Limits...
Novel feature for catalytic protein residues reflecting interactions with other residues.

Li Y, Li G, Wen Z, Yin H, Hu M, Xiao J, Li M - PLoS ONE (2011)

Bottom Line: In an original attempt to quantify the effects of several key residues on catalytic residues, a power function was used to model interactions between residues.The results indicate that focusing on a few residues is a feasible approach to identifying catalytic residues.Values of 88.6 for sensitivity and 88.4 for specificity were obtained by 10-fold cross-validation.

View Article: PubMed Central - PubMed

Affiliation: College of Chemistry and State Key Laboratory of Biotherapy, Sichuan University, Chengdu, Peoples Republic of China.

ABSTRACT
Owing to their potential for systematic analysis, complex networks have been widely used in proteomics. Representing a protein structure as a topology network provides novel insight into understanding protein folding mechanisms, stability and function. Here, we develop a new feature to reveal correlations between residues using a protein structure network. In an original attempt to quantify the effects of several key residues on catalytic residues, a power function was used to model interactions between residues. The results indicate that focusing on a few residues is a feasible approach to identifying catalytic residues. The spatial environment surrounding a catalytic residue was analyzed in a layered manner. We present evidence that correlation between residues is related to their distance apart most environmental parameters of the outer layer make a smaller contribution to prediction and ii catalytic residues tend to be located near key positions in enzyme folds. Feature analysis revealed satisfactory performance for our features, which were combined with several conventional features in a prediction model for catalytic residues using a comprehensive data set from the Catalytic Site Atlas. Values of 88.6 for sensitivity and 88.4 for specificity were obtained by 10-fold cross-validation. These results suggest that these features reveal the mutual dependence of residues and are promising for further study of structure-function relationship.

Show MeSH

Related in: MedlinePlus

The spatial structure and local contact network for                                dihydropteroate synthase (1aj0).(a) The local structure of the catalytic residues (yellow) and                                keyAAs (red). (b) The local contact network for the                            catalytic residues and keyAAs. Here, Asn22, Arg63, and                            Arg255 are catalytic residues, which were observed adjacent to                                keyAAs Met18, Asn115, Leu215, Ile253 and Arg255 and                            their interactions are shown.
© Copyright Policy
Related In: Results  -  Collection


getmorefigures.php?uid=PMC3066176&req=5

pone-0016932-g003: The spatial structure and local contact network for dihydropteroate synthase (1aj0).(a) The local structure of the catalytic residues (yellow) and keyAAs (red). (b) The local contact network for the catalytic residues and keyAAs. Here, Asn22, Arg63, and Arg255 are catalytic residues, which were observed adjacent to keyAAs Met18, Asn115, Leu215, Ile253 and Arg255 and their interactions are shown.

Mentions: A detailed case study of dihydropteroate synthase PDB1aj0 is presented Fig. 3. Residues Met18, Asn115, Leu215, Ile253 and Arg255 are distant in the sequence but spatially close and were identified as the keyAAs in this structure. The catalytic site consists of the catalytic residues Asn22, Arg63 and Arg255, which was observed adjacent to keyAAs. The local interaction network for keyAAs and catalytic residues is shown in Fig. 3b. Arg255 was determined as a keyAA with direct interactions with other keyAAs. Asn22 has direct contact with Arg255, whereas the length of its shortest path to the other keyAAs is 2. Arg63 was far from the keyAAs however, close connections were found between this and the two other catalytic residues.


Novel feature for catalytic protein residues reflecting interactions with other residues.

Li Y, Li G, Wen Z, Yin H, Hu M, Xiao J, Li M - PLoS ONE (2011)

The spatial structure and local contact network for                                dihydropteroate synthase (1aj0).(a) The local structure of the catalytic residues (yellow) and                                keyAAs (red). (b) The local contact network for the                            catalytic residues and keyAAs. Here, Asn22, Arg63, and                            Arg255 are catalytic residues, which were observed adjacent to                                keyAAs Met18, Asn115, Leu215, Ile253 and Arg255 and                            their interactions are shown.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3066176&req=5

pone-0016932-g003: The spatial structure and local contact network for dihydropteroate synthase (1aj0).(a) The local structure of the catalytic residues (yellow) and keyAAs (red). (b) The local contact network for the catalytic residues and keyAAs. Here, Asn22, Arg63, and Arg255 are catalytic residues, which were observed adjacent to keyAAs Met18, Asn115, Leu215, Ile253 and Arg255 and their interactions are shown.
Mentions: A detailed case study of dihydropteroate synthase PDB1aj0 is presented Fig. 3. Residues Met18, Asn115, Leu215, Ile253 and Arg255 are distant in the sequence but spatially close and were identified as the keyAAs in this structure. The catalytic site consists of the catalytic residues Asn22, Arg63 and Arg255, which was observed adjacent to keyAAs. The local interaction network for keyAAs and catalytic residues is shown in Fig. 3b. Arg255 was determined as a keyAA with direct interactions with other keyAAs. Asn22 has direct contact with Arg255, whereas the length of its shortest path to the other keyAAs is 2. Arg63 was far from the keyAAs however, close connections were found between this and the two other catalytic residues.

Bottom Line: In an original attempt to quantify the effects of several key residues on catalytic residues, a power function was used to model interactions between residues.The results indicate that focusing on a few residues is a feasible approach to identifying catalytic residues.Values of 88.6 for sensitivity and 88.4 for specificity were obtained by 10-fold cross-validation.

View Article: PubMed Central - PubMed

Affiliation: College of Chemistry and State Key Laboratory of Biotherapy, Sichuan University, Chengdu, Peoples Republic of China.

ABSTRACT
Owing to their potential for systematic analysis, complex networks have been widely used in proteomics. Representing a protein structure as a topology network provides novel insight into understanding protein folding mechanisms, stability and function. Here, we develop a new feature to reveal correlations between residues using a protein structure network. In an original attempt to quantify the effects of several key residues on catalytic residues, a power function was used to model interactions between residues. The results indicate that focusing on a few residues is a feasible approach to identifying catalytic residues. The spatial environment surrounding a catalytic residue was analyzed in a layered manner. We present evidence that correlation between residues is related to their distance apart most environmental parameters of the outer layer make a smaller contribution to prediction and ii catalytic residues tend to be located near key positions in enzyme folds. Feature analysis revealed satisfactory performance for our features, which were combined with several conventional features in a prediction model for catalytic residues using a comprehensive data set from the Catalytic Site Atlas. Values of 88.6 for sensitivity and 88.4 for specificity were obtained by 10-fold cross-validation. These results suggest that these features reveal the mutual dependence of residues and are promising for further study of structure-function relationship.

Show MeSH
Related in: MedlinePlus