to protein structures recorded in the PDB, is the main challenges for homology modeling of proteins. 

In reference 21, the Fe-protein X-ray structures of A. vinelandii, Av2, PDB code 2NIP, at 2.2-A resolution is compared to that of C. pasteurianum, Cp2, PDB code 1CP2, at resolution 1.93 A as well as to Fe-protein aa sequences and... 

Due to the ready accessibility of SH2 domains by molecular biology techniques, numerous experimentally determined 3D structures of SH2 domains derived by X-ray crystallography as well as heteronuclear multidimensional NMR spectroscopy are known today. The current version of the protein structure database, accessible to the scientific community by, e.g., the Internet (http //www.rcsb.org/pdb/) contains around 80 entries of SH2 domain structures and complexes thereof. Today, the SH2 domain structures of Hck [62], Src [63-66], Abl [67], Grb2 [68-71], Syp [72], PLCy [73], Fyn [74], SAP [75], Lck [76,77], the C- and N-terminal SH2 domain ofp85a [78-80], and of the tandem SH2 domains Syk [81,82], ZAP70 [83,84], and SHP-2 [85] are determined. All SH2 domains display a conserved 3D structure as can be expected from multiple sequence alignments (Fig. 4). The common structural fold consists of a central three-stranded antiparallel ft sheet that is occasionally extended by one to three additional short strands (Fig. 5). This central ft sheet forms the spine of the domain which is flanked on both sides by regular a helices [49, 50,60]. 

Fig. 12. 3D Structure of a pTyr-containing oligopeptide bound to the IRS-1 (insulin receptor substrate) PTB domain (lIRS.pdb). The Asn-Pro-Ala-pTyr tetrapeptide sequence adopts a regular pi turn conformation [181]...

Fig. 3. Refolding model of insulin protofilaments, from Jimenez et al. (2002). (A) Ribbon diagram of the crystal structure of porcine insulin (PDB ID code 3INS), generated with Pymol (DeLano, 2002). The two chains are shown as dark and light gray with N- and C-termini indicated. The dotted lines represent the three disulfide bonds 1 is the intrachain and 2 and 3 are the interchain bonds. (B) Cartoon representation of the structure of monomeric insulin in the fibril, as proposed by Jimenez et al. (2002). The thick, arrowed lines represent /1-strands, and thinner lines show the remaining sequence. The disulfide bonds are as represented in panel A, and N- and C-termini are indicated. (Components of this panel are not to scale.) (C) Cartoon representation of an insulin protofilament, showing a monomer inside. The monomers are proposed to stack with a slight twist to form two continuous /(-sheets. (Components of this panel, including the protofilament twist, are not to scale.) In the fibril cross sections presented byjimenez et al. (2002), two, four, or six protofilaments are proposed to associate to form the amyloid-like fibrils.

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