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Ignasi Belda, PhD CEO
1st of February 2013
Jornada TOX®
Business lines
Intelligent Discovery
We carry out computational chemistry projects using our self-developed and third party technologies for drug discovery, cosmetics and nutraceuticals.
Intelligent Software
We offer advanced software development solutions for companies and institutions working in life sciences.
Intelligent Knowledge
We commercialize third party software application for knowledge management focusing on life sciences.
Collaborations:
Synthesis and Medicinal Chemistry Software Partners
Barcelona Science Park Spain
Technologie Park Heidelberg Germany
Offices: Clients:
• Pharmaceutical companies
• Biotech companies
• Life Sciences institutions:
Hospitals, Universities,
Technological Transfer Offices
BioPark Hertfordshire United Kingdom
185 Alewife Brook Parkway Cambridge, MA USA
Markets:
• Europe
• USA
• South America: Mexico, Brazil
• Asia: Korea
Type of Projects
> 100 Research Projects in 5 years
Type of targets
> 100 Research Projects in 5 years
Therapeutic Areas
Identification of new active compounds Determination of inhibitors Identification of off-targets Selectivity Studies
Drug Reprofiling Identification of back-ups
Determination of mechanism of action
Computer-aided Hit to Lead optimization ADME/Tox prediction Solving physicochemical problems
Extension of patent protection
Allosterics Prof. Alejandro Pankovich, Xavier Daura Universitat Autònoma de Barcelona
Molecular Dynamics Pharmacophor Modeling Bio-informatic tools
PREDICTIVE TOXICOLOGY/PHARMACOLOGY
Initiatives Computational Toxicology Research Program (CompTox) USA – environmental protection agency (http://www.epa.gov/heasd/edrb/comptox.html)
Predictive Toxicology Europe – joint research center (http://ihcp.jrc.ec.europa.eu/our_labs/predictive_toxicology)
Computational toxicology at the European Commission's Joint Research Centre Europe Union
The methods and tools of computational toxicology form an essential and
integrating pillar in the new paradigm of predictive toxicology, which seeks
to develop more efficient and effective means of assessing chemical
toxicity, while also reducing animal testing.*
*Mostrag-Szlichtyng A., Zaldivar Comenges JM, Worth AP. Computational toxicology at the European Commission's Joint Research Centre (2010) Expert Opin Drug Metab Toxicol, 6(7), 785-92.
Biological molecules as Sugars, DNA & Proteins
Molecules used as pharmaceuticals/active ingredients
3-D structure Primary sequence
3-D structure 2-D structure
Biological Function
hERG & KCQN1 is responsible for Cardiovascular Toxicity
Molecules with measured Cardiovascular Toxicity
3-D structure
3-D structure 2-D structure
Cardiovascular Toxicity
1 O Trott, AJ Olson J Comput Chem. 2010, 31, 455–461. 2 G Morris, D Goodsell, R Halliday, R Huey, W Hart, R Belew, A Olson J Comput Chem. 1998, 19, 1639–62.
Receptor-based Virtual Screening
Only receptor’s information is needed
Determines Binding Energy and Binding Constants Kd (mM, μM and nM)
Obtains Structural Data
High throughput screening
Based on Docking Docking algorithms based on Vina1 & Autodock 4.22
Binding Energies & Binding Modes
Determination of inhibitors Hit to lead optimization Design more potent ligands Drug Reprofiling Determination of MOA
DISCOVERY PROJECTS
Biological Target Receptor
+ Molecules
HMG-CoA Reductase
Active
Inactive
-13kcal/mol Expected binding mode -6kcal/mol Other binding mode
QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIP
423 358 284 …
7 3 0 …
110 60 160 …
…. … … … …
Descriptors
MW
RotBond
PSA
Mathematical tools
PLS
hERG 3,1 6,7 4,3 …
Model
hERG 6.0
Pred. Func. = w1Des1 + w2Des2 + …
VALIDITY OF QSAR MODEL
423 358 284 …
7 3 0 …
110 60 160 …
…. … … … …
Descriptors
MW
RotBond
PSA
Mathematical tools
PLS
IC50 1 16 4 …
Model
IC
50(p
red
)
IC50(pred)
Based on different descriptors & algorithms Descriptors: Property based Circular fingerprints (ECFP2, Molprint2D3) Fragments (Lingo4) 2D molecular fields (GRIND1) Mathematical tools: PLS SVM Bayesian PCA
423 358 284 …
7 3 0 …
110 60 160 …
…. … … … …
MW
RotBond
PSA
1 M Pastor, G Cruciani, I McLay, S Pickett, S Clementi J. Med. Chem. 2000, 43, 3233-43.
2 D Rogers, M Hahn J. Chem. Inf. Model. 2010, 50, 742-54.
3 A Bender, HY Mussa, RC Glen J. Chem. Inf. Comput. Sci. 2003, 44, 170-88.
4 D Vidal, M Thormann, M Pons J. Chem. Inf. Model. 2005, 45, 386-93.
3,1
5,8
6,7
4,5
4,3
5,8
hERG & KCQN1
6,0
Drug Reprofiling Macromolecular Modeling
Determination of MOA
Hit to Lead
Hit Identification
DB and Collaborative Tools Management
Training on Macromolecular Modeling
Parc Científic de Barcelona C/ Baldiri Reixac, 4-8 08028 Barcelona Spain T: +34 934 034 551
Sales & Business Development Department Jascha Blobel, PhD [email protected] Anna Serra, PhD [email protected] Irene Meliciani, PhD [email protected]
Technologie Park Heidelberg Im Neuenheimer Feld 582 69120 Heidelberg Germany T: +49 (0) 6221 5025716
www.intelligentpharma.com
BioPark Broadwater Road, Welwyn Garden City Hertfordshire AL7 3AX, United Kingdom T: +44 (0) 1707 356100
USA 185 Alewife Brook Parkway, #410 Cambridge, MA 02138