GC4 Affinity Prediction - BACE (Stage 1A)

Grand Challenge 4 - Affinity Prediction - BACE (Stage 1A)

Kendall's τ

Legend
△ - Structure Based; ◯ - Ligand Based; ▢ - Free Energy
Gray Fill - Manual Intervention
Orange Outline - Machine Learning

RMSE_c

Legend
△ - Structure Based; ◯ - Ligand Based; ▢ - Free Energy
Gray Fill - Manual Intervention
Orange Outline - Machine Learning

Pearson's r

Legend
△ - Structure Based; ◯ - Ligand Based; ▢ - Free Energy
Gray Fill - Manual Intervention
Orange Outline - Machine Learning

Spearman's ρ

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	RMSE_c	RMSE_c Error	Method Name	Software	Method Type
7f74g	Sukanya/lea Sasmal/el khoury	David mobley	34	0.17	0.12	0.22	0.17	0.2	0.17	8.17	0.7	chimera/omega/hybrid/mm-gbsa	amber18 for md, amber16 for mmpbsa.py protein forcefield amberff19sb ligand forcefield gaff2 water model tip3p	structure_based_scoring
7x3ay	Thomas Evangelidis	Pavel hobza	34	0.25	0.11	0.36	0.16	0.34	0.14	8.27	0.93	sqm-cosmo_selwat	homoligalign, sqm/cosmo protein forcefield amber14sb ligand forcefield gaff2 water model tip3p	structure_based_scoring
yuxiz			34	0.01	0.11	0.03	0.17	0.07	0.15	4.7	0.49	dock_mmpbsa	autodock vina 1.1.2/rdkit 2018.03.1/openbabel/pymol/fkcombu/acpype/gromacs 5.1.5/g_mmpbsa protein forcefield amber99sb-ildn ligand forcefield gaff water model tip3p	structure_based_scoring
efemt	Pin Chen	Chen Pin	34	0.01	0.1	0.05	0.16	0.07	0.14	1.73	0.17	pin chen	schrodinger (2018-2) protein forcefield opls_2005 ligand forcefield opls_2005 water model no water model is used in this method	structure_based_scoring
aa6sn	Thomas Evangelidis	Pavel hobza	34	0.13	0.13	0.19	0.18	0.22	0.16	9.61	1.17	sqm-cosmo2_selwat	homoligalign, sqm/cosmo2 protein forcefield amber14sb ligand forcefield gaff2 water model tip3p	structure_based_scoring
gcjgs	Alejandro Varela rial	Gianni de fabritiis	34	0.11	0.11	0.17	0.17	0.17	0.16	1.47	0.16	deltadelta skeledock	htmd1.13.8/acemd3/rdkit2018.03.4/mmenergy/deltadelta protein forcefield amber ligand forcefield amber water model tip3	ligand_based_scoring
cphi3	Andre Stander	Dr andre stander	34	0.28	0.11	0.41	0.15	0.41	0.14	1.73	0.2	g_mmpbsa	gromacs, g_mmpbsa, acpype protein forcefield amber ligand forcefield gaff amber14 water model tip3p	structure_based_scoring
af8gx	Thomas Evangelidis	Pavel hobza	34	0.12	0.12	0.19	0.17	0.23	0.16	9.35	1.05	sqm-cosmo2_nowat	homoligalign, sqm/cosmo2 protein forcefield amber14sb ligand forcefield gaff2 water model tip3p	structure_based_scoring
oytcm	Sukanya/lea Sasmal/el khoury	David mobley	34	0.13	0.11	0.23	0.16	0.15	0.13	12.91	2.09	chimera/omega/hybrid/mm-pbsa	amber18 for md, amber16 for mmpbsa.py protein forcefield amberff19sb ligand forcefield gaff2 water model tip3p	structure_based_scoring
nos76	Thomas Evangelidis	Pavel hobza	34	0.24	0.1	0.38	0.15	0.35	0.14	8.19	0.94	sqm-cosmo_nowat	homoligalign, sqm/cosmo protein forcefield amber14sb ligand forcefield gaff2 water model tip3p	structure_based_scoring
t4eb6	Jingxiao Bao	John zhang group	34	0.42	0.1	0.58	0.12	0.6	0.11	1.55	0.17	as-ie	amber16, ambertools17, as-ie (developed by our own laboratory, doi10.1021/acs.jctc.7b01295) protein forcefield ff14sb ligand forcefield gaff water model tip3p	free_energy
xswg3	Thomas Evangelidis	Thomas evangelidis	34	0.11	0.14	0.18	0.19	0.19	0.19	9.64	0.75	deepscaffopt_fcfp_ecfp	deepscaffopt	ligand_based_scoring
xhxwo	Thomas Evangelidis	Thomas evangelidis	34	0.16	0.13	0.24	0.17	0.32	0.17	1.39	0.15	deepscaffopt_onlyfcfp	deepscaffopt	ligand_based_scoring
fmju8	Thomas Evangelidis	Thomas evangelidis	34	0.14	0.14	0.2	0.19	0.25	0.19	1.42	0.18	deepscaffopt_onlyecfp	deepscaffopt	ligand_based_scoring
wmkp3	Xianjin Xu	Xiaoqin zou	34	-0.25	0.11	-0.37	0.15	-0.36	0.14	2.14	0.2	bace1_cnnscore	tensorflow	structure_based_scoring
fdspa	Paul Francoeur	David koes	34	-0.33	0.1	-0.49	0.14	-0.45	0.13	10.53	0.84	aligned autodock vina	rdkit/gnina/smina	structure_based_scoring
xuqp2	Paul Francoeur	David koes	34	-0.28	0.12	-0.39	0.17	-0.41	0.16	10.48	0.87	blind cnn	rdkit/gnina/smina	structure_based_scoring
bejbw	Paul Francoeur	David koes	34	0.04	0.13	0.07	0.18	0.09	0.18	9.79	0.77	blind autodock vina	rdkit/gnina/smina	structure_based_scoring
dtyvb	Paul Francoeur	David koes	34	0.11	0.13	0.15	0.18	0.12	0.18	9.74	0.82	aligned cnn	rdkit/gnina/smina	structure_based_scoring
ugrpw	Bo Wang	Ho-leung ng	34	0.24	0.11	0.35	0.15	0.13	0.13	31.53	12.03	omega/smina-vinardo/rf-score	omega 3/datawarrior 4.7.3/smina version apr. 29, 2017 with vinardo scoring function/rf-score vs v2	structure_based_scoring
ri7k3	Xianjin Xu	Xiaoqin zou	34	0.21	0.11	0.29	0.16	0.25	0.17	1.41	0.15	itscore2	itscore	structure_based_scoring
m20gt	Rodrigo Quiroga	Villarreal marcos	34	0.31	0.09	0.48	0.12	0.45	0.11	1.47	0.14	2vinardo-beta	rdkit / mgltools/ smina (modified)	structure_based_scoring

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

RMSE_c

RMSE_c Error

Method Name

Software

Method Type

7f74g

Sukanya/lea Sasmal/el khoury

David mobley

0.17

0.12

0.22

0.17

0.2

0.17

8.17

0.7

chimera/omega/hybrid/mm-gbsa

amber18 for md, amber16 for mmpbsa.py protein forcefield amberff19sb ligand forcefield gaff2 water model tip3p

structure_based_scoring

7x3ay

Thomas Evangelidis

Pavel hobza

0.25

0.11

0.36

0.16

0.34

0.14

8.27

0.93

sqm-cosmo_selwat

homoligalign, sqm/cosmo protein forcefield amber14sb ligand forcefield gaff2 water model tip3p

structure_based_scoring

yuxiz

0.01

0.11

0.03

0.17

0.07

0.15

4.7

0.49

dock_mmpbsa

autodock vina 1.1.2/rdkit 2018.03.1/openbabel/pymol/fkcombu/acpype/gromacs 5.1.5/g_mmpbsa protein forcefield amber99sb-ildn ligand forcefield gaff water model tip3p

structure_based_scoring

efemt

Pin Chen

Chen Pin

0.01

0.1

0.05

0.16

0.07

0.14

1.73

0.17

pin chen

schrodinger (2018-2) protein forcefield opls_2005 ligand forcefield opls_2005 water model no water model is used in this method

structure_based_scoring

aa6sn

Thomas Evangelidis

Pavel hobza

0.13

0.19

0.18

0.22

0.16

9.61

1.17

sqm-cosmo2_selwat

homoligalign, sqm/cosmo2 protein forcefield amber14sb ligand forcefield gaff2 water model tip3p

structure_based_scoring

gcjgs

Alejandro Varela rial

Gianni de fabritiis

0.11

0.17

0.16

1.47

0.16

deltadelta skeledock

htmd1.13.8/acemd3/rdkit2018.03.4/mmenergy/deltadelta protein forcefield amber ligand forcefield amber water model tip3

ligand_based_scoring

cphi3

Andre Stander

Dr andre stander

0.28

0.11

0.41

0.15

0.41

0.14

1.73

0.2

g_mmpbsa

gromacs, g_mmpbsa, acpype protein forcefield amber ligand forcefield gaff amber14 water model tip3p

structure_based_scoring

af8gx

Thomas Evangelidis

Pavel hobza

0.12

0.19

0.17

0.23

0.16

9.35

1.05

sqm-cosmo2_nowat

homoligalign, sqm/cosmo2 protein forcefield amber14sb ligand forcefield gaff2 water model tip3p

structure_based_scoring

oytcm

Sukanya/lea Sasmal/el khoury

David mobley

0.13

0.11

0.23

0.16

0.15

0.13

12.91

2.09

chimera/omega/hybrid/mm-pbsa

amber18 for md, amber16 for mmpbsa.py protein forcefield amberff19sb ligand forcefield gaff2 water model tip3p

structure_based_scoring

nos76

Thomas Evangelidis

Pavel hobza

0.24

0.1

0.38

0.15

0.35

0.14

8.19

0.94

sqm-cosmo_nowat

homoligalign, sqm/cosmo protein forcefield amber14sb ligand forcefield gaff2 water model tip3p

structure_based_scoring

t4eb6

Jingxiao Bao

John zhang group

0.42

0.1

0.58

0.12

0.6

0.11

1.55

0.17

as-ie

amber16, ambertools17, as-ie (developed by our own laboratory, doi10.1021/acs.jctc.7b01295) protein forcefield ff14sb ligand forcefield gaff water model tip3p

free_energy

xswg3

Thomas Evangelidis

Thomas evangelidis

0.11

0.14

0.18

0.19

9.64

0.75

deepscaffopt_fcfp_ecfp

deepscaffopt

ligand_based_scoring

xhxwo

Thomas Evangelidis

Thomas evangelidis

0.16

0.13

0.24

0.17

0.32

0.17

1.39

0.15

deepscaffopt_onlyfcfp

deepscaffopt

ligand_based_scoring

fmju8

Thomas Evangelidis

Thomas evangelidis

0.14

0.2

0.19

0.25

0.19

1.42

0.18

deepscaffopt_onlyecfp

deepscaffopt

ligand_based_scoring

wmkp3

Xianjin Xu

Xiaoqin zou

-0.25

0.11

-0.37

0.15

-0.36

0.14

2.14

0.2

bace1_cnnscore

tensorflow

structure_based_scoring

fdspa

Paul Francoeur

David koes

-0.33

0.1

-0.49

0.14

-0.45

0.13

10.53

0.84

aligned autodock vina

rdkit/gnina/smina

structure_based_scoring

xuqp2

Paul Francoeur

David koes

-0.28

0.12

-0.39

0.17

-0.41

0.16

10.48

0.87

blind cnn

rdkit/gnina/smina

structure_based_scoring

bejbw

Paul Francoeur

David koes

0.04

0.13

0.07

0.18

0.09

0.18

9.79

0.77

blind autodock vina

rdkit/gnina/smina

structure_based_scoring

dtyvb

Paul Francoeur

David koes

0.11

0.13

0.15

0.18

0.12

0.18

9.74

0.82

aligned cnn

rdkit/gnina/smina

structure_based_scoring

ugrpw

Bo Wang

Ho-leung ng

0.24

0.11

0.35

0.15

0.13

31.53

12.03

omega/smina-vinardo/rf-score

omega 3/datawarrior 4.7.3/smina version apr. 29, 2017 with vinardo scoring function/rf-score vs v2

structure_based_scoring

ri7k3

Xianjin Xu

Xiaoqin zou

0.21

0.11

0.29

0.16

0.25

0.17

1.41

0.15

itscore2

itscore

structure_based_scoring

m20gt

Rodrigo Quiroga

Villarreal marcos

0.31

0.09

0.48

0.12

0.45

0.11

1.47

0.14

2vinardo-beta

rdkit / mgltools/ smina (modified)

structure_based_scoring

Grand Challenge 4 - Affinity Prediction - BACE (Stage 1A)

Kendall's τ

RMSEc

Pearson's r

Spearman's ρ

RMSE_c