Legend
△ - Structure Based; ◯ - Ligand Based; ▢ - Free Energy
Gray Fill - Manual Intervention
Orange Outline - Machine Learning
Legend
△ - Structure Based; ◯ - Ligand Based; ▢ - Free Energy
Gray Fill - Manual Intervention
Orange Outline - Machine Learning
Legend
△ - Structure Based; ◯ - Ligand Based; ▢ - Free Energy
Gray Fill - Manual Intervention
Orange Outline - Machine Learning
Legend
△ - Structure Based; ◯ - Ligand Based; ▢ - Free Energy
Gray Fill - Manual Intervention
Orange Outline - Machine Learning
Receipt ID | Submitter Name | PI/Group Name | Number of Ligands | Kendall's τ | Kendall's τ Error | Spearman's ρ | Spearman's ρ Error | Pearson's r | Pearson's r Error | RMSEc | RMSEc Error | Method Name | Software | Method Type |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
4tb6s | Liu Cong | Ken dill | 34 | -0.1 | 0.12 | -0.17 | 0.17 | -0.17 | 0.15 | 1.6 | 0.16 | laufer_seed | meld (0.3.10) chimera (1.10.1) openbabel (2.4.1) mdtraj( 1.9.1) cpptraj (v17.00b) antechamber tleap protein forcefield amber ff14sb ligand forcefield gaff (1.8) water model tip3p | free_energy |
34b20 | Thomas Evangelidis | Pavel hobza | 34 | 0.1 | 0.12 | 0.16 | 0.17 | 0.09 | 0.18 | 10.03 | 1.22 | sqm-cosmo_allwat | homoligalign, sqm/cosmo protein forcefield amber14sb ligand forcefield gaff2 water model tip3p | structure_based_scoring |
eupjg | Thomas Evangelidis | Pavel hobza | 34 | 0.16 | 0.12 | 0.22 | 0.17 | 0.12 | 0.16 | 10.52 | 1.63 | sqm-cosmo_nowat | homoligalign, sqm/cosmo protein forcefield amber14sb ligand forcefield gaff2 water model tip3p | structure_based_scoring |
37fp6 | Thomas Evangelidis | Pavel hobza | 34 | 0.1 | 0.12 | 0.16 | 0.17 | 0.09 | 0.18 | 10.03 | 1.21 | sqm-cosmo_selwat | homoligalign, sqm/cosmo protein forcefield amber14sb ligand forcefield gaff2 water model tip3p | structure_based_scoring |
nbjaz | Thomas Evangelidis | Pavel hobza | 34 | 0.14 | 0.11 | 0.21 | 0.17 | 0.15 | 0.18 | 9.18 | 1.14 | sqm-cosmo2_allwat | homoligalign, sqm/cosmo2 protein forcefield amber14sb ligand forcefield gaff2 water model tip3p | structure_based_scoring |
n4kfo | Thomas Evangelidis | Pavel hobza | 34 | 0.2 | 0.11 | 0.31 | 0.16 | 0.18 | 0.15 | 9.64 | 1.36 | sqm-cosmo2_nowat | homoligalign, sqm/cosmo2 protein forcefield amber14sb ligand forcefield gaff2 water model tip3p | structure_based_scoring |
20eu5 | Thomas Evangelidis | Pavel hobza | 34 | 0.14 | 0.11 | 0.21 | 0.17 | 0.15 | 0.18 | 9.18 | 1.16 | sqm-cosmo2_selwat | homoligalign, sqm/cosmo2 protein forcefield amber14sb ligand forcefield gaff2 water model tip3p | structure_based_scoring |
87eyt | Thomas Evangelidis | Thomas evangelidis | 34 | 0.28 | 0.12 | 0.37 | 0.16 | 0.39 | 0.15 | 1.33 | 0.14 | deepscaffopt_fcfpl_ecfpl_2dpp_nolossweights | deepscaffopt | ligand_based_scoring |
37yqv | Thomas Evangelidis | Thomas evangelidis | 34 | 0.15 | 0.12 | 0.21 | 0.17 | 0.27 | 0.17 | 1.39 | 0.15 | deepscaffopt_only2dpp_nolossweights | deepscaffopt | ligand_based_scoring |
0drpa | Thomas Evangelidis | Thomas evangelidis | 34 | 0.29 | 0.11 | 0.41 | 0.15 | 0.4 | 0.15 | 1.33 | 0.14 | deepscaffopt_onlyecfpl_nolossweights | deepscaffopt | ligand_based_scoring |
2c4r7 | Thomas Evangelidis | Thomas evangelidis | 34 | 0.15 | 0.12 | 0.2 | 0.17 | 0.24 | 0.17 | 1.5 | 0.16 | deepscaffopt_onlyfcfpl_nolossweights | deepscaffopt | ligand_based_scoring |
u2v0p | Paul Francoeur | David koes | 34 | 0.31 | 0.11 | 0.44 | 0.14 | 0.49 | 0.12 | 1.27 | 0.15 | aligned autodock vina | rdkit/gnina/smina | structure_based_scoring |
gdczi | Paul Francoeur | David koes | 34 | 0.36 | 0.1 | 0.53 | 0.13 | 0.54 | 0.12 | 1.3 | 0.14 | aligned cnn | rdkit/gnina/smina | structure_based_scoring |
36ac0 | Anatoly Chernyshev | Anatoly chernyshev | 34 | 0.09 | 0.12 | 0.11 | 0.18 | 0.13 | 0.16 | 1.44 | 0.16 | bace macrocyclic inhibitors | autodock vina 1.1.2 ucsf chimera 1.13.1 (http//www.cgl.ucsf.edu/chimera/) with vina interface plugin pdbbind database 2018 (http//www.pdbbind.org.cn) ms excel | structure_based_scoring |
yz8ty | Paul Francoeur | David koes | 34 | 0.22 | 0.12 | 0.3 | 0.17 | 0.38 | 0.15 | 1.36 | 0.16 | blind autodock vina | rdkit/gnina/smina | structure_based_scoring |
k2xai | Paul Francoeur | David koes | 34 | 0.17 | 0.13 | 0.23 | 0.18 | 0.25 | 0.19 | 1.43 | 0.16 | blind cnn | rdkit/gnina/smina | structure_based_scoring |
7jdsb | Léa/sukanya El khoury/sasmal | David l. mobley | 34 | 0.01 | 0.13 | 0.02 | 0.18 | 0.05 | 0.18 | 8.14 | 0.84 | chimera/omega/hybrid/mm-gbsa | chimera/omega 3.0.8/hybrid 3.2.0.2/mm-gbsa/amber16 | structure_based_scoring |
nc872 | Léa/sukanya El khoury/sasmal | David l. mobley | 34 | 0.04 | 0.13 | 0.06 | 0.18 | 0.07 | 0.17 | 9.02 | 1.04 | chimera/omega/hybrid/mm-pbsa | chimera, omega 3.0.8/hybrid 3.2.0.2/mm-pbsa/amber16 | structure_based_scoring |
h0znk | Xianjin Xu | Xiaoqin zou | 34 | -0.16 | 0.11 | -0.25 | 0.16 | -0.23 | 0.15 | 1.98 | 0.2 | cnnscore-bace | tensorflow | structure_based_scoring |
rsq0i | Xianjin Xu | Xiaoqin zou | 34 | -0.27 | 0.1 | -0.38 | 0.14 | -0.39 | 0.14 | 2.32 | 0.23 | cnnscore-pl | tensorflow | structure_based_scoring |
0oaoj | Duc Nguyen | Guo-wei wei | 34 | 0.26 | 0.12 | 0.36 | 0.16 | 0.35 | 0.14 | 1.35 | 0.14 | deep learning package | ag/dg/tdl-bp/schrodinger | structure_based_scoring |
i2y56 | Kaifu/duc Gao/nguyen | Guo-wei wei | 34 | 0.1 | 0.12 | 0.15 | 0.17 | 0.18 | 0.14 | 1.42 | 0.15 | deep-learning-package-d | ag/dg/tdl-bp/schrodinger | structure_based_scoring |
5q8bw | Duc Nguyen | Guo-wei wei | 34 | 0.09 | 0.11 | 0.14 | 0.16 | 0.23 | 0.18 | 1.4 | 0.15 | deep-learning-package-d | ag/dg/tdl-bp/schrodinger | structure_based_scoring |
8frur | Kaifu/duc Gao/nguyen | Guo-wei wei | 34 | 0.42 | 0.09 | 0.6 | 0.11 | 0.52 | 0.1 | 1.24 | 0.13 | deep-learning-package-dc | ag/dg/tdl-bp/schrodinger | structure_based_scoring |
j2ydn | Duc Nguyen | Guo-wei wei | 34 | 0.18 | 0.11 | 0.23 | 0.17 | 0.12 | 0.18 | 1.57 | 0.2 | deep-learning-package-dc | ag/dg/tdl-bp/schrodinger | structure_based_scoring |
bxuha | Menglun/duc Wang/nguyen | Guo-wei wei | 34 | 0.25 | 0.09 | 0.37 | 0.13 | 0.37 | 0.12 | 1.34 | 0.14 | deep-learning-package-mlc | ag/dg/tdl-bp/schrodinger | structure_based_scoring |
ae6kd | Menglun/duc Wang/nguyen | Guo-wei wei | 34 | 0.3 | 0.11 | 0.42 | 0.14 | 0.46 | 0.13 | 1.29 | 0.14 | deep-learning-package-mlcl | ag/dg/tdl-bp/schrodinger | structure_based_scoring |
jp82q | Xianjin Xu | Xiaoqin zou | 34 | 0.04 | 0.13 | 0.06 | 0.18 | 0.05 | 0.19 | 1.67 | 0.21 | itscore2 | itscore | structure_based_scoring |
unkrk | Ye Zou | Ho-leung ng | 34 | 0.11 | 0.13 | 0.16 | 0.18 | 0.19 | 0.18 | 1.47 | 0.17 | nnscore | yasara/open drug discovery toolkit | structure_based_scoring |
ung7y | Ye Zou | Ho-leung ng | 34 | 0.22 | 0.12 | 0.29 | 0.17 | 0.28 | 0.17 | 1.38 | 0.14 | rf-score v3 | yasara/open drug discovery toolkit | structure_based_scoring |
5mxnz | Alejandro Varela rial | Gianni de fabritiis | 34 | 0.59 | 0.08 | 0.79 | 0.09 | 0.79 | 0.08 | 1.22 | 0.14 | skeledock kdeep | htmd1.13.8/rdkit2018.03.4/kdeep | structure_based_scoring |