A Batch Fuzzy Query System for Predicting Protein Stability Changes

Predicting protein mutant stability changes is important for protein design. Although many methods have tried to improve prediction accuracy by various models, it will be difficult to employ them when the required input information is incomplete. Therefore, we have proposed a fuzzy query method previously to predict stability changes upon single mutations using partial input information. However, when a researcher has tens or hundreds of queries to predict, he needs to input query data repeatedly. It is better to issue queries in a batch, which incurs another problem. Because our proposed fuzzy query method is implemented in the FuzzyCLIPS language, it takes a long time to process a batch of queries. To shorten the response time, we propose parallelizing queries in emerging cluster systems or grid systems. Furthermore, to address the problem of heterogeneous computing power of cluster and grid nodes, a variety of self-scheduling schemes have been implemented for better load balance. Experimental results show that our proposed parallel fuzzy query system can provide hundreds of predications in more reasonable response time.