Parallel sequence-search tools are rising in popularity among computational biologists. With the rapid growth of sequence databases, database segmentation is the trend of the future for such search tools. While I/O currently is not a significant bottleneck for parallel sequence-search tools, future technologies including faster processors, customized computational hardware such as FPGAs, improved search algorithms, and exponentially growing databases will emphasize an increasing need for efficient parallel I/O in future parallel sequence-search tools. Our paper focuses on examining different I/O strategies for these future tools in a modern parallel file system (PVFS2). Because implementing and comparing various I/O algorithms in every search tool is labor-intensive and time-consuming, we introduce S3aSim, a general simulation framework for sequence-search which allows us to quickly implement, test, and profile various I/O strategies. We examine a variety of I/O strategies (e.g., master-writing and various worker-writing strategies using individual and collective I/O methods) for storing result data in sequence-search tools such as mpiBLAST, pioBLAST, and parallel HMMer. Our experiments fully detail the interaction of computing and I/O within a full application simulation as opposed to typical I/O-only benchmarks.