webinar: discovering small molecule protein-protein interaction inhibitors through computational...

COMPUTISTBIO-NANOTECH

DESIGNING THE RIGHT DRUG COMPOUND FOR THE RIGHT DISEASE TARGET

Live Webinar November 16 - 19, 2015Discovering Small Molecule Protein-Protein Interaction Inhibitors

through Computational Design

Watch the webinar http://www.computistresearch.com/webinar.html

http://www.computistresearch.com/webinar.html

© 2015 Computist Bio-Nanotech

COMPUTIST BIO-NANOTECHDesigning the right drug compound for the right disease target

Dr Wolfgang Kissel

Strategy and Business DevelopmentA/Prof. Herbert Treutlein

Co-Founder and CEO

• Expert in developing and

implementing strategies,

organizational excellence,

leadership.

• Expert in molecular

modelling and computational

drug design

Discovering Small Molecule Protein-Protein Interaction Inhibitors

through Computational Design

Presenters


Highlights of this WebinarDesigning the right drug compound for the right disease target

• A novel solution for a non-existing problem

• The everyday Challenge of R&D

• Trend reversals and game changers

• Defining Methods

• Small molecule Protein-Protein Interaction Inhibitors

• Ras/Raf example

• Benefits of computational design

• Q&A


Who benefits most from this WebinarDesigning the right drug compound for the right disease target

Who benefits most:

• R&D decision makers who want

to accelerate drug discovery

• R&D specialists who want to

get results quickly

• R&D Finance Managers on the

lookout for productivity gains

Tough

Decisions

Ahead


Key Insights from this Webinar IDesigning the right drug compound for the right disease target

Computational design, the future

way of drug discovery

• Small Molecule Protein-Protein-

Interaction inhibitors (smPPII) as a

new drug class → easy accessible

with computational methods

• Good computational methods are

validated and proven to work

PDB id: 3KUD


Key Insights from this Webinar IIDesigning the right drug compound for the right disease target

Computational methods, the future

way of smPPII discovery and design

• High speed and most cost-effective

smPPII development

• Find the needle in the haystacks –

not just another haystack

• Determination of drugability of

disease targets

• Double de-risk strategy in drug

development

➤ Quantum leap in R&D productivity

1010

107


Designing the right drug compound for the right disease target

A novel solution for a non-existing problem


Tropomyosin InhibitorDesigning the right drug compound for the right disease target

Our 2009 challenge

Novel fragment design method validated for protein-protein interaction

targets: Tropomyosin polymerization inhibitors (tested in vitro)



Starting Point

• Tropomyosin not accepted as drug target

• Initial data showed specific isoforms in certain cancer cells (UNSW)

• Only cellular assay available to test SAR of inhibitors, no mode-of-action

• No clear way forward to establish tropomyosin as drug target

• Focus on non-muscle tropomyosin



Process

4 rounds of design and optimization

• Speed: 1 month/round

• Our rigorous PM applied



Outcome

• Design based on initial models as well as dynamical structures (MD simulations)

• Specificity: Access regions of sequence variability / remove of dynamin binding

• Establish SAR for compound series and mode-of-action

• Work was published and Tropomyosin accepted as drug target

• Novogen Ltd. acquired project and IP



The everyday Challenge of R&D


The Everyday Challenge for R&DHigh input, low output

Constant pressure:

• Too expensive, too slow, too risky

• Alleged productivity decline

• Small Molecule R&D unprofitable

• Ongoing fight for recognition

• Small vs. big molecules


Rising Costs for ever more expensive cures

Trend to biologic (protein-based) drugs

• Higher prices

• Higher profitability than Small Molecules

→ increasing health-care costs

OECD Data for Health

Expenditure: e.g. 17% of

GDP in the USA, 2010.


Finding Novel Molecules That Work

Novel Drug Compounds: The needle in the haystack

Q: How many possible drugs could be synthesized?

A: Synthesizable molecules: 1040 ≈ (number of stars)2

• Easy to handle: 1010

General Screening Libraries in HTS: 106

⇒ Unlikely that HTS or VS will find a drug/lead candidate in one single experiment

⇒ From diverse to highly focused libraries through iterative screening cycles

⇒ Computist delivers binding mode, mode of action, new compound options

Computational approach not restricted to compound libraries

1010

107



Trend reversals and game changers


Trend Reversals on the Horizon

Computational Design of drug compounds

Design molecules that interact with (this is

what we are doing):

• Surfaces

• Non-standard and standard binding sites

• Reliable binding mode and mode-of action

on protein surfaces

• Drugability evaluation

1010


Trend Reversals on the Horizon

Small Molecule Protein-Protein Interaction Inhibitors?

• Higher R&D productivity

• Higher profitability

→ lower prices possible

Small Molecule Protein-Protein Interaction Inhibitors!

• Higher success rate in later development stages

• Can replace biologic (protein-based) drugs

• Convenient application: oral delivery vs. injection

• More attractive than conventional small molecule R&D


Game Changers for Solutions Have ArrivedDesigning the right drug compound for the right disease target

Manifold acceleration of Discovery by Computational Design

• Compounds come with Mode-of-Action

• Optimizing good compounds to great compounds

• Up to 80% time savings

• Up to 80% cost savings

• “Impossible” projects now doable



Small Molecule Protein-Protein Interaction Inhibitors


Prospects of Small Molecule PPIIs

Emergence of a new class of Therapeutics

De-risking: shift of development risk to early stage• Double de-risking in combination with computational design

Simplification of disease targeting

• Convenient application: oral delivery vs. injection


Protein-Protein Interaction Inhibitors (PPII)Designing the right drug compound for the right disease target


• Targeting specific ‘hot spots’ on the protein surface, a growing trend

From: Meier, C., et al. (2013). Drug Discovery Today, 18(13-14), 607–609. Study by “The

Boston Consulting Group.”




• PPII development considered risky in early stage but

• Computational methods de-risk PPII development through:

• Our MFMD evaluates quickly drugability of target

• Fast, reliable low cost evaluation with virtual screening

• Tailor-made design of early stage compounds.

• More projects/targets evaluated and less money spent




Examples:

• Chemokine receptor interactions (e.g., Pfizer’s Selzentry),

• Integrin interactions (e.g., SAR code’s Lifitegrast),

• p53-MDM2 interaction (e.g., Roche’s RG7112).

Emerging market with highly attractive prospects

• 15 projects in development (2013)

• Licensing agreements crossed $1B (2012)

From: Meier, C., et al. (2013). Drug Discovery Today, 18(13-14), 607–609. Study by “The

Boston Consulting Group.”



Defining Methods


Computist’s Defining Methods: Designing the right drug compound for the right disease target

The heart of our method: Multiple Fragment Molecular Dynamics MFMD

Quantum Mechanics QM:

• Overcomes limitations of current force-field based methods (MM)

for small molecule ⟷ target interactions

Our Dynamical Score:

• Adds structural dynamical stability to find the right compound


Benefits of Computational Design Designing the right drug compound for the right disease target

Benefits of our MFMD approach:

• Explore and determine drugability of a target’s binding site

• Determine and map out binding site features using

your preferred small fragments

• MFMD enables precision docking of molecules

• Design optimized compounds with MFMD fragment

clusters combined with docked molecules

• Design specific compounds through mapping out

differences of MFMD clusters from two targets


Our Unique Skills and Methods AppliedDesigning the right drug compound for the right disease target

Computational Design of Protein-Protein Interaction Inhibitors

• Molecules designed to interact with surfaces / non-standard binding sites

• Proven success in our PPII design through experimental verification:

• Small molecules as tropomyosin polymerization inhibitors

• Novel fragments suitable for inhibitor design the Ras/Raf interaction

Small Molecule Alternatives for Protein Drugs

• Protein drugs are often used as PPIIs.

• Our technology proved successful in designing small molecules that

can replace an antibody

• All our designed PPIIs are small molecules or peptides

1010



Ras/Raf Example


Ras/Raf Protein-Protein Interaction InhibitorDesigning the right drug compound for the right disease target

Computational Design of Protein-Protein Interaction Inhibitors

• Proven success in our PPII design through experimental verification:

• Designed peptides to inhibit the Ras/Raf interaction in 1998

• Identified novel fragments suitable for inhibitor design the Ras/Raf

interaction in 2014 (collaboration with Circa Group Pty Ltd)


MFMD Scans

(selected fragments)

methyl-gua

Design of Ras/Raf interaction inhibitorsDesigning the right drug compound for the right disease target


MFMD Scans



phenol


MFMD Scans



benzene


2015: Fragment-based small molecule design

• Identified and verified fragments suitable for PPII

design leading to novel NCEs.

• Fragments are based on levoglucosenone.

• Experimentally verified

• IP is shared with Circa Group Pty. Ltd.

• Further discussions possible (NDA)




Benefits of Computational Design


😠Highly

expensive

No

Mode-of-action

Benefits of Computational DesignDesigning the right drug compound for the right disease target

• Quality of compounds

• Speed

• Cost per project

• Tailored compounds

• Mode-of-action clarified

• More projects/$$$ invested

↓

Increased success rate of projects

Experimental FragmentScreening

Computist’sMFMD

100-1000

fragments

Purchase

Fragments

Wet/NMR

Screening

Hits

50

Small

Fragments

MFMD

Tailored

Compound

Design

CompoundsFragment

Hits

Significantly

lower cost

Mode-of-action

clarified

😉


Summary and ConclusionDesigning the right drug compound for the right disease target

Combining Small Molecule PPII Discovery with Computational Design

• Access new class of drugs quicker, with

lower risk and at lower cost

→ higher R&D ROI

• From good PPII candidates To great PPIIs

• “Impossible” projects now doable


What We Do and How We Work Together Designing the right drug compound for the right disease target

Computational discovery & design of small molecule compounds• The most productive alternative to HTS

Our rigorous process leads to quicker

and better results

Our customized design cycles are clear-

cut and focused on your goals.

Together we change the way your drug candidates are discovered and developed

Computer Model:

Binding Mode & Specificity

Compound Data

(from client)

Wet Screening

performed by client

Compound Design


For Whom It Works BestDesigning the right drug compound for the right disease target

De-risking drug discovery

Existing infrastructure: Manifold optimization of drug discovery

No infrastructure: Jump start a drug discovery pipeline with

affordable infrastructure

Being stuck: Accelerating slow progressing/difficult projects


The Computist DifferenceDesigning the right drug compound for the right disease target

We are Digital Accelerators of Drug Discovery

Superior Value Creation

• Quick Mode-of-Action/binding mode clarification

• Better and improved compounds

• Earlier “time to market”

• Improved IP position

Significant Cost Savings

• Minimal infrastructure cost / investment

• Less personnel and material cost

• Accelerated process

Rigorous and disciplined project execution

+

+


“If you always do what you've always done, you'll always get

what you've always got!”

Henry Ford



Q&A

Computist Bio-Nanotech Pty Ltd

Scoresby, VIC, Australia

[email protected]

+61 412 367 935

www.computistresearch.com

mailto:[email protected]

http://www.computistresearch.com

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