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

Observed frequency distribution of the shortest path between                            catalytic residues.
© Copyright Policy
Related In: Results  -  Collection


getmorefigures.php?uid=PMC3066176&req=5

pone-0016932-g002: Observed frequency distribution of the shortest path between catalytic residues.

Mentions: The shortest path between catalytic residues was analyzed Fig. 2. In most cases, intimate interactions were observed between catalytic residues. The fraction of interactions with direct contact and those with an interval of one residue are 57 and 26, respectively, which indicates collaboration between catalytic residues for effective function. In this method, some catalytic residues were also scored highly by closeness and were therefore treated as keyAAs. In this sense, correlations among catalytic residues are also, at least partially, implied by DNSC.


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)

Observed frequency distribution of the shortest path between                            catalytic residues.
© Copyright Policy
Related In: Results  -  Collection

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

pone-0016932-g002: Observed frequency distribution of the shortest path between catalytic residues.
Mentions: The shortest path between catalytic residues was analyzed Fig. 2. In most cases, intimate interactions were observed between catalytic residues. The fraction of interactions with direct contact and those with an interval of one residue are 57 and 26, respectively, which indicates collaboration between catalytic residues for effective function. In this method, some catalytic residues were also scored highly by closeness and were therefore treated as keyAAs. In this sense, correlations among catalytic residues are also, at least partially, implied by DNSC.

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