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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
d8n3z | Antonia Mey | Julien michel | 39 | 0.09 | 0.12 | 0.07 | 0.17 | 0.09 | 0.16 | 1.16 | 0.13 | alchemical free energies using biosimspace. | biosimspace (feature-freenrgy) https//github.com/michellab/biosimspace/tree/feature-freenrg sire (feature-mapping) https//github.com/michellab/sire/tree/feature-mapping ambertools (18) gromacs (2018) pymbar (3.0.3) freenrgworkflows (1.1) fesetup 1.2.1, sui version 0.8.3 rdkit 18.09.01 protein forcefield amber ff14sb ligand forcefield amber gaff2 water model tip3p | free_energy |
53cvi | Junjie Zou | Carlos simmerling/Daniel Raleigh | 39 | 0.61 | 0.09 | 0.78 | 0.11 | 0.8 | 0.1 | 0.5 | 0.08 | am1-bcc/ti | maestro/schrödinger,pmemd.gti,antechamber protein forcefield amber ff14sb ligand forcefield gaff2 water model tip3p | free_energy |
szgth | Chuan Tian | Carlos simmerling | 39 | 0.61 | 0.09 | 0.78 | 0.11 | 0.8 | 0.1 | 0.5 | 0.08 | am1-bcc/ti | maestro/schrödinger,pmemd.gti,antechamber protein forcefield amber ff14sb ligand forcefield gaff2 water model tip3p | free_energy |
3gjm2 | Junjie Zou | Carlos simmerling/Daniel Raleigh | 39 | 0.62 | 0.09 | 0.8 | 0.11 | 0.82 | 0.1 | 0.49 | 0.08 | am1-bcc/ti | maestro/schrödinger,pmemd.gti,antechamber protein forcefield amber ff14sb ligand forcefield gaff2 water model tip3p | free_energy |
tkkqh | Chuan Tian | Carlos simmerling | 39 | 0.62 | 0.09 | 0.8 | 0.11 | 0.82 | 0.1 | 0.49 | 0.08 | am1-bcc/ti | maestro/schrödinger,pmemd.gti,antechamber protein forcefield amber ff14sb ligand forcefield gaff2 water model tip3p | free_energy |
pwv5e | Anita Chen | Dr. jie zheng at zheng lab | 39 | 0.16 | 0.11 | 0.25 | 0.16 | 0.23 | 0.16 | 0.8 | 0.11 | glide free energy scoring | maestro molecular modeling interface version 11.5.011, mmshare version 4.1.011, release 2018-1, platform linux-x86_64; glide protein forcefield opls3 (default) ligand forcefield opls3 (default) water model gb/sa continuum solvation (default) | structure_based_scoring |
dm2x6 | Thomas Evangelidis | Pavel hobza | 39 | -0.13 | 0.11 | -0.19 | 0.16 | -0.17 | 0.14 | 13.72 | 1.55 | sqm-cosmo_allwat | homoligalign, sqm/cosmo protein forcefield amber14sb ligand forcefield gaff2 water model tip3p | structure_based_scoring |
ka4xp | Thomas Evangelidis | Pavel hobza | 39 | 0.01 | 0.11 | 0.03 | 0.15 | 0.04 | 0.15 | 4.94 | 0.58 | sqm-cosmo_nowat | homoligalign, sqm/cosmo protein forcefield amber14sb ligand forcefield gaff2 water model tip3p | structure_based_scoring |
seq8s | Thomas Evangelidis | Pavel hobza | 39 | -0.01 | 0.11 | -0.01 | 0.16 | 0 | 0.15 | 7.44 | 0.99 | sqm-cosmo_selwat | homoligalign, sqm/cosmo protein forcefield amber14sb ligand forcefield gaff2 water model tip3p | structure_based_scoring |
40ixd | Thomas Evangelidis | Pavel hobza | 39 | -0.15 | 0.1 | -0.25 | 0.15 | -0.2 | 0.14 | 13.25 | 1.44 | sqm-cosmo2_allwat | homoligalign, sqm/cosmo2 protein forcefield amber14sb ligand forcefield gaff2 water model tip3p | structure_based_scoring |
4rgx7 | Thomas Evangelidis | Pavel hobza | 39 | -0.09 | 0.11 | -0.15 | 0.16 | -0.1 | 0.15 | 5.7 | 0.73 | sqm-cosmo2_nowat | homoligalign, sqm/cosmo2 protein forcefield amber14sb ligand forcefield gaff2 water model tip3p | structure_based_scoring |
3h4sv | Thomas Evangelidis | Pavel hobza | 39 | 0.01 | 0.11 | -0.02 | 0.16 | 0.03 | 0.15 | 7.22 | 1.01 | sqm-cosmo2_selwat | homoligalign, sqm/cosmo2 protein forcefield amber14sb ligand forcefield gaff2 water model tip3p | structure_based_scoring |
k4gpy | Thomas Evangelidis | Thomas evangelidis | 39 | 0.3 | 0.11 | 0.45 | 0.15 | 0.53 | 0.13 | 0.54 | 0.08 | deepscaffopt_onlyecfpl_nolossweights | deepscaffopt | ligand_based_scoring |
i7kce | Thomas Evangelidis | Thomas evangelidis | 39 | 0.3 | 0.11 | 0.44 | 0.15 | 0.53 | 0.14 | 0.53 | 0.08 | deepscaffopt_onlyfcfpl_lossweights | deepscaffopt | ligand_based_scoring |
ffnbb | Thomas Evangelidis | Thomas evangelidis | 39 | 0.33 | 0.11 | 0.47 | 0.14 | 0.54 | 0.14 | 0.53 | 0.08 | deepscaffopt_onlyfcfpl_nolossweights | deepscaffopt | ligand_based_scoring |
i3b0v | Antonia Mey | Julien michel | 39 | 0.15 | 0.12 | 0.22 | 0.17 | 0.25 | 0.17 | 1.05 | 0.14 | free energies from docking | flare 2.0 revision 34140 fkcombu rdkit 2018.09.01 | ligand_based_scoring |
f86i0 | Rodrigo Quiroga | Villarreal marcos | 39 | 0.13 | 0.11 | 0.19 | 0.16 | 0.24 | 0.17 | 0.75 | 0.11 | 2vinardo-beta | rdkit / mgltools/ smina (modified) | structure_based_scoring |
znpsx | Xianjin Xu | Xiaoqin zou | 39 | -0.01 | 0.12 | -0.02 | 0.17 | -0.16 | 0.17 | 0.66 | 0.09 | cnnscore-cats | tensorflow | structure_based_scoring |
pfsfn | Xianjin Xu | Xiaoqin zou | 39 | 0.19 | 0.12 | 0.26 | 0.16 | 0.32 | 0.16 | 0.9 | 0.12 | cnnscore-pl | tensorflow | structure_based_scoring |
mheam | Duc Nguyen | Guo-wei wei | 39 | 0.28 | 0.1 | 0.44 | 0.14 | 0.43 | 0.13 | 0.57 | 0.09 | deep learning package | ag/dg/tdl-bp/schrodinger | structure_based_scoring |
24b03 | Duc Nguyen | Guo-wei wei | 39 | 0.48 | 0.1 | 0.66 | 0.13 | 0.69 | 0.13 | 0.48 | 0.08 | deep-learning-package-d | ag/dg/tdl-bp/schrodinger | structure_based_scoring |
ar5p6 | Kaifu/duc Gao/nguyen | Guo-wei wei | 39 | 0.45 | 0.1 | 0.62 | 0.13 | 0.67 | 0.13 | 0.47 | 0.08 | deep-learning-package-d | ag/dg/tdl-bp/schrodinger | structure_based_scoring |
2d76f | Duc Nguyen | Guo-wei wei | 39 | 0.27 | 0.11 | 0.38 | 0.16 | 0.46 | 0.15 | 0.56 | 0.08 | deep-learning-package-dc | ag/dg/tdl-bp/schrodinger | structure_based_scoring |
qian4 | Kaifu/duc Gao/nguyen | Guo-wei wei | 39 | 0.47 | 0.1 | 0.64 | 0.13 | 0.6 | 0.14 | 0.5 | 0.08 | deep-learning-package-dc | ag/dg/tdl-bp/schrodinger | structure_based_scoring |
jxb8i | Menglun/duc Wang/nguyen | Guo-wei wei | 39 | 0.34 | 0.11 | 0.46 | 0.15 | 0.41 | 0.15 | 0.59 | 0.09 | deep-learning-package-mlc | ag/dg/tdl-bp/schrodinger | structure_based_scoring |
4pnwo | Menglun/duc Wang/nguyen | Guo-wei wei | 39 | 0.17 | 0.11 | 0.28 | 0.16 | 0.36 | 0.16 | 0.59 | 0.08 | deep-learning-package-mlcl | ag/dg/tdl-bp/schrodinger | structure_based_scoring |
wbvqk | Antonia Mey | Julien michel | 39 | 0.01 | 0.11 | 0 | 0.16 | 0.05 | 0.15 | 2 | 0.27 | free energies from docking | flare 2.0 revision 34140 fkcombu rdkit 2018.09.01 | structure_based_scoring |
txa7r | Xianjin Xu | Xiaoqin zou | 39 | -0.02 | 0.12 | -0.04 | 0.17 | 0.06 | 0.18 | 1.16 | 0.14 | itscore2 | itscore | structure_based_scoring |
vjzfo | Alejandro Varela rial | Gianni de fabritiis | 39 | -0.07 | 0.11 | -0.12 | 0.16 | -0.19 | 0.15 | 0.89 | 0.12 | skeledock kdeep | htmd1.13.8/rdkit2018.03.4/kdeep | structure_based_scoring |