INNOVATIVE FRAGMENT-BASED DRUG DESIGN AT PDB SCALE
Transcript of INNOVATIVE FRAGMENT-BASED DRUG DESIGN AT PDB SCALE
OverviewOverview
IINNOVATIVENNOVATIVE FFRAGMENTRAGMENT--BBASEDASED D DRUGRUG D DESIGNESIGN
ATAT PDB PDB SCALESCALE
MEDMED--Hybridise protocolHybridise protocol
MED-Hybridise is an innovative software protocol that generates fragment-based chemical compounds by crossing the Protein Data Bank (PBD) and chemical supplier databases.
MED-Hybridise is based on the validated MED-SuMo technology, a very powerful target-based drug design software that compares any interaction surface against the full PDB in a few minutes. Us-ing MED-SuMo makes it possible to retrieve all MED-Portions (fragment compounds from chemical suppliers) exerting 3D local interaction similarities with your protein of interest. Those MED-Portions are then combined in 3D and compared, using fast struc-ture comparison technology, to chemical supplier’s databases. As an output of MED-Hybridise, users obtain a large list of innovative
compounds showing interactions with the 3D target.
By taking advantage of the PDB quadratic growth, MED-Hybridise is actually able to generate a large number of innovative com-pounds in most of the cases. Because MED-portions and all out-put molecules originate from the selected chemical libraries, it produces material that adheres to the medicinal chemistry area.
Compared to other de novo methods in fragment based drug de-sign, MED-Hybridise is the first protocol to take advantage of both chemical information from the PDB and chemical suppliers lists to deliver new active compounds to medicinal chemists.
1. Define your binding pocket of interest from an existing co-crystallized ligand or any manual selection, or by using suggested binding site from a prior MED-SuMo run on a full surface of your protein.
2. Compare this binding pocket with MED-SuMo to a new proprietary database en-coding MED-Portions, a complete set of protein-fragment interactions extracted by crossing the PDB and any chemical data-bases; MED-SuMo will retrieve any hit that has similar 3D interactions (chemical fea-tures and shape).
3. Browse those MED-Portions fitting into your binding query into the MED-SuMo graphical interface: optionally filter out low score hits or unwanted clusters.
4. Hybridise in 3D those MED-Portions with methods implemented into the MED-Hybridise graphical interface ; optionally remove duplicate on 2D or 3D rules and control the level of diversity.
5. Browse at each step molecules matching any chemical database supplier.
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RRESULTSESULTS = = IINNOVATIVENNOVATIVE FRAGMENTFRAGMENT--BASEDBASED
M MOLECULESOLECULES INCLUDINGINCLUDING A ANNOTATIONNNOTATION ONTOONTO C CHEMICALHEMICAL L LIBRARIESIBRARIES
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Hierarchical classifica-tion
of MED-Portions (Fragment hits)according to the
MED-SuMo signature
Superimposed hits on the query
with all MED-SuMo objects
from the common signature
Very interactive hit list including each MED-SuMo object
in signature (Hbond donor, ac-ceptor, aromatic, hydrophobic, 2)
Molecular spreadsheet to browse very large number of MED-Portions and hy-
bridise molecules Includes various chemin-
formatic tools
Copyright MEDIT SA, January 2008
IINNOVATIVENNOVATIVE F FRAGMENTRAGMENT--BASEDBASED DRUGDRUG DESIGNDESIGN ATAT PDB PDB SCALESCALE
Extended application on VEGFrExtended application on VEGFr--2 protein to generate innovative scaffolds2 protein to generate innovative scaffolds
RREQUESTEQUEST FURTHERFURTHER INFORMATIONINFORMATION ABOUTABOUT TODAYTODAY!!
►► Innovative fragmentInnovative fragment--based drug design protocol based drug design protocol
based on Protein Data Bank and chemical supplier based on Protein Data Bank and chemical supplier
database informationdatabase information
►► Take advantage of the MEDIT Take advantage of the MEDIT MEDMED--SuMo SuMo software to software to
compare, superimpose and score interaction surface compare, superimpose and score interaction surface
in term of chemical features (Charge, HBond, hydro-in term of chemical features (Charge, HBond, hydro-
phobic, aromatic, .) and 3D shapephobic, aromatic, .) and 3D shape
►► Support proprietary protein structure databaseSupport proprietary protein structure database
►► Full interaction between 3D protein query, Full interaction between 3D protein query, MEDMED--
PortionPortion fragments, spreadsheet hit list, clustering fragments, spreadsheet hit list, clustering
window, and pharmacophoric signature window, and pharmacophoric signature
►► Advanced filtering options upon 3D hybridisation Advanced filtering options upon 3D hybridisation
step to remove duplicates and to characterize final step to remove duplicates and to characterize final
output proposed moleculesoutput proposed molecules
►► Stick to chemistry art by using structural information Stick to chemistry art by using structural information
from chemical supplier database to generate from chemical supplier database to generate MEDMED--
PortionPortion fragments and final molecules fragments and final molecules
Application on VEGFrApplication on VEGFr--2 protein2 protein
SummarySummary
MEDIT SA:
2 rue du Belvédère, 91120 Palaiseau, France
Tel: +33 (0)1 6014 8743
[email protected] www.medit.fr
This MED-Hybridise application is about the Vascular Endothelial cell Growth Factor receptor 2 from the Receptor tyrosine kinase family. From the 3D protein structure, MED-Hybridise gener-ates a large amount of chemical-like fragments (MED-Portions) that have 3D interactions with the query binding pocket. MED-Hybridise then combines 3D overlapping of MED-Portions to deliver a large set of new molecules. We retrieve known molecules from the PDB and active compounds from PubChem (subset having bioassay values). Here is the protocol we applied:
Hybrid_N°9784 1H1R
1YOM_01_008(PO1 Ligand) 2C60_01_005(4SP Ligand)
Generate Valuable Compounds from your 3D binding pocket Generate Valuable Compounds from your 3D binding pocket Generate Valuable Compounds from your 3D binding pocket by crossby crossby cross---mining the PDB and Chemical supplier databasesmining the PDB and Chemical supplier databasesmining the PDB and Chemical supplier databases
2hzn
1oi9
1h1r
1pye
2chl 2j51 2jfl
2baj
1w83
1wbs
Fig.: two proposed MED-Portions having interactions with 2OH4 (upper view) then
combined into a hybrid candidate molecule (yellow, lower view) which is an inhibitor of
CDK2 (grey, PDB code 1H1H)
1. MED-SuMo standard comparison of the 2OH4 binding site (crystal struc-ture of VEGFr-2 with a benzimidazole-urea inhibitor), defined around the co-crystallized ligand, with the database of Protein-Fragment interactions (generated by MED-Hybridise from the actual PDB and a subset of Pub-Chem database); the output hit list has more than 5000 MED-Portions that all have 3D interactions with the protein query.
2. Filtering out false positive hits (MED-SuMo-Score > 4 and first hit occur-rence filter): 798 remaining MED-Portions.
3. 3D hybridisation of those 798 MED-Portions in 2 steps with MED-Hybridise algorithm: generation of 203528 molecules.
4. Annotation of this final compound list with PDB and PubChem detected ligand: 519 molecules are in the PDB while 52 have bioassay values in PubChem. Fig.: some of the 519
molecules matching to existing ligands in the PDB
Here we limit all 3D hybridisations to only those between MED-Portions (from protein-fragments hits) and a given scaffold. The phenyl amide moiety selected is particularly suited to generate DFG-out ligand like Gleevec in the Abl kinase and c-kit kinase.
Fig.: increasing number of hybridisation steps, exponentially increases number of molecules and scaffolds while druglikeness stays acceptable
Fig.: in orange the query 2OH4 (VEGFr-2), in side view the
phenylamide central scaffold
The 3D hybridisation in 5 iterations of the phenylamide moiety with 1129 fragments suggested leads to 22824 molecules.
In this list, we identified 3585 differ-ent scaffolds, 298 are in PubChem, 46 in the PDB attesting of the di-versity and quality of those gener-ated molecules. 25 are marked as active on protein kinases in Pub-Chem bioassay.