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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+

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

info@medit.fr 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.