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

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/}.