Estimating Protein Complex Model Accuracy Using Graph Transformers and Pairwise Similarity Graphs.

ABSTRACT:

Motivation

Estimation of protein complex structure accuracy is an essential step in protein complex structure prediction and is also important for users to select good structural models for various applications, such as protein function analysis and drug design. Despite the success of structure prediction methods such as AlphaFold2 and AlphaFold3, predicting the quality of predicted complex structures (structural models) and selecting top ones from large model pools remains challenging.

Results

We present GATE, a novel method that uses graph transformers on pairwise model similarity graphs to predict the quality (accuracy) of complex structural models. By integrating single-model and multi-model quality features, GATE captures both the characteristics of individual models an

SUBMITTER: Liu J 

PROVIDER: S-EPMC11838578 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature