Discovering structural motifs using a structural alphabet: Application to magnesium-binding sites
© Dudev and Lim; licensee BioMed Central Ltd. 2007
Received: 27 October 2006
Accepted: 28 March 2007
Published: 28 March 2007
For many metalloproteins, sequence motifs characteristic of metal-binding sites have not been found or are so short that they would not be expected to be metal-specific. Striking examples of such metalloproteins are those containing Mg2+, one of the most versatile metal cofactors in cellular biochemistry. Even when Mg2+-proteins share insufficient sequence homology to identify Mg2+-specific sequence motifs, they may still share similarity in the Mg2+-binding site structure. However, no structural motifs characteristic of Mg2+-binding sites have been reported. Thus, our aims are (i) to develop a general method for discovering structural patterns/motifs characteristic of ligand-binding sites, given the 3D protein structures, and (ii) to apply it to Mg2+-proteins sharing <30% sequence identity. Our motif discovery method employs structural alphabet encoding to convert 3D structures to the corresponding 1D structural letter sequences, where the Mg2+-structural motifs are identified as recurring structural patterns.
The structural alphabet-based motif discovery method has revealed the structural preference of Mg2+-binding sites for certain local/secondary structures: compared to all residues in the Mg2+-proteins, both first and second-shell Mg2+-ligands prefer loops to helices. Even when the Mg2+-proteins share no significant sequence homology, some of them share a similar Mg2+-binding site structure: 4 Mg2+-structural motifs, comprising 21% of the binding sites, were found. In particular, one of the Mg2+-structural motifs found maps to a specific functional group, namely, hydrolases. Furthermore, 2 of the motifs were not found in non metalloproteins or in Ca2+-binding proteins. The structural motifs discovered thus capture some essential biochemical and/or evolutionary properties, and hence may be useful for discovering proteins where Mg2+ plays an important biological role.
The structural motif discovery method presented herein is general and can be applied to any set of proteins with known 3D structures. This new method is timely considering the increasing number of structures for proteins with unknown function that are being solved from structural genomics incentives. For such proteins, which share no significant sequence homology to proteins of known function, the presence of a structural motif that maps to a specific protein function in the structure would suggest likely active/binding sites and a particular biological function.
Magnesium is one of the most versatile metal cofactors in cellular biochemistry, serving both intra and extracellular, catalytic and/or structural roles . It is used to stabilize a variety of protein structures; e.g., the interface of the ribonucleotide reductase subunits . It is also used to stabilize nucleic acids by alleviating electrostatic repulsion between negatively charged phosphates. Furthermore, Mg2+, together with Ca2+, stabilize biological membranes by charge neutralization after binding to the carboxylated and phosphorylated headgroups of lipids. It also activates enzymes that regulate the biochemistry of nucleic acids such as restriction nucleases, ligases, and topoisomerases, and is essential for the fidelity of DNA replication . Divalent Mg2+ is a "hard" ion and prefers "hard" ligands of low polarizability like oxygen. It tends to bind directly to the amino acid residues, primarily to the Asp/Glu carboxylic side chains, followed by the Asn/Gln side chains or peptide backbone carbonyl groups . The rest of the metal coordination sphere, which is usually octahedral, is complemented by water ligand(s).
Unlike Zn2+ and Ca2+-binding sites, only a few, relatively short, sequence motifs have been discovered for Mg2+ proteins with close sequence homology. These include the -NAD FD GD- motif, found in different RNA polymerases, DNA Pol I and HIV reverse transcriptase, and the -YXDD- or -LXDD- motifs in reverse transcriptase and telomerase, where residues in bold are the Mg2+ ligands . As the known Mg2+ sequence motifs are short, they could easily be found in other nonMg2+-proteins and would not be expected to be Mg2+-specific. Interestingly, some homology in the 3D structure of the Mg2+-binding sites has been observed for certain classes of enzymes such as restriction enzymes, bacterial and viral RNase H domains, and viral integrases . However, systematic studies of the structural preference/conservation of Mg2+-binding sites in nonhomologous proteins have not been reported; hence, no structural motifs of the Mg2+-binding sites have been extracted.
The aims in this work are to address the following intriguing questions: (1) Do Mg2+-binding sites exhibit any preference for certain local/secondary structures? If so, which types of local/secondary structures are favored and which are disfavored? (2) Even when the Mg2+-proteins share no significant sequence homology, do they share a similar Mg2+-binding site structure? (3) If structural motifs of the Mg2+-binding sites exist, do they map to specific protein functions? (4) Are the structural motifs Mg2+-specific? In particular, are they found in proteins that do not bind metal ions or in proteins that bind Ca2+, which like Mg2+, is also a divalent "hard" ion, binding preferentially to "hard" oxygen-containing ligands?
To address the aforementioned questions, we have developed a general strategy for discovering 3D motifs that are hidden in the local structure of the active/binding site, based on the fact that the local structure is generally more evolutionary conserved than the amino acid sequence . The 3D motifs of the metal-binding sites were obtained by encoding the 3D representation based on Cartesian coordinates into a 1D representation based on a 16-letter structural alphabet [6, 7]. The structural alphabet represents recurring short structural prototypes and has been used to (i) compare/analyze 3D structures [8–10], (ii) predict protein 3D structures from amino acid sequences [6, 11], (iii) reconstruct the protein backbone , and (iv) model loops . However, it has not been used to discover structural motifs of metal/ligand-binding sites in proteins. First, the structural-alphabet based motif discovery approach was validated by using it to "rediscover" the structural motif of Cys4 Zn-finger domains, which are known to adopt a specific structure. Next, it was used to discover structural motifs of Mg2+-binding sites in a set of nonredundant Mg2+-proteins sharing <30% sequence identity. The results reveal clear trends in the structural composition of Mg2+-binding sites, 4 Mg2+-structural motifs, and important relationships between these motifs and other features of the proteins. The specificity of the structural motifs discovered for certain Mg2+-binding sites was assessed by determining their occurrence in a set of nonredundant non-metal containing protein structures and in a set of nonredundant Ca2+-bound protein structures.
Validation against Proteins with known Structural Motifs
Structural Preference of Mg2+-Binding Sites
The letter and secondary structural element (SSE) frequency distributions and 2-sample T-tests of first-and second-shell amino acid residues vs. all amino acid residues in the Mg2+-proteins
1st-shell vs. all residues
2nd-shell vs. all residues
In summary, the Mg2+-binding sites generally prefer certain local structures: compared to all amino acid residues in the Mg2+ proteins, both first and second-shell ligands tend to prefer loops to helices. This may be due to the need to position not only the first and second-shell ligands, but also the helix dipole, in a proper orientation for metal binding.
Structural Motifs of Mg2+-Binding Sites
1st-shell structural motifs in Mg2+-proteins
Mg 2+ -Ligands
CATH number b
Functional Group c
EC code d
D189, E214, D239
D191, E219, D244
D244, E292, D317
D1008, D1010, D1170
D11, D13, D123
D351, T353, D703
D44, D46, D167
D9, D11, D201
D142, D145, D294
D1118, D1121, E1280
E1090, D1093, D1220
D168, N198, I200
D447, N474, Q476
D175, N204, Y206
D440, N467, G469
D963, T991, V993
Each of the 4 motifs in Table 2 is found in proteins containing Mg2+-binding domains belonging to the same superfamily. This is evidenced by the fact that proteins with the same Mg2+-structural motif have Mg2+-binding domains belonging to the same superfamily with the same CATH numbers (Table 2), implying structurally homologous domains. For example, all 3 proteins with the f(2)h(126–158)m motif possess in common a Mg2+-binding domain belonging to the fructose-1,6-bisphosphatase, subunit A, domain 1 superfamily (CATH number 3.30.540.10). Likewise, all 5 proteins with the k(26–29)h(1)a motif possess Mg2+-binding domains with the same CATH number, 188.8.131.520. The fact that the motifs are found in structurally homologous Mg2+-binding domains further supports the use of the structural alphabet to discover motifs.
Relation between Mg2+-Structural Motifs and PROSITE Sequence Motifs
To see if any of the Mg2+-proteins containing structural motifs match sequence motifs stored in the PROSITE database , the sequences of the proteins listed in Table 2 were scanned for the occurrence of PROSITE sequence motifs. None of the proteins match any PROSITE sequence motifs encompassing residues involved in Mg2+-binding. However, the halotolerance protein hal 2 (1KA1) containing the f(2)h(126–158)m motif matched 2 inositol monophosphatase family signatures (PROSITE PDOC00547) containing conserved metal-binding residues. This supports the 'f(2)h(126–158)m' motif as a signature of Mg2+-binding sites.
Relation between Mg2+-Structural Motifs and Protein Function
Do any of the structural motifs found for the Mg2+-proteins map to specific protein functions? To answer this question, for each of the Mg2+-proteins found with a structural motif, the functional group of the protein from the PDB header and enzyme classification (EC) code, if applicable, are listed in Table 2. Note that proteins belonging to the same functional group have the same first EC number. The results in Table 2 show that most of the structural motifs found for the Mg2+-proteins map to certain protein functions. For example, proteins with the partial f(1–2)h motif are all hydrolases, catalyzing the hydrolytic cleavage of mostly ester bonds (EC3.1.-.-), except for beta-phosphoglucomutase (1O08), which is an isomerase converting beta-D-glucose 1-phosphate to beta-D-glucose 6-phosphate. Interestingly, although class b acid phosphatase (2B82) and the halotolerance protein hal 2 (1KA1) contain structurally nonhomologous Mg2+-binding domains with different CATH numbers, both are phosphoric monoester hydrolases (EC3.1.3.-). Proteins with the e(24–47)h(24)k motif are either lyases and/or isomerases, whereas proteins with the k(26–29)h(1)a motif have even more diverse functions: 3 are oxidoreductases (1POX, 1UMD, 2C3M), one is a lyase (1ZPD) and the other is a transferase (1ITZ). This shows that even if the proteins share structurally homologous domains (CATH number 184.108.40.2060) and structurally similar Mg2+-binding sites, as represented by the k(26–29)h(1)a motif, they can perform different functions.
Statistical Significance of the Mg2+-Structural Motifs
Do the structural motifs found for Mg2+-proteins in Table 2 occur in other proteins that do not bind metal ions? To address this question, de Brevern's databank of protein structures that have been encoded into 1D structural sequences was searched for the occurrence of each of the 4 structural motifs listed in Table 2. Consistent with the Mg2+ and Ca2+ datasets, proteins in de Brevern's databank sharing ≥ 30% sequence identity with ≥ 2.5-Å resolution X-ray structures were removed. Proteins in de Brevern's databank whose structures are complexed with metal ions were also removed, yielding a set of 385 non-homologous test proteins. In order to eliminate those matched structural letters that cannot spatially bind Mg2+, the maximum Cα-Cα distance between any pair of Mg2+-ligands belonging to proteins of a given structural motif in Table 2 was extracted; this distance is 9.32 Å for the e(24–47)h(24)k motif, 8.32 Å for f(1)h(109–349)b, 8.44 Å for f(2)h(126–158)m, and 7.86 Å for k(26–29)h(1)a. For a given structural motif in Table 2, matched letters in the test proteins whose Cα-Cα distances exceed the respective maximum distance were eliminated. This resulted in no matches for the e(24–47)h(24)k and f(2)h(126–158)m motifs, whereas 2 proteins (1C3K, 1GPE) contained the f(1)h(109–349)b motif, and another 2 proteins (1A7U, 1JFR) contained the k(26–29)h(1)a motif. A check of the literature confirmed that these 4 proteins (1C3K, 1GPE 1A7U, 1JFR) do not bind metal ions. This suggests that (i) the 4 Mg2+-structural motifs discovered are statistically significant, and (ii) the e(24–47)h(24)k and f(2)h(126–158)m motifs could be used to predict metal-binding sites.
Metal Preference of the Mg2+-Structural Motifs
To check the specificity of the 4 structural motifs in Table 2 for Mg2+, the same procedure used to represent the Mg2+-binding sites in terms of their local structure was repeated for Ca2+, which is the metal ion most similar to Mg2+. Both Mg2+ and Ca2+ are closed-shell divalent cations belonging to the same group (IIA) with similar chemical properties: They are both "hard" dications that prefer to bind directly to "hard" oxygen-containing anions, and are hence often found to bind in the same protein cavity . Thus, the 3D structure of each of the 177 nonredundant Ca2+ proteins was represented by a 16-letter structural alphabet (see Methods), and the 1D structural letter representation of the 230 Ca2+-binding sites are listed in Additional file 3.
None of the structural motifs in Table 2 or Additional file 2 were found in 3 or more Ca2+-binding sites, and therefore cannot be classified as Ca2+-structural motifs according to our definition. The f(1)h(109–349)b motif is found in the Ca2+-binding site of the hydrolase from the haloacid dehalogenase family (2FI1), which appears to utilize Mg2+ as a natural co-factor . Although the k(26–29)h(1)a motif is found in the calcium-binding sites of the transketolase protein (1TRK) and benzoylformate decarboxylase (1Q6Z), the latter is a Mg2+-dependent enzyme . The e(24–47)h(24)k and f(2)h(126–158)m motifs did not match any first-shell structural letters of the Ca2+-binding sites, indicating that they seem to favor Mg2+ over its competitor, Ca2+.
Discussion and conclusion
Comparison with Previous Structural Motif Discovery Methods
Assuming that similarity in the local active site structure implies similarity in biological function, 3D patterns/templates of key active sites have been used to suggest the function of a protein whose structure is known. The 3D patterns/templates have been constructed either manually or automatically using various methods, which have been reviewed recently by Watson et al. . Recently, 3D templates in the absence of experimental data have been constructed using the evolutionary trace method to identify evolutionarily important, solvent accessible residues that cluster in the protein structure . Furthermore, structural motifs for the metal-binding sites of 3 distinct metalloenzymes families; viz., DNase 1 homologs, dimetallic phosphatases, and dioxygenases, have been obtained by first identifying physical chemical property-based sequence motifs in homologous protein sequences, and subsequently identifying those motifs whose structures are conserved in members of a family/superfamily [23, 24]. However, to the best of our knowledge, 3D patterns of key active sites and recurrent patterns (structural motifs) have not been identified using the structural alphabet to convert 3D structures to the respective 1D letter sequences. Also, systematic studies of the structural preference or conservation of Mg2+-binding sites in nonhomologous proteins and Mg2+-specific structural motifs have not been reported.
Advantages of the Structural-Alphabet Based Motif Discovery Approach
This work presents the first application of the structural alphabet approach to define the 3D patterns of metal active sites and to identify recurrent patterns (structural motifs). The method requires as input only the 3D protein structure to define a 1D structural representation of the respective active site. The structural alphabet-based approach has several advantages: (i) It is efficient at handling many structures as it takes less than a minute on a present-day PC to convert a 3D structure to the corresponding 1D structural sequence. (ii) It requires no sequence comparisons, no parameters or scoring functions and can thus produce consistent structural motifs, whose structures are readily visualized, as illustrated in Figures 4 and 5. (iii) It is general and can be used to define 3D patterns not only in metal-binding sites, but also in enzyme active sites, ligand-binding clefts and interacting regions between proteins and their respective partners. The 3D patterns/motifs discovered could be incorporated in methods to detect metal/ligand-binding sites to improve their prediction accuracy.
Secondary Structure Preference of Mg2+-Binding Residues
In this work, the structural alphabet-based approach has been used to reveal the structural preference of Mg2+-binding sites. Even though helix-like segments represented by the letter 'm' is the most common building block of the Mg2+-proteins in the dataset, residues that bind Mg2+ disfavor helices, but favor loops. The similarity in the structural preference of the first and second-shell residues supports previous conclusions regarding the relationship between these 2 layers; namely, the structure and properties of the 2nd- shell are dictated by those of the 1st layer .
Similar Mg2+-Binding Site Structures in Dissimilar Protein Sequences
The motif discovery method herein has revealed 4 structural motifs, comprising 21% of the Mg2+-binding sites. The 3D structural motifs discovered seems to have more predictive utility in identifying Mg2+-binding sites than 1D sequence motifs: A scan of the Mg2+-protein sequences in our dataset for the occurrence of sequence motifs stored in the PROSITE  database yielded only a single positive match, 1WC1, which contains a PROSITE sequence motif predicting the protein to bind Mg2+. However, the ScanProsite results did not identify any of the Mg2+ proteins with structural motifs.
Functional Preference of the Mg2+-Structural Motifs
The structural motifs discovered generally relate to the biological role of Mg2+ and the function of the respective proteins. They capture some essential biochemical and/or evolutionary properties, as proteins found to contain a specific structural motif possess structurally homologous Mg2+-binding domains, even though they share no significant sequence homology. Furthermore, the f(2)h(126–158)m motif maps to a specific functional group, namely, hydrolases, indicating the apparent importance of the local Mg2+-binding site structure for the function of these hydrolases. As the f(2)h(126–158)m motif was not found in non-metalloproteins and in Ca2+-binding proteins, the presence of this motif in a novel protein structure may suggest a likely Mg2+-binding site and the protein function. On the other hand, the other 3 motifs map to more than one functional group, suggesting that the local Mg2+-binding site structure is not the only determinant of the protein's function.
Why Mg2+-Specific Structural Motifs are Not Found For Most Mg2+-Proteins
Out of the 70 nonhomologous Mg2+-proteins, only 16 have first-shell structural motifs, while the rest do not seem to possess any metal-binding site structural motifs-why? One reason might be that some Mg2+-structural motifs may have been missed out in this work. As the dataset employed only proteins with Mg2+-bound structures (see Database subsection below), some PDB structures complexed with heavier metal ions such as Mn2+ may in fact correspond to native Mg2+-binding site(s); moreover, not all structures of proteins whose native co-factor is Mg2+ have been solved. A second reason is that for native Mg2+-binding sites that can accommodate other metal ions such as Ca2+ or Mn2+, the binding-site structure need not be conserved in order to recognize a specific metal co-factor. A third reason is that although Mg2+ occupied the binding site in the 3D structure, it is not the native cofactor. Although all 70 proteins are bound to Mg2+ in our dataset, according to PDBSUM  and from the UniProt annotation and references therein, 14 proteins do not employ Mg2+ as the native co-factor, while for 6 proteins, the native metal-cofactor is apparently not known (see Additional file 1). For example, calbindin d9K is a vitamin D-dependent calcium-binding protein, but in the 1IG5 structure, the native cofactor Ca2+ has been replaced by Mg2+. In Mg2+-proteins with multiple Mg2+-binding sites, one or more sites may be non-native, as they have been artificially induced by the high Mg2+ concentration used during crystallization. In these cases, the local structure of the non-native metal-binding site would not be expected to share any similarity with that of a native Mg2+-binding site, where the conserved local structure (as in the f(2)h(126–158)m motif) plays an important role in the protein's function. The absence of structural motifs for non-native Mg2+-binding sites indirectly supports our strategy.
A set of 70 nonredundant Mg2+ proteins was created by searching the PDB  for structures with resolution < 2.5-Å containing Mg2+ with <30% sequence identity. Structures with residues missing in the middle of the sequence were excluded because such gaps in the structure could alter the spacing in the binding-site motifs (see below). Structures with Mg2+ bound to <3 protein ligands were also excluded, as 2-residue motifs cannot be considered specific enough for any practical use. The resulting Mg2+ dataset comprise 77 binding sites in 70 proteins. Note that although most Mg2+-proteins have only one binding site, some proteins have more than one Mg2+-binding sites (PDB entries 1MXG, 1NUY, 1VCL, 1WL6, 2BJI, and 2BVC). A set of nonredundant Ca2+ proteins was created following the same procedure used to create the Mg2+ dataset. This resulted in 230 Ca2+-binding sites in 177 proteins. The PDB entries, EC code, and amino acid residues bound to the metal ion in the 77 Mg2+ and 230 Ca2+ sites are given in Additional files 1 and 3, respectively.
The Structural Alphabet
Each metalloprotein structure was encoded into its 1D structural sequence according to the original structural alphabet defined by de Brevern and co-workers . We refer the reader to the original work  for details of how this alphabet was devised, and briefly outline the procedure here. The backbone of each protein from a nonredundant protein structure database was represented by consecutive 5-residue segments, each described by a vector of 8 backbone dihedral angles V(ψn-2, φn-1, ψn-1, φn, ψn, φn+1, ψn+1, φn+2). The dissimilarity between 2 vectors V1 and V2 of dihedral angles is measured by the root-mean-square deviations of the dihedral angle values (rmsda), which is defined as the Euclidean distance among the 4 links:
Using an unsupervised cluster analyzer based on the above rmsda of the segments, 16 letters (also called protein blocks) were identified, which in turn comprise the structural 'alphabet'.
Converting 3D Structure to 1D Structural Alphabet
Definition of 1st and 2nd-Shell Metal Ligands
Analyses of high-resolution X-ray structures with crystallographic R factor ≤ 0.065 of small metal complexes in the Cambridge Structural Database  have shown that the mean 1st-shell Mg-Owater, Mg-Ocarboxylate, and Mg-Oalcohol distances do not exceed 2.11 Å, while the Ca-Owater, Ca-Ocarboxylate, Ca-Oalcohol, and Ca-Nimidazole bond distances do not exceed 2.55 Å . To account for the lower resolution of the PDB structures, a slightly larger cutoff was used to locate the 1st-shell amino acid ligands. Thus, the Mg2+ and Ca2+ ligands were defined as residues with a donor atom within 2.5 Å and 2.7 Å from the metal ion, respectively. The heavy atoms of the metal-bound amino acid residues were then selected as centers to search for the 2nd-shell protein ligands using a hydrogen-bonding cutoff of 3.5 Å . Note that water molecules in the first and second shells were not identified, as they were not used to define a structural motif.
Definition of 1st and 2nd-Shell Structural Representation/Pattern
Since the 3D structure of each metalloprotein has been converted into the respective 1D letter sequence as described above, the letters that correspond to the metal-bound amino acid residues yielded a structural representation of the first-shell, as shown in the last columns of Additional files 1 and 3 for each metal-binding site. For example, in the case of the human/chicken estrogen receptor (1HCQ), the letters corresponding to the Zn-binding Cys residues at position 7, 10, 24 and 27 are f, o, f, and m, respectively, yielding a f(2)o(13)f(2)m representation of the first-shell for 1HCQ (see Figure 1).
Definition of Structural Motifs
In previous work , all values of k between 2 and 20 were used to define a structural motif, where k is the number of first-shell structural patterns with the same structural letters and similar interletter spacing. Here, k ≥ 3 was used to define a structural motif. Thus, if 3 or more proteins possess first-shell structural patterns with the same structural letters and similar interletter spacing, these proteins are assumed to share a common structural motif. For example, transketolase (1ITZ), pyruvate oxidase (1POX), 2 oxo-acid dehydrogenase alpha subunit (1UMD), pyruvate decarboxylase (1ZPD), and pyruvate-ferredoxin oxidoreductase (2C3M) share the first-shell structural pattern, k(26–29)h(1)a, which thus defines a structural motif.
We thank anonymous reviewers for constructive comments/suggestions. We are grateful to Steven Wu, Michael J. B. Lin, and Backy Chen for assistance in the statistical analyses, and Leon Li, Todor Dudev, and Gopi Kuppuraj for literature assistance. This work was supported by NSC contract no. NSC 94-2113-M-001-018 to CL.
- Cowan JA: Biological Chemistry of Magnesium. New York , VCH; 1995.Google Scholar
- Nordlund P, Sjoberg BM, Eklund H: Three-dimensional structure of the free radical protein of ribonucleotide reductase. Nature 1990, 345: 593. 10.1038/345593a0View ArticlePubMedGoogle Scholar
- Dudev T, Cowan JA, Lim C: Competitive Binding in Magnesium Coordination Chemistry: Water versus Ligands of Biological Interest. J Am Chem Soc 1999, 121: 7665–7673. 10.1021/ja984470tView ArticleGoogle Scholar
- Cowan JA: Metal activation of enzymes in nucleic acid biochemistry. Chem Rev 1998, 98: 1067–1087. 10.1021/cr960436qView ArticlePubMedGoogle Scholar
- Chotia C, Lesk AM: The relation between the divergence of sequence and structure in proteins. EMBO J 1986, 5: 823–826.Google Scholar
- de Brevern AG, Etchebest C, Hazout S: Bayesian probabilistic approach for predicting backbone structures in terms of protein blocks. Proteins: Struct Funct Genet 2000, 41: 271–287. Publisher Full Text 10.1002/1097-0134(20001115)41:3<271::AID-PROT10>3.0.CO;2-ZView ArticleGoogle Scholar
- de Brevern AG: New assessment of a structural alphabet. In Silico Biol 2005, 5: 26.Google Scholar
- Unger R, Sussman JL: The importance of short structural motifs in protein structure analysis. J Comput Aided Mol Des 1993, 7: 457–472. 10.1007/BF02337561View ArticlePubMedGoogle Scholar
- Tyagi M, Sharma P, Swamy CS, Cadet F, Srinivasan N, de Brevern AG, Offman B: Protein block expert (PBE): a web-based protein structure analysis server using a structural alphabet. Nucleic Acids Res 2006, 34: W119-W123. 10.1093/nar/gkl199PubMed CentralView ArticlePubMedGoogle Scholar
- Tyagi M, Gowri VS, Srinivasan N, de Brevern AG, Offmann B: A substitution matrix for structural alphabet based on structural alignment of homologous proteins and its applications. Proteins: Structure, Function & Bioinformatics 2006 , 65(1):32–39. 10.1002/prot.21087View ArticleGoogle Scholar
- Bystroff C, Baker D: Prediction of local structure in proteins using a library of sequence- structure motifs. J Mol Biol 1998, 281(3):565–577. 10.1006/jmbi.1998.1943View ArticlePubMedGoogle Scholar
- Kolodny R, Koehl P, Guibas L, Levitt M: Small libraries of protein fragments model native structures accurately. J Mol Biol 2002, 323: 297–307. 10.1016/S0022-2836(02)00942-7View ArticlePubMedGoogle Scholar
- Fourrier L, Benros C, de Brevern AG: Use of a structural alphabet for analysis of short loops connecvting repetitive structures. BMC Bioinformatics 2004, 5: 58. 10.1186/1471-2105-5-58PubMed CentralView ArticlePubMedGoogle Scholar
- Dudev T, Lin YL, Dudev M, Lim C: First-Second Shell Interactions in Metal Binding Sites in Proteins: A PDB Survey and DFT/CDM Calculations. J Am Chem Soc 2003, 125: 3168–3180. 10.1021/ja0209722View ArticlePubMedGoogle Scholar
- Petkovich M, Brand NJ, Krust A, Chambon P: A human retinoic acid receptor which belongs to the family of nuclear receptors. Nature 1987, 330: 444–450. 10.1038/330444a0View ArticlePubMedGoogle Scholar
- Berman HM, Battistuz T, Bhat TN, Bluhm WF, Bourne PE, Burkhardt K, Iype L, Jain S, Fagan P, Marvin J, Padilla D, Ravichandran V, Schneider B, Thanki N, Weissig H, Westbrook JD, Zardecki C: The Protein Data Bank. Acta Crystallogr D 2002, 58: 899–907. 10.1107/S0907444902003451View ArticlePubMedGoogle Scholar
- Sigrist CJ, Cerutti L, Hulo N, Gattiker A, Falquet L, Pagni M, Bairoch A, Bucher P: PROSITE: a documented database using patters and profiles as motif desriptors. Brief Bioinform 2002, 3: 265–274. 10.1093/bib/3.3.265View ArticlePubMedGoogle Scholar
- Dudev T, Lim C: Principles Governing Mg, Ca, and Zn Binding and Selectivity in Proteins. Chem Rev 2003, 103: 773–787. 10.1021/cr020467nView ArticlePubMedGoogle Scholar
- Lahiri SD, Zhang GF, Dunaway-Mariano D, Allen KN: Diversification of function in the haloacid dehalogenase enzyme superfamily: The role of the cap domain in hydrolytic phosphorussingle bondcarbon bond cleavage. Bioinorg Chem 2006, 34: 394–409.View ArticleGoogle Scholar
- Iding H, Dunnwald T, Greiner L, Liese A, Muller M, Siegert P, Grotzinger J, Demir AS, Pohl M: Benzoylformate decarboxylase from Pseudomonas putida as stable catalyst for the synthesis of chiral 2-hydroxy ketones. Chemistry -A Eur J 2000, 6: 1483–1495. Publisher Full Text 10.1002/(SICI)1521-3765(20000417)6:8<1483::AID-CHEM1483>3.0.CO;2-SView ArticleGoogle Scholar
- Watson JD, Laskowski RA, Thornton JM: Predicting protein function from sequence and structural data. Curr Op Struct Biol 2005, 15: 275–284. 10.1016/j.sbi.2005.04.003View ArticleGoogle Scholar
- Kristensen DM, Chen BY, Fofanov VY, Ward RM, Lisewski AM, Kimmel M, Kavraki L, Lichtarge O: Recurrent use of evolutionary importance for functional annotation of proteins based on local structural similarity. Prot Sci 2006, 15: 1530–1536. 10.1110/ps.062152706View ArticleGoogle Scholar
- Mathura VS, Schein CH, Braun W: Identifying property based sequence motifs in protein families and superfamilies: application to DNase-1 related endonucleases. Proteins: Structure, Function and Bioinformatics 2003, 19: 1381–1390.PubMedGoogle Scholar
- Schein CH, Zhou B, Oezguen N, Mathura VS, Braun W: Molego-based definition of the architecture and specificity of metal-binding sites. Proteins: Structure, Function and Bioinformatics 2005, 58: 200–210. 10.1002/prot.20253View ArticleGoogle Scholar
- Laskowski RA: PDBsum: summaries and analyses of PDB structures. Nucleic Acids Res 2001, 29(1):221–222. 10.1093/nar/29.1.221PubMed CentralView ArticlePubMedGoogle Scholar
- Allen FH: The Cambridge structural database: a quarter of a million crystal structures and rising. Acta Cryst 2002, B58: 380–388.View ArticleGoogle Scholar
- Harding MM: The geometry of metal-ligand interactions relevant to proteins. Acta Cryst 1999, D55: 1432–1443.Google Scholar
- McDonald IK, Thornton JM: Satisfying hydrogen bonding potential in proteins. J Mol Biol 1994, 238(5):777–793. 10.1006/jmbi.1994.1334View ArticlePubMedGoogle Scholar
- Jonassen I, Eidhammer I, Conklin D, Taylor WR: Structure motif discovery and mining the PDB. Bioinformatics 2001, 18: 362–367. 10.1093/bioinformatics/18.2.362View ArticleGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.