Evaluation Metrics for Protein Structure Generation

Joshua Southern, Arne Schneuing, Michael M. Bronstein, Bruno Correia

Keywords: Protein design, generative model, machine learning, evaluation

Abstract: Generative models have become increasingly popular for sampling novel proteins. To compare and evaluate these models, we need metrics that can assess the quality of the generated structures. We propose a set of standardized metrics for benchmarking protein generation. We experimentally show that these metrics can measure differences between proteins on a distributional level, as well as quantify the novelty, diversity and designability of the generated proteins.

Submission Number: 6