Java Solutions for Cheminformatics March 2005. About Us Molecule Drawing and Visualization Structure...

Java Solutions for Cheminformatics

March 2005

About Us

About UsMolecule Drawing and Visualization

Structure Searching

Cartridge

Structure Standardization

Molecular Predictions

Chemical Expressions

Screening

Clustering

Fragment Analysis

Virtual Synthesis

Current Developments

History

Formed:

1998 Budapest, Hungary

Skills base:

• Chemistry,

• Software development,

• Predictive tools

Aim:

Platform independent software for chemistry

Highlights

• 1998: Custom projects

• 1999: Java tools for sketching/viewing structures

• 2000: Structure database support

• 2001: Clustering and diversity analysis

• 2003: Pharmacophore screening, property predictions, reaction processing, fragmenting

• 2004: Cartridge technology, virtual synthesis, improved SMARTS support

People

Developers: 17 (7 Phd, 10 MSc)

Technical expertise

• Cheminformatics

• Synthetic and physico-chemistry

• Virtual drug design

• Java

• Web technology

Business Support: 3 (1 MSc, 2 BSc)

Commercial expertise

• Negotiation & contracting

• Relationship management

• Collaboration steering and development

• Strategic marketing

• Mutually benefitial (win win) business relationships

Selected Application Areas

Global licenses

Custom development projects

Value added constructions

Websites/portal front and back end

Educational

Product developmentC

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ica

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19981998 20032003

JChem

Applets, Molfiles, stereo support, Windows, Unix

SMILES, SMARTS, PDB, Rgroups, isotopes, shortcuts, Marvin Beans

Ball and stick, JPG, PNG, SVG, Cut&Paste with Isis/ChemDraw, 2D cleaning, (de)aromatization, reactions

2002200220002000 2001200119991999

SDF, RDF, XYZ animations, CML, templates, compressed formats, Swing, 3D rendering

Mac support, signed applets, Java Web Start, atom mapping

Partial charge,

pKa, logP, logD,

3D generation, radicals, Sgroups

Oracle, MySQL, SQLServer, Access, hashed fingerprints, substructure and similarity searching

DB2, PostgreSQL, Rgroup searching

reaction searching, reaction processing, pharmacophore analysis. screening, standardization, fragmentation

clustering, diversity

Marvin

20042004

Marvin file format, enhanced stereo, enhanced SMARTS support, shapes, text boxes, multiple groups, TPSA, Donor/Acceptor...

cartridge, enhanced stereo searching, recursive SMARTS, chemical expressions, virtual synthesis… S

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Current Products Overview

Multiple Deployment Formats

• Applications

• Java Applets

• Signed Java Applets

• Java Web Start

• Java Beans

• Plugins

• JSP

Why ChemAxon?

• Sophisticated virtual chemistry technology

• Platform independence and Web (Java)

• High performance tools (speed, capacity)

• Client oriented development

• Comprehensive API for the developers

• Detailed documentation

• Competitive prices

• Fast and reliable support

Product Support

• Fast response to support question – max. 24 hour response (fast solution also!)

• Final and beta releases available online.

• Detailed documents available online and extensive help bundled within software

• Skilled and relevant human support quality (direct developer to developer)

• Product development based on support requests

„Developers supporting developers”

Molecule Drawing and Visualization

About Us

Molecule Drawing and VisualizationStructure Searching




Screening

Clustering

Fragment Analysis

Virtual Synthesis


Operating Systems

• 100% pure java

• Windows– 95, 98, Me,

NT, 2000, XP

• Macintosh– OS 9, OS X

• Unix– Linux, Solaris, Irix,

etc.

Web Browsers

• Internet Explorer

• Netscape

• Mozilla

• Safari

• Opera

Marvin

• Various file formats

• Isotopes, charges, radicals

• Alias, pseudo atoms

• Templates

• Abbreviated groups

• Reactions

• Atom maps

• R-groups

• Stereo bonds, stereo configurations (R/S, E/Z)

• Enhanced stereo(ABS/AND/OR)

• SMARTS properties (atoms, bonds, recursive SMARTS)

• Chemical error checking

• Generic atoms and bonds

• Atom lists and not lists

• 2D cleaning

• 3D cleaning

• Various 3D models

• Shapes, text boxes

• Plugins

Various File Formats

Isotopes, Charges, Radicals

Templates

Abbreviated Groups

R-groups

Reactions

Rendered 3D displays with MarvinSpace

Structure Cleaning

CC(C)NCC(O)COC1=C2C=C(C)NC2=CC=C1

3D3D2D2D

topologytopology

Structure Searching

About Us


Structure SearchingCartridge




Screening

Clustering

Fragment Analysis

Virtual Synthesis


• Rapid fingerprint-based database scanning

• Sophisticated graph-based searching

• Integration with databases– Oracle– MS SQL Server– DB2– MYSQL– PostgreSQL– InterBase– Access

• Custom standardization

• JChem Cartridge for searching in Oracle

• JSP integration

JChem Base Features

Import with JChem Base Manager

• Exact structure

• Substructure

• Atom lists and notlists

• Explicit hydrogens

• Generic atoms

• Generic bonds

• SMARTS atom properties– Aliphatic, aromatic– Hydrogen count– Connection count– Valence– Ring count– Smallest ring size– Recursive SMARTS

• Stereo atoms

• Stereo bonds

• R-group queries– R-groups– Occurence– if / then conditions– RestH

• Reaction search– Transformation recognition– Component identification– Stereospecific reactions

(inversion, retention)

• Diastereomers– Enhanced stereo groups

(Abs, And, Or)

Query Features

JChem Base JSP Integration

Thin client support: only a web browser and Java required

Cartridge Technology

About Us


Structure Searching

Cartridge TechnologyStructure Standardization



Screening

Clustering

Fragment Analysis

Virtual Synthesis


JChem Cartridge for Oracle

Oracle can be extended to support chemical database operations using the JChem Cartridge for Oracle

Examples:

Substructure search displaying ID, SMILES codes, and molweight:

SELECT cd_id, cd_smiles, cd_molweight FROM my_structuresWHERE jc_contains(cd_smiles, 'CC(=O)Oc1ccccc1C(O)=O') = 1;

Finding benzene derivatives conforming the Lipinski’s rule of five:

SELECT count(*) FROM my_structures WHERE jc_compare(structure, 'c1ccccc1','sep=!t:s!ctFilter:(mass() <= 500) &&(logP() <= 5) && (donorCount() <= 5) &&(acceptorCount() <= 10)') = 1;

JChem Cartridge for Oracle

JChem Cartridge for OracleJChem Cartridge for Oracle

Example Oracle search returning similar structures with logP >1, which were acquired after April 14th, 2002. MarvinView below.


About Us


Structure Searching


Structure StandardizationMolecular Predictions


Screening

Clustering

Fragment Analysis

Virtual Synthesis


Standardization

• Explicit hydrogens

• Aromatic bonds

• Mesomers

• Tautomers

• Counterions

Standardization Example

afterafterbeforebefore


About Us


Structure Searching



Molecular PredictionsChemical Expressions

Screening

Clustering

Fragment Analysis

Virtual Synthesis


Calculator Plugins

Available Calculations

• Elemental analysis

• Charge distribution

• Polarizability

• pKa

• logP

• logD

• Polar surface area

• Huckel Analysis

• H-bond donor-acceptor

• Major microspecies

• Refractivity

Calculation Interface

• Marvin GUI

• Command line

• Chemical Terms

• API

Elemental Analysis

Polar Surface Area

Partial Charge Distribution

Partial Charge Distribution Calculation

Partial Equalization of Orbital Electronegativities (PEOE)

Orbital electronegativity defined by Mulliken

Orbital electronegativity of atom i:i=at+btqi+ctqi

2 qi: partial charge

Partial charge of atom i is iteratively calculated based on Gasteiger’s method:

i(0)

= atqi(0)

= 0qi

(n+1) = qi

(n) + )n(i- k)/ max(i, k)k: index of a neighbor of atom i

Polarizability

logP = fi

fI: atomic logP increment

logP Example

Validation of the logP prediction

logD is computed using micro ionization constants (ki), micro partition coefficients (pi), and pH

123(0)

1+(1)

2+(2)

3-(3)

1+2+(4)

1+3-(5)

2+3-(6)

1+2+3-(7)

k1

k2

k3

k4

k5

k6

k7

][H][H

][H][H][H

1

]H[][H

][H][H][H

loglog

41

7

2

6

1

5

41

23

21

species ionized-tri

41

77

species ionized-di

2

66

1

55

41

2

4

species ionized-mono

33

22

11

species neutral

0

kkk

kppp

kkppppp

D

kk

kk

kkk

kk

kk

kk

kkk

kk

logD Example

pKa Plugin - Microconstants

Micro ionization constants (logk) are calculated from regression equations that have three types of calculated parameters:

Polarizabilities

Partial chargesIntramolecular interactions

logk

Macro ionization constants (pKa) are calculated from the microconstants (logk)

pKa Plugin - Macroconstants

Ionization scheme

1- 1-2+

123 2+ 1-3- 1-2+3-

3- 2+3-

1

2

3

Hydrogen Bonds in pKa Calculation

logk = a qi - qk) + ba,b: regression parameters

Intramolecular hydrogen bonds are also taken into account

Validation of the pKa prediction


About Us


Structure Searching




Chemical ExpressionsScreening

Clustering

Fragment Analysis

Virtual Synthesis


Chemical Terms

searching match("olefine.mol") && !match("c1ccncc1") && (atomCount(16) == 0) || (mass() < 300);

goal functions inhibitor = inhibitor.mol;

(similarity(inhibitor, pharmacophore_tanimoto) > 0.8) && (similarity(inhibitor, chemical_tanimoto) < 0.5);

filtering (mass() <= 500) &&

(logP() <= 5) &&

(donorCount() <= 5) &&

(acceptorCount() <= 10);

• structure matching functions (describing functional groups, reaction sites, similarity…)

• property calculations (partial charge distribution, pKa, logP, electrophility…)

• arithmetic and logic-operators

Elements of the language

Chemical Terms examples

Applications of Chemical Terms

CT

virtual synthesisreaction and synthesis rules

pharmacophore analysispharmacophore definitions

drug designgoal functions

structure searchingadvanced query expressions

Screening

About Us


Structure Searching





ScreeningClustering

Fragment Analysis

Virtual Synthesis


Pharmacophore Mapping

■ hydrophobic (h) ■ aromatic (r)■ acceptor (a) ■ acceptor / donor (a/d)■ donor / cationic (d/c) ■ donor / aromatic (d/r)

atom type colorsatom type colors pharmacophore type colorspharmacophore type colors

Topological Pharmacophore Fingerprint

h h

h

h

h

h

h

d/+

r/d

r

r

r

r

r

r

rr d/a

d/a

Hypothesis Fingerprints

Advantages Disadvantages

Minimumstrict selection of common features

very sensitive to one missing feature

Averagenot that sensitive to

outliersless selective if actives

are similar

Dissimilarity Metrics

Euclidean

• standard

• normalized

• weighted

• asymmetric

Tanimoto

• standard

• scaled

• asymmetric

Screening Optimization

10,000 test compounds (from NCI)

50 active compounds(ß-adrenoreceptor antagonists)

9,700validation

300optimization

1/3training set

1/3spikes

1/3query set

TRAINING

VALIDATION

Screening Validationß2-adrenoreceptor antagonists

All compounds: 9,700Known active compounds: 18minimum hypothesis

before optimization

after optimization

all hits 2,476 18

known active hits 15 18

enrichment 3.27 539.89

Mixing 18 active compounds with random 9,700 NCI molecules. Sorting by pharmacophore similarity.

Active Hit Distributionß2-adrenoreceptor antagonists

Screening Validation

10,000 NCI compounds before optimization after optimization

family actives all hits active hits enrichment all hits active hits enrichment

ACE 7 6,537 6 1.27 171 6 47.01

Angiotensin2 4 177 3 40.40 66 3 105.50

D2 5 417 5 22.90 31 5 269.08

delta 7 60 5 106.70 9 5 495.25

FTP 13 1020 11 7.97 13 10 422.30

mGluR1 7 1744 3 2.38 10 7 571.10

NPY Y5 49 6370 38 1.18 145 45 47.12

thrombin 3 328 2 19.6 57 2 109.64

Optimized ScreeningJSP Example

Optimized ScreeningJSP Example Hits

Clustering

About Us


Structure Searching





Screening

ClusteringFragment Analysis

Virtual Synthesis


JKlustor

• Jarvis Patrick

• Ward

• Ward's minimum variance method

• Murtagh's reciprocal nearest neighbor (RNN) algorithm

• O(n2) time complexity

• O(n) memory complexity

Ward Clustering Features

• 8 active compound sets– 5-HT3-antagonists– ACE inhibitors– angiotensin 2 antagonists– D2 antagonists– delta antagonists– FTP antagonists– mGluR1 antagonists– thrombin inhibitors

Ward Pharmacophore Clustering Example

Ward Centroids

A Ward Cluster D2 antagonists

Maximum Common Substructure Clustering

Drug Design

About Us


Structure Searching





Screening

Clustering

Fragment AnalysisVirtual Synthesis


RECAP fragmentation example

amide:1amine:2 ether:2

ether:1

amine:1

amide:2

Virtual Synthesis

About Us


Structure Searching





Screening

Clustering

Fragment Analysis

Virtual SynthesisCurrent Developments

The Ideal Virtual Reaction

• Generic (simple)– the equation describes the

transformation only– few hundred generic reactions can

form the basic armory of a preparative chemist

• Specific (complex)– chemo-, recognizes reactive and

inactive functional groups– regio-, "knows" directing rules– stereo-, inversion/retention

• Customizable– to improve reaction model quality

• Processing selective "smart" reactions

• Batch mode (sequential or combinatorial combinations)

• Reverse direction

• High performance (speed and capacity)

Customizable Reaction Engine!

Reaction Modeling

Chemoselective Reaction Definition

REACTIVITY: !match(ratom(3), "[#6][N,O,S:1][N,O,S]", 1) && !match(ratom(3), "[N,O,S:1][C,P,S]=[N,O,S]", 1)

Reactants

2920 amines, alcohols and thiols

369 isocyanatesand isothiocyanates

Chemoselective Reaction Products

1,264,391 single site products

Regioselectivity (Markovnikov, Zaitsev)

An elimination reaction definition with Zaitsev’s rule.

r2

Addition reaction definition with the Markovnikov rule.

r1

SELECTIVITY: hcount(ratom(2))

SELECTIVITY: -hcount(ratom(2))

Regioselective Reaction Example

Chlorine migration example in four steps by consecutive elimination and addition reactions.

r2 r1

r2 r1

Regioselectivity (SeAr)

Reaction definition of aromatic electrophile bromination of the benzene ring. The expression defines a regioselectivity rule for the major product.

SELECTIVITY: -charge(ratom(1))TOLERANCE: 0.0045

Regioselectivity (SeAr) Products

The virtual bromination of toluene with the above reacton definition results the ortho and para isomer as main product…

… and bromine is directed into the meta position in case of nitro-benzene.

Regioselectivity (SeAr) Example Products

1,198 monobrominated main products(tolerance is set to zero)

• Multiple steps

• Flexible compound dispatching

• Synthesis rules

• Synthesis tree building

• Memory, file and database mode

• Graphical synthesis browser

• Building block coloring

Customizable Synthesis Engine!

Virtual Synthesis

Synthesis Example

Derek S. Tan, Michael A. Foley, Matthew D. Shair, Stuart L. Schreiber*, J. Am. Chem. Soc., 1998, 120, 8565-8566

lacton aminolysisalkyne coupling

esterification

Synthesis Definition

Component set definition

Set1: ASet2: B1, B2, B3Set3:Set4: D1, D2Set5:Set6: F1, F2Set7:

"Smart" reaction library

R1: alkyl-iodid + alkyne >> alkyl-alkyneR2: lacton + amine >> amideR3: alcohol + carboxylic acid >> ester

Synthesis route definition

Step1: A + B CR1

Step2: C + D ER2

Step3: E + F GR3

Synthesis Browser


About Us


Structure Searching





Screening

Clustering

Fragment Analysis

Virtual Synthesis


Recent Developments

• Automatic searching of low-energy conformers

• Improved Oracle cartridge

• Structure searching combined with chemical calculations

• Exhaustive Synthesis for metabolism applications

• R-group decomposition

• Maximum common substructure search in molecule pairs and in libraries


• MarvinSpace, an OpenGL based 3D molecule and surface visualisation engine for small and macromolecules

• Instant JChem Base, a desktop and enterprise chemical database client with form builder

• IUPAC naming plugin

• Isoelectric point plugin

• Random Synthesis for building up a diverse virtual space of synthetically feasible compounds

• Extension of the reaction library

• Further descriptors in the Topology Analysis plugin

Future Plans

• Metabolic transformation library

• Diverse database of synthetically accessible compounds

• Search in Markush compounds

• Peptide builder

• Fragment-based activity analysis of compound libraries

• AnalogMaker (fragment based random evolutionary analog design)

• Retrosynthesis

Visit us

• Home page– www.chemaxon.com

• Forum– www.chemaxon.com/forum

• Animated demos and tutorials– www.chemaxon.com/demos

• Presentations and posters– www.chemaxon.com/conf

Máramaros köz 3/a Budapest, 1037Hungary

[email protected]

www.chemaxon.com

Thank you for your attention

Java Solutions for Cheminformatics March 2005. About Us Molecule Drawing and Visualization Structure...

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Transcript of Java Solutions for Cheminformatics March 2005. About Us Molecule Drawing and Visualization Structure...