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Rapid catalytic template searching as an enzyme function prediction procedure.

ABSTRACT: We present an enzyme protein function identification algorithm, Catalytic Site Identification (CatSId), based on identification of catalytic residues. The method is optimized for highly accurate template identification across a diverse template library and is also very efficient in regards to time and scalability of comparisons. The algorithm matches three-dimensional residue arrangements in a query protein to a library of manually annotated, catalytic residues--The Catalytic Site Atlas (CSA). Two main processes are involved. The first process is a rapid protein-to-template matching algorithm that scales quadratically with target protein size and linearly with template size. The second process incorporates a number of physical descriptors, including binding site predictions, in a logistic scoring procedure to re-score matches found in Process 1. This approach shows very good performance overall, with a Receiver-Operator-Characteristic Area Under Curve (AUC) of 0.971 for the training set evaluated. The procedure is able to process cofactors, ions, nonstandard residues, and point substitutions for residues and ions in a robust and integrated fashion. Sites with only two critical (catalytic) residues are challenging cases, resulting in AUCs of 0.9411 and 0.5413 for the training and test sets, respectively. The remaining sites show excellent performance with AUCs greater than 0.90 for both the training and test data on templates of size greater than two critical (catalytic) residues. The procedure has considerable promise for larger scale searches.

SUBMITTER: Nilmeier JP

PROVIDER: S-EPMC3651201 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Rapid catalytic template searching as an enzyme function prediction procedure.

Nilmeier Jerome P JP Kirshner Daniel A DA Wong Sergio E SE Lightstone Felice C FC

PloS one 20130510 5

We present an enzyme protein function identification algorithm, Catalytic Site Identification (CatSId), based on identification of catalytic residues. The method is optimized for highly accurate template identification across a diverse template library and is also very efficient in regards to time and scalability of comparisons. The algorithm matches three-dimensional residue arrangements in a query protein to a library of manually annotated, catalytic residues--The Catalytic Site Atlas (CSA). T ...[more]

PMID: 23675414

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Project description:The hierarchical clustering and statistical techniques usually used to analyse microarray data do not inherently represent the underlying biology. Herein, a hybrid approach involving characteristics of both supervised and unsupervised learning is presented. This approach is based on template matching in which the interaction of the variables of inherent malignancy and the ability to express the malignant phenotype are modelled. Immortalised normal urothelial cells and bladder cancer cells of different malignancy were grown in conventional two-dimensional tissue culture and in three dimensions on extracellular matrices (ECMs) that were either permissive or restrictive for expression of the malignant phenotype. The transcriptome represents the effects of two variables--inherent malignancy and the modulatory effect of ECM. By assigning values to each of the biological variables of inherent malignancy and the ability to express the malignant phenotype, a template was constructed, which encapsulated the interaction between them. Gene expression correlating both positively and negatively with the template was observed, but when iterative correlations were carried out, the different models for the template converged on the same actual template. A subset of 21 genes was identified, which correlated with two a priori models or an optimised model above the 95% confidence limits identified in a bootstrap resampling with 5000 permutations of the data set. The correlation coefficients of expression of several genes were > 0.8. Analysis of upstream transcriptional regulatory elements (TREs) confirmed that these genes were not a randomly selected set of genes. Several TREs were identified as significantly over-expressed in the sample of 20 genes for which TREs were identified, and the high correlations of several genes were consistent with transcriptional co-regulation. The authors suggest that the template method can be used to identify a unique set of genes for further investigation.

Dataset Information

Rapid catalytic template searching as an enzyme function prediction procedure.

Publications

Rapid catalytic template searching as an enzyme function prediction procedure.

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