Transcript Slide 1
In the Name of God
Progress of Chemometrics in Iran
Mehdi Jalali-Heravi
February 2009
8th Iranian workshop of Chemometrics
7-9 February 2009
First paper of Chemometrics in Iran
8th Iranian workshop of Chemometrics
7-9 February 2009
Chemometrics Events
Iranian Chemometrics Committee under Iranian Chemical
Society, 2000
First Chemometrics seminar held in Arak, 2006
Seven annual Iranian Chemometrics workshops
8th Iranian workshop of Chemometrics
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Iranian workshops of Chemometrics
1st (2001)
2nd (2002) : PCA, PLS, ITTFA, MCR
3rd (2003): PCA, QSAR, Net Analytical signal
4th (2004) : Three-way analysis, EFA, Factor selection methods
5th (2006): Rank annihilation based methods (RAFA, GRAM), QSAR
6th (2007): Model-based analysis
7th (2008): Model-free analysis
8th (2009): QSAR
8th Iranian workshop of Chemometrics
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Paul Geladi, Sweden
Richard G. Brereton, England
Roma Tauler, Spain
Marcel Maeder, Australia
8th Iranian workshop of Chemometrics
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Roberto Todeschini
Davide Ballabio
8th Iranian workshop of Chemometrics
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8th Iranian workshop of Chemometrics
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Participants in Iranian Workshop of Chemometrics
8th Iranian workshop of Chemometrics
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Chemometrics in Iran
MVC: 33.1
8th Iranian workshop of Chemometrics
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Quantitative-Structure Activity Relationship (QSAR)
Quantitative Structure Property/Activity Relationship is the process by which chemical
structure is quantitatively correlated with a well defined process, such as chemical
property/biological activity.
Descriptors calculation
Data compression
Model construction and validation
MLR, PLS, PCR
KPLS, ANN, GA-ANN, ANFIS
CART, SVM, MARS
8th Iranian workshop of Chemometrics
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Quantitative Structure-Activity Relationship (QSAR) Models
Set of Compounds
Activity Data (Y)
Molecular Descriptors (Xi)
QSAR
Y = f(Xi)
Prediction
Interpretation
Types of Molecular Descriptors
O
Constitutional, Topological
*
O
CH2
CH2
O
O
CH2 CH2
NH
CH
CH2
O
2-D structural formula
O
CH2
OH
Geometrical
3-D shape and structure
Quantum Chemical
Electrostatic
Hybrid descriptors
8th Iranian workshop of Chemometrics
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O
n
*
8th Iranian workshop of Chemometrics
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QSAR and Drug Design
Compounds + biological activity
QSAR
New compounds with
improved biological activity
8th Iranian workshop of Chemometrics
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Drug Discovery Process
Time and Money
50,000 - 5,000,000 compounds are
often screened to find a single drug
>1,000 “hits”
12 “leads”
6 drug candidates
Discovery & Preclinical trials
Clinical trials: Phase I, Phase II, Phase III
12 to 24 years
$300 to >$500 million
1 drug
Application of Cheminformatics
Screening
• Substructure
searching
• Similarity
comparison
• Pharmacophore
matching
Classification
Prediction
Unsupervised Learning
• Principal Components
Analysis
• Cluster Analysis
QSAR
• MLR
• PLS
• ANN
Supervised Learning
• k-Nearest Neighbors
• SIMCA
• Neural Nets (ANN)
3D-QSAR
• CoMFA
• Catalyst
8th Iranian workshop of Chemometrics
Introduction to QSAR and Molecular Descriptors
Model Development and Validation
Distance and Correlation Measures between Sets of Variables
MOLMAP: a Chemometric Strategy Based on the Kohonen Maps
Chance Correlation
Kohonen Maps and Counter-Propagation Artificial Neural Networks
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Is there a future for Chemometrics?
Editorial, Chemom. Intell. Lab. Syst., 91 (2008) 99-100
Most of the pioneers of Chemometrics have retired or have passed away
All of the original goals of Chemometrics have been reached
Chemometrics is in danger of being absorbed by *omics
Lack of interest in the physical sciences for the last decade
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What can we do to increase the popularity of
Chemometrics?
Explain the past of the Chemometrics and its achievement to newcomers
Reevaluate the Chemometrics curriculum
These could be done in the format of sort introductions,
holding workshops and brainstorming sessions
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Herbal Medicine in Iran
8th Iranian workshop of Chemometrics
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Acknowledgements
• Administration of IASBS
• Colleagues of Chemistry
Department of IASBS
• Dr. H. Abdollahi
• Dr. M. Kompany-Zareh
• My students
8th Iranian workshop of Chemometrics
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