DCI: An Accurate Quality Assessment Criteria for Protein Complex Structure Models

TL;DR

This paper introduces DCI, a new evaluation metric for protein complex structure models that improves accuracy and applicability over existing methods like DockQ, especially in non-docking scenarios.

Contribution

The authors propose DCI, a novel evaluation strategy based on distance and contact-interface maps, which outperforms DockQ in accuracy and handles non-docking cases effectively.

Findings

DCI achieves comparable evaluation accuracy to DockQ according to CAPRI classification.

DCI performs well on CASP datasets, aligning with official assessments.

DCI better evaluates overall structure deviations caused by interface prediction errors.

Abstract

The structure of proteins is the basis for studying protein function and drug design. The emergence of AlphaFold 2 has greatly promoted the prediction of protein 3D structures, and it is of great significance to give an overall and accurate evaluation of the predicted models, especially the complex models. Among the existing methods for evaluating multimer structures, DockQ is the most commonly used. However, as a more suitable metric for complex docking, DockQ cannot provide a unique and accurate evaluation in the non-docking situation. Therefore, it is necessary to propose an evaluation strategy that can directly evaluate the whole complex without limitation and achieve good results. In this work, we proposed DCI score, a new evaluation strategy for protein complex structure models, which only bases on distance map and CI (contact-interface) map, DCI focuses on the prediction accuracy of the contact interface based on the overall evaluation of complex structure, is not inferior to DockQ in the evaluation accuracy according to CAPRI classification, and is able to handle the non-docking situation better than DockQ. Besides, we calculated DCI score on CASP datasets and compared it with CASP official assessment, which obtained good results. In addition, we found that DCI can better evaluate the overall structure deviation caused by interface prediction errors in the case of multi-chains. Our DCI is available at \url{https://gitee.com/WendaWang/DCI-score.git}, and the online-server is available at \url{http://mialab.ruc.edu.cn/DCIServer/}.