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Fast Computational  M ethod for Fragment Fast Computational  M ethod for Fragment

Fast Computational M ethod for Fragment - PowerPoint Presentation

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Fast Computational M ethod for Fragment - PPT Presentation

G rowing and Joining Using Molecular F ields Dr Martin J Slater Cresset BMD W ho are we Cresset was founded in 2002 by innovator Andy Vinter We provide and continually develop a suite of unique cutting edge molecular ID: 933704

search fragment field sim fragment search sim field dfg hinge rank pdb fields results molecule result gly select region

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Slide1

Fast Computational Method for Fragment Growing and Joining Using Molecular Fields

Dr Martin J Slater

Slide2

Cresset BMD: Who are we?

Cresset was

founded

in 2002 by innovator Andy Vinter We provide and continually develop a suite of unique cutting edge molecular modelling software for drug discovery.We have clients from big pharma, agrochem, biotech and academia

Slide3

Cresset’s unique technology

It uses a condensed 3D representation

of

the electrostatic, hydrophobic and shape properties of molecules together with the full fields.

3D

Molecular Electrostatic

Potential (MEP

)

What proteins see?

Field Points2D

RepresentationWhat chemists see?

= Positive

= Negative

= Shape

=

Hydrophobic

What

our CPUs

see?

Slide4

Field patterns from Cresset’s proprietary XED force field reproduce experimental results

XEDs make

fields

workInteraction of Acetone and Any-OH from small molecule crystal structuresExperimentalUsing XEDs

Not using XEDs

XED adds p-orbitals to get better representation of atoms

Slide5

Biologically

Relevant Molecular Comparisons

Bioisosteres

Bioisosteric groups

Slide6

View

fields

Field points give you new insights into your molecule

Experimental

(Data from small molecule

xray

structures)

Fields

Structure

Slide7

Comparing 2D and 3D metrics

Similar

2D=3D_FS

2D=3DDissimilar 2D=3D_FS2D = 3D_FS

Slide8

Example - Higher 3D Sim

2D sim =

0.1

(other methods=0.3)

3D field sim = 0.82

Slide9

Example - Higher 3D Sim

141

2D sim =

0.23D sim = 0.7454

Slide10

Spark’s Approach

Rofecoxib

Valdecoxib

Etoricoxib12nM

Find

bioisosteres

by replacing sections of the molecule

Slide11

Spark’s Approach

Select

a region to

replace and remove these atoms

Slide12

Wrong distance

Spark’s Approach

Select

a region to replace and remove these atomsSearch database for matching fragments(geometric search only)(search runs on fragment conformations)

Slide13

Spark’s Approach

Wrong angle

Select

a region to replace and remove these atomsSearch database for matching fragments(geometric search only)(search runs on fragment conformations)

Slide14

Select a region to

replace and remove these atoms

Search

database for matching fragments geometric search only (search runs on fragment conformations)Form Products minimise and add field pointsSpark’s ApproachGood match

Slide15

Select a region to

replace and remove these atoms

Search

database for matching fragmentsgeometric search onlysearch runs on fragment conformationsForm Productsminimise and add field pointsScoreSpark’s Approach0.88

Slide16

Produces more diverse, non-obvious bioisosteresAvoids fragment scoring limitationsAllows for electronic influence of replacing a moiety on the rest of the molecule and vice versa

Allows for neighbouring group effects

Whole-Molecule Scoring Advantages

Slide17

Example - COX-2Search for Bioisosteres for cyclic lactone of

Rofecoxib

Actives:

9 of the first 10 clusters21 of the first 30 clusters Search Common Dbs87,225 frags

Slide18

Cluster,

Result

NosCluster idFieldStere result2D simclosest lit compd10,120.52Same, 60nM

13,19

0.509

7nM32

, 104

0.48

NoneCOX-2 Results

Cluster,

Result Nos

Cluster idSPARK result

2D sim

closest lit compd1,1

0.646

2,2

0.531

6.5uM

5,5

0.500

Same, 10nM

9,11

0.532

70nM

Slide19

Scaffold replacement ‘Sildanafil’

s

park (10

mins)NEAT?spark results 2-5Fsim score

0.985

0.985

0.9820.978

spark results 6, 7, 10, 13

Fsim

score

0.973

0.973

0.959

0.957

spark results 14, 18, 26, 30

Fsim

score

0.953

0.951

0.943

0.939

Pfizer J

. Chem. Inf.

Model. 2012

Slide20

Fragment growing example

FieldStere

version

3.0.0 fragment growth example:P38 kinase bound to a fragment fluorescent probe PDB:3K3I specific to the ‘DFG-out’ conformation ‘DFG-in’ example with specificity towards the ‘Gly’ flipped hinge PDB:3ROC and/or 3HUBSelectivity potentially to be gained by combining ‘Gly flip’ and ‘DFG-out’ in one moleculeCan we use the new version of SparkV10 to grow the DFG-out fragment into the DFG-in hinge?

Slide21

Fragment in DFG-out pocket, PDB:3K3I

predominant hinge

c

onformationGraphics from Pymol from Delano Scientific

Slide22

+Gly hinge flip ligand_1, PDB:3ROC

Hinge

Gly

flipGraphics from Pymol from Delano Scientific

Slide23

Fragment compatibility – DFG-out

Slide24

Structure

Rank

Sim

StructureRank

Sim

1

0.528

11

0.492

4

0.507

13

0.489

6

0.501

53

0.476

Fieldstere

output: 2D

mols

Slide25

Fieldstere output: 3D mols and fields

Fragment and reference

Rank 4

Rank 6

Rank 11

Rank 13

Rank 53

Slide26

OutcomeFragment growth both possible and a facile using an automated

process

with

SparkV10Interesting and sensible candidate molecules generatedPredict highly selective p38 activesAbsolute requirement for 3D insight

Slide27

Any relevance? – Pfizer compound for COPD

Deposited in PDB

: 2YIS

November 2011Clinical trials for COPDVirtual compounds in the output list……prepared for ACS San Diego Late Summer 2011

Slide28

ConclusionCresset offer a wide variety of software and collaborative solutions for drug discovery

Cutting edge technology

Provide

key insights

Slide29

martin@cresset-group.comQuestions welcomed

Slide30

COX-2 Results

Slide31

Product Space

Target

Result 5

Result 1,484

Slide32

+Gly hinge flip ligand_2, PDB:3HUB

Hinge

Gly

flip