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DGCddG: Deep Graph Convolution for Predicting Protein-Protein Binding Affinity Changes Upon Mutations.

IEEE/ACM transactions on computational biology and bioinformatics - 1 Jan 2000

Jiang Yelu, Quan Lijun, Li Kailong, Li Yan, Zhou Yiting, Wu Tingfang, Lyu Qiang

Abstract excerpt

Effectively and accurately predicting the effects of interactions between proteins after amino acid mutations is a key issue for understanding the mechanism of protein function and drug design. In this study, we present a deep graph convolution (DGC) network-based framework, DGCddG, to predict the changes of protein-protein binding affinity after mutation. DGCddG incorporates multi-layer graph convolution to...

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PMID: 37018301
DOI: 10.1109/TCBB.2022.3233627

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