Kalliokoski T, Olsson TSG, Vulpetti A. J. Chem. Inf. Model. 2013, 53, 131-141.
SubCav - Tool for subpocket
comparison and alignment
Dr. Tuomo Kalliokoski
Lead Discovery Center GmbH, Dortmund, Germany
Work conducted at
Novartis Institutes for Biomedical Research, Basel, Switzerland
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Protein Databank (PDB) is growing
• Number of searchable structures 1972-Mar 2013
100000
90000
80000
70000
60000
50000
40000
30000
20000
10000
0
How many fragments are there?
8 million unique chemical structures
2 million lead-like structures
400,000 Rule-Of-Three compliant structures
Zuegg and Cooper. Drug-Likeness and Increased Hydrophobicity of Commercially
Available Compound Libraries for Drug Screening. Curr Top Med Chem 2012, 12,
1500-1513.
Bridging “Structural”-Space and
“Fragment”-Space
The information content
of PDB is increasing
Fragment chemical space is
too large for experimental
Fragment-Based Drug Design
(FBDD)
The need to develop
tools for FBDD to take
advantage of PDB!
Binding site similarity
“The availability of such data provides a basis for
the identification of bioisosteres that are target
specific. The resulting bioisosteres might be
expected to provide more reliable information
when modifying an existing lead compound than do
existing approaches, which are based either on
empirical measures of inter-substituent similarity or
on non-target specific crystallographic data.”
Kennewell EA, Willett P, Ducrot P, Luttmann C. Identification of target-specific bioisosteric fragments from
ligand–protein crystallographic data. J Comput Aided Mol Des 2006, 20, 385-394.
Subpockets and fragments
BRICS*
*Degen J, Wegscheid-Gerlach C, Zaliani A, Rarey M. On the art of compiling and using
’drug-like’ chemical fragment spaces. ChemMedChem 2008, 3, 1503–1507.
SubCav
• Tool for subpocket similarity searching and
alignment
• Based on pharmacophoric fingerprints with
geometric hashing-inspired alignment
• Source code available via
anna.vulpetti@novartis.com
Fingerprint descriptor
SubCav atom type
PDB atom types
Acceptors with sp2
character (πacceptor) (A=)
ALA.O ARG.O ASN.O ASN.OD1 ASP.O ASP.OD1
ASP.OD2 CYS.O GLN.O GLN.OE1 GLU.O
GLU.OE1 GLU.OE2 GLY.O HIS.O ILE.O LEU.O
LYS.O MET.O PHE.O PRO.O SER.O THR.O TRP.O
TYR.O VAL.O
α-carbon (CA)
ALA.CA ARG.CA ASN.CA ASP.CA CYS.CA GLN.CA
GLU.CA GLY.CA HIS.CA ILE.CA LEU.CA LYS.CA
MET.CA PHE.CA PRO.CA SER.CA THR.CA
TRP.CA TYR.CA VAL.CA
LYS.NZ
Donor (D)
Donors with sp2
character (π-donor)
(D=)
ALA.N ARG.N ARG.NE ARG.NH1 ARG.NH2
ASN.N ASN.ND2 ASP.N CYS.N GLN.N GLN.NE2
GLU.N GLY.N HIS.N ILE.N LEU.N LYS.N MET.N
PHE.N SER.N THR.N TRP.N TRP.NE1 TYR.N
VAL.N
Hydrophobe (H)
ALA.CB ARG.CB ARG.CD ARG.CG ASN.CB
ASP.CB CYS.CB CYS.SG GLN.CB GLN.CG GLU.CB
GLU.CG HIS.CB HIS.CG ILE.CB ILE.CD1 ILE.CG1
ILE.CG2 LEU.CB LEU.CD1 LEU.CD2 LEU.CG
LYS.CB LYS.CD LYS.CE LYS.CG MET.CB MET.CE
MET.CG MET.SD PHE.CB PRO.CB PRO.CD
PRO.CG SER.CB THR.CB THR.CG2 TRP.CB
TYR.CB VAL.CB VAL.CG1 VAL.CG2
π-hydrophobe (H=)
HIS.CD2 HIS.CE1 PHE.CD1 PHE.CD2 PHE.CE1
PHE.CE2 PHE.CG PHE.CZ TRP.CD1 TRP.CD2
TRP.CE2 TRP.CE3 TRP.CG TRP.CH2 TRP.CZ2
TRP.CZ3 TYR.CD1 TYR.CD2 TYR.CE1 TYR.CE2
TYR.CG TYR.CZ
CA
9.3Å=4
D=
6.0Å=2
3.4Å=1
A=
Bin Range (Å)
1
2.1-4.5
neutral donor &
acceptor (P)
HIS.ND1 HIS.NE2 SER.OG THR.OG1 TYR.OH
2
4.5-6.3
Ignored
PRO.N and all HETATM
3
6.3-8.0
4
8.0-10.0
Alignment algorithm
Implementation details
Validation study
• Align pairwise all similar subpockets in
PSMDB* (non-redundant subset of PDB)
• 3,268,620 pairs from 3,886 PDBs with 17,044
subpockets with 332 different fragments
• Two alignment methods:
– Fragment-based alignment
– SubCav-based alignment
* Wallach I, Lilien R. The Protein–Small-Molecule Database (PSMDB), A Non-Redundant Structural
Resource for the Analysis of Protein-Ligand Binding, Bioinformatics 2009, 25, 615-620.
When are two subpockets similar?
• Two subpockets are similar if both after
alignment have
– Root-Median-Square-Deviation (RMSD) of
fragments found in subpockets is less than 1.5 Å
– Enough matched features*
RMSD = 1.00
Overlap = 0.79
*Matched feature=if two features from the two subpockets are
within 1 Å distance
Very rarely subpockets with same
fragments are geometrically similar...
3500000
3000000
2500000
2000000
Fragment-based OK
SubCav- based OK
Both OK
1500000
Not matched
1000000
500000
0
0.5
0.6
0.7
0.8
0.9
1
SubCav finds 73%-85% of fragmentbased (plus something else!)
120000
100000
80000
Fragment-based OK
SubCav- based OK
Both OK
60000
40000
20000
0
0.5
0.6
0.7
0.8
0.9
1
Three structures of thrombin aligned. The query
(magenta) fragment-aligned (green) vs. SubCav
aligned (cyan)
Bioisosteric replacement example
ACP
Heat Shock Protein 90 (HSP 90)
Bioisosteric replacement example
Escherichia coli DNA gyrase B
(sequence similarity 30%)
Bioisosteric replacement example
Adenine ->
pyrazole?
Escherichia coli DNA gyrase B
(sequence similarity 30%)
Bioisosteric replacement example
HSP90 inhibitor
Analysis of Histone Methyl-Transferase
Binding Sites
S-adenosylmethionine (SAM) or S-adenosyl-l-homocysteine (SAH)
Fragmented in three: adenine, ribose, and tail fragments
Pairwise SubCav-alignment and hierarchical clustering based on Overlap
Analysis of Histone Methyl-Transferase
Binding Sites
The clustering of the cofactor binding site by subpockets around each specific fragment
revealed different levels of local similarity within the selected proteins set.
Analysis of Histone Methyl-Transferase
Binding Sites
The clustering of the cofactor binding site by subpockets around each specific fragment
revealed different levels of local similarity within the selected proteins set.
Analysis of Histone Methyl-Transferase
Binding Sites
A
B C
D
Take home message
Subpocket analysis can provide ideas in CADD
Acknowledgements
• Novartis Institutes for Biomedical Research:
– Dr. Anna Vulpetti (mentor & co-author)
– Education office (Presidential Postdoctoral
Fellowship)
• Cambridge Crystallographic Data Centre:
– Dr. Tjelvar Olsson (mentor & co-author)
• Chemical Computing Group:
– Dr. Guido Kirsten (idea for alignment protocol)