Lipinski Jmrc Lecture1 Nov2008

JMRC lecture 1 in "Drug Development in Academia", Krakow, November 6, 2008 1

Academic drug discovery: the chemistry challenges of target choice and

screening library selection

Christopher A. Lipinski

Scientific Advisor, Melior Discovery

[email protected]


Outline• Technology – “good targets”

– biology - chemistry perceptions– why they occur– solutions

• People issues – training and world view– biology - chemistry conflicts– why they occur– solutions

• Rules and filters• Target tractability can improve• My success formula for academic drug discovery


Defining druggability for targets (1)

• Chemical druggability

–3000 proteins might bind low MWT ligand

• Biologically relevant druggability

–??? Low 100’s (guess at 10% - 300)

• Medicinally relevant druggability

–??? (guess at less than 100)


Historically few “innovator” targets / yearCHEMISTRY CAS NAME YEAR MWT TARGETGlucophage 657-24-9 Glucophage 1994 67.09115 perhaps acetylCoA carboxylase 2Precose 56180-94-0 Precose 1995 645.6174 a-glucosidaseCozaar 124750-99-8 Cozaar 1995 422.9212 Angiotensin receptor AT1Fosamax 66376-36-1 Fosamax 1995 249.0983 perhaps farnesyl diphosphatase dehydrogenaseCellCept 116680-01-4 CellCept 1995 433.506 Inosine monophosphatase dehydrogenaseAccolate 107753-78-6 Accolate 1996 575.6892 Leukotriene receptorRezulin 97322-87-7 Rezulin 1997 441.5505 Peroxizome proliferator activated receptorPlavix 120202-66-6 Plavix 1997 321.8284 Platelet P2Y12 receptorIntegrilin 188627-80-7 Integrilin 1998 831.9771 Platelet glycoprotein Iib/IIIa receptorAggrastat 142373-60-2 Aggrastat 1998 440.6066 Platelet glycoprotein Iib/IIIa receptorCelebrex 169590-42-5 Celebrex 1998 381.3792 Cyclooxygenase 2Viagra 139755-83-2 Viagra 1998 474.5862 Phosphodiesterase type 5

180288-69-1 Herceptin 1998 ERBB2 (aka HER2/neu)185243-69-0 Enbrel 1998 Recombinant receptor for TNF170277-31-3 Remicade 1998 antibody for TNF

Rapamune 53123-88-9 Rapamune 1999 914.1972 FK-binding protein & target of rapamycin TOR kinaseTargretin 153559-49-0 Targretin 1999 348.4896 Retinoid X receptorsXenical 96829-58-2 Xenical 1999 495.7495 Gastrointestinal lipase

220578-59-6 Mylotarg 2000 Antibody to CD33Tracleer 147536-97-8 Tracleer 2001 551.6261 Endothelin receptorGleevec 152459-95-5 Gleevec 2001 493.6167 BCR-ABL

189032-40-4 Natrecor 2001 Recombinant B-type natriuretic peptide143090-92-0 Kineret 2001 Recombinant interleukin 1 receptor antagonist98530-76-8 Xigris 2001 Recombinant activated protein C

24 New Ligands in 8 Years Across Everybody


Non combichem innovator drugs

Precose

CHIRAL

H H

HOH

OH

OOH

OH

OH

OH

OH

OH

NH

O

OH

OH

OHOH

OH

O

O

O

Integrilin

CHIRAL

H

N2H

NH

NH

O

NH

O

SS

O NH2

NH

O OH

O

NH

O

NH

O

N

O

NH

NH

Rapamune

CHIRAL

H

HH

OO

OH

OH

O

O

O

OO

OOH

O

NO

Glucophage

NH2

NHNH

N NH


Defining druggability for targets (2)

• Target exists in the literature

• Literature citation to a ligand exists

–6000 “druggable” targets

–ref. Prous Integrity®

–no drug discovery chemistry quality implied

–e.g. nitropropionate ligand for isocitrate lyase


Target Choice

• A good target has distinctly different meaning to biology and chemistry personnel

• In a biology sense, a good target is a biological pathway that can be intercepted in some way to give a useful therapeutic outcome

• In a chemistry sense, a good target is a biological pathway that can be intercepted in a useful sense by an orally active small organic molecule

Interplay of the disciplines leads to success


What is a good target

• Biology/genomics viewpoint

–must be validated

• Chemistry viewpoint

–low MWT ligand can be found

• Both viewpoints must be correct

–non validated

•chemistry succeeds - worthless

–validated

•chemistry fails - worthless


Biology and Chemoinformatics

Biology approach

Is this target druggable in chemistry?


Space in screening and ligands

• Mechanistic screening– narrow target opportunity space

• Phenotypic screening– broad target opportunity space

• Typical medicinal chemistry compounds– broad chemistry space

• Natural products and diversity oriented synthesis– narrow chemistry space


Matching targets and ligand space

• Natural products and DOS

–phenotypic targets - good

–mechanistic targets – poor

• Typical medicinal chemistry

–phenotypic targets – excellent: BUT• mechanism deciphering is tough

–Mechanistic targets – good• mechanism is known so not an issue


Decline of natural products

• Similar decision across most of Pharma– pragmatic, based on results

– chemistry complexity is no advantage unless needed

• Decline coincident with:– rise of automated chemistry

– demise of phenotypic screening

– decline of infectious disease research

• Resurrection:– watch for reversal of the above three trends


Phenotypic screening leverage example

• Phenotypic screening– enhanced target opportunity space

• Melior Discovery runs 35 phenotypic screens– highly efficient in-vivo mouse assays– finds activity in type II diabetes models– compound is a clinically tested Pfizer anti-ulcer drug– novel mechanism - Lyn kinase activator

• Wildly lucky or predictable in drug repurposing?– 97 mechanisms for type II diabetes in Prous’ Integrity– 36 targets with low MWT ligand


MLR-1023 aka Tolimidone


Not all targets are equal in screening

Reproduced with permission from “Targeting signal transduction with large combinatorial collections”, D. S. Auld, D. Diller, K. Ho, Drug Discovery Today, 2002, 7(24) 1206-13.

Size of colored graphic = screening success at Pharmacopeia


Distribution Parameters for 7483 INN/USAN Drugs Define the 90%

Limits Corresponding to Properties Unfavorable for Oral Drug Absorption.


The “rule of five” mnemonic• Poor absorption or permeation are more likely

when there are:

• More than 5 H-bond donors.

• The MWT is over 500.

• The CLog P is over 5 (or MLOGP is over 4.15).

• The sum of N’s and O’s is over 10.

• Substrates for transporters and natural products are exceptions.


Targets, ligands and the rule of 5

• Beautiful targets and very do-able– GPCR’s aminergic– phosphodiesterases– kinases

• Difficult targets but still do-able– GPCR’s peptidergic– proteases

• Hopeless (or nearly so) targets– protein protein interactions– phosphatases


Target tractability can change

• Protein-protein interactions

–hopeless from an HTS screening viewpoint

• Scientific advances

–fragment screening

–SAR by nmr and x-ray

–Bcl-2 family success from Abbott


Protein protein ligand garbage

84-82-2

NONN

NN

O

121263-19-2

OH

O

O

O

OH

O

O

OH

O

O

O

O

OO

Lepourcelet, Maina; Chen, Ying-Nan P.; France, Dennis S.; Wang, Huisheng; Crews, Phillip; Petersen, Frank; Bruseo, Charles; Wood, Alexander W.; Shivdasani, Ramesh A. Small-molecule antagonists of the oncogenic Tcf/-catenin protein complex. Cancer Cell (2004), 5(1), 91-102.


Protein protein ligand ABT-737

Bruncko, Milan; Oost, Thorsten K.; Belli, Barbara A.; Ding, Hong; Joseph, Mary K.; Kunzer, Aaron; Martineau, Darlene; McClellan, William J.; Mitten, Michael; Ng, Shi-Chung; Nimmer, Paul M.; Oltersdorf, Tilman; Park, Cheol-Min; Petros, Andrew M.; Shoemaker, Alexander R.; Song, Xiaohong; Wang, Xilu; Wendt, Michael D.; Zhang, Haichao; Fesik, Stephen W.; Rosenberg, Saul H.; Elmore, Steven W. Studies Leading to Potent, Dual Inhibitors of Bcl-2 and Bcl-xL. Journal of Medicinal Chemistry (2007), 50(4), 641-662.


Nice chemistry: topology in DOS libraries


Bad chemistry: aggregation false positives in HTS assays

Remove these types of compounds from any assaysThese looked good to

PHARMACIA screeners


Chemistry “quality” and biology effortCHEMISTRY CAS NAME Promiscous Refs

117-39-5 117-39-5 Quercetin 1 9644482-89-3 482-89-3 Indigo 1 1170479-41-4 479-41-4 Indirubin 1 263133052-90-1 133052-90-1 Bisindolylmaleimide I 1 155109511-58-2 109511-58-2 U0126 1 127125314-64-9 125314-64-9 Bisindolylmaleimide IX 1 9982-08-6 82-08-6 Rottlerin 1 9585753-43-1 85753-43-1 K-252c 1 74145-63-1 145-63-1 Suramin 0 134919545-26-7 19545-26-7 Wortmannin 0 510103745-39-7 103745-39-7 HA-1077 0 140146986-50-7 146986-50-7 Y-27632 0 113152121-47-6 152121-47-6 SB203580 0 262167869-21-8 167869-21-8 PD 98059 0 310318480-82-9 318480-82-9 SC68376 0 8

OH

OH

OH

OH

O

OH

O

> 80%

flawed compounds?


The amygdala and emotional memory

• Pattern recognition is evolutionarily selected

• Chemists are particularly social

• Chemists are superb at pattern recognition

• Structure of “emotionally significant” compounds is locked into the amygdala

• Biologists just do not understand this


Incomprehensible“Reality” depiction in chemistry is incomprehensible to biology / genomics and vice versa.

Chemistry much closer to pathology than to biology / genomics.

Graphical pattern recognition is the forte of chemists


Chemistry pattern recognition


Screening - what is the goal?

• Target validation–tool like compounds

–relaxed chemistry criteria permissible

–chemical biology

• Drug discovery–lead-like or drug-like compounds

–strict chemistry criteria necessary

–needs pharma skills


Target validation versus drug discovery

• Use a chemical tool to probe biology–relaxed chemistry criteria permissible

–chemical costs go down

–50,000 or fewer compounds in HTS

• Drug discovery–strict chemistry criteria

–cost as high as $200-400 for 15 mg compound

–500,000 compounds in an HTS


Tools for target validation

• Selectivity is paramount

• Covalent functionality can be OK

• But in a complex structure

N

O

Cl

O

N

O

Cl


Questioning diversity

• How many targets are there?

• 23,000 genes, 106 proteins

• How many MWT 500 cpds in a human?

• 200 moles x 6.02 *1023 = 1026

• Diverse compounds = 1060

• Compounds / targets = 10-34 (1 hit / target)

• Compounds / targets = 10-25 (1 billion hits/ target)

• Truly diverse library should never give a hit


True diversity does not exist

• HTS does indeed find hits

• True diversity does exist in silico

• True diversity does not exist experimentally–chemistry success bias

–reagent access bias

–people selection bias

• Involve medicinal chemists in screening library choices


Chemistry space, drug-like and tool-like

December 16, 2004 Nature


Sparse activity in chemistry scaffold space

Quest for the Rings. In Silico Exploration of Ring Universe to Identify Novel Bioactive Scaffolds, Ertl et al. J. Med Chem., (2006), 49(15), 4568-4573.


Sparse oral activity in property space

Global mapping of pharmacological space. Paolini et al., Nature Biotechnology (2006), 24(7), 805-815.


Success formula for academic drug discovery

• Leave the biology alone–in depth biology is the core strength

• Competent medicinal chemistry–people with industrial experience

–good screening libraries

• Competent screening facility

• Competent project management

• Access to experts as needed


Achnowledgement

The financial support of the Kosciuszko Foundation is gratefully acknowledged

The Kosciuszko Foundation, An American Center for Polish Culture, Promoting Educational and Cultural Exchanges and Relations Between the

United States and Poland since 1925.

Lipinski Jmrc Lecture1 Nov2008

Health & Medicine

Transcript of Lipinski Jmrc Lecture1 Nov2008