GC3 Affinity Ranking - VEGFR2

Grand Challenge 3 - Affinity Ranking - VEGFR2

Kendall's τ

Spearman's ρ

Receipt ID Submitter Name PI/Group Name Number of Ligands Kendall's τ Kendall's τ Error Spearman's ρ Spearman's ρ Error Method Name Software Method Type
fsfua Jonathan BohmannMedicinal and process chemistry 43 0.21 0.1 0.3 0.14 rhodium hts rhodium 380e9-x9/ openbabel 2.3.90 / pymol 1.3 structure-based scoring
uv5tc Xiaoqin ZouXiaoqin zou 43 0.4 0.1 0.55 0.13 itscore2 itscore2 structure-based scoring
jjbof Zixuan CangGuo-wei wei 43 0.08 0.1 0.12 0.15 tml&tdl-bp/ri-score/gold/autodock-vina schrodinger, gold, autodock vina, r-tda, javaplex, scikit-learn structure-based scoring
y0048 Polo LamMax totrov 43 0.43 0.09 0.61 0.11 icm/apf 3d qsar molsoft icm 3.8-6 structure-based scoring
hnjio Bentley WingertCarlos camacho 43 0.22 0.11 0.32 0.16 min-cross smina feb 28 2016, based on autodock vina 1.1.2 openbabel 2.3.2 pymol 1.8.4.2 python 2.7.11 matplotlib 1.5.1 scipy 0.17.0 click 6.6 structure-based scoring
i6yrw Bentley WingertCarlos camacho 43 0.36 0.09 0.49 0.13 dock_close smina feb 28 2016, based on autodock vina 1.1.2 openbabel 2.3.2 pymol 1.8.4.2 python 2.7.11 matplotlib 1.5.1 scipy 0.17.0 click 6.6 structure-based scoring
nueqs Jocelyn SunseriDavid koes 43 0.18 0.1 0.27 0.14 cnn docking with affinity model ranking docking performed with gnina commit b3fa6ae13fc6b42924f49b2d751d68f1bc14bc08 available from https//github.com/gnina/gnina , conformer generation performed with rdkit via https//github.com/dkoes/rdkit-scripts/rdconf.py, ensemble of receptors chosen via pocketome. structure-based scoring
upgfc Bentley WingertCarlos camacho 43 0.15 0.11 0.22 0.16 min-cross smina feb 28 2016, based on autodock vina 1.1.2 openbabel 2.3.2 pymol 1.8.4.2 python 2.7.11 matplotlib 1.5.1 scipy 0.17.0 click 6.6 structure-based scoring
ftbnx Jinan WangWeiliang zhu 43 0.14 0.13 0.19 0.17 sqmpc maestro 10.4 mopac 2016 amber 16 structure-based scoring
a7ha2 Zixuan CangGuo-wei wei 43 0.13 0.1 0.19 0.14 tml&tdl-bp/ri-score/gold/autodock-vina schrodinger, gold, autodock vina, r-tda, javaplex, scikit-learn structure-based scoring
zv8gb Bentley WingertCarlos camacho 43 0.01 0.12 -0.01 0.17 min-cross smina feb 28 2016, based on autodock vina 1.1.2 openbabel 2.3.2 pymol 1.8.4.2 python 2.7.11 matplotlib 1.5.1 scipy 0.17.0 click 6.6 structure-based scoring
ghkfr Bentley WingertCarlos camacho 43 0.25 0.11 0.35 0.15 dock_close smina feb 28 2016, based on autodock vina 1.1.2 openbabel 2.3.2 pymol 1.8.4.2 python 2.7.11 matplotlib 1.5.1 scipy 0.17.0 click 6.6 structure-based scoring
ggusw Xiaoqin ZouXiaoqin zou 43 0.3 0.1 0.42 0.14 mmpbsa amber11 structure-based scoring
yeduj Duc NguyenGuo-wei wei 43 0.27 0.12 0.35 0.16 ri-score-k1/tdl-bp/autodock vina ri-score/tdl-bp/autodock vina structure-based scoring
8civr Jocelyn SunseriDavid koes 43 0.23 0.1 0.34 0.14 autodock vina docking with cnn scoring model rescoring docking performed with smina static binary available at https//sourceforge.net/projects/smina/files/ with default scoring function, then rescoring performed using gnina commit b3fa6ae13fc6b42924f49b2d751d68f1bc14bc08 available from https//github.com/gnina/gnina and the default cnn scoring model, conformer generation performed with rdkit via https//github.com/dkoes/rdkit-scripts/rdconf.py, ensemble of receptors chosen via pocketome. structure-based scoring
qikvs Duc NguyenGuo-wei wei 43 0.16 0.1 0.22 0.15 ri-score-k1/tdl-bp/autodock vina ri-score/tdl-bp/autodock vina structure-based scoring
5as54 Xiaoqin ZouXiaoqin zou 43 0.32 0.09 0.45 0.12 itscore2 itscore2 structure-based scoring
348gt Zixuan CangGuo-wei wei 43 0.09 0.1 0.15 0.15 tml&tdl-bp/ri-score/gold/autodock-vina schrodinger, gold, autodock vina, r-tda, javaplex, scikit-learn structure-based scoring
p0eja Bentley WingertCarlos camacho 43 0.29 0.09 0.41 0.13 min-cross smina feb 28 2016, based on autodock vina 1.1.2 openbabel 2.3.2 pymol 1.8.4.2 python 2.7.11 matplotlib 1.5.1 scipy 0.17.0 click 6.6 structure-based scoring
wdzo8 Xiaoqin ZouXiaoqin zou 43 0.28 0.1 0.41 0.14 vina score vina score structure-based scoring
mttdx Duc NguyenGuo-wei wei 43 0.15 0.11 0.22 0.16 ri-score-k1-v/tdl-bp/autodock vina ri-score/tdl-bp/autodock vina structure-based scoring
sct32 Bentley WingertCarlos camacho 43 0.14 0.11 0.21 0.15 dock_close smina feb 28 2016, based on autodock vina 1.1.2 openbabel 2.3.2 pymol 1.8.4.2 python 2.7.11 matplotlib 1.5.1 scipy 0.17.0 click 6.6 structure-based scoring
e62j3 Jonathan BohmannMedicinal and process chemistry 43 0.19 0.11 0.26 0.15 rhodium hts rhodium 380e9-x9/ openbabel 2.3.90 / pymol 1.3 structure-based scoring
kn4cm Bentley WingertCarlos camacho 43 0.23 0.11 0.31 0.16 dock_close smina feb 28 2016, based on autodock vina 1.1.2 openbabel 2.3.2 pymol 1.8.4.2 python 2.7.11 matplotlib 1.5.1 scipy 0.17.0 click 6.6 structure-based scoring
rtv8m Duc NguyenGuo-wei wei 43 0.37 0.1 0.51 0.13 ri-score-k1-v/tdl-bp/autodock vina ri-score/tdl-bp/autodock vina structure-based scoring
umw4e Bing XieDavid d.l. minh 43 -0.06 0.1 -0.08 0.15 algdock openeye quacpac modeller 9.18 ucsf dock6 ambertools 14 namd 2.9 structure-based scoring
d8qvs Jocelyn SunseriDavid koes 43 0.25 0.09 0.39 0.12 cnn docking with scoring model ranking docking performed with gnina commit b3fa6ae13fc6b42924f49b2d751d68f1bc14bc08 available from https//github.com/gnina/gnina , conformer generation performed with rdkit via https//github.com/dkoes/rdkit-scripts/rdconf.py, ensemble of receptors chosen via pocketome. structure-based scoring
bcwmg Xiaoqin ZouXiaoqin zou 43 0.24 0.08 0.37 0.12 vina score vina score structure-based scoring
4a5x3 Zixuan CangGuo-wei wei 43 0.37 0.1 0.51 0.14 tml&tdl-bp/ri-score/gold/autodock-vina schrodinger, gold, autodock vina, r-tda, javaplex, scikit-learn structure-based scoring
r5is6 Jocelyn SunseriDavid koes 43 0.21 0.11 0.31 0.15 autodock vina docking with cnn affinity model rescoring docking performed with smina static binary available at https//sourceforge.net/projects/smina/files/ with default scoring function, then rescoring performed using gnina commit b3fa6ae13fc6b42924f49b2d751d68f1bc14bc08 available from https//github.com/gnina/gnina and the default cnn affinity model, conformer generation performed with rdkit via https//github.com/dkoes/rdkit-scripts/rdconf.py, ensemble of receptors chosen via pocketome. structure-based scoring
7smbe Alexandre BonvinAlexandre bonvin 43 0.38 0.08 0.56 0.11 vegfr-specific ligand-similarity based prediction chemminer, libsvm 3.21 ligand-based scoring
4qmwz Bing XieDavid d.l. minh 43 0.3 0.1 0.42 0.14 algdock openeye quacpac modeller 9.18 ucsf dock6 ambertools 14 namd 2.9 ligand-based scoring
0gmqd Bing XieDavid d.l. minh 43 0.37 0.09 0.52 0.12 algdock openeye quacpac modeller 9.18 ucsf dock6 ambertools 14 namd 2.9 ligand-based scoring