RAGPPI: New Benchmark Dataset for AI-Assisted Protein Interaction Analysis in Drug Discovery
Researchers have created RAGPPI, a benchmark dataset of 4,420 question-answer pairs designed to evaluate AI systems at identifying biological impacts of protein-protein interactions for drug development. The dataset combines expert-annotated gold-standard data (500 pairs) with machine-generated silver-standard data (3,720 pairs), using an ensemble evaluation method. This addresses a gap in tools for testing retrieval-augmented generation (RAG) systems that could accelerate the target identification phase of drug discovery.
RAGPPI is a new factual question-answer benchmark created to evaluate how well large language models and RAG frameworks can identify the biological impacts of protein-protein interactions—a critical step in drug target identification. The researchers built the dataset through a two-stage process: first creating a gold-standard dataset of 500 expert-annotated question-answer pairs based on criteria identified through expert interviews, then expanding it to 3,720 silver-standard pairs using an ensemble auto-evaluation LLM that incorporates expert labeling characteristics and fact-similarity metrics. The benchmark addresses a previously unmet need, as no existing evaluation dataset focused specifically on assessing AI systems' ability to retrieve and reason about PPI biological impacts. The authors developed custom evaluation metrics (F1 and F2 scores) to measure factual accuracy and similarity. The team has committed to maintaining RAGPPI as a community resource to support ongoing research in AI-assisted drug discovery.
What's missing
The paper does not discuss potential limitations of the benchmark (e.g., coverage of specific protein classes, generalization to novel interactions, or potential biases in expert annotations), nor does it address how the benchmark performs with different LLM architectures or whether results have been validated against independent expert review beyond the initial annotation phase.
What different sources said
- arXiv cs.CLCenter
RAGPPI: RAG Benchmark for Protein-Protein Interactions in Drug Discovery
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