Evolution-Informed Structural Subgraph Protein Representations

Problem

Foundation models like ESM-2 provide powerful protein embeddings, while explicit structural and evolutionary features may add complementary information for function prediction.

Approach

We developed graph-based protein representations using structural subgraph counts combined with evolutionary features. The method constructs protein graphs from structures and extracts interpretable features that capture local geometry and conservation patterns.

Evaluation

We are evaluating whether structural and evolutionary features improve pathogenicity prediction over ESM-2 and GNN baselines. The representation also provides interpretable features that domain experts can analyze.

Status

Manuscript in preparation. Code includes baseline comparisons and evaluation protocols. Code and data will be released.