La chemoinformatica: uno strumento computazionale per la chimica farmaceutica

Matteo Floris La chemoinformatica uno strumento computazionale per la chimica farmaceutica CRS4 - collana seminari 2012 3 Maggio 2012

Mi presento

Matteo Floris Laurea in C.T.F., Univ di Padova Master in Bioinformatica, Koeln Univ. Dottorato in Biochimica, Univ. Roma “La Sapienza” Chemoinformatica: sviluppo di metodi per ligand based drug design Bioinformatica presso il CRS4 per 6 anni (genomica computazionale) [email protected]

Chemoinformatics or cheminformatics?

Chemoinformatics is a vast discipline, standing on the interface of chemistry, biology and computer science D. Agrafiotis, J&J

Premessa

Premessa

Rational drug design o rational design Ricerca di nuovi (potenziali!) farmaci sulla base della conoscenza di un target biologico

Drug design

Premessa

Rational drug design o rational design Ricerca di nuovi (potenziali!) farmaci sulla base della conoscenza di un target biologico Drug design spesso si serve di tecniche di modeling computazionale (computer-aided drug design, CADD)

Drug design

Premessa

Rational drug design o rational design Ricerca di nuovi (potenziali!) farmaci sulla base della conoscenza di un target biologico Drug design spesso si serve di tecniche di modeling computazionale (computer-aided drug design, CADD) Se la struttura tridimensionale del target molecolare è nota, allora si parla di structure-based drug design.

Drug design

Premessa

Ligand based CADD Structure based CADD

Premessa

Basato sulla conoscenza di altre molecole che in grado di legarsi col target biologico di interesse. Queste altre molecole possono essere utilizzate per costruire una ipotesi farmacoforica che definisca le caratteristiche minime richieste per avere l'interazione. In alternativa, le techiche quantitative structure-activity relationship (QSAR) permettono di cercare una correlazione tra proprietà chimico-fisiche della molecola e l'attività biologica.


Premessa

Basato sulla conoscenza di altre molecole che in grado di legarsi col target biologico di interesse. Queste altre molecole possono essere utilizzate per costruire una ipotesi farmacoforica che definisca le caratteristiche minime richieste per avere l'interazione. In alternativa, le techiche quantitative structure-activity relationship (QSAR) permettono di cercare una correlazione tra proprietà chimico-fisiche della molecola e l'attività biologica.

Si basa sulla conoscenza della struttura del target biologico di interesse, ottenuta tramite tecniche di x-ray crystallography o spetroscopia NMR. Qualora la struttura del target non fosse a disposizione, si può ovviare con la costruzione di modelli tridimensionali per omologia. Con l'ausilio di strumenti computazionali è possibile stimare l'affinità e la selettività di uno o più composti per il target.


A virtual space odyssey

One of the main goals in drug discovery is to identify and develop new ligands with high binding affinity towards a protein target. Today, there is increased reliance on computer-based tools […]. These help select molecules from the vast expanse of chemical space and aid optimization of compounds of interest into drugs. Cath O'Driscoll, Nature, 2004

A real world odyssey

L'universo chimico

L'universo chimico

Chemical space is the space spanned by all possible (i.e. energetically stable) molecules and chemical compounds – that is, all stoichiometric combinations of electrons and atomic nuclei, in all possible topology isomers. Chemical reactions allow us to move in chemical space.

L'universo chimico

Chemical space is the space spanned by all possible (i.e. energetically stable) molecules and chemical compounds – that is, all stoichiometric combinations of electrons and atomic nuclei, in all possible topology isomers. Chemical reactions allow us to move in chemical space. The mapping between chemical space and molecular properties is often not unique, meaning that there can be multiple molecules which exhibit the same properties

CAS REGISTRY is the most authoritative collection of disclosed chemical substance information, containing more than 65 million organic and inorganic substances and 63 million sequences 67,370,815 Commercially available chemicals in CAS Pubchem Pcsubstance contains about 85 million records. Pccompound contains nearly 30 million unique structures. PCBioAssay contains more than 585,000 BioAssays. Each BioAssay contains a various number of data points.

L'universo chimico

L'universo chimico

GDB-13 enumerates small organic molecules up to 13 atoms of C, N, O, S and Cl following simple chemical stability and synthetic feasibility rules. With 977.468.314 structures, GDB-13 is the largest publicly available small organic molecule database to date

L'universo chimico

L'universo chimico

150 possibili sostituenti da mono a 14 sostituenti

10^29 derivati teorici

L'universo chimico

Navigating chemical space for biology and medicine

Christopher Lipinski & Andrew Hopkins Nature 432, 855–861 (16 December 2004) doi:10.1038/nature03193 Despite over a century of applying organic synthesis to the search for drugs, we are still far from even a cursory examination of the vast number of possible small molecules that could be created. Indeed, a thorough examination of all ‘chemical space’ is practically impossible. Given this, what are the best strategies for identifying small molecules that modulate biological targets?

L'universo chimico

Navigating chemical space for biology and medicine

Christopher Lipinski & Andrew Hopkins Nature 432, 855–861 (16 December 2004) doi:10.1038/nature03193 Despite over a century of applying organic synthesis to the search for drugs, we are still far from even a cursory examination of the vast number of possible small molecules that could be created. Indeed, a thorough examination of all ‘chemical space’ is practically impossible. Given this, what are the best strategies for identifying small molecules that modulate biological targets?

Il salvarsan (o arsfenamina o 606) è un farmaco utilizzato nel trattamento della sifilide e della tripanosomiasi africana. È stato il primo agente chemioterapico conosciuto.

L'universo chimico

L'universo chimico

Trust, but verify

Many scientists TRUST chemistry and biology databases that are so often reused, reanalyzed and integrated with new cheminformatics or bioinformatics tools. The authors of such articles do not appear to analyze for problems caused by poor DATA QUALITY or hypotheses that are incorrect due to poor underlying data. Antony Williams, ChemSpider

Rappresentare molecole

MOLECULES real objects

MOLECULE REPRESENTATIONS

models

MOLECULAR DESCRIPTORS

information


Chemical table file

benzene 6 6 0 0 0 0 0 0 0 0 1 V2000 1.9050 -0.7932 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0 1.9050 -2.1232 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0 0.7531 -0.1282 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0 0.7531 -2.7882 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0 -0.3987 -0.7932 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0 -0.3987 -2.1232 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0 2 1 1 0 0 0 0 3 1 2 0 0 0 0 4 2 2 0 0 0 0 5 3 1 0 0 0 0 6 4 1 0 0 0 0 6 5 2 0 0 0 0 M END $$$$


SMILES ® Benzene: c1ccccc1 Metano: C Etino: C#C Sildenafil citrato (Viagra): OC(=O)CC(O)(CC(O)=O)C(O)=O.CCCc1nn(C)c2c1nc([nH]c2=O)-c1cc(ccc1OCC)S(=O)(=O)N1CCN(C)CC1


InChI The IUPAC International Chemical Identifier (InChI) is a non-proprietary identifier for chemical substances that can be used in printed and electronic data sources thus enabling easier linking of diverse data compilations http://www.inchi-trust.org/


InChI is short for International Chemical Identifier. InChIs are text strings comprising different layers and sublayers of information separated by slashes (/). Each InChI strings starts with the InChI version number followed by the main layer. This main layer contains sublayers for chemical formula, atom connections and hydrogen atoms. Depending on the structure of the molecule the main layer may be followed by additional layers e. g. for charge, stereochemical and/or isotop information. InChI=1S/C6H6/c1-2-4-6-5-3-1/h1-6H



Astrazioni: grafi grafi astratti markush descrittori (rappresentazioni numeriche) fingerprints (rappresentazioni binarie)

Descrittori molecolari

"The molecular descriptor is the final result of a logic and mathematical procedure which transforms chemical information encoded within a symbolic representation of a molecule into a useful number or the result of some standardized experiment. The field of molecular descriptors is strongly interdisciplinary and involves a mass of different theories. For the definition of molecular descriptors, a knowledge of algebra, graph theory, information theory, computational chemistry, theories of organic reactivity and physical chemistry is usually required, although at different levels. For the use of the molecular descriptors, a knowledge of statistics, chemometrics, and the principles of the QSAR/QSPR approaches is necessary in addition to the specific knowledge of the problem. Moreover, programming, sophisticated software and hardware are often inseparable fellow-travelers of the researcher in this field. From the introduction to the "Handbook of Molecular Descriptors" by Roberto Todeschini and Viviana Consonni, Wiley-VCH, 2000.

Descrittori molecolari

• 0D-descriptors (i.e. constitutional descriptors, count descriptors), • 1D-descriptors (i.e. list of structural fragments, fingerprints), • 2D-descriptors (i.e. graph invariants), • 3D-descriptors (such as, for example, 3D-MoRSE descriptors,

WHIM descriptors, GETAWAY descriptors, quantum-chemical

descriptors, size, steric, surface and volume descriptors), • 4D-descriptors (such as those derived from GRID or CoMFA

methods, Volsurf).

The main classes of theoretical molecular descriptors are:

QSAR

More than a century ago, Crum-Brown and Fraser expressed the idea that the physiological action of a substance in a certain biological system (A) was a function (f) of its chemical constitution C:

A = f C

QSAR

More than a century ago, Crum-Brown and Fraser expressed the idea that the physiological action of a substance in a certain biological system (A) was a function (f) of its chemical constitution C:

A = f C

To explain the complex relationships between molecules and observed quantities, two main streams were developed, the first related to the search for relationships between molecular structures and physico-chemical properties (QSPR, Quantitative Structure-Property Relationships) and the second between molecular structures and biological activities (QSAR, Quantitative Structure-Activity Relationships).

QSAR

There is a consensus among current predictive toxicologists that Corwin Hansch is the founder of modern QSAR. In the classic article it was illustrated that, in general, biological activity for a group of ‘congeneric’ chemicals can be described by a comprehensive model:

Log 1/C50 = a π + b ε + cS + d in which C, the toxicant concentration at which an endpoint is manifested (e.g. 50% mortality or effect), is related to a hydrophobicity term, p, an electronic and a steric term, S, (typically Taft’s substituent constant, ES).

Librerie computazionali

CDK Openbabel CACTVS RDKit SVL/MOE



Web: cdk.sf.net Linguaggio: Java (Jython, Groovy) GUI: n.a. Pro: licenza LGPL, Jmol Cons: solo per programmatori 1 AMBIT 2 Bioclipse 3 CDK Taverna 4 CDKDescUI 5 Evince 6 HyperDossier 7 JChemPaint 8 JOELib 9 Jumbo 10 KNIME CDK feature 11 LICSS 12 NMRShiftDB 13 Nomen 14 PaDEL 15 QueryConstructor 16 rcdk 17 SafeBase(TM) 18 Scaffold Hunter 19 SENECA 20 SmileMS 21 Obsolete projects 21.1 XB Edit (Working title) 22 Jmol



Web: openbabel.org Linguaggio: c++, python/java/ perl bindings GUI: si! Pro: flessibilita' Cons:



Web: xemistry.com Linguaggio: Tcl GUI: a pagamento Pro: free for academics, team Cons: Tcl



Web: www.rdkit.org/ Linguaggio: Python, c++ GUI: n.a. Pro: smirks, team Cons: installazione, eta'

Algoritmi: similarity search



Similarity measures, calculations that quantify the similarity of two molecules, and screening, a way of rapidly eliminating molecules as candidates in a substructure search, are both processes that use fingerprints. Fingerprints are a very abstract representation of certain structural features of a molecule


Structural keys

• The presence/absence of each element, or if an element is common (nitrogen, for example), several bits might represent "at least 1 N", "at least 2 N", "at least 4 N", and so forth.

• Unusual or important electronic configurations, such as "sp3 carbon" or "triple-bonded nitrogen."

• Rings and ring systems, such as cyclohexane, pyridine, or napthalene. • Common functional groups, such as alcohols, amines, hydrocarbons, and

so forth. • Functional groups of special importance in a particular database. For

example, a database of organo-metallic molecules might have bits assigned for metal-containing functional groups; in a drug database one might have bits for specific skeletal features such as steroids and barbiturates.


For example, the molecule OC=CN would generate the following patterns: 0-bond paths: C O N 1-bond paths: OC C=C CN 2-bond paths: OC=C C=CN 3-bond paths: OC=CN


10001001010001001010001001110100100010101 001001011100111010010010000100101011010010 Tanimoto index = c/(a + b + c)

Algoritmi: substructure search

Database pubblici

Pubchem Chembl ZINC Vendors vari BindingDB

Librerie chimiche

Problematiche Registrazione Unicità Strumenti

1. filtering 2. normalizzazione 3. generazione dei tautomeri 4. stati ionici 5. unicizzazione 6. generazione dei conformeri

MMsINC 1.0

3.967.056 total compounds 3.297.001 parent compounds 449.482 ionic states 220.573 tautomers 283.464.647 conformers (about 30confs/mol); ordered by empirical E-pot; max 5 confs/mol (= about 4.6 conformers per compound) Final number of conformers: 18.461.878 (for which we have ph4-FP and USR descriptors) Fanton et al, IEEE, 2008; Masciocchi et al, Nucleic acid research, 2009

MMsINC 2.0

92.355.744 compounds from 65 public data sources and commercial catalogs 71.206.303 after single-vendor-based cleaning 42.073.344 unique compounds after redundancy washing 40 M of alternative tautomers 5 M of ionic states Expected number of conformers: about 220 M Average intra-vendor redundancy: 14% 10 vendors with redundancy more than 40%! 4 vendors with redundancy = 0% (small sets, 100 - 2000 comp.)

Ridondanza chimica

L'impatto della tautomeria

Skin DevTox LC50DM LC50FM Carcinogenicity Mutagenicity BCF

0

50000

100000

150000

200000

250000

total pairs taut/neu

different pred

Different AD

diff pred & diff AD

Mimicking peptides... in silico


Floris et al, Nucleic acid research, 2011; Floris M and Moro S, Molecular Informatics, 2011



Screening farmacoforico su larga scala

• 2 minutes for the screening of 1 ph4 model on the CRS4 cluster resources over 17 M of conformers (4 M of commercial compounds)

• Output: SDF with top commercial compounds with highest overlap with the original pharmacophore hypothesis

• Possibility of multiple simultaneous screenings and parameter tuning in a reasonable time lapse

La cassetta degli attrezzi del chemoinformatico

• Python, Java • R, Weka • Openbabel, CDK • Marvin Beans • un database personale • il BlueObelisk

L'importanza di un ambiente di lavoro sano

Ringraziamenti

• Alessandro Bulfone • Prof Stefano Moro • Silvana Urru, Andrea Cristiani, Ricardo Medda, Stefania Olla • i colleghi di Outreach del CRS4 • i colleghi del CNR (IRGB-CNR, Prof F. Cucca) • Marco Fanton, Mattia Sturlese, Fabian Cedrati, Davide Sabbadin • tutti gli altri collaboratori: Alberto Manganaro, Emilio Benfenati, i

colleghi del gruppo ministeriale QSAR-Reach, i colleghi del BlueObeslik, il gruppo TNBC

• la mia famiglia (Lolli, Ric, Vera, nonni assortiti, sorelle varie)

[email protected]

Technology

La chemoinformatica: uno strumento computazionale per la chimica farmaceutica