cheminfo2016 - uspnequimed.iqsc.usp.br/files/2009/09/cheminfo2016.pdf · substâncias zinc ,...

22/09/2016

1

1

UNIVERSIDADE DE SÃO PAULO - USP

Instituto de Química de São Carlos - IQSC

Grupo de Química Medicinal do IQSC/USP

Carlos Montanari([email protected])

cheminfo2016

In memory of

Ex-Pfizer Sandwich, UK

22/09/2016

2

4

22/09/2016

3

Bibliografia[1] Carlos A. Montanari. Química Medicinal: Métodos e Fundamentos em Planejamento de Fármacos.

1a. ed. São Paulo - SP: Editora da Universidade de São Paulo, 2011.

[2] Kowalski, B.R. Chemometrics: Mathematics and Statistics in Chemistry. Ednato Asi Series, D.

Reidel Publ. Co., Dordrecht, 1984

[3] Denis Fourches, Eugene Muratov & Alexander Tropsha. Curation of chemogenomics data. Nature

Chemical Biology 2015, 11, 535

[4] Johannes Kirchmair, Andreas H. Göller, […], Gisbert Schneider Predicting drug metabolism:

experiment and/or computation? Nature Reviews Drug Discovery 2015, 14, 387–404

[5] Jayme L. Dahlin, James Inglese & Michael A. Walters. Mitigating risk in academic preclinical drug

discovery. Nature Reviews Drug Discovery 2015, 14, 279–294

[6] Johann Gasteiger. Cheminformatics: Computing target complexity. Nature Chemistry 2015, 7, 619–

620

[7] Benício B. Neto, Ieda S. Scarminio, Roy, E. Bruns “Como fazer experimentos”, Ed. da UNICAMP,

Campinas, 2001

[8] (a) David B. Searls. Data integration: challenges for drug discovery. Nature Reviews Drug

Discovery, 2005 4, 45–58 (b) Douglas B. Kitchen, Hélène Decornez, […].Jürgen Bajorath. Docking and

scoring in virtual screening for drug discovery: methods and applications. Nature Reviews Drug

Discovery 2004, 3, 935–949

[9] Jason G Lomnitz & Michael A Savageau. Elucidating the genotype–phenotype map by automatic

enumeration and analysis of the phenotypic repertoire. Systems Biology and Applications 2015, 1,

15003

[10] Yi Sun, Zhen Sheng, […], Zhiwei Cao. Combining genomic and network characteristics for

extended capability in predicting synergistic drugs for cancer. Nature Communications 2015, 6, 8481

22/09/2016

4

Desafios da descoberta de fármacos:Encontrar uma substância com valores múltiplos agregados

Fármaco

New drugs?

(Zingales et al. Mem Inst Oswaldo Cruz 2014)

22/09/2016

5

1D

2D

3D

Coligativas

Estereodinâmica

Estereoeletrônica

InteraçãoLigante-receptor

Benznidazole

Fexinidazole

Data continues to grow…

22/09/2016

6

Combinatorial paradigm

(Kihlberg et al. J. Med. Chem. 2016 )

All living organisms: CHONPS 99%+

How many substances can be

synthesized?

(Reymond et al. J. Chem. Info. Model. 2012)

22/09/2016

7

How to discover a new drug?

‘the most fruitful basis for the discovery of a new drug is to

start with an old drug’

Sir James Black

22/09/2016

8

Integrating Technologies...

Virtual

ScreeningChemical space

navigation

1D

2D3D

ColigativasEstereodinâmica

Estereoeletrônica

InteraçãoLigante-receptor

Social moleculesDB

Ro3

X ray (PDB)

Receptor mapping

DockingPharmacophore

hypothesis

Cloning.

Expression.

Isolation.

Purification

(Gaudio e Montanari J. Comput.-Aided Mol. Des. 2002Montanari et al. Bioorg. Med. Chem. 2008)

(Montanari et al. Eur. J. Med. Chem. 2008)

QSAR 2D and 3DMM SAR

Ligand-

similar

Drug-

similar

Drug

Chem-Bio

space

Optimized

PD & PK

Enzyme

kinectics

(MOA)

Synthesis

DrugLigandsTarget

ValidationLeads

Pre- andclinicalphases

Drugapproval

Calorimetry

(MOA/TD signature)

TD

(MOB)(Montanari. et al. J. Med. Chem. 2000; Montanari. et al. Burger’s MedChem 2010. vol.7. 685)

Frag-

similar

22/09/2016

9

Descoberta de novos agentes quimioterápicos por

integração de tecnologias

SELEÇÃO

(nosso sistema)

• Coleção de substâncias

• (DOCAGEM, PCA, SIMCA, ANN, RANDOM FOREST)

• Agrupamento (SIMILARIDADE, HCA)

• Modelos DMPK: Solubilidade, Absorção, Metabolismo, BBB, Toxidez (GRID/VolSurf)

• QSAR 2D e 3D (CoMFA/CoMSIA/HQSAR/ROCS)

• Assinatura molecular

2.000.000

20

Fragmento-similar

Ligante-similar

Fármaco-similar

Efi

ciê

ncia

atô

mic

a e

Lip

ofí

lica d

o l

igan

tre

Coleção de substâncias

ZINC, (in-home DB)

F

i

l

t

e

r

1. MM

2. Lig.-H

3. Rotação

4. NHOH

5. ClogP

Banco de dados filtrado

1. 2D 3D

2. Ad H/Carga

3. Conformeros

O

m

e

g

a

Conformeros

Docagem de

corpo rígidoF

r

e

d

Inibidores

conhecidos

30-60% melhores

pontuados

Alvo

3D

(Glide)

F

L

E

x

-

X

A

-

d

o

c

k

Análise pós-docagem

M1

P1

P2 P3

P4

P5

Candidatos a fármacos

Ensaio

Bioquímico

Ensaio Celular

30-60% melhores

pontuados

Seletivi-

dade

Propriedades fármacosadministrados por via oral

(Yusof & Segall, DDT 2013)

Nossa meta Candidatos a fármacos:

T. cruzi pEC50 > 5 SI > 10 PFI < 8

# anéis Ar < 5 MW < 500 Da

22/09/2016

10

Estratégias de planejamento de fármacos

Sem 3D, sem ligantes

Combichem, VS, HTS

3D, sem ligantes

de novo

Sem 3D, ligantes

Farmacóforos, similaridade 3D

QSAR 3D

3D, ligantes

Planejamento baseado naestrutura

LBVS

TBVS

Hypothesis-driven Molecular Design

(Plowright et al. DDT 2012. 56)

22/09/2016

11

22/09/2016

12

Informações contidas na proteína

Estrutura terciária

Sequência primária

Sequência de “assinaturas”

Localização Genôma/cromossomo

Substratos

Co-fatores

Compartimento celular

Tipo de célula

Tecido

Organismos

Navegação de espaço químico

22/09/2016

13

Similaridade molecular

Descritores físico-químicos e similaridade molecular

22/09/2016

14

Estratégias quimiométricas

Dados Exploração de dados

OtimizaçãoRegressãoClassificação

Análise de agrupamentos

Experimentos

Planejamento experimental

Problema Objetivo

s

Hipótese

s

Modelo qualitativo Modelo quantitativo Modelo empírico

Literatura. Exploração de Dados & Informação

Chemometrics & cheminformatics techniques

Four building blocks

o Methods

•Experimental design

•Pattern Recognition

•Calibration

o Software

o Instrumentation (LC-MS)

o Applications

MOTIVATIONS FOR DESIGN

• Screening

•Saving time

•Quantitative modelling

•Optimisation

PATTERN RECOGNITION

“PCA”, “Discriminant analysis” and “Cluster analysis”

•Exploratory Data Analysis

•Unsupervised Pattern Recognition

•Supervised Pattern Recognition

22/09/2016

15


Decision Trees


ANN

R: A neural network plot created using functions from the neuralnet package. (https://beckmw.wordpress.com)

22/09/2016

16

Physicochemical musings& ChEMBL

MedChemBuzz

1791 oral drugs colour-coded

according to their ADMET score

Same drugs compared with the scores for

the total content of the ChEMBL database

(approximately 200k compounds)

14% of drugs have

ADME/Tox scores > 2

compared with 39% of

ChEMBL molecules

1. Average oral drug potency is approx 50 nM

2. 8% of oral drugs have both MM > 400 and AlogP > 4 (41% of ChEMBL molecules with nanomolar potency)

3. The majority of oral drugs have off-target pharmacological activities (392 oral drugs, N = number of

off-target hits with reported potencies ≤ 1 µM):

MedChemBuzz

4. There was no

clear relationship

between in vitro

potency and

therapeutic dose

https://medchembuzz.wordpress.com/2011/04/05/more-physicochemical-musings/

https://medchembuzz.wordpress.com/


22/09/2016

17

Structural moieties known to form reactive metabolites

MedChemBuzz

Improved PK profile through fluorine and deuterium incorporation

MedChemBuzz



22/09/2016

18

Reducing bioactivationpotential by chemical design

MedChemBuzz

Bioisosteres in Drug Design


Bioisosteres.pdf

22/09/2016

19

Softwares required for solving it, and learning

through them, can be free, or is available through free

web services, or is commercial.

http://www.chemaxon.com : ChemAxon Marvin Beans and JCHEM software for

molecular editing and visualization, conversion of molecular formats,

canonicalization, and generation of hashed fingerprints.

http://cran.r-project.org : R statistical and machine learning software.

http://www.vcclab.org: The VCCLAB web service includes an interface to the

DRAGON program for the generation of molecular descriptors, and to the

CORINA program for the generation of 3D molecular models.

https://www.libreoffice.org/: The free OpenOffice package includes a

spreadsheet application.

http://www.rdkit.org/: RDKit: Open-Source Cheminformatics Software

https://www.knime.org/:Navigate complex data with the agility and

freedom that only an open platform can bring

http://www.eyesopen.com/: molecular modeling and cheminformatics

(NEQUIMED/IQSC/USP license)

https://www.libreoffice.org/

http://www.rdkit.org/

https://www.knime.org/

http://www.eyesopen.com/

22/09/2016

20

Online DBhttp://nequimed.iqsc.usp.br/

http://nequimed.iqsc.usp.br/blogs-medchem/banco-de-

dados/

Structural Bioinformatics

http://www.vls3d.com/index.php

CheminfoBioinfo.pdf

22/09/2016

21

http://www.brenda-enzymes.org/: Brenda, the comprehensive enzyme informationsystem

http://zinc.docking.org/: a free database of commercially-available compounds

for virtual screening

http://www.rcsb.org/pdb/home/home.do: A Structural View of Biology

http://www.drugbank.ca/: a unique bioinformatics and cheminformatics resource

that combines detailed drug data (chemical, pharmacological and pharmaceutical)

http://www.bindingdb.org/bind/index.jsp: a database of measured binding affinities,

focusing chiefly on the interactions of protein considered to be drug-targets

with small, drug-like molecules

http://www.ebi.ac.uk/thornton-srv/databases/cgi-

bin/pdbsum/GetPage.pl?pdbcode=index.html: a pictorial database that provides an

at-a-glance overview of the contents of each 3D structure deposited in the

http://www.molinspiration.com/: offers broad range of cheminformatics software

tools supporting molecule manipulation and processing

http://www.organic-chemistry.org/:offers an overview of recent topics,

interesting reactions, and information on important chemicals for

organic chemists

http://www.cheminformatics.org/datasets/index.shtml: datasets

http://archive.ics.uci.edu/ml/: UC Irvine Machine Learning Repository

https://www.ebi.ac.uk/chembldb/: a manually curated chemical database of

bioactive molecules with drug-like properties

http://www.brenda-enzymes.org/

http://zinc.docking.org/

http://www.rcsb.org/pdb/home/home.do

http://www.drugbank.ca/

http://www.bindingdb.org/bind/index.jsp

http://www.ebi.ac.uk/thornton-srv/databases/cgi-bin/pdbsum/GetPage.pl?pdbcode=index.html

http://www.molinspiration.com/

http://www.organic-chemistry.org/

http://www.cheminformatics.org/datasets/index.shtml

http://archive.ics.uci.edu/ml/

https://www.ebi.ac.uk/chembldb/

22/09/2016

22

Team-Based Learning

http://www.teambasedlearning.org/

Pre-class reading

Chemoinformatics: A view of the field and

current trends in method development

Por: Vogt, Martin; Bajorath, Juergen

BIOORGANIC & MEDICINAL CHEMISTRY

Volume: 20 Edição: 18 Páginas: 5317-

5323 Publicado: SEP 15 2012

Open PHACTS: semantic interoperability

for drug discovery

Por: Williams, Antony J.; Harland, Lee;

Groth, Paul; et al.

DRUG DISCOVERY TODAY Volume: 17

Edição: 21-22 Páginas: 1188-1198

Publicado: NOV 2012

TBL.ppt

22/09/2016

23

ZINC – A Free Database of Commercially

Available Compounds for Virtual Screening

John J. Irwin and Brian K. Shoichet*

J Chem Inf Model. 2005; 45(1): 177–182.

doi: 10.1021/ci049714

ChEMBL: a large-scale bioactivity

database for drug discovery

Anna Gaulton,1 Louisa J. Bellis,1 A.

Patricia Bento,1 Jon Chambers,1 Mark

Davies,1 Anne Hersey,1 Yvonne Light,1

Shaun McGlinchey,1 David Michalovich,2

Bissan Al-Lazikani,3 and John P.

Overington1*

Nucleic Acids Res. 2012 Jan; 40(Database

issue): D1100–D1107.

doi: 10.1093/nar/gkr777

Open Babel: An open chemical toolbox

Por: O'Boyle, Noel M.; Banck, Michael;

James, Craig A.; et al.

JOURNAL OF CHEMINFORMATICS

Volume: 3 Número do artigo: 33

Publicado: OCT 7 2011

DrugBank: a comprehensive resource for

in silico drug discovery and exploration

Por: Wishart, David S.; Knox, Craig; Guo,

An Chi; et al.

NUCLEIC ACIDS RESEARCH Volume:

34 Edição especial: SI Páginas: D668-

D672 Publicado: JAN 1 2006

22/09/2016

24

Virtual screening strategies in drug

discovery

Por: McInnes, Campbell

CURRENT OPINION IN CHEMICAL

BIOLOGY Volume: 11 Edição: 5

Páginas: 494-502 Publicado: OCT 2007

How were new medicines discovered?

Por: Swinney, David C.; Anthony, Jason

NATURE REVIEWS DRUG DISCOVERY

Volume: 10 Edição: 7 Páginas: 507-519

Publicado: JUL 2011

Integrating Everything: The Molecule

Selection Toolkit, a System for Compound

Prioritization in Drug Discovery

David J. Cummins* and Michael A. Bell

Eli Lilly and Company, 893 South Delaware

Street, Indianapolis, Indiana 46285, United

States

J. Med. Chem., 2016, 59 (15), pp 6999–

7010

DOI: 10.1021/acs.jmedchem.5b01338

Drug-like properties and the causes of

poor solubility and poor permeability

Por: Lipinski, CA

JOURNAL OF PHARMACOLOGICAL AND

TOXICOLOGICAL METHODS Volume:

44 Edição: 1 Páginas: 235-249

Publicado: JUL-AUG 2000

Molecular properties that influence the

oral bioavailability of drug candidates

Por: Veber, DF; Johnson, SR; Cheng, HY;

et al.

JOURNAL OF MEDICINAL CHEMISTRY


2623 Publicado: JUN 6 2002

22/09/2016

25

Intramolecular Hydrogen Bonding in

Medicinal Chemistry

Por: Kuhn, Bernd; Mohr, Peter; Stahl,

Martin



2611 Publicado: MAR 25 2010

When barriers ignore the "rule-of-five"

Por: Kramer, Stefanie D.; Aschmann,

Helene E.; Hatibovic, Maja; et al.

ADVANCED DRUG DELIVERY REVIEWS

Volume: 101 Páginas: 62-74 Publicado:

JUN 1 2016

Cell permeability beyond the rule of 5

Por: Matsson, Par; Doak, Bradley C.; Over,

Bjorn; et al.

ADVANCED DRUG DELIVERY REVIEWS

Volume: 101 Páginas: 42-61 Publicado:

JUN 1 2016

How Beyond Rule of 5 Drugs and Clinical

Candidates Bind to Their Targets

Por: Doak, Bradley C.; Zheng, Jie;

Dobritzsch, Doreen; et al.



2327 Publicado: MAR 24 2016

22/09/2016

26

Ligand efficiency: a useful metric for lead

selection

Por: Hopkins, AL; Groom, CR; Alex, A


Edição: 10 Páginas: 430-431 Número do

artigo: PII S1359-6446(04)03106-X

Publicado: MAY 15 2004

Ligand efficiency metrics considered

harmful

Por: Kenny, Peter W.; Leitao, Andrei;

Montanari, Carlos A.

JOURNAL OF COMPUTER-AIDED

MOLECULAR DESIGN Volume: 28

Edição: 7 Páginas: 699-710 Publicado:

JUL 2014

Improving the Plausibility of Success with

Inefficient Metrics

Por: Shultz, Michael D.

ACS MEDICINAL CHEMISTRY LETTERS


Publicado: JAN 2014

22/09/2016

27

ADMET in silico modelling: Towards

prediction paradise?

Por: van de Waterbeemd, H; Gifford, E

NATURE REVIEWS DRUG DISCOVERY


Publicado: MAR 2003

An integrated approach to fragment-

based lead generation: Philosophy,

strategy and case studies from

AstraZeneca's drug discovery programmes

Por: Albert, Jeffrey S.; Blomberg, Niklas;

Breeze, Alexander L.; et al.

CURRENT TOPICS IN MEDICINAL

CHEMISTRY Volume: 7 Edição: 16

Páginas: 1600-1629 Publicado: 2007

Hypothesis driven drug design:

improving quality and effectiveness of the

design-make-test-analyse cycle

Por: Plowright, Alleyn T.; Johnstone, Craig;

Kihlberg, Jan; et al.


Edição: 1-2 Páginas: 56-62 Publicado:

JAN 2012

Virtual screening of chemical libraries

Por: Shoichet, BK

NATURE Volume: 432 Edição: 7019

Páginas: 862-865 Publicado: DEC 16

2004

22/09/2016

28

BindingDB: a web-accessible database of

experimentally determined protein-ligand

binding affinities

Por: Liu, Tiqing; Lin, Yuhmei; Wen, Xin; et

al.

NUCLEIC ACIDS RESEARCH Volume:

35 Edição especial: SI Páginas: D198-

D201 Publicado: JAN 2007

The Cambridge Structural Database in

Retrospect and Prospect

Por: Groom, Colin R.; Allen, Frank H.

ANGEWANDTE CHEMIE-

INTERNATIONAL EDITION Volume: 53

Edição: 3 Páginas: 662-671 Publicado:

JAN 13 2014

cheminfo2016 - uspnequimed.iqsc.usp.br/files/2009/09/cheminfo2016.pdf · substâncias zinc ,...

Documents