Table 3.
A Summary of Structure Prediction Models
| Model | Architecture | Dataset | N_train | Performance | Testset | Citation |
|---|---|---|---|---|---|---|
| / | MLP(2-layer) | proteases | 13 | 3.0 Å RMSD (1TRM),1.2 Å RMSD (6PTI) | 1TRM, 6PTI | Bohr et al.9 |
| PSICOV | graphical Lasso | – | – | precision: Top-L 0.4, Top-L/2 0.53,Top-L/5 0.67, Top-L/10 0.73 | 150 Pfam | Jones et al.141 |
| CMAPpro | 2D biRNN + MLP | ASTRAL | 2,352 | precision: Top-L/5 0.31, Top-L/10 0.4 | ASTRAL 1.75 CASP8, 9 | Di Lena et al.142 |
| DNCON | RBM | PDB SVMcon | 1,230 | precision: Top-L 0.46, Top-L/2 0.55, Top-L/5 0.65 | SVMCON_TEST, D329, CASP9 | Eickholt et al.143 |
| CCMpred | LM | – | – | precision: Top-L 0.5, Top-L/2 0.6, Top-L/5 0.75, Top-L/10 0.8 | 150 Pfam | Seemayer et al.144 |
| PconsC2 | Stacked RF | PSICOV set | 150 | positive predictive value (PPV) 0.44 | set of 383 CASP10(114) | Skwark et al.145 |
| MetaPSICOV | MLP | PDB | 624 | precision: Top-L 0.54, Top-L/2 0.70, Top-L/5 0.83, Top-L/10 0.88 | 150 Pfam | Jones et al.146 |
| RaptorX-Contact | ResNet | subset of PDB25 | 6,767 | TM score: 0.518 (CCMpred: 0.333, MetaPSICOV: 0.377) | Pfam, CASP11, CAMEO, MP | Wang et al, 2017102 |
| RaptorX-Distance | ResNet | subset of PDB25 | 6,767 | TM score: 0.466 (CASP12), 0.551 (CAMEO), 0.474 (CASP13) | CASP12 + 13, CAMEO | Xu, 2018147 |
| DeepCov | 2D CNN | PDB | 6,729 | precision: Top-L 0.406, Top-L/2 0.523, Top-L/5 0.611, Top-L/10 0.642 | CASP12 | Jones et al, 2018148 |
| SPOT | ResNet, Res-bi-LSTM | PDB | 11,200 | AUC: 0.958 (RaptorX-contact ranked 2nd: 0.909) | 1,250 chains after June 2015 | Hanson et al.149 |
| DeepMetaPSICOV | ResNet | PDB | 6,729 | precision: Top-L/5 0.6618 | CASP13 | Kandathil et al, 2019150 |
| MULTICOM | 2D CNN | CASP 8-11 | 425 | TM score: 0.69, GDT_TS: 63.54, SUM Z score (− 2.0): 99.47 | CASP13 | Hou et al.151 |
| C-I-TASSER∗ | 2D CNN | – | – | TM score: 0.67, GDT_HA: 0.44, RMSD: 6.19, SUM Z score(): 107.59 | CASP13 | Zheng et al.152 |
| AlphaFold | ResNet | PDB | 31,247 | TM score: 0.70, GDT_TS: 61.4,SUM Z score (− 2.0): 120.43 | CASP13 | Senior et al.22 |
| MapPred | ResNet | PISCES | 7,277 | precision: 78.94% in SPOT, 77.06% in CAMEO, 77.05 in CASP12 | SPOT, CAMEO, CASP12 | Wu et al, 2019153 |
| trRosetta | ResNet | PDB | 15,051 | TM_score: 0.625 (AlphaFold: 0.587) | CASP13, CAMEO | Yang et al, 2020103 |
| RGN | bi-LSTM | ProteinNet 12 (before 2016)∗∗ | 104,059 | 10.7 Å dRMSD on FM, 6.9 Å on TBM | CASP12 | AlQuraishi, 2019101 |
| / | biGRU, Res LSTM | CUProtein | 75,000 | preceded CASP12 winning team, comparable with AlphaFold in RMSD | CASP12 + 13 | Drori et al.78 |
FM, free modeling; GRU, gated recurrent unit; LM, pseudo-likelihood maximization; MLP, multi-layer perceptron; MP, membrane protein; RBM, restricted Boltzmann machine; RF, random forest; RMSD, root-mean square deviation; TBM, template-based modeling.
∗C-I-TASSER and C-QUARK were reported, we only report one here.
∗∗RGN was trained on different ProteinNet for each CASP, we report the latest one here.