Workshops June 2016 - Cresset · 2019-06-25 · Tag the BCML compounds with a ‘BCML’ tag and...

Becoming a power user of Forge

Cresset European User Group Meeting – Workshops

June 2016

Files for this workshop

> The files used in this workshop are available for download on

request

> Please send an email to enquiries@cresset-group.com stating the

name of the workshop

Forge workflow

Ligand conformation

known?

Develop pharmacophore (FieldTemplater)

Use low energy conformation

Load ligand as reference

‘Protein

guided’ –

shape and

electrostatics

‘Ligand guided’

– field guided

substructure

Align to References

Look for 2D and 3D activity cliffs

Design new molecules

Summarize SAR in Activity Atlas Models

Design against Activity Atlas

models

Summarize SAR in Activity Atlas models

Build 2D and 3D QSAR models

Look for 2D and 3D activity cliffs (Activity Miner)

Use score for virtual screening

Score designs against

QSAR models

Core Forge experiments

3 CCR5 actives

Convert 2D to 3D

binding hypothesis

Align all tested

compounds

> Uses ligand alignment as a basis for

SAR interpretation

> Ligands aligned to a reference or

‘template’ using

> Electrostatics and shape

> Shape only

> Substructure

> Templates from XRAY or built-in

FieldTemplater module

> Aligned ligands from multiple

chemotypes used for

> Virtual screening

> Relating activities from different series

> SAR transfer

> Align ligands from single

chemotype used for

> 3D activity cliff analysis

> Activity Atlas Models

> 3D QSAR

> Understanding design of new

molecules

Understand structure-activity using Forge

> Normal: Field-based alignment

> Uses Cresset electrostatic, shape and hydrophobic field points to align

> Scored 50% field-based similarity with 50% shape similarity

> Independent of chemical structure

> Better for datasets that have structurally diverse compounds

Which alignment. Normal or (Maximum Common) Substructure?

Normal

> Maximum Common Substructure alignment

> Common structural features in database molecules are mapped onto conformation of corresponding

features in reference molecule

> All other parts of the molecule are conformationally hunted

> Field/shape based scoring

> Good for datasets with a common core or concentric series

Which alignment. Normal or (Maximum Common) Substructure?

Substructure

Field based alignment

Fields

Field based alignment and scoring

Fields

Cheeseright et al, J. Chem Inf. Mod., 2006, 665

Fields

Cheeseright et al,

J. Chem Inf. Mod., 2006, 665

Grant, Gallardo, Pickup,

J. Comp. Chem., 1996, 1653

Alignment, scoring and comparisons

Combined

> Common substructure matched to reference geometry

> All other moieties are conformationally hunted

> Generated conformations are scored against reference

> Control of Maximum Common Substructure (MCS) is in Alignment options

Maximum Common Substructure alignment

Normal

Permissive

> Use Normal with scoring set to

Weighed Average to:

> Align heterogeneous data sets

> Best for virtual screening and ligand

design

> Use Maximum Common

Substructure with scoring set to

Maximum to:

> Align congeneric data sets

> Best for quantitative or qualitative SAR

Working with multiple reference structures

Four typical alignment scenarios

> Case 2: One chemical class, I have

the X-ray structure of one reference

compound

> Case 4: Several chemical classes, I

have the X-ray structure of one (or

more) reference compounds

> Case 1: One chemical class, I don’t

have the X-ray structure of the

reference compound

> Case 3: Several chemical classes, I

don’t have the X-ray structure of

any reference compounds

Case 1

One chemical class, I don’t have the X-ray structure of one reference compound

Case 1: One chemical class, I don’t have the X-ray structure of the

reference compound

Select one of the most potent/less flexible compounds

Carry out an accurate conformation hunt on this compound

Choose a reasonable low energy conformation

Promote to reference

Use it to align the data set

Alignment and SAR of NaV1.7 sodium channels antagonists

Practical

> Published X-ray ligand/target structure information is not available for NaV1.7 sodium channels

> The lowest energy conformation of one of the most active compounds in the dataset was promoted to reference structure

> ortho, meta substitution will facilitate alignment of substituted phenyls in the data set

Reference molecule

NaV1.7 pIC50 7.7

Choose the smallest, more rigid, more active

compound (ligand efficiency)

Perform 'Very accurate but Slow'

conformation analysis in Forge, no alignment

Turn conformations into alignments

Explore low energy conformations, choose

one and promote to Reference role

Align the Training set to the new Reference:

Accurate but Slow conf hunt

Substructure alignment

Case 2

One chemical class, I have the X-ray structure of one reference compound

Case 2: One chemical class, I have the X-ray structure of one

reference compound

Download the X-ray structure from the PDB into Forge

Check atoms/bonds/protonation

Gently minimize and compare with original reference

Use it to align all the other compounds in the data set

Several chemical classes, I don’t have the X-ray structure of any reference

compounds

Case 3

Case 3: Several chemical classes, I don’t have the X-ray structure

of any reference compounds

Select the best references (most potent, less flexible compounds, representative of the chemical classes in the data set)

Build a FieldTemplater bioactive conformation hypothesis

Send it to Forge as a set of aligned references

CCR5: Finding a pharmacophore

3 CCR5 actives

Convert 2D to 3D

binding hypothesis

Align all tested

compounds

> Compare other molecules to our template using Fields

> - Actives, inactives, ideas, libraries, HTS results

> Understand SAR through activity cliffs

> Build QSAR models

> Design new molecules using the Fields

Template gives alignment of larger dataset

FieldTemplater process

> Choose molecules to template

> Load (paste) into Forge

> Transfer to FieldTemplater module

> Run menu

> Right click menu

> Drag and drop

> Process

> Visually inspect results

> Return results to Forge

Things to note

> FieldTemplater relates actives only

> It tries to generate more than a ‘pharmacophore’ – a bio-active

conformation hypotheses

> Alignment of inactives to a template gives additional information

> FieldTemplater compares molecules in pairs

> The pairwise data is used to find templates

> The defaults work – but the best results come from changing

parameters

FieldTemplater hints and tips

> Enter 3-5 active, efficient ligands; choose:

> Similar size with same binding site

> Prefer more active, more efficient compounds with fewer rotatable bonds

SCH-417690 Vicriviroc Ki 1.6nM

UK-427857 Maraviroc IC50 1nM

MLN1251

TAK-220 IC50 3.5 nM

Alignment of CCR5 inhibitors using a FieldTemplater hypothesis

Practical

CCR5 inhibitors: Building the FieldTemplater hypothesis

Open the CCR5_start file in Forge

Select molecules in ‘Molecules to be

Templated’ role and send to FieldTemplater

Define constraints on basic N and set-up the

FieldTemplater processing

Build the FT hypothesis

Transfer the chosen FT hypothesis to Forge

into Reference role

SCH-417690 Vicriviroc Ki 1.6nM

TAK-220 IC50 3.5 nM

BMCL_15_2129_73

Set-up of FieldTemplater processing

> When you are happy with the

set-up, press Start Change this value to 4

CCR5 inhibitors: aligning the BCML and UK series

Filter by substructure to identify the BCML

and UK series

Tag the BCML compounds with a ‘BCML’ tag

and the UK compounds with a ‘UK’ tag

Remove compounds without BCML/UK tag

Remove TAK and SCH References

Align the Training set to the Reference:

• ‘Accurate but slow’ conf hunt

• Substructure alignment using ‘Very

permissive’ matching rules

• ‘Maximum’ scoring method

BMCL_15_2129_73

Several chemical classes, I have the X-ray structure of one (or more) reference

compounds

Case 4

Case 4: Several chemical classes, I have the X-ray structure of

one (or more) reference compounds

Download the X-ray structure of the reference from the PDB into Forge

Select references for the other classes (most potent, less flexible, representative of the data set)

Build a FieldTemplater bioactive conformation hypothesis

Send it to Forge as a set of aligned references

cressetgroup

Questions welcomed

support@cresset-group.com

Example files available from

enquiries@cresset-group.com

Contact us for our tailored training courses

Workshops June 2016 - Cresset · 2019-06-25 · Tag the BCML compounds with a ‘BCML’ tag and...

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