DISTEMA: distance map-based estimation of single protein model accuracy with attentive 2D convolutional neural network.
Journal:
BMC bioinformatics
Published Date:
Apr 19, 2022
Abstract
BACKGROUND: Estimation of the accuracy (quality) of protein structural models is important for both prediction and use of protein structural models. Deep learning methods have been used to integrate protein structure features to predict the quality of protein models. Inter-residue distances are key information for predicting protein's tertiary structures and therefore have good potentials to predict the quality of protein structural models. However, few methods have been developed to fully take advantage of predicted inter-residue distance maps to estimate the accuracy of a single protein structural model.