University of Missouri researchers published PSBench, a curated database of 1.4 million protein structure models annotated and quality‑checked by independent experts. The resource is intended to improve benchmarking and validation of AI systems that predict protein structure—tools that underpin structure‑based drug discovery and biologics design. PSBench provides standardized, annotated test sets for model evaluation and should help developers reduce false positives and overfitting in protein modeling pipelines. The dataset aims to accelerate translation of computational predictions into reliable experimental hypotheses for therapeutic target validation.