Optimizing Your Leads for Potency AND Drug-Likeness - …...Optimizing Your Leads for Potency AND...
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Optimizing Your Leads for Potency AND Drug-Likeness or “How to Have it All” Optibrium UGM at the ACS Fall Meeting 2012 Dr Robert Scoffin CEO
Transcript of Optimizing Your Leads for Potency AND Drug-Likeness - …...Optimizing Your Leads for Potency AND...
Optimizing Your Leads for Potency AND Drug-Likenessor “How to Have it All”
Optibrium UGM at the ACS Fall Meeting 2012Dr Robert Scoffin
CEO
> About Cresset> Cresset Technology
> Science
> Applications
> Example
Agenda
About Cresset
> Cresset supplies software tools and consulting services to life sciences customers
> Particular focus on molecular design within drug discovery
> Users include:> Medicinal chemists
> Computational chemists
> Patent officers
Cresset Summary
> Cresset’s solutions enable:> Deeper understanding of actual drug activity
> Prediction of likely activity for novel compounds
> Unique underlying technology provides a much more accurate representation of drug-protein interactions than other computational approaches
> Proven techniques through an extensive portfolio of successful consulting projects
Cresset Summary
NN
Br
F FF
SH2NOO
Example Customers
Cresset Technology
NN
Br
F FF
SH2NOO
Condensed representation of electrostatic, hydrophobic and shape properties (“protein’s view”)
> Molecular Field Extrema (“Field Points”)
Field Points
3D Molecular Electrostatic
Potential (MEP)
Field Points= Positive = Negative= Shape= Hydrophobic
2D
NN
Br
F FF
SH2NOO
Field Points - an analogy
2D drawing very useful for synthesis planning, quick recognition of structural type, IP protection, etc. Not particularly useful for understanding shape and interactions with
proteins.
3D representation of shape and electronic properties very useful for understanding
complex characteristics and interactions. Not useful for rapidly analyzing large numbers of
molecules to e.g. find matches.
Field point representation allows for rapid analysis of collections of molecules, whilst
retaining the ability to understand shape and electronic properties.
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H-bond donor
H-bond acceptor
Hydrophobes
Aromatic cloud
‘H acceptor’
Aromatic in-plane ‘H donor’
-ve ionic
+ve ionic
“Stickiest” surfaces(high vdW)
N
NH
O
O
OH H
H
Explanatory Power of Fields
Field points give you new insights into your molecule
= Positive = Negative= Shape= Hydrophobic
Field point size show importance
> Field patterns from Cresset’s proprietary XED force field reproduce experimental results
XEDs Make Fields Work
Interaction of Acetone and Any-OH from small
molecule crystal structures
Experimental Using XEDs Not using XEDs
XED adds p-orbitals to get better representation of atoms
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Information Provided by Fields
Field points give you new insights into your molecule
Experimental
Fields
Structure
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Bioisosteres – PDE III
Bioisosteres
Biologically relevant method for comparing molecules
> Ligand-based virtual screening> Diverse lead like hits> Large library design> HTS rescue
Cresset Applications
> Expert computational tool for SAR, QSAR and design
> Build predictive models> Improve design
> Singles> Libraries
> Bioisostere generation and replacement> New chemistry directions> Patent protection> Patent busting
> Med.Chem. tool for SAR and design> Relate chemical series> Understand shape and electrostatic
properties> Play models built in forgeV10 to predict
activity or properties
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forgeV10 – Alignment/Similarity/[Q]SAR
Viagra – Levitra
Viagra(Sildenafil)
Levitra(Vardenafil)
> Molecule treated as single conformation> e.g. Ligand from protein crystal structure
> Pharmacophore hypothesis
> Includes multiple pre-aligned single conformations
> Molecule treated as conformation population> All other cases
> Conformations generated where necessary
> Results for all conformations concatenated together
Handling Conformation
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sparkV10 – Bioisostere Replacement
Viagra(Sildenafil)
O
S
OO
N
H+N
O
O
N
HN
N
N
Novartis compound – 100nM
#1 Result
Example: SARS PLpro
> Severe Acute Respiratory Syndrome (SARS)> Caused by a viral infection
> Viral DNA encodes for a polyprotein which then cleaves into multiple components, including several proteases which further process the polyprotein into active components (and also play a role in the release of viral particles from the infected cell)
The Target
> PLpro (Papain-like protease) is one of the key proteases in this process.
> Crystal structures available with bound ligands from 2 series of compounds> Structurally related (PDB entries 3E9S and 3MJ5)
> Small number of analogues> Challenge to see if we can use 3D-QSAR for small data sets
The Target
> Series 1 (3E9S)
> Series 2 (3MJ5)
Compound Series
Example Alignment
Model
PLS Components = 3 RMSE = 0.36 RMSEP = 0.77
> First series has good binding, but a problem is highlighted around the amide oxygen
> Replace in second series with +ve contribution
Med. Chem. Directions?
> Able to build a predictive 3D-QSAR model based on small number of analogues
> Model was able to retrospectively predict improvements which were actually made
Summary
