Computational Grid technology has been noticed as an issue to solve large-scale bioinformatics-related problems and improves data accuracy and processing speed on multiple computation platforms with distributed bioDATA sets. This paper proposes a Gridbased intelligence ART1 classifier which operates an ART1 clustering classification using Grid computational resources with distributed GPCR data sets. This paper evaluates performance of the Gridbased ART1 classifier in comparing to the Grid-based ART1 classifier and the Grid-based 3-tier ART1 classifier. The number of communication message of the Grid-based intelligence ART1 classifier is less than the others classifier. And the classification processing time of the Grid-based intelligence ART1 classifier is 13% classification processing time of the Grid-based ART1 classifier and is 25% classification processing time of the Grid-based 3-tier ART1 classifier. Computational Grid in bioinformatics applications gives a great promise of high performance processing with large-scale and geographically distributed bioDATA sets and provides a good progress in guaranteeing high bioData accuracy with reasonable processing resources.