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ATP-binding site as a further application of neural networks to residue level prediction

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2 Author(s)
Ahmad, S. ; Nat. Inst. of Biomed. Innovation, Ibaraki ; Ahmad, Z.

Similar neural network models based on single sequence and evolutionary profiles of residues have been successfully used in the past for predicting secondary structure, solvent accessibility, protein-, DNA- and carbohydrate- binding sites. ATP is a ubiquitous ligand in all living-systems, involved in most biological functions requiring energy and charge transfer. Prediction of ATP-binding site from single sequences and their evolutionary profiles at a high throughput rate can be used at genomic level as well as quick clues for site-directed mutagenesis experiments. We have developed a method for such predictions to demonstrate yet another application of sequence-base prediction algorithms using neural networks. This method can achieve 81% sensitivity and 69% specificity which are mutually adjustable in a wide range on a three-fold cross-validation data set.

Published in:

Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on

Date of Conference:

1-8 June 2008