chris ullman, isogenica, 'the use of cis display for drug discovery

The Use of CIS Display for Drug Discoveryp y g yCresset European Users Meeting 2011

Overview

Next generation approaches

BIC Technology

ApplicationsApplications

CIS Display Molecular Evolution Technique

CIS display is an acellular, in vitro display technology

• Uses biochemical process of E. coli

• No cloning, therefore larger libraries (>1013) are rapidly

generated

• CIS display is a powerful discovery engine for peptides and

other protein scaffoldsother protein scaffolds

Molecular Evolution vs HTSMolecular Evolution vs HTS

Molecular evolution – 1010‐1013 per week HTS – 106 per week

4

Phage Display

DNA librarypreparation

transformation

Li k b• Link between genotype and phenotypephenotype

• Typically upto 1010peptides but has disadvantages

Ribosomedisplay

mRNAdisplay

IVC CISdisplay

Acellular

emuls

AcellularTechnologies

sion

Expression of proteinExpression of protein from an in vitro transcription/translation mixture

CIS

translation mixture

ori

RepAMattheakis et al, 1994 PNASNemoto et al, 1997 FEBS Lett.Roberts and Szostak, 1997 PNASA

Tawfik & Griffiths 1998, Nat. BiotechDoi et al, 1999 FEBS Lett.Odegrip et al., 2004 PNAS

RNA template | DNA template

CIS Display Mechanism

Promoter Library repA oriCIS Linear dsDNAtemplate

mRNA

Translating

Nascent polypeptide

RNA polymerase

Translating ribosome

Odegrip et al., 2004 PNAS, 2806‐2810

RNA polymerase

Promoter Library repA oriCISDisplayed polypeptide

RepA

Promoter Library repA oriCIS

CIS Display – Libraries to Active Candidates

1. Cis‐activity of DNA‐bi di ibinding protein RepA

2. Libraries expressed in vitro→ stable protein‐vitro→ stable proteinDNA complexes

3. Protein‐DNA l bj d

CIS di l complexes subjected

to affinity selection

4. Eluted complexes

displaypanning

. uted co p e esregenerated by PCR

5. Optimal ligands after 3 5 i d3‐5 successive rounds

6. Optimised with in‐house lysatey

Next Generation Approach to Biologics Discovery

Next generation sequencing

Next generation sequencing

CIS display selectionCIS display selection

QCQC

In silico screeningIn silico screening

Peptide tagsPeptide tags

DNA tagsDNA tags

Peptide clustersPeptide clusters

Peptide tagsPeptide tagsPeptide outputPeptide output

Enriched peptidesEnriched peptides

ScreeningScreeningQC QC

MaturationMaturation

Next Generation Peptide Screening Platform

CIS display peptide selection process monitored by Illumina NGS.Approximately 4 million sequences from panning rounds 1 4 ofApproximately 4 million sequences from panning rounds 1‐4 of CIS display determined

f 0 1% (f d l 4 000 i )

30selelection BSelection B

Percentage of sequences ≥0.1% (found at least ~4,000 times)

15

20

25

ences

5

10

15

% se

que

0

R1 R2 R3 R4

Evolution of Top 20 Peptide SequencesEvolution of Top 20 Peptide Sequences

Evolution of top 20 sequences through panning rounds 2‐4Evolution of top 20 sequences through panning rounds 2‐4Enrichment of individual sequences can be monitored in the process

12%

14%

2.5%

3.0%

6%

8%

10%

1 0%

1.5%

2.0%

0%

2%

4%

0.0%

0.5%

1.0%

R2 R3 R4 R2 R3 R4

Bioinformatics Analysis Following CIS DisplayAfter 4 rounds of enrichment using CIS display from ~1013 sequences against client target:

~4.5x106 DNA sequencesanalysed in hours

14,000 peptides

447 clusters

197 enriched fragmentsfragments

Next Generation Sequencing – In Silico ScreeningBi i f ti A l iBioinformatics Analysis

Selection output:>6x106 sequenced clones

FLAG‐tag: YKxxD

Peptide Screening – Anti‐TNFα Peptide Selection

Library 1, 36‐mer; Library 2 and 3, biased sequences; Library 4, constrained and 16‐mer linear mix. 3 different lysates.co st a ed a d 6 e ea . 3 d e e t ysates.Selection generated high hit rate but difficult to determine consensus15,526 16‐mer peptides from library 4 passed to PEPperPRINT for high‐density peptide synthesis

Peptide Screening – Anti‐TNFα PeptidesFollowing 4 rounds of enrichment using CIS display from >1013 sequences :

• In collaboration with PEPperPRINT• Result: >15,000 16‐mer peptides synthesised

in parallel• Binding motifs and better discrimination between specific and non‐specificbetween specific and non‐specific

P f l d t tPowerful dataset• Library designs validated through

peptide synthesis and bindingM tif i t t f IP t ti• Motifs important for IP protection, therapeutics, epitopes

• Firm basis for maturation libraries

Isogenica’s Maturation ApproachesIsogenica s Maturation Approaches

Sequential amino acid scanq(Single mutation)

Consensus based libraryConsensus‐based library(Multiple changes but maintain important sidechains)

Variable consensus library(Additonal conservative substitutions at consensus)

Error‐prone library(Mutations at random positions)(Mutations at random positions)

Fully doped library(mutations introduced at custom rates)

CIS Display Maturations • Using the speed of CIS display to build multiple maturation libraries –

driving to optimal binders• Picomolar binders, best binder to date <20 pM

originally selected clone

improved peptidesimproved peptides

16‐mer peptide libraries

Maturation of Anti‐NGF PeptidesMaturation of Anti NGF PeptidesInitial selections identified NGF binding peptidesMaturations have identified 2 candidate peptides that inhibit NGF binding to its high affinity receptorbinding to its high affinity receptor TrkA involved in the pain response pathwayThe peptides inhibit a phenotypic change in rat PC12 cells (from pheochromocytoma of the rat p yadrenal medulla) in the presence of NGF

NGF causes neurite outgrowth in rat PC12 cells. Peptides A2 and D9 pinhibit this change

Maturation of Anti‐NGF PeptidesMaturation of Anti NGF Peptides

peptide candidates inhibit receptorpeptide candidates inhibit receptor interaction with high activitypeptides have now been PEGylatedpeptides have now been PEGylatedfor in vivo studies (Polytherics Ltd.)

Valuable OutputsValuable OutputsPotential to identification of binding sites and identify epitopesepitopesCIS display can provide an evolutionary approach to determine natural substitution matrices based upon a peptidedetermine natural substitution matrices based upon a peptide backboneImportant sidechains are identified through consensusImportant sidechains are identified through consensus sequencesHowever, current clustering algorithms can be ineffectual –, g gsequence not shapeNew algorithms to cluster peptides based upon field g p p pcharacteristics

BIC Platform PartnersBIC Platform Partners

IsogenicaVery large diverse

tid lib i

Cresset GroupProven field based h i t f fi ld

BiolauncherNovel representation f tid bi dipeptide libraries

Intracellular and extracellular targets

chemistry force fieldsExpert Peptidomimeticdesign

of peptide binding populationsCluster binding

id i iHarnesses NGS to process very large screens

Identifies active compoundsGenerates diverse

peptides into active conformationsInformatics driven

Extensive coverage of chemical spaceEnrichment cycle

active bioisosteresIdentify pharmacophore

BLOSUM62 matrix vs Field Based Substitution MatrixBLOSUM62 matrix vs Field Based Substitution MatrixBLOSUM62FBSM10

New matrices more appropriate to PPIs

Cresset’s Field‐Based Virtual Screening

Cresset’s Backbone vs Field ComparisonCresset s Backbone vs Field Comparison

2D structural diversity of the HIV NNRTIs contrasts with strong Field similarity when structures are overlaid

Applications of CIS Display

P t l it d t i tiProtease cleavage site determinationPeptide stability

Cell penetrating peptide discoveryScaffold engineeringScaffold engineering

CIS Display: Protease Site Determination

FLAG epitope random librar

CIS Display: Protease Site Determination

FLAG epitope random library┌─────────────┐D-Y-K-F-D-D-Y-W-H-x-x-x-x-x-x-x-x-x-x-LINKER-REPA

Protease sensitive library peptides

cleaved

Genes encoding protease i i id lsensitive peptides lost

GPCR Ligand StabilisationStability maturation of native GPCR ligandStability maturation of native GPCR ligand

• Aim of project: select a peptide with increased stability in human plasma whilst maintaining activity and specificity over a membrane of related target.

• Library based upon a consensus sequence derived from the wild type.• The target was presented as an overexpressing cell membrane fraction.

80

WT peptide Peptide X90

100

Activity Stability in human plasma

40

60

rodu

ction

Peptide XPeptide Y

Peptide X

5060708090

activ

ity

20

IP pr

1020304050

% a

WT peptide

00 ‐10 ‐9 ‐8 ‐7 ‐6

Peptide (log M) Time/min

010

0 50 100 150 200

Selection for Cell Penetrating Peptides

Initial

DNA library encoding peptide RepA fusions

library

Peptide‐RepA‐DNAcomplexes formed

Isolate CPPsLysis to release

internalisedcomplexesp

Digest/wash away exposedprotein‐DNA complexes

DNasep p

Protease

CPP Confocal Study Live CHO CellsCPP Confocal Study Live CHO Cells

C lE5 ControlE5 Tat

Peptide (green)

+ Annexin V (red)

Transmittedli hlight

Peptide E5 labelled with N‐terminal (5/6)‐fluorescein

CIS Display and Proteins

CIS display is suitable for the i f l t i f iexpression of larger protein fusions

Has been used for next generation protein scaffolds and antibody p yfragmentsLysate has been developed to h dl lti l t i t i ihandle multiple cysteine containing systemsLicenced to Centocor for Centyrinyscaffold

Alternative scaffoldsB t t i (I i )

Can be recombinantly expressed or chemically synthesised

Betatein (Isogenica)

y p y yRandomly mutate surface residuesLess than 40 amino acidsLess than 40 amino acidsReversible folding

folded

f ld dunfolded

Alternative scaffoldsB t t i

Selection from naïve library: affinity for VEGFR2

Betatein

y yBest clone : KD = 24.0±4.0nM (ForteBio)

3 5Binding specificy

1.5

2.0

2.5

3.0

3.5

sorb

ance

VEGFR2 huIgGmAb enzyme Xalbumin neg

0.0

0.5

1.0

1.5

A1 B1 E1 H4 H6 neg

abs

lclone

Isogenica SummaryIsogenica Summary

A cost effective biologics discovery platform combining rapidA cost effective biologics discovery platform combining rapid library display and next generation sequencing for multiple library formatsyAmenable to high throughput automationResulting data rich output enables design of maturationResulting data rich output enables design of maturation librariesRapid progression through maturation to lead identificationRapid progression through maturation to lead identificationDisplay of peptides, protein scaffolds and antibody fragments and other proteins upto 90kDafragments and other proteins upto 90kDaApplicable to small molecule drug discovery through BIC collaborationcollaboration

Partners

Th kThank youAny Questions?Any Questions?

www.isogenica.comTel: +44 (0)1799 533680