Bioisosteres & Validation

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Bioisosteres & Validation

Bioisosteres & Validation

Geoff Skillman, Paul Hawkins,

Bob Tolbert, Anthony Nicholls

CUP VIII, Santa Fe, Feb 2007


Shape similarity & Optimization?

Screening Hit Lead Clinical

ROCS

Eon

Docking

Bioisosteres

FEP

MMPB/SA

QSAR

CUP VIII, Santa Fe, Feb 2007


The attraction

“structurally related compounds that elicit

the same biological activity”

• replacing a group of atoms in a

biologically active molecule with

another, broadly similar group of atoms

resulting in a new compound that is

still active and may have improved PK

properties

• No free-energy predictions!!

• May require medicinal chemistry, rarely causes headache, fever, nausea.

Friedman, H.L. NASRCP No. 206, Washington, DC, 1951, 295-395

Thornber, C.W., Quart. Rev. Chem. Soc. 8:563 1979

CUP VIII, Santa Fe, Feb 2007


Bioisostere Strategy

O

O

O

R O

N

O

R

O

R

S

N

O

O

R R N

N

N

R

R

N

R

H

Properties

Fragment

Database

N

O

O

S

N

O

N

CUP VIII, Santa Fe, Feb 2007


Bioisostere Method: Overlay

Paul Watson, Willett P, Gillet V & Verdonk M, JCAMD 15:835 2001

CUP VIII, Santa Fe, Feb 2007


Bioisostere Method: Shape

Paul Watson, Willett P, Gillet V & Verdonk M, JCAMD 15:835 2001

CUP VIII, Santa Fe, Feb 2007


Bioisostere Method: Color

Paul Watson, Willett P, Gillet V & Verdonk M, JCAMD 15:835 2001

CUP VIII, Santa Fe, Feb 2007


Bioisostere Method: Combo

Paul Watson, Willett P, Gillet V & Verdonk M, JCAMD 15:835 2001

CUP VIII, Santa Fe, Feb 2007


Goal of exercise

• Show that this strategy for bioisostere

identification can help in compound

optimization.

• Validate

Bioisosteres

– Similarity method

– Database

• Concept

• Robust

• Limitations

CUP VIII, Santa Fe, Feb 2007


“You can’t validate bioisosteres.”

Not even wrong…

Paul Hawkins

CUP VIII, Santa Fe, Feb 2007


Bioisostere Triumph

• CNS

• (S) Glutamic acid activity modulators

Bang-Anderson et.al., J.Med.Chem., 43:4910-4918, 2000.

CUP VIII, Santa Fe, Feb 2007


Bioisostere Triumph

0.01% (230/189K) 1.65% (3130/189K)

Bang-Anderson et.al., J.Med.Chem., 43:4910-4918, 2000.

CUP VIII, Santa Fe, Feb 2007


Bioisostere Triumph

• CNS

• (S) Glutamic acid activity modulators

IC 50 0.04µM 0.02µM

Bang-Anderson et.al., J.Med.Chem., 43:4910-4918, 2000.

CUP VIII, Santa Fe, Feb 2007


Further optimization

• Desire kainic acid receptor selectivity

HO

N

H 2

O

O

C 2 H 5

O

N O

OH

Bang-Anderson et.al., J.Med.Chem., 43:4910-4918, 2000.

CUP VIII, Santa Fe, Feb 2007


Carboxylic acid bioisosteres

12/189K

1/189K

CUP VIII, Santa Fe, Feb 2007


α-amino carboxylate bioisosteres

0.2% (390/189K)

CUP VIII, Santa Fe, Feb 2007


A good theory ruined…

• So much for the modern definition

HO

N

H 2

O

O

C 2 H 5

O

N O

OH

Bang-Anderson et.al., J.Med.Chem., 43:4910-4918, 2000.

CUP VIII, Santa Fe, Feb 2007


Regroup

• Adjust expectations

– Correct pairs may give retained activity

– Dick’s “Good Bet”

• Context (in)dependent

• Fragment pair evaluation

• No direct experiment

– Anecdotal

– No probability

– Selection error

CUP VIII, Santa Fe, Feb 2007


Goal of exercise

• Show that this strategy can select

reasonable bioisosteric pairs.

• Validate

Bioisosteres

– Similarity method

– Database

• Lommerse

• Large test set

• Training set

CUP VIII, Santa Fe, Feb 2007


Simple validation

percent of total

80

70

60

50

40

30

20

10

0

Conservative Bioisosteres

Color Similarity (N=42)

1.8

similarity (0-2)

Random

Known

CUP VIII, Santa Fe, Feb 2007


Lommerse Bioster test set

• Filtered Bioster database (2281)

– 1042, 940, 149 - R1,R2,R3 pairs

• WDI Decoys (30000)

– 10K random pairs each for R1,R2,R3

• Bad

– Not strictly bioisosteres

– Dalmations versus Lassie

• Good

– Statistical power

– Independent samples

– Gold standard

Wagener and Lommerse, JCIM, 46:682 2006

CUP VIII, Santa Fe, Feb 2007


ROC in disguise

• 2 new methods

• Δ

– Assumes normal

– No active std dev

• Perc5

– TP%@5%FP rate

– Single point on

the ROC curve

CUP VIII, Santa Fe, Feb 2007


Comparison to Wagener training set

R2

R1

R3

CUP VIII, Santa Fe, Feb 2007


ROC Curve

TP Rate

1

0.8

0.6

0.4

0.2

0

Lommerse

0 0.2 0.4 0.6 0.8 1

FP Rate

R1

R2

R3

IBIS

CUP VIII, Santa Fe, Feb 2007


Total & Individual AUCs

AUCs

1

0.95

0.9

0.85

0.8

0.75

Lommerse

Total R1 R2 R3

CUP VIII, Santa Fe, Feb 2007


True-positive selection sanity

R

R OH

AUCs

1

0.95

0.9

0.85

0.8

0.75

Lommerse

Total R1 R2 R3

All

At Ct

CUP VIII, Santa Fe, Feb 2007


Fragment sampling

AUCs

1

0.95

0.9

0.85

0.8

0.75

AtCt Lommerse

Total R1 R2 R3

rms 0.8

rms 0.5

rms 0.3

CUP VIII, Santa Fe, Feb 2007


ET & Color

AUCs

1

0.95

0.9

0.85

0.8

0.75

AtCt Lommerse

Total R1 R2 R3

Combo

ET Combo

CUP VIII, Santa Fe, Feb 2007


Scaled color vs Tanimoto color

2.0

•Ken Brameld

2.0

1.87

CUP VIII, Santa Fe, Feb 2007


Scaled & Tanimoto Color

AUCs

1

0.95

0.9

0.85

0.8

0.75

Lommerse

Total R1 R2 R3

Scaled

Tanimoto

CUP VIII, Santa Fe, Feb 2007


Good, Better, Best

45.0%

40.0%

35.0%

30.0%

25.0%

20.0%

15.0%

10.0%

5.0%

0.0%

All Compounds, V1.0.1

1.5-1.7

0.1 0.3 0.5 0.7 0.9 1.1 1.3 1.5 1.7 1.9

Combo score

1.8-2.0

Active

Decoy

CUP VIII, Santa Fe, Feb 2007


Goal of exercise

• Show that this strategy can predict valid

bioisosteres.

• Validate

Bioisosteres

– Similarity method

– Database

Why?

Complete

CUP VIII, Santa Fe, Feb 2007


Database evaluation

• Similarity measure

– “sine qua non”

• Database problems masquerade

– No similar compounds

• Hitlist has only poor matches

• Looks like similarity failed

– Too many “undesirable compounds”

• ROC overwhelmed by low prevalence

• Looks like similarity failed

CUP VIII, Santa Fe, Feb 2007


Completeness test

• 30000 WDI fragments from Lommerse

• Test if they exist in brood database

• Caveats

– Fragmentation scheme

– Aldehydes

– Known problem

CUP VIII, Santa Fe, Feb 2007


Embarrassment, but no riches

30.0%

25.0%

20.0%

15.0%

10.0%

5.0%

0.0%

WDI fragments

28

189

3R

1R

2R

CUP VIII, Santa Fe, Feb 2007


Molecular Fragmentation

O O O

N

N

O

O

N

O

O N

•Functional Groups

•Ring Systems

•Structural Components

•No predefined list

CUP VIII, Santa Fe, Feb 2007


Redesigned fragmentation

• Version 1.0

• 1M available cpds

• Filtered

• 28K Primary fragments

• Combinations

– Up to 3 fragments

• 189K combined

• Version 1.1

• 8M known cpds

• Not filtered

• 180K Primary fragments

• Combinations within

– Degree (3)

– Frequency (1)

– Molecular weight (300)

– Heavy atoms (15)

• 1-4 million

CUP VIII, Santa Fe, Feb 2007


Fragment complete database

100.0%

80.0%

60.0%

40.0%

20.0%

0.0%

WDI fragments

28 189 4000 1000

3R

1R

CUP VIII, Santa Fe, Feb 2007


Rare fragments dominate

Percent of all fragments

70.00%

60.00%

50.00%

40.00%

30.00%

20.00%

10.00%

0.00%

Fragment frequency

1 2 3 4 5 6 7 8 9 10

Number of parent molecules

CUP VIII, Santa Fe, Feb 2007


R-group count representation

1

2

3

4

5

CUP VIII, Santa Fe, Feb 2007


14.0%

12.0%

10.0%

8.0%

6.0%

4.0%

2.0%

0.0%

1

3

v1.2

v1.0

Expected distribution

5

7

9

11

13

15

Heavy atoms

17

19

CUP VIII, Santa Fe, Feb 2007


Fragments (in 1000's)

120

100

80

60

40

20

0

1

Larger Fragment Database

3

v1.2

v1.0

5

7

9

11

13

Heavy atoms

15

17

19

CUP VIII, Santa Fe, Feb 2007


Primary fragments aren’t saturated

Unique fragments

(thousands)

200

150

100

50

0

Unique Primary fragments

unfiltered

0 2 4 6 8 10

Compounds fragmented (millions)

CUP VIII, Santa Fe, Feb 2007


Conclusions

Bioisosteres are anecdotal but real & useful.

Great test set doesn’t exist, but Lommerse is a

good start.

Brood often identifies bioisosteres of the query.

Bioisosteres may provide a useful means of

optimizing a ligand’s properties.

CUP VIII, Santa Fe, Feb 2007

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