Download ligand design and selection: using 3d fragments with

LIGAND DESIGN AND SELECTION:
USING 3D FRAGMENTS WITH PDB
BINDING CONTEXT
Overview
MED-Ligand platform is a powerful software solution for expert
modellers and medicinal chemists. It will help you to design
innovative ligands from fragment structures or protein-fragment
3D biostructural information mined from the Protein Data Bank.
Combining in 3D large set of fragments or ligands in such chemoproteomic context makes it easier for your best Fragment Based
Drug Design experience.
including list of unwanted chemistry from literature and MEDIT
expertise, (3) MEDL-Hybridise to combine in 3D ligands,
fragments and MED-Portions (fragments with PDB context
information),
(4) MEDL-Fragment to fragment large set
molecules in a fragment/scaffold, (5) MEDL-Search to identify
existing chemistry in large set of molecular hypothesis, (6) MEDL3Dconformer to optimize 3D geometry of hybrid molecules in the
protein context.
MED-Ligand is a reconfigurable software based on the MEDIT
expert cheminformatic modules including: (1) MEDL-Chemistry
to provide standard 1D/2D/3D cheminformatics tools into a
chemical spreadsheet, (2) MEDL-Filter to build your own set of
chemical compound based on advanced 1D/2D/3D filtering rules
In conjunction with MED-SuMo and MEDP-Fragmentor to
superpose protein-fragment similar interactions from the PDB on
your binding site of interest, MED-Ligand platform is a powerful
technology for FBDD, Scaffold Hopping and Drug Repurposing.
MED-Ligand modules
► Generate innovative potential hits
from 3D aligned fragments/ligands
by 3D hybridisation
► Explore and analyse 2D/3D Ligands in a
fragment perspective
► Build and apply customized filtering
rules based on 2D descriptors,
2D and 3D substructures
► Use powerful search tools into
chemical libraries and focus
on pharmacology relevant
molecules
To browse 3D interactions surfaces in the PDB
ACCESS A NEW PARADIGM IN DRUG DISCOVERY:
MINE CHEMO-PROTEOMIC BIOSTRUCTURAL DATA
IN YOUR INNOVATIVE FBDD AND LIGAND DESIGN
Ligand Selection/Design managing 3D Fragments
in a PDB context information
FBDD in MED-Ligand from 3D pre-aligned fragments/ligands
This MED-Ligand application is about to generate potential hits of egfr (the Epidermal Growth Factor Receptor) from a pool of prealigned fragments of the PDB that are combined in the 3D pocket of egfr (PDB code 1xkk). Our MED-SuMo/MEDP-Fragmentor
technology were used first to cross-mine the PDB with libraries of small molecules to build a 3D database of MED-Portion (proteinfragment objects), and then to detect 3D local similarities on the Protein interaction surface between egfr binding sites and MEDPortions. This case study shows that the hybridisation results are improved using all MED-Portion fragments (8500) rather than MEDPortion fragments originating only from protein-kinases (2200). Here is the protocol we applied:
1. MEDL-Hybridise in MED-Ligand platform: 3 steps to hybridise MED-Portion fragments
to generate potential egfr hits. Restraints are introduced to focus on compounds with
MW>350 Da and having the substructure quinazolin-4-amin bound to the hinge like the
egfr inhibitors drugs gefitinib, lapatinib and erlotinib. 31 554 unique kinase hybrids are
obtained using only MED-Portion fragments from protein kinases and 135 553 using all
MED-Portions fragments (including then interfamily protein-fragment al.
2. MEDL-Fragment: the hybrids are then characterized in terms of unique scaffolds. The
options to keep exocyclic and linker double bonds in the scaffold are selected.
3. MEDL-Filter: a subset of 33 057 unique compounds relevant to this case study with
MW>350 Da and having the substructure quinazolin-4-amin is filtered from Pubchem
compounds (27 Millions compounds). This subset contains 33 117 compounds
representing 10 024 unique scaffolds.
4. MEDL-Search: all Kinase hybrids are searched in the subset from Pubchem and in a set
of 797 known egfr actives from Pubchem.
Fig. Pose in the 3D viewer of an hybrid matching a
Pubchem compound (CID 22140840) from the whole set
of 8500 MED-Portions (pre-aligned fragments):
before (white) and after (orange) in situ minimisation
using MEDL-3Dconformer
Fig. first step of hybridization in MEDL-Hybridise ;
left window: 500 MED-Portions fragment are imported from
MED-SuMo/MEDP-Fragmentor (pre-aligned on egfr) ;
right window: 31 MED-Portion fragments are having a
quinazolin-4-amin chemical moiety bound to the hinge.
Hybrids
from 2200
Protein Kinase
MED-Portion
fragments
from the whole set
of 8500
MED-Portion
fragments
Unique
31 554
135 553
Unique scaffolds
1 151
2 798
Matching exactly a Pubchem compound
113
153
Matching exactly a known active
9
54
Summary
► Generate innovative molecules by 3D hybridisation
on aligned fragments and ligands (MEDL
(MEDL--Hybridise)
Hybridise)
► Integrated to MEDMED-SuMo/MEDPSuMo/MEDP-Fragmentor suite
(extract proteinprotein-fragment interactions from the PDB
and compare/superpose 3D interaction surfaces
defined by chemical features on binding site of
interest)
► Optimized for multicore processors
► Ensure desirable chemistry for fragments by mining
supplier databases
► Customized filtering rules based on 1D/2D/3D
descriptors and substructures (MEDL
(MEDL--Filter)
Filter)
► Fast search into chemical libraries to focus on
pharmacology relevant molecules (MEDL
(MEDL--Search)
Search)
► Access to a broad range of customizable fragmenting
rules on 2D and 3D molecules (MEDL
(MEDL--Fragment)
Fragment)
► Train and apply classification models to easily
predict any molecular property (MEDL
(MEDL--Chemistry)
Chemistry)
► 2D/3D chemical spreadsheet (SDF, mol2, PDB, smiles)
and various molecular descriptors (MEDL
(MEDL--Chemistry)
Chemistry)
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