Protein 3D structure-based neural networks highly improve the accuracy in compound-protein binding affinity prediction.
Binjie GuoHanyu ZhengHuan HuangHaohan JiangXiaodan LiNaiyu GuanYanming ZuoYicheng ZhangHengfu YangXuhua WangPublished in: CoRR (2022)
Keyphrases
- contact map
- contact maps
- protein secondary structure
- tertiary structure
- protein structure
- neural network
- prediction accuracy
- physicochemical properties
- subcellular localization
- amino acids
- multiple sequence alignments
- protein structure prediction
- improve the prediction accuracy
- protein secondary structure prediction
- amino acid sequences
- secondary structure
- protein tertiary structure
- protein sequences
- molecular structures
- predicting protein
- dna binding
- protein interaction
- protein function
- high accuracy
- protein folding
- mhc class ii
- protein structural
- coarse grained
- pairwise
- remote homology detection
- protein function prediction
- drug design
- hiv protease
- protein homology
- protein protein interactions
- protein chains
- sequence similarity
- experimentally determined
- protein fold recognition
- protein interaction networks
- back propagation
- pattern recognition