library design for leadlike compounds: a historical perspective tudor i. oprea est lead informatics

Library Design for Leadlike Compounds:

A Historical Perspective

Tudor I. Oprea

EST Lead Informatics

Medicinal Chemistry / AstraZeneca MölnalTudor I. Oprea

What Is A Lead?

• Many compounds are active, but not all actives are leads

• Leads have to meet project dependent criteria:

biological activity validated, both in primary and secondary screens, against known targets, for a series of compounds (when available)

• must be patentable, and display good initial DMPK profile


Common Sources for Leads in Drug Discovery

Druglike leadsaffinity > 0.1 MMW > 350CLogP > 3

Leadlike leadsaffinity > 0.1 MMW < 350CLogP < 3

DRUG

High-affinity leadsaffinity << 0.1 MMW >> 350CLogP < 3

• One needs to distinguish “leadlike” leads from other sources of lead structures, e.g., natural products that are high-affinity compounds (NPY or taxol are leads!) or from “druglike” leads that are marketed structures (e.g., propranolol)


Is There A Leadlike Space?

• There is a general consensus that lead discovery is an essential goal that precludes drug discovery

• For the time being, the only way to analyse the nature of the “leadlike” space is to examine the structures that, historically, were leads.

• The problem is: can these structures provide an objective link between lead-space and drug-space?

• Can we define how these two spaces overlap?


Is There A Leadlike Space? (2)• Initial goal of the retrospective leadlike analysis: gather as

much information as possible about leads, i.e., which drug has been developed from which lead

• Only a few authors describe the chemical structure of the lead compound that was used to derive a given drug.

• Lead structures are often disclosed in a series (SAR), making it difficult to pinpoint at a given compound.

• Furthermore, a drug can have 1 or more leads

• a lead can be a drug

• a lead can lead to several drugs.


Mifepristone (RU486):

Drug with multiple leads:

• Mifepristone originates from progesterone and RU2323

O

O

H

H

H

O

OH

H

O

O

N

H

H

Progesterone RU2323

RU486


Cocaine:Drugs that are leads:

• Cocaine (local anesthetic) was the lead for procaine (local anesthetic) which was, in turn, the lead for procainamide (antiarrhythmic)

N

O

O

O

O

H

H

O

ON N

N

ON N

Cocaine

ProcaineProcainamide


Diltiazem:Classes of leads that have generate drugs with diverse medical applications:

benzodiazepines are a well described class of leadlike structures that resulted in several drugs, ranging from CNS agents (hypnotics, anxiolytics) to calcium channel blockers and ACE inhibitors26 launched BZDs in MDDR

N

S

O

N

N

N

O

O

Cl

S

ONO

O

O

N

H

H

Thiazesim

Oxazepam

Diltiazem


M.W. & CMRAv. 302Md. 315

Av. 391Md. 384

Av. 8.3Md. 8.4

Av. 10.6Md. 10.2

62 “pure” leads 75 “pure” drugs

CMR

MW0

5

10

15

20

156 208 260 312 364 416 468 520 572 624

Fre

qu

ency

02468

10121416

129 182 234 286 339 391 444 496 548

Fre

qu

ency

0

2

4

6

8

10

12

3 4 5 6 7 8 9 10 11 12 13 14 15 16

Fre

qu

ency

0

2

4

6

8

10

12

14

3 4 5 6 7 8 9 10 11 12 13 14 15 16

Fre

qu

en

cy


RNG & RTBAv. 2.37Md. 2

Av. 3.36Md. 3

Av. 5.48Md. 4

Av. 7.51Md. 6


RTB

RNG

Fre

qu

ency

Fre

qu

ency

Fre

qu

ency

Fre

qu

en

cy

0

5

10

15

20

25

0 1 2 3 4 5 6

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5 6 7 8 9 10 More

0

2

4

6

8

10

12

0 1 2 3 4 5 6 7 8 9 10 11 12 More

0

2

4

6

8

10

12

14

16

18

20

0 1 2 3 4 5 6 7


CLogP & LogD7.4

Av. 0.72Md. 0.72n=57

Av. 1.69Md. 1.69n=71


LogD7.4

Av. 1.57Md. 2.11n=58

Av. 2.73Md. 2.54 n=70

CLogP

0

2

4

6

8

10

12

- 7.5 - 6.5 - 5.5 - 4.5 - 3.5 - 2.5 - 1.5 - 0.5 0.5 1.5 2.5 3.5 4.5 5.5

Fre

qu

en

cy

0

2

4

6

8

10

12

14

- 7.5 - 6.5 - 5.5 - 4.5 - 3.5 - 2.5 - 1.5 - 0.5 0.5 1.5 2.5 3.5 4.5 5.5F

req

uen

cy

0

2

4

6

8

10

12

-2.3 -1.8 -1.3 -0.8 -0.3 0.3 0.8 1.3 1.8 2.3 2.8 3.3 3.8 4.3 4.8 5.3 5.8

Fre

qu

en

cy

0

1

2

3

4

5

6

7

-3.8 -2.8 -1.8 -0.8 0.3 1.3 2.3 3.3 4.3 5.3

Fre

qu

ency


Donors & Acceptors

Av. 4.8Md. 4

Av. 5.8Md. 5


HAC

Av. 2.3Md. 2

Av. 2.1Md. 2

HDO

0

24

6

8

1012

14

16

0 1 2 3 4 5 6 7 8 9 10 11

Fre

qu

ency

0

2

4

6

8

10

12

14

0 1 2 3 4 5 6 7 8 9 10 11 12 More

Fre

qu

en

cy

0

5

10

15

20

25

0 1 2 3 4 5 6 7 8 9

Fre

qu

ency

0

2

4

6

8

10

12

14

0 1 2 3 4 5 6 7 8 9 10 11 12 MoreF

req

ue

nc

y


Druglike ScoreAv. 0.66Md. 0.66

Av. 0.81Md. 0.81

Av. 0.45Md. 0.54

Av. 0.54Md. 0.66

62 “pure” leads 75 “recent” drugs

PPFS

DFPS0

5

10

15

20

0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Fre

qu

ency

0

2

4

6

8

10

12

14

0.4 0.5 0.6 0.7 0.8 0.9 1.0

Fre

qu

en

cy

0

5

10

15

20

0.4 0.5 0.6 0.7 0.8 0.9 1.0

Fre

qu

ency

0

5

10

15

20

0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Fre

qu

en

cy


Is There A Difference?

Index RNG RTB RGB MW HDO HAC CLPMeanMean 0.550.55 1.90 1.90 3.34 78.97 3.34 78.97 -0.18-0.18 0.45 0.45 1.25 1.25Std Err. 0.13 0.42 0.67 10.13 0.2 0.23 0.31MedianMedian 00 2 2 3 3 69.88 69.88 0 0 1 1 0.67 0.67STDEV 1.06 3.41 5.45 82.95 1.62 1.88 2.58Min. -2 -12 -11 -120.1 -5 -5 -5.95Max. 5 12 24 386.3 3 5 9.7

Data from 67 drug-lead unique pairs. For more than 1:1 correspondence, only larger structures were considered.


Is There A Real Difference?!

Index RNG RTB RGB MW HDO HAC CLPMeanMean 1.01.0 2.48 2.48 5.86 111 5.86 111 -0.21-0.21 0.41 0.41 1.90 1.90Std Err. 0.14 0.61 0.73 16.6 0.38 0.41 0.47MedianMedian 11 2 2 6 6 96.2 96.2 0 0 1 1 0.21 0.21STDEV 0.78 3.3 3.93 89.2 2.0 2.2 2.54Min. 0 -3.0 -1 -19 -5.0 -5.0 -3.74Max. 3 12 13 386.3 3 4 9.7

Data from 29 recent drug-lead unique pairs. For more than 1:1 correspondence, only larger structures were considered.


What Have We Learned?

• There is a difference between “leads” and “drugs”• However, this difference is apparent mostly in this difference is apparent mostly in

pairwise comparisonspairwise comparisons, as the “leadspace” and “drugspace” appear to overlap

• Average difference: 1 ring, 2 rotatable bonds, 100 1 ring, 2 rotatable bonds, 100 daltons, 1 acceptor and 0.5-1 LogP unitdaltons, 1 acceptor and 0.5-1 LogP unit

• Scoring leads yields 0.1-0.2 less units than drugs…

• The optimal way to use this information is to provide “leadlike” profiles for combichem libraries, as well as guidelines for HTS “hit” analysis in medicinal chemistry efforts


How to Reach a Leadlike Profile?

• There is no universal answer for a leadlike library• However, depending on the final goal (e.g., CNS depending on the final goal (e.g., CNS

vs. urinary antiinflammatory drugs)vs. urinary antiinflammatory drugs), one can generate criteria to focus combichem or HTS libraries (go into “cherry-picking” mode right from the start)

• For example: 1-5 rings, 2-15 rotatable bonds, up to 1-5 rings, 2-15 rotatable bonds, up to 400 daltons, 0-2 donors, 1-8 acceptors and 0-3 400 daltons, 0-2 donors, 1-8 acceptors and 0-3 LogP units LogP units would cover MDDR-like space (75%)

• Additional criteria provided by druglike scoring schemes (e.g., DFPS > 0.4, PPFS > 0.4)

• PSA < 60 Å2 for CNS; PSA < 140 Å2 for oral activity...


Lipinski’s Rule of 5: Just How Good Is It?!Lipinski’s Rule of 5: Just How Good Is It?!

0%

10%

20%

70%

80%

PASS FAIL SKIPPED

ACD

MDDRPDR

HB-acceptors

clogP

8070

6060

50

4030

2010

Ora

l abs

orpt

ion

2 3 4 5 6 7 8 9

More reagents than drugs pass the “Rule of 5” testMore reagents than drugs pass the “Rule of 5” test

Towards a computational model for oral absorption


There Is A Leadlike Space

• The bottom line is that we can direct discovery towards leadlike profiling

• For the time being, we are limited by the number of lead-drug pairs in our historycal analysis

• An ISIS database is available for those interested.

• We are currently working on expanding this for including validated HTS hits (is there a “HTS-hits” space? Is it different from the leadlike space?)


Thanks to...

• Andy Davis, Simon Teague & Paul Leeson

• Bertil Samuelsson

• Mark Divers & Lennart Svensson

• Johan Gottfries, Ismael Zamora

• Thomas Kühler & Bob Carter

library design for leadlike compounds: a historical perspective tudor i. oprea est lead informatics

Documents

leadlike leads

pure leads

lead compound

frequency slide

sources of lead structures

multiple leads

classes of leads

druglike leads