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Many processes in biology and drug discovery involve various 3D interactions between molecules, such as protein and protein, protein and small molecule, etc.
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Pdb-wide collection of binding data: current status of the pdbbind database
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Updates to the integrated protein–protein interaction benchmarks: docking benchmark version 5 and affinity benchmark version 2
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Schnet: A continuous-filter convolutional neural network for modeling quantum interactions
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Mmseqs2 enables sensitive protein sequence searching for the analysis of massive data sets
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Attention is all you need
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K deep: protein–ligand absolute binding affinity prediction via 3d-convolutional neural networks
Jiménez, J., Skalic, M., Martinez-Rosell, G., and De Fabritiis, G · 2018
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Junction tree variational autoencoder for molecular graph generation
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Deepdta: deep drug–target binding affinity prediction
Öztürk, H., Özgür, A., and Ozkirimli, E · 2018
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Comparative assessment of scoring functions: the casf-2016 update
Su, M., Yang, Q., Du, Y., Feng, G., Liu, Z., Li, Y., and Wang, R · 2018
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Tensor field networks: Rotation-and translation-equivariant neural networks for 3d point clouds
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Learning protein sequence embeddings using information from structure
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Mace: Higher order equivariant message passing neural networks for fast and accurate force fields
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E (3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials
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Evaluating protein transfer learning with tape
Rao, R., Bhattacharya, N., Thomas, N., Duan, Y., Chen, P., Canny, J., Abbeel, P., and Song, Y · 2019
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Applications of machine learning in drug discovery and development
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Anti-hcv, nucleotide inhibitors, repurposing against covid-19
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Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning
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Intrinsic-extrinsic convolution and pooling for learning on 3d protein structures
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Learning from protein structure with geometric vector perceptrons
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Is transfer learning necessary for protein landscape prediction?
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Equivariant graph mechanics networks with constraints
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Equiformer: Equivariant graph attention transformer for 3d atomistic graphs
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Generating 3d molecules for target protein binding
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Antigen-specific antibody design and optimization with diffusion-based generative models
Luo, S., Su, Y., Peng, X., Wang, S., Peng, J., and Ma, J · 2022
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Tranception: protein fitness prediction with autoregressive transformers and inference-time retrieval
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Pocket2mol: Efficient molecular sampling based on 3d protein pockets
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Current progress and open challenges for applying deep learning across the biosciences
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Protein sequence and structure co-design with equivariant translation
Shi, C., Wang, C., Lu, J., Zhong, B., and Tang, J · 2022
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3d infomax improves gnns for molecular property prediction
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Geodiff: A geometric diffusion model for molecular conformation generation
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Pre-training via denoising for molecular property prediction
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