marcus gastreich -...
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Marcus GastreichSpotting Binders in 1012 Compounds
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2Marcus Gastreich Jan 2013
Estimated no. of stars in universe: 1023
Compounds searched traditionally: 107
“Interesting” compounds: 1060
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3Marcus Gastreich Jan 2013
Given the “Similarity Principle”…
1. Which of the 1060 are accessible?
2. How to search that many compounds?
3. Four eyes may see more than two… - Right?
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4Marcus Gastreich Jan 2013
“Lead-like”, good ADME/tox properties
Synthetically accessible
Unpatented(but given the high number of molecules, this should be a smaller problem…)
1. Which Ones are the Appealing Ones?
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5Marcus Gastreich Jan 2013
Many of the compounds will not be accessible It is un-doable to test every molecule:
Assumption: 1 millisecond compute time per compoundExample:1012 x 0.001s = 109s
~ 16,666,666 mins~ 277,777 hrs~ 11,500 days
The Synthesis Dilemma
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6Marcus Gastreich Jan 2013
Instead of checking compounds afterwards, we can encode “reactions” and assemble molecules on-the-fly.
Solution: Do not Enumerate!
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7Marcus Gastreich Jan 2013
Our Approach: Fragments to Leads
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8Marcus Gastreich Jan 2013
Encoding Reactions in a Nutshell
L5
L3NH
N
NH
L1
N
N
N
N
L2
L6
L4
N
N
N
N
Cl
HF
NH2
NH2
NOH
N
N
N
N
NH
NH
NAlkylation, Amination, Cleavages
extract core
Identify link atoms
clip reagent lists
attach link atoms
store unified reagents
maintain link atomcompatibility matrix
O
NH
OH
O
NH
N NNH
N
N CH2
N
S
O
HN
O OH
OH
HC
NHN
NN
SO O
NH2
NN
O
NHNN
N
N
S
O
HN
OOH
NCH2OH
HC
S
N
O
O
N
S
O
HN
O OH
NN
N CH2
N CH2NCH2 N
S
O
HN
O OHNO S
O
HN
O OH
N
S
O
HN
OH
S
N
OO
NH
OH
O
NHN
NN N
NH
N
N NNH
N
N NN
NH
N
NO
F
NH
OCl
NH2OO
S
N
O
ONN
NH
N CH2
O
Cl
NH2OO
F
O
F
O
F
A Fragment Space L1 L2 L3 L4 L5
L1
L2
L3
L4
L5
X
X
X
X
L6
L6
X
X
……
…
N
N
N
N
L2
L6
L4
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9Marcus Gastreich Jan 2013
What makes a Fragment Space ?
L4
L1
O
NH
L2
L4
NH
O A fragment to us is a virtual molecule with link atoms
Fragments can be connected
fragments+ link compatibility rules= Fragment Space
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10Marcus Gastreich Jan 2013
The Classification of Spaces
N
N
NH
NH
N
F
Fragment Space
SO O
NH2
NN
O
NHNN
N
N
S
O
HN
OOH
NCH2OH
HC
S
N
O
O
N
S
O
HN
O OH
NN
N CH2
N CH2NCH2 N
S
O
HN
O OHNO S
O
HN
O OH
N
S
O
HN
OH
S
N
OO
NH
OH
O
NHN
NN N
NH
N
N NNH
N
N NN
NH
N
NO
F
NH
OCl
NH2OO
S
N
O
ONN
NH
N CH2
OCl
NH2OO
F
O
F
O
F
Shred Molecules:
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11Marcus Gastreich Jan 2013
The Classification of Spaces
N
N
N
N
Cl
HF
NH2
NH2
NOH
N
N
N
N
NH
NH
NAlkylation, Amination, Cleavages
Fragment Space
SO O
NH2
NN
O
NHNN
N
N
S
O
HN
OOH
NCH2OH
HC
S
N
O
O
N
S
O
HN
O OH
NN
N CH2
N CH2NCH2 N
S
O
HN
O OHNO S
O
HN
O OH
N
S
O
HN
OH
S
N
OO
NH
OH
O
NHN
NN N
NH
N
N NNH
N
N NN
NH
N
NO
F
NH
OCl
NH2OO
S
N
O
ONN
NH
N CH2
OCl
NH2OO
F
O
F
O
F
Exploit combinatorial chemistry:
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12Marcus Gastreich Jan 2013
The Classification of Spaces
N
N
N
N
Cl
HF
NH2
NH2
NOH
N
N
N
N
NH
NH
NAlkylation, Amination, Cleavages
Fragment Space
SO O
NH2
NN
O
NHNN
N
N
S
O
HN
OOH
NCH2OH
HC
S
N
O
O
N
S
O
HN
O OH
NN
N CH2
N CH2NCH2 N
S
O
HN
O OHNO S
O
HN
O OH
N
S
O
HN
OH
S
N
OO
NH
OH
O
NHN
NN N
NH
N
N NNH
N
N NN
NH
N
NO
F
NH
OCl
NH2OO
S
N
O
ONN
NH
N CH2
OCl
NH2OO
F
O
F
O
F
N
N
NH
NH
N
F
Fragment Space
SO O
NH2
NN
O
NHNN
N
N
S
O
HN
OOH
NCH2OH
HC
S
N
O
O
N
S
O
HN
O OH
NN
N CH2
N CH2NCH2 N
S
O
HN
O OHNO S
O
HN
O OH
N
S
O
HN
OH
S
N
OO
NH
OH
O
NHN
NN N
NH
N
N NNH
N
N NN
NH
N
NO
F
NH
OCl
NH2OO
S
N
O
ONN
NH
N CH2
OCl
NH2OO
F
O
F
O
F
Shredding Approach: CombiChemApproach
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13Marcus Gastreich Jan 2013
Complete Compounds vs. Combinatorics
Searching n complete (‘enumerated‘) compounds leads ton possible compounds searched.
IP Gain = 0 Synthetic access: usually no problem. Computation times are! (must touch every cpd!)
Exploiting combinatorial chemistry surely can lead to many more compounds to search.
IP Gain much higher. Synthetic access: must be taken care of! Incomputable – unless clever approach used.
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14Marcus Gastreich Jan 2013
In-house Chemical
Knowledge
KnowledgeSpace™
≈ 12 000 000 000compounds
N
N
NH
NH
N
F N
N
NH2
NH
F
N
NN
NH
F
N
N
O
OH
F
Query
FS SelectionFTrees –
FS SelectionCombi Lib 3
Combi Lib 2Combi Lib 1
Combi Lib 3Combi Lib 2
Combi Lib 1L1O
NH2
NHL2
NH
ONH2
+
Results
from Library X
from Library Y
from Library Z
SO O
NH2
NN
O
NHNN
N
N
S
O
HN
OOH
NCH2OH
HC
S
N
O
O
N
S
O
HN
O OH
NN
N CH2
N CH2NCH2 N
S
O
HN
O OHNO S
O
HN
O OH
N
S
O
HN
OH
S
N
OO
NH
OH
O
NHN
NN N
NH
N
N NNH
N
N NN
NH
N
NO
F
NH
OCl
NH2OO
S
N
O
ONN
NH
N CH2
OCl
NH2OO
F
O
F
O
F
CoLibriCoLibri
How is This Done In Real Life?
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15Marcus Gastreich Jan 2013
Search for 5HT3 antagonists
It Works: Pfizer’s PGVL Space: 1012 Cpds
N
O
O N
N
N O
N N
O
N
N
ON
N
ONN
N
21 (Tropisetron)
26 (171862; score: 0.887)DY: 0.483; PP: 0.296
23 (151363; score: 0.971)DY: 0.516; PP: 0.362
24 (151368; score: 0.971)DY: 0.504; PP: 0.362
25 (156106; score: 0.910)DY: 0.376; PP: 0.177
[ether] [urea]
[ether][amide]
[ester]
Böhm et al., J. Med. Chem. 51, 2468–2480, 2008
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16Marcus Gastreich Jan 2013
2. Search Technology
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17Marcus Gastreich Jan 2013
“What looks similar, behaves similarly.”
Of course, this is not always true, but sometimes we cannot do better.
The Similarity Principle – umm… Assumption:
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18Marcus Gastreich Jan 2013
00101110101010110001typical 2D and 3D descriptors:
N
NH+
NN
NH2NH2
N
O
NH
O
O
OO
Similarity Descriptors: Bitstrings
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19Marcus Gastreich Jan 2013
2½D FTrees descriptor:
N
NH+
NN
NH2NH2
N
O
NH
O
O
OO Molecule represented as a tree
no bit string
no 3D conformers
Nodes: chemistry/physics
Topology preservedVol.: 44.27
Ring cl: 1Profile:
Aro
Don
Acc
Amd
Hyd
Original Idea, first implementation:M.Rarey and S.Dixon, JCAMD, 12 (1998)
Similarity Descriptors: FTrees
Feature Tree
Don
Acc
Aro
Amd
Hyd
Vol.: 33.9Ring cl: 0Profile:
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20Marcus Gastreich Jan 2013
Advantages of FTrees
more than just a similarity score
fast like 2D, but retains topology
fuzzy
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21Marcus Gastreich Jan 2013
Principle of FTrees
NHN
N
N
SO
ON NH
+
O
O
S
O
NH
OCl
Cl
ONH
• FTrees Similarity: 0.85• global for whole molecule • local for each match
• Mapping of substructures
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22Marcus Gastreich Jan 2013
FTrees
0.764
0.655
0.550
OBr
NH
S
O
NH2
S
2D Fingerprints(Unity)
0.203
0.203
0.203
N
Cl NH
O S
N
OH
Oquery D.R. Flower, JCICS, 38, 379-386
(1998)“On the properties of bit string-based measures of chemical similarity”
FTrees “Intuition”
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23Marcus Gastreich Jan 2013
O
NH
O
N
N
SN
NH
OO
queryPAF antagonist
hit PAF antagonist
2D: rank 729 / 957FTrees: rank 5 / 957
H.Briem, U.Lessel, PD3, 20, 231 (2000) “In vitro and in silico affinity fingerprints: Finding similarities beyond structural classes”
PAF Application by Boehringer-Ingelheim
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24Marcus Gastreich Jan 2013
GPCR Application by Sanofi-Aventis
Evers et al., J.Med.Chem., 48, 5448-65 (2005)
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25Marcus Gastreich Jan 2013
Alignments Explain Similarities
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26Marcus Gastreich Jan 2013
The Actual Searching
query
dynamic programming
M.Rarey, M. Stahl, JCAMD, 15, 479–520 (2001)
deterministic: - same result for every run- always identify best mol
*
*
Your Frag Space
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27Marcus Gastreich Jan 2013
J. Ambler et al., Bioorganic & Medicinal Chemistry Letters 9 (1999) 73P. Tempest et al., Tetrahedron Letters 42 (2001) 4959--4962B. Beck, Dissertation, TU München, Fakultät für Chemie, 2003C. Kalinski, Dissertation, TU München, Fakultät für Chemie, 2006A.M. Boldi et al. , Tetrahedmn Letters 40 (1999) 619-622P.Chen et al. Bioorganic & Medicinal Chemistry Letters 12 (2002) 136M. Eguchi et al., Journal of Medicinal Chemistry, 2002, Vol. 45, No. 7A. Golebiowski et al., Tetrahedron Letters 41 (2000) 4841-4844H. Habashita et al., J. Med. Chem. 2006, 49, 4140-4152E. González-Zamora et al. Chem. Commun., 2001, 1684--1685S. Tadesse et al.,J. Comb. Chem. 1999, 1, 184-187H. Slee et al. J. Med. Chem. 2003, 46, 1120-1122G. Peng et al., J. Org. Chem. 1999, 64, 8342-8349Y. Zhang et al. ,Bioorganic & Medicinal Chemistry Letters 9 (1999) 282C. Hulme et al., Tetrahedron Letters 40 (1999) 5295-5299C. Hulme et al., Tetrahedron Letters 41 (2000) 1509--1514J.R. Appel et al., Molecular Diversity, 4: 91--102, 1999.A. Bhandari et al., Synthesis 1999, No. 11, 1951--1960C. Blackburn et al., Tetrahedron ~tters39(1998) 3635-3638J.G. Breitenbucher et al., Tetrahedron Letters 39 (1998) 1295-l 298C.J. Burns et al., Angew. Chem. Int. Ed. 1998, 37, No. 20C.D. Carroll et al.,Bioorganic & Medicinal Chemistry Letters 8 (1998) 2L. El Kaim et al., Angew. Chem. Int. Ed. 2005, 44, 7961 --7964T. Guo et al., Bioorganic & Medicinal Chemistry Letters 15 (2005) 3696Y.Han et al., Bioorganic & Medicinal Chemistry Letters 15 (2005) 1173I.R Hardcastle et al., Bioorganic & Medicinal Chemistry Letters 15(200E. Farrant et al., Tetrahedron Letters 41 (2000) 5383-5386D. Fancelli et al., J. Med. Chem. 2005, 48, 3080-3084O. de Frutos et al., J. Comb. Chem. 2000, 2, 639-649C.Gil et al., Chem. Eur. J. 2005, 11, 2680 -- 2688S.Gray et al., SCIENCE VOL 281 24 JULY 1998J.P. Killburn et al., Tetrahedron Letters 41 (2000) 5419-5421R. Kuang et al., J. Am. Chem. Soc. 1999, 121, 8128-8129S.H. Lee et al., Tetrahedron Letters 39 (1998) 9469-9472C.E. Lee et al., J. Am. Chem. Soc. 1998, 120, 9735S.V. Ley et al., J. Comb. Chem. 2000, 2, 104
Lu et al., J. Comb. Chem. 2000, :
KnowledgeSpaceTM: a Public cLib-Space (1010)
Distribution of Targets in KnowledgeSpaceTMChem. Driven GPCRProtease KinaseOther
SO O
NH2
NN
O
NHNN
N
N
S
O
HN
OOH
NCH2OH
HC
S
N
O
O
N
S
O
HN
O OH
NN
N CH2
N CH2NCH2 N
S
O
HN
O OHNO S
O
HN
O OH
N
S
O
HN
OH
S
N
OO
NH
OH
O
NHN
NN N
NH
N
N NNH
N
N NN
NH
N
NO
F
NH
OCl
NH2OO
S
N
O
ONN
NH
N CH2
OCl
NH2OO
F
O
F
O
F
82 protocols
10,879 unique fragments
488 unique linkers
11,725,417,388 virtual products
KnowledgeSpaceTM
http://www.biosolveit.de/datasets
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28Marcus Gastreich Jan 2013
KnowledgeSpaceTM Is Publicly Available:
www.biosolveit.com/KnowledgeSpace
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29Marcus Gastreich Jan 2013
FTrees: Interfaces and GUIs
KNIME®
Pay-per-Use including visualization:mcule.com
All possibilities: MOE®PipelinePilot®
Free & simple web interface:biosolveit.de/FTreesWeb
Pipelining Platforms:
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30Marcus Gastreich Jan 2013
FTrees Successes – A First Summary
Searches synthetically accessible molecules reports the reaction alongside
covers 1012 possibilities in 5 minutes
Highly efficient 250.000 molecule:molecule comparisons per minute
high enrichment ratios
Helps with various drug design tasks scaffold hopping
virtual screening
open chain vs. ring structures are found
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31Marcus Gastreich Jan 2013
3. Four Eyes May See More Than Two…
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32Marcus Gastreich Jan 2013
Search for 5HT3 antagonists
It Works: Pfizer’s PGVL Space: 1012 Cpds
N
O
O N
N
N O
N N
O
N
N
ON
N
ONN
N
21 (Tropisetron)
26 (171862; score: 0.887)DY: 0.483; PP: 0.296
23 (151363; score: 0.971)DY: 0.516; PP: 0.362
24 (151368; score: 0.971)DY: 0.504; PP: 0.362
25 (156106; score: 0.910)DY: 0.376; PP: 0.177
[ether] [urea]
[ether][amide]
[ester]
Böhm et al., J. Med. Chem. 51, 2468–2480, 2008
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33Marcus Gastreich Jan 2013
Highly Effective: An Orthogonal View!
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34Marcus Gastreich Jan 2013
FTrees do not “see” stereochemistry.
FTrees cannot distinguish ortho-, meta-, para.
FTrees make one “blob” per cycle.
FTrees are conformation independent.
=> Let us use 3D then!
What Complements the FTrees-”View”
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35Marcus Gastreich Jan 2013
Search Space (BI-CLAIM):1,600 scaffolds + 30,000 reagents -> 500,000,000,000 virtual productsA typical workflow (part 1):
Prospectively: Boehringer's BI-CLAIM (1011)
The typical workflow (part 2)select scaffolds design focused lib / purchase prototypes refinement
Rapid success stories GPCR: 1000 virtual hits, 2 focused libs, 100 nM inhibitors identified Proteinase: 1200 cmpd screened, 2 active scaffolds, refined to 10 nM
N
N
NHNH
N
F
SCIOS-1TGFß inhib.
lit query
O
NH
OH
O
NH
N NNH
N
N CH2
N
S
O
HN
O OH
OH
HC
NHN
NN SO O
NH2
NN
O
NHNN
N
N
S
O
HN
OOH
NCH2OH
HC
S
N
O
O
N
S
O
HN
O OH
NN
N CH2
N CH2NCH2 N
S
O
HN
O OHNO S
O
HN
O OH
N
S
O
HN
OH
S
N
OO
NH
OH
O
NHN
NN N
NH
N
N NNH
N
N NN
NH
N
NO
F
NH
O
Cl
NH2OO
S
N
O
ONN
NH
N CH2
O
Cl
NH2OO
F
O
F
O
F
Fragment Space
1000s hits shape filter
NN
NH
F
N
N
NHN
N
LillyIC50 0.05 µM
N
N
N
SO O
IC50 22.6 µM
knownpyrazoles
act’y ?
vis. inspect.
Lessel et al., ICCS‘08 & J Chem Inf Model. 2009 Feb;49(2):270-9.
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36Marcus Gastreich Jan 2013
This just appeared online:
Boehringer Ingelheim J.Med.Chem. ASAP
21+/-15nM activity against GPR119 (a GPCR relevant for diabetes)
Wellenzohn et al., J.Med.Chem. 2012 asap: “Identification of new Potent GPR119 Agonists by Combining Virtual Screening and Combinatorial Chemistry
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37Marcus Gastreich Jan 2013
The Search Cascade Used (taken from JMC)
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38Marcus Gastreich Jan 2013
If you have a protein structure… Visual affinity computation using HYDE Hydrophobic effect and H-bonds (etc.) balanced intrinsically
Another, New Orthogonal Method: HYDE
PDB: 1GKC
Methods described in a paper JUST out:doi: 10.1007/s10822-012-9626-2 Schneider et al., JCAMD Dec2012
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39Marcus Gastreich Jan 2013
So… Orthogonal Views Help a Great Lot
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40Marcus Gastreich Jan 2013
Summary
1. Trillions of compounds can be searched
2. High likelihood of synthetic access / proven success in Pharma
3. Combine 2D and 3D
CAVEAT: Searching your own chemistry involves yourself!
Happy FTrees Users: Pfizer, Novartis, AstraZeneca, Merck USA/NL, Merck-Serono, Hoffmann-LaRoche, Johnson&Johnson, Sanofi-Aventis, Bayer, Boehringer-Ingelheim, Dupont, and many more