GraphQA: protein model quality assessment using graph convolutional networks.

ABSTRACT:

Motivation

Proteins are ubiquitous molecules whose function in biological processes is determined by their 3D structure. Experimental identification of a protein's structure can be time-consuming, prohibitively expensive and not always possible. Alternatively, protein folding can be modeled using computational methods, which however are not guaranteed to always produce optimal results. GraphQA is a graph-based method to estimate the quality of protein models, that possesses favorable properties such as representation learning, explicit modeling of both sequential and 3D structure, geometric invariance and computational efficiency.

Results

GraphQA performs similarly to state-of-the-art methods despite using a relatively low number of input features. In addition, the graph net

SUBMITTER: Baldassarre F 

PROVIDER: S-EPMC8058777 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature