cheminfo2016 - USPnequimed.iqsc.usp.br/files/2009/09/Cheminfo2016.pdf · substâncias ZINC ,...
Transcript of cheminfo2016 - USPnequimed.iqsc.usp.br/files/2009/09/Cheminfo2016.pdf · substâncias ZINC ,...
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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
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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
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Desafios da descoberta de fármacos:Encontrar uma substância com valores múltiplos agregados
Fármaco
New drugs?
(Zingales et al. Mem Inst Oswaldo Cruz 2014)
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1D
2D
3D
Coligativas
Estereodinâmica
Estereoeletrônica
InteraçãoLigante-receptor
Benznidazole
Fexinidazole
Data continues to grow…
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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)
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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
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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
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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
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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
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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)
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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
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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
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Chemometrics & cheminformatics techniques
Decision Trees
Chemometrics & cheminformatics techniques
ANN
R: A neural network plot created using functions from the neuralnet package. (https://beckmw.wordpress.com)
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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
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Structural moieties known to form reactive metabolites
MedChemBuzz
Improved PK profile through fluorine and deuterium incorporation
MedChemBuzz
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Reducing bioactivationpotential by chemical design
MedChemBuzz
Bioisosteres in Drug Design
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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)
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Online DBhttp://nequimed.iqsc.usp.br/
http://nequimed.iqsc.usp.br/blogs-medchem/banco-de-
dados/
Structural Bioinformatics
http://www.vls3d.com/index.php
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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
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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
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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
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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
Volume: 45 Edição: 12 Páginas: 2615-
2623 Publicado: JUN 6 2002
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Intramolecular Hydrogen Bonding in
Medicinal Chemistry
Por: Kuhn, Bernd; Mohr, Peter; Stahl,
Martin
JOURNAL OF MEDICINAL CHEMISTRY
Volume: 53 Edição: 6 Páginas: 2601-
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.
JOURNAL OF MEDICINAL CHEMISTRY
Volume: 59 Edição: 6 Páginas: 2312-
2327 Publicado: MAR 24 2016
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Ligand efficiency: a useful metric for lead
selection
Por: Hopkins, AL; Groom, CR; Alex, A
DRUG DISCOVERY TODAY Volume: 9
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
Volume: 5 Edição: 1 Páginas: 2-5
Publicado: JAN 2014
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ADMET in silico modelling: Towards
prediction paradise?
Por: van de Waterbeemd, H; Gifford, E
NATURE REVIEWS DRUG DISCOVERY
Volume: 2 Edição: 3 Páginas: 192-204
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.
DRUG DISCOVERY TODAY Volume: 17
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
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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