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Chemoinformatics: a Hot Topic inChemoinformatics: a Hot Topic in
Distance EducationDistance Education
Zarrin Es’haghiZarrin Es’haghi
Department of Chemistry, Faculty of SciencesDepartment of Chemistry, Faculty of Sciences
Payame Noor University, Mashhad, IranPayame Noor University, Mashhad, Iran
E-Mail: z_eshaghi@pnu.ac.irE-Mail: z_eshaghi@pnu.ac.ir
Payame Noor University
Chemoinformatics: a Hot Topic inChemoinformatics: a Hot Topic in
Distance EducationDistance Education
Zarrin Es’haghiZarrin Es’haghi
Department of Chemistry, Faculty of SciencesDepartment of Chemistry, Faculty of Sciences
Payame Noor University, Mashhad, IranPayame Noor University, Mashhad, Iran
E-Mail: z_eshaghi@pnu.ac.irE-Mail: z_eshaghi@pnu.ac.ir
Payame Noor University
3
Chemoinformatics
 Chem(o)informatics is a generic
term that encompasses the;
 design, creation, organization,design, creation, organization,
management, analysis, visualizationmanagement, analysis, visualization
and use of chemical information.and use of chemical information.
 In fact, Chemoinformatics is the
application of informatics methods
to solve chemical problems.
What is Chemoinformatics?What is Chemoinformatics?
Chemoinformatics,
Cheminformatics, Chemical
Informatics, Computational
Chemistry, …
“the set of computer algorithms
and tools to store and analyse
chemical data in the context
of drug discovery and design
projects etc…”
4
What is Chemoinformatics?What is Chemoinformatics?
“the mixing of information resources to
transform data into information and
information into knowledge, for the
intended purpose of making better
decisions faster in the arena of drug lead
identification and optimizaton”
5
What is Chemoinformatics?What is Chemoinformatics?
“chemoinformatics encompasses the
design, creation, organisation,
management, retrieval,analysis,
dissemination, visualization and use
of chemical information”
6
Chemoinformatics : a new scienceChemoinformatics : a new science)?()?(
7
Why do we needWhy do we need
ChemoinformaticsChemoinformatics??
To handle large amounts of information
To move chemistry into the computer age
To move from data to knowledge.
9
And last but not least:
•To get funding (bioinformatics is
doing well currently, whereas
computational chemistry seems
to be lagging behind).
•Data information knowledge
•measurements/calculations
Why do we need ChemoinformaticsWhy do we need Chemoinformatics?
10
How do we learn?How do we learn?
Inductive learning vs..Inductive learning vs..
Deductive learningDeductive learning
Inductive learning vs. DeductiveInductive learning vs. Deductive
learninglearning
Deductive learning:Deductive learning:
A fundamental theory exists which allows us
to calculate properties and predict the
behavior of molecules.
The fundamental theory for Chemistry is
quantum mechanics.
Inductive learning vs. Deductive learningInductive learning vs. Deductive learning
Inductive learning = Learning from examplesInductive learning = Learning from examples
13
General scheme for inductive learningGeneral scheme for inductive learning
14
The fundamental tasks of a chemistThe fundamental tasks of a chemist
property prediction, synthesis, design, reaction prediction, and
structure elucidation
15
The realm of ChemoinformaticsThe realm of Chemoinformatics
a) Representing Chemical
Compounds
b) Searching Chemical
Structures
c) Similarity Searches
d) Relating structure to
properties with models
16
Machine Learning MethodsMachine Learning Methods
• Important role in chemoinformaticsImportant role in chemoinformatics
–For example, it is usually difficult to
predict which types of descriptors are
most suitable for a given search,
classification.
• Therefore, machine learning techniques are
often used to facilitate descriptor selection
17
Machine Learning MethodsMachine Learning Methods
– Genetic algorithms– Genetic algorithms
• Different parameters and model solutions to given
problems are encoded in a chromosome and subjected to
random variation, thus generating a population.
• Solutions provided by these chromosomes are evaluated by
fitness function that assign high scores to desired results.
• Chromosomes yielding best intermediate solutions are
subjected to mutation and crossover operation that
correspond to random genetic mutations and gene
recombination events.
• The resulting modified chromosomes represent the next
generation and the process is continued until the obtained
results meet a satisfactory convergence criterion
18
Quantitative Structure ActivityQuantitative Structure Activity
Relationship Analysis (QSAR)Relationship Analysis (QSAR)
Goal :Goal : Evaluation of molecular features that
determine biological activity and the
prediction of compound potency as a
function of structural modification
19
Virtual Screening and Compound FilteringVirtual Screening and Compound Filtering
VS(Virtual Screening)
- the process of screening large databases on the
computer for molecules having desired
properties and biological activity.
A major application of VS techniques is the
identification of novel active molecules in large
compound databases.
20
Impact of new technology on drug discoveryImpact of new technology on drug discovery
• The last few years have seen a number of
“revolutionary” new technologies:
– Gene chips, genomics and HGP
– Bioinformatics & Molecular biology
– More protein structures
– High-throughput screening & assays
– Virtual screening and library design
– Combinatorial chemistry
– Other computational methods
• How do we make it all work for us?
21
How Chemoinformatics can help outHow Chemoinformatics can help out
Producing and manage information for metrics
to reduce risk, e.g.
–Virtual screening
–Library design,
–Docking
–Cost/benefit analysis
• Making information available at the right time
and the right place Needs to be integrated
into processes
22
Software relevance:Software relevance:
Bridge between computation & scienceBridge between computation & science
clustering
sim. searching
activity models
scaffold detection
docking
logp calculation
tasks:
“doing a cluster
analysis”
“identifying
activity-related
fragments”
tools
chemoinformatics science
tasks:
work out a chemical
synthesis
choose good reagents
try and document some
reactions
goals:
e.g. produce compounds
that have high biological
activity
?
23
Chemoinformatics: WChemoinformatics: Where It Hashere It Has
Come From, Where It Is Now AndCome From, Where It Is Now And
Where It Is GoingWhere It Is Going
OverviewOverview
From Chemical Information ToFrom Chemical Information To
ChemoinformaticsChemoinformatics
– Integration with techniques from molecular
modeling
– Developments in computer hardware and
software
– Data explosion arising from developments in
combinatorial chemistry and high-throughput
screening
25
Molecular ModellingMolecular Modelling
• Positioning of a putative ligand into a
protein’s active site, first attempted
by the DOCK program (UCSF, 1982)
• Initially restricted to rigid ligands and
rigid proteins: current programs
permit some degree of flexibility
• Use in structure-based design
– Move from docking a single
ligand to sequential docking of
large datasets
26
27
Graph TheoryGraph Theory
• Graph theory is a branch of mathematics that
considers sets of objects, called nodesnodes, and
the relationships, called edgesedges, between pairs
of these objects
• The definition is completely general, allowing
graphs to be used in many different
application domains as long as an appropriate
representation can be derived
28
Examples Of GraphsExamples Of Graphs
29
Proposed courses for a DistanceProposed courses for a Distance
learning Programlearning Program
• Chemoinformatics Virtual ClassroomChemoinformatics Virtual Classroom
30
At present there are no specific software tools for
chemical information training in the IranIran.
A number of commercial software products used in
the pharmaceutical and biotechnology industry are
either too expensive or of limited utility for training in
either academic or business settings.
By employing distance learningdistance learning through a web
delivery system, the training software will provide an
effective, low cost solution for academic institutions,
whether they are offering a single course to students
in a remote setting, or an entire program in
cheminformatics.
31
32
In addition, such training tools will be
very useful in industry settings with local
area networks, where in a multidiscipline
setting individuals need to receive
training on the concepts employed by
industrial chemoinformatics software's.
Chemoinformatics: aimsChemoinformatics: aims
• Develop an awareness of Informatics Management
techniques used in the design and implementation of
chemoinformatics systems
• Enable students to demonstrate skills learned by
carrying out a small-scale industrially relevant
chemoinformatics research project
• Basic structure
– Three semesters of taught modules
– One semester dissertation working at the site of
one of the companies supporting the programme
33
Proposed Cources ;Proposed Cources ;
• An introduction to chemoinformatics.
– Chemoinformatics (Fundamental)
– Information Systems Modelling
– Information Storage and Retrieval
– Foundations of Object-Oriented Programming
34
35
• Chemoinformatics (Advance ; more
programming)
• Database Design
• Research Methods and Dissertation
Preparation
• Two from a range of elective modules,
including Molecular Modelling
(Chemistry), Healthcare Information...etc
ConclusionsConclusions
Distance learning is becoming increasingly accepted by
the professional bodies. The image of distance learning
would need to be improved. The concept would have to
be well presented as something new, modern and
completely different from the old-style correspondence
courses.
Chemoinformatics can step in to assist in this effort. And
it can do so in all fields of chemistry, inorganic, analytical,
organic, physical, medicinal, and bio-chemistry. And it
can reach beyond chemistry provide methods and
information that can be used in biology, medicine, and
physics.
36
ReferencesReferences
Journal Articles
• Y. M. Alvarez-Ginarte,et al. Bioorganic &
Medicinal Chemistry 16 (2008) 6448–6459.
• S. D. Lindell, L. C. Pattenden, J. Shannon,
Bioorganic & Medicinal Chemistry 17 (2009)
4035–4046.
• J. Gasteiger, Chemometrics and Intelligent
Laboratory Systems 82 (2006) 200 – 209.
37
ReferencesReferences
Books
• An introduction to chemoinformatics. A.R. Leach & V.J. Gillet.
Kluwer, 2003.
• Chemoinformatics – A textbook. J. Gasteiger & T. Engel (eds).
Wiley-VCH, 2003.
• Handbook of chemoinformatics. J. Gasteiger (ed.). Wiley-VCH,
2003.
• Chemoinformatics: Concepts, Methods, and Applications
(Methods in Molecular
Biology). J. Bajorath. Humana Press, 2004.
• Molecular Modelling Principles and Applications. A. R. Leach.
Longman, 1996.
38
39
40
41
Chemoinformatics
 Chem(o)informatics is a generic
term that encompasses the;
 design, creation, organization,design, creation, organization,
management, analysis, visualizationmanagement, analysis, visualization
and use of chemical information.and use of chemical information.
 In fact, Chemoinformatics is the
application of informatics methods
to solve chemical problems.
What is Chemoinformatics?What is Chemoinformatics?
Chemoinformatics,
Cheminformatics, Chemical
Informatics, Computational
Chemistry, …
“the set of computer algorithms
and tools to store and analyse
chemical data in the context
of drug discovery and design
projects etc…”
42
What is Chemoinformatics?What is Chemoinformatics?
“the mixing of information resources to
transform data into information and
information into knowledge, for the
intended purpose of making better
decisions faster in the arena of drug lead
identification and optimizaton”
43
What is Chemoinformatics?What is Chemoinformatics?
“chemoinformatics encompasses the
design, creation, organisation,
management, retrieval,analysis,
dissemination, visualization and use
of chemical information”
44
Chemoinformatics : a new scienceChemoinformatics : a new science)?()?(
45
Why do we needWhy do we need
ChemoinformaticsChemoinformatics??
To handle large amounts of information
To move chemistry into the computer age
To move from data to knowledge.
47
And last but not least:
•To get funding (bioinformatics is
doing well currently, whereas
computational chemistry seems
to be lagging behind).
•Data information knowledge
•measurements/calculations
Why do we need ChemoinformaticsWhy do we need Chemoinformatics?
48
How do we learn?How do we learn?
Inductive learning vs..Inductive learning vs..
Deductive learningDeductive learning
Inductive learning vs. DeductiveInductive learning vs. Deductive
learninglearning
Deductive learning:Deductive learning:
A fundamental theory exists which allows us
to calculate properties and predict the
behavior of molecules.
The fundamental theory for Chemistry is
quantum mechanics.
Inductive learning vs. Deductive learningInductive learning vs. Deductive learning
Inductive learning = Learning from examplesInductive learning = Learning from examples
51
General scheme for inductive learningGeneral scheme for inductive learning
52
The fundamental tasks of a chemistThe fundamental tasks of a chemist
property prediction, synthesis, design, reaction prediction, and
structure elucidation
53
The realm of ChemoinformaticsThe realm of Chemoinformatics
a) Representing Chemical
Compounds
b) Searching Chemical
Structures
c) Similarity Searches
d) Relating structure to
properties with models
54
Machine Learning MethodsMachine Learning Methods
• Important role in chemoinformaticsImportant role in chemoinformatics
–For example, it is usually difficult to
predict which types of descriptors are
most suitable for a given search,
classification.
• Therefore, machine learning techniques are
often used to facilitate descriptor selection
55
Machine Learning MethodsMachine Learning Methods
– Genetic algorithms– Genetic algorithms
• Different parameters and model solutions to given
problems are encoded in a chromosome and subjected to
random variation, thus generating a population.
• Solutions provided by these chromosomes are evaluated by
fitness function that assign high scores to desired results.
• Chromosomes yielding best intermediate solutions are
subjected to mutation and crossover operation that
correspond to random genetic mutations and gene
recombination events.
• The resulting modified chromosomes represent the next
generation and the process is continued until the obtained
results meet a satisfactory convergence criterion
56
Quantitative Structure ActivityQuantitative Structure Activity
Relationship Analysis (QSAR)Relationship Analysis (QSAR)
Goal :Goal : Evaluation of molecular features that
determine biological activity and the
prediction of compound potency as a
function of structural modification
57
Virtual Screening and Compound FilteringVirtual Screening and Compound Filtering
VS(Virtual Screening)
- the process of screening large databases on the
computer for molecules having desired
properties and biological activity.
A major application of VS techniques is the
identification of novel active molecules in large
compound databases.
58
Impact of new technology on drug discoveryImpact of new technology on drug discovery
• The last few years have seen a number of
“revolutionary” new technologies:
– Gene chips, genomics and HGP
– Bioinformatics & Molecular biology
– More protein structures
– High-throughput screening & assays
– Virtual screening and library design
– Combinatorial chemistry
– Other computational methods
• How do we make it all work for us?
59
How Chemoinformatics can help outHow Chemoinformatics can help out
Producing and manage information for metrics
to reduce risk, e.g.
–Virtual screening
–Library design,
–Docking
–Cost/benefit analysis
• Making information available at the right time
and the right place Needs to be integrated
into processes
60
Software relevance:Software relevance:
Bridge between computation & scienceBridge between computation & science
clustering
sim. searching
activity models
scaffold detection
docking
logp calculation
tasks:
“doing a cluster
analysis”
“identifying
activity-related
fragments”
tools
chemoinformatics science
tasks:
work out a chemical
synthesis
choose good reagents
try and document some
reactions
goals:
e.g. produce compounds
that have high biological
activity
?
61
Chemoinformatics: WChemoinformatics: Where It Hashere It Has
Come From, Where It Is Now AndCome From, Where It Is Now And
Where It Is GoingWhere It Is Going
OverviewOverview
From Chemical Information ToFrom Chemical Information To
ChemoinformaticsChemoinformatics
– Integration with techniques from molecular
modeling
– Developments in computer hardware and
software
– Data explosion arising from developments in
combinatorial chemistry and high-throughput
screening
63
Molecular ModellingMolecular Modelling
• Positioning of a putative ligand into a
protein’s active site, first attempted
by the DOCK program (UCSF, 1982)
• Initially restricted to rigid ligands and
rigid proteins: current programs
permit some degree of flexibility
• Use in structure-based design
– Move from docking a single
ligand to sequential docking of
large datasets
64
65
Graph TheoryGraph Theory
• Graph theory is a branch of mathematics that
considers sets of objects, called nodesnodes, and
the relationships, called edgesedges, between pairs
of these objects
• The definition is completely general, allowing
graphs to be used in many different
application domains as long as an appropriate
representation can be derived
66
Examples Of GraphsExamples Of Graphs
67
Proposed courses for a DistanceProposed courses for a Distance
learning Programlearning Program
• Chemoinformatics Virtual ClassroomChemoinformatics Virtual Classroom
68
At present there are no specific software tools for
chemical information training in the IranIran.
A number of commercial software products used in
the pharmaceutical and biotechnology industry are
either too expensive or of limited utility for training in
either academic or business settings.
By employing distance learningdistance learning through a web
delivery system, the training software will provide an
effective, low cost solution for academic institutions,
whether they are offering a single course to students
in a remote setting, or an entire program in
cheminformatics.
69
70
In addition, such training tools will be
very useful in industry settings with local
area networks, where in a multidiscipline
setting individuals need to receive
training on the concepts employed by
industrial chemoinformatics software's.
Chemoinformatics: aimsChemoinformatics: aims
• Develop an awareness of Informatics Management
techniques used in the design and implementation of
chemoinformatics systems
• Enable students to demonstrate skills learned by
carrying out a small-scale industrially relevant
chemoinformatics research project
• Basic structure
– Three semesters of taught modules
– One semester dissertation working at the site of
one of the companies supporting the programme
71
Proposed Cources ;Proposed Cources ;
• An introduction to chemoinformatics.
– Chemoinformatics (Fundamental)
– Information Systems Modelling
– Information Storage and Retrieval
– Foundations of Object-Oriented Programming
72
73
• Chemoinformatics (Advance ; more
programming)
• Database Design
• Research Methods and Dissertation
Preparation
• Two from a range of elective modules,
including Molecular Modelling
(Chemistry), Healthcare Information...etc
ConclusionsConclusions
Distance learning is becoming increasingly accepted by
the professional bodies. The image of distance learning
would need to be improved. The concept would have to
be well presented as something new, modern and
completely different from the old-style correspondence
courses.
Chemoinformatics can step in to assist in this effort. And
it can do so in all fields of chemistry, inorganic, analytical,
organic, physical, medicinal, and bio-chemistry. And it
can reach beyond chemistry provide methods and
information that can be used in biology, medicine, and
physics.
74
ReferencesReferences
Journal Articles
• Y. M. Alvarez-Ginarte,et al. Bioorganic &
Medicinal Chemistry 16 (2008) 6448–6459.
• S. D. Lindell, L. C. Pattenden, J. Shannon,
Bioorganic & Medicinal Chemistry 17 (2009)
4035–4046.
• J. Gasteiger, Chemometrics and Intelligent
Laboratory Systems 82 (2006) 200 – 209.
75
ReferencesReferences
Books
• An introduction to chemoinformatics. A.R. Leach & V.J. Gillet.
Kluwer, 2003.
• Chemoinformatics – A textbook. J. Gasteiger & T. Engel (eds).
Wiley-VCH, 2003.
• Handbook of chemoinformatics. J. Gasteiger (ed.). Wiley-VCH,
2003.
• Chemoinformatics: Concepts, Methods, and Applications
(Methods in Molecular
Biology). J. Bajorath. Humana Press, 2004.
• Molecular Modelling Principles and Applications. A. R. Leach.
Longman, 1996.
76
77
78

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Chemoinformatic

  • 1. Chemoinformatics: a Hot Topic inChemoinformatics: a Hot Topic in Distance EducationDistance Education Zarrin Es’haghiZarrin Es’haghi Department of Chemistry, Faculty of SciencesDepartment of Chemistry, Faculty of Sciences Payame Noor University, Mashhad, IranPayame Noor University, Mashhad, Iran E-Mail: z_eshaghi@pnu.ac.irE-Mail: z_eshaghi@pnu.ac.ir Payame Noor University
  • 2. Chemoinformatics: a Hot Topic inChemoinformatics: a Hot Topic in Distance EducationDistance Education Zarrin Es’haghiZarrin Es’haghi Department of Chemistry, Faculty of SciencesDepartment of Chemistry, Faculty of Sciences Payame Noor University, Mashhad, IranPayame Noor University, Mashhad, Iran E-Mail: z_eshaghi@pnu.ac.irE-Mail: z_eshaghi@pnu.ac.ir Payame Noor University
  • 3. 3 Chemoinformatics  Chem(o)informatics is a generic term that encompasses the;  design, creation, organization,design, creation, organization, management, analysis, visualizationmanagement, analysis, visualization and use of chemical information.and use of chemical information.  In fact, Chemoinformatics is the application of informatics methods to solve chemical problems.
  • 4. What is Chemoinformatics?What is Chemoinformatics? Chemoinformatics, Cheminformatics, Chemical Informatics, Computational Chemistry, … “the set of computer algorithms and tools to store and analyse chemical data in the context of drug discovery and design projects etc…” 4
  • 5. What is Chemoinformatics?What is Chemoinformatics? “the mixing of information resources to transform data into information and information into knowledge, for the intended purpose of making better decisions faster in the arena of drug lead identification and optimizaton” 5
  • 6. What is Chemoinformatics?What is Chemoinformatics? “chemoinformatics encompasses the design, creation, organisation, management, retrieval,analysis, dissemination, visualization and use of chemical information” 6
  • 7. Chemoinformatics : a new scienceChemoinformatics : a new science)?()?( 7
  • 8. Why do we needWhy do we need ChemoinformaticsChemoinformatics??
  • 9. To handle large amounts of information To move chemistry into the computer age To move from data to knowledge. 9
  • 10. And last but not least: •To get funding (bioinformatics is doing well currently, whereas computational chemistry seems to be lagging behind). •Data information knowledge •measurements/calculations Why do we need ChemoinformaticsWhy do we need Chemoinformatics? 10
  • 11. How do we learn?How do we learn? Inductive learning vs..Inductive learning vs.. Deductive learningDeductive learning
  • 12. Inductive learning vs. DeductiveInductive learning vs. Deductive learninglearning Deductive learning:Deductive learning: A fundamental theory exists which allows us to calculate properties and predict the behavior of molecules. The fundamental theory for Chemistry is quantum mechanics.
  • 13. Inductive learning vs. Deductive learningInductive learning vs. Deductive learning Inductive learning = Learning from examplesInductive learning = Learning from examples 13
  • 14. General scheme for inductive learningGeneral scheme for inductive learning 14
  • 15. The fundamental tasks of a chemistThe fundamental tasks of a chemist property prediction, synthesis, design, reaction prediction, and structure elucidation 15
  • 16. The realm of ChemoinformaticsThe realm of Chemoinformatics a) Representing Chemical Compounds b) Searching Chemical Structures c) Similarity Searches d) Relating structure to properties with models 16
  • 17. Machine Learning MethodsMachine Learning Methods • Important role in chemoinformaticsImportant role in chemoinformatics –For example, it is usually difficult to predict which types of descriptors are most suitable for a given search, classification. • Therefore, machine learning techniques are often used to facilitate descriptor selection 17
  • 18. Machine Learning MethodsMachine Learning Methods – Genetic algorithms– Genetic algorithms • Different parameters and model solutions to given problems are encoded in a chromosome and subjected to random variation, thus generating a population. • Solutions provided by these chromosomes are evaluated by fitness function that assign high scores to desired results. • Chromosomes yielding best intermediate solutions are subjected to mutation and crossover operation that correspond to random genetic mutations and gene recombination events. • The resulting modified chromosomes represent the next generation and the process is continued until the obtained results meet a satisfactory convergence criterion 18
  • 19. Quantitative Structure ActivityQuantitative Structure Activity Relationship Analysis (QSAR)Relationship Analysis (QSAR) Goal :Goal : Evaluation of molecular features that determine biological activity and the prediction of compound potency as a function of structural modification 19
  • 20. Virtual Screening and Compound FilteringVirtual Screening and Compound Filtering VS(Virtual Screening) - the process of screening large databases on the computer for molecules having desired properties and biological activity. A major application of VS techniques is the identification of novel active molecules in large compound databases. 20
  • 21. Impact of new technology on drug discoveryImpact of new technology on drug discovery • The last few years have seen a number of “revolutionary” new technologies: – Gene chips, genomics and HGP – Bioinformatics & Molecular biology – More protein structures – High-throughput screening & assays – Virtual screening and library design – Combinatorial chemistry – Other computational methods • How do we make it all work for us? 21
  • 22. How Chemoinformatics can help outHow Chemoinformatics can help out Producing and manage information for metrics to reduce risk, e.g. –Virtual screening –Library design, –Docking –Cost/benefit analysis • Making information available at the right time and the right place Needs to be integrated into processes 22
  • 23. Software relevance:Software relevance: Bridge between computation & scienceBridge between computation & science clustering sim. searching activity models scaffold detection docking logp calculation tasks: “doing a cluster analysis” “identifying activity-related fragments” tools chemoinformatics science tasks: work out a chemical synthesis choose good reagents try and document some reactions goals: e.g. produce compounds that have high biological activity ? 23
  • 24. Chemoinformatics: WChemoinformatics: Where It Hashere It Has Come From, Where It Is Now AndCome From, Where It Is Now And Where It Is GoingWhere It Is Going
  • 25. OverviewOverview From Chemical Information ToFrom Chemical Information To ChemoinformaticsChemoinformatics – Integration with techniques from molecular modeling – Developments in computer hardware and software – Data explosion arising from developments in combinatorial chemistry and high-throughput screening 25
  • 26. Molecular ModellingMolecular Modelling • Positioning of a putative ligand into a protein’s active site, first attempted by the DOCK program (UCSF, 1982) • Initially restricted to rigid ligands and rigid proteins: current programs permit some degree of flexibility • Use in structure-based design – Move from docking a single ligand to sequential docking of large datasets 26
  • 27. 27
  • 28. Graph TheoryGraph Theory • Graph theory is a branch of mathematics that considers sets of objects, called nodesnodes, and the relationships, called edgesedges, between pairs of these objects • The definition is completely general, allowing graphs to be used in many different application domains as long as an appropriate representation can be derived 28
  • 30. Proposed courses for a DistanceProposed courses for a Distance learning Programlearning Program • Chemoinformatics Virtual ClassroomChemoinformatics Virtual Classroom 30
  • 31. At present there are no specific software tools for chemical information training in the IranIran. A number of commercial software products used in the pharmaceutical and biotechnology industry are either too expensive or of limited utility for training in either academic or business settings. By employing distance learningdistance learning through a web delivery system, the training software will provide an effective, low cost solution for academic institutions, whether they are offering a single course to students in a remote setting, or an entire program in cheminformatics. 31
  • 32. 32 In addition, such training tools will be very useful in industry settings with local area networks, where in a multidiscipline setting individuals need to receive training on the concepts employed by industrial chemoinformatics software's.
  • 33. Chemoinformatics: aimsChemoinformatics: aims • Develop an awareness of Informatics Management techniques used in the design and implementation of chemoinformatics systems • Enable students to demonstrate skills learned by carrying out a small-scale industrially relevant chemoinformatics research project • Basic structure – Three semesters of taught modules – One semester dissertation working at the site of one of the companies supporting the programme 33
  • 34. Proposed Cources ;Proposed Cources ; • An introduction to chemoinformatics. – Chemoinformatics (Fundamental) – Information Systems Modelling – Information Storage and Retrieval – Foundations of Object-Oriented Programming 34
  • 35. 35 • Chemoinformatics (Advance ; more programming) • Database Design • Research Methods and Dissertation Preparation • Two from a range of elective modules, including Molecular Modelling (Chemistry), Healthcare Information...etc
  • 36. ConclusionsConclusions Distance learning is becoming increasingly accepted by the professional bodies. The image of distance learning would need to be improved. The concept would have to be well presented as something new, modern and completely different from the old-style correspondence courses. Chemoinformatics can step in to assist in this effort. And it can do so in all fields of chemistry, inorganic, analytical, organic, physical, medicinal, and bio-chemistry. And it can reach beyond chemistry provide methods and information that can be used in biology, medicine, and physics. 36
  • 37. ReferencesReferences Journal Articles • Y. M. Alvarez-Ginarte,et al. Bioorganic & Medicinal Chemistry 16 (2008) 6448–6459. • S. D. Lindell, L. C. Pattenden, J. Shannon, Bioorganic & Medicinal Chemistry 17 (2009) 4035–4046. • J. Gasteiger, Chemometrics and Intelligent Laboratory Systems 82 (2006) 200 – 209. 37
  • 38. ReferencesReferences Books • An introduction to chemoinformatics. A.R. Leach & V.J. Gillet. Kluwer, 2003. • Chemoinformatics – A textbook. J. Gasteiger & T. Engel (eds). Wiley-VCH, 2003. • Handbook of chemoinformatics. J. Gasteiger (ed.). Wiley-VCH, 2003. • Chemoinformatics: Concepts, Methods, and Applications (Methods in Molecular Biology). J. Bajorath. Humana Press, 2004. • Molecular Modelling Principles and Applications. A. R. Leach. Longman, 1996. 38
  • 39. 39
  • 40. 40
  • 41. 41 Chemoinformatics  Chem(o)informatics is a generic term that encompasses the;  design, creation, organization,design, creation, organization, management, analysis, visualizationmanagement, analysis, visualization and use of chemical information.and use of chemical information.  In fact, Chemoinformatics is the application of informatics methods to solve chemical problems.
  • 42. What is Chemoinformatics?What is Chemoinformatics? Chemoinformatics, Cheminformatics, Chemical Informatics, Computational Chemistry, … “the set of computer algorithms and tools to store and analyse chemical data in the context of drug discovery and design projects etc…” 42
  • 43. What is Chemoinformatics?What is Chemoinformatics? “the mixing of information resources to transform data into information and information into knowledge, for the intended purpose of making better decisions faster in the arena of drug lead identification and optimizaton” 43
  • 44. What is Chemoinformatics?What is Chemoinformatics? “chemoinformatics encompasses the design, creation, organisation, management, retrieval,analysis, dissemination, visualization and use of chemical information” 44
  • 45. Chemoinformatics : a new scienceChemoinformatics : a new science)?()?( 45
  • 46. Why do we needWhy do we need ChemoinformaticsChemoinformatics??
  • 47. To handle large amounts of information To move chemistry into the computer age To move from data to knowledge. 47
  • 48. And last but not least: •To get funding (bioinformatics is doing well currently, whereas computational chemistry seems to be lagging behind). •Data information knowledge •measurements/calculations Why do we need ChemoinformaticsWhy do we need Chemoinformatics? 48
  • 49. How do we learn?How do we learn? Inductive learning vs..Inductive learning vs.. Deductive learningDeductive learning
  • 50. Inductive learning vs. DeductiveInductive learning vs. Deductive learninglearning Deductive learning:Deductive learning: A fundamental theory exists which allows us to calculate properties and predict the behavior of molecules. The fundamental theory for Chemistry is quantum mechanics.
  • 51. Inductive learning vs. Deductive learningInductive learning vs. Deductive learning Inductive learning = Learning from examplesInductive learning = Learning from examples 51
  • 52. General scheme for inductive learningGeneral scheme for inductive learning 52
  • 53. The fundamental tasks of a chemistThe fundamental tasks of a chemist property prediction, synthesis, design, reaction prediction, and structure elucidation 53
  • 54. The realm of ChemoinformaticsThe realm of Chemoinformatics a) Representing Chemical Compounds b) Searching Chemical Structures c) Similarity Searches d) Relating structure to properties with models 54
  • 55. Machine Learning MethodsMachine Learning Methods • Important role in chemoinformaticsImportant role in chemoinformatics –For example, it is usually difficult to predict which types of descriptors are most suitable for a given search, classification. • Therefore, machine learning techniques are often used to facilitate descriptor selection 55
  • 56. Machine Learning MethodsMachine Learning Methods – Genetic algorithms– Genetic algorithms • Different parameters and model solutions to given problems are encoded in a chromosome and subjected to random variation, thus generating a population. • Solutions provided by these chromosomes are evaluated by fitness function that assign high scores to desired results. • Chromosomes yielding best intermediate solutions are subjected to mutation and crossover operation that correspond to random genetic mutations and gene recombination events. • The resulting modified chromosomes represent the next generation and the process is continued until the obtained results meet a satisfactory convergence criterion 56
  • 57. Quantitative Structure ActivityQuantitative Structure Activity Relationship Analysis (QSAR)Relationship Analysis (QSAR) Goal :Goal : Evaluation of molecular features that determine biological activity and the prediction of compound potency as a function of structural modification 57
  • 58. Virtual Screening and Compound FilteringVirtual Screening and Compound Filtering VS(Virtual Screening) - the process of screening large databases on the computer for molecules having desired properties and biological activity. A major application of VS techniques is the identification of novel active molecules in large compound databases. 58
  • 59. Impact of new technology on drug discoveryImpact of new technology on drug discovery • The last few years have seen a number of “revolutionary” new technologies: – Gene chips, genomics and HGP – Bioinformatics & Molecular biology – More protein structures – High-throughput screening & assays – Virtual screening and library design – Combinatorial chemistry – Other computational methods • How do we make it all work for us? 59
  • 60. How Chemoinformatics can help outHow Chemoinformatics can help out Producing and manage information for metrics to reduce risk, e.g. –Virtual screening –Library design, –Docking –Cost/benefit analysis • Making information available at the right time and the right place Needs to be integrated into processes 60
  • 61. Software relevance:Software relevance: Bridge between computation & scienceBridge between computation & science clustering sim. searching activity models scaffold detection docking logp calculation tasks: “doing a cluster analysis” “identifying activity-related fragments” tools chemoinformatics science tasks: work out a chemical synthesis choose good reagents try and document some reactions goals: e.g. produce compounds that have high biological activity ? 61
  • 62. Chemoinformatics: WChemoinformatics: Where It Hashere It Has Come From, Where It Is Now AndCome From, Where It Is Now And Where It Is GoingWhere It Is Going
  • 63. OverviewOverview From Chemical Information ToFrom Chemical Information To ChemoinformaticsChemoinformatics – Integration with techniques from molecular modeling – Developments in computer hardware and software – Data explosion arising from developments in combinatorial chemistry and high-throughput screening 63
  • 64. Molecular ModellingMolecular Modelling • Positioning of a putative ligand into a protein’s active site, first attempted by the DOCK program (UCSF, 1982) • Initially restricted to rigid ligands and rigid proteins: current programs permit some degree of flexibility • Use in structure-based design – Move from docking a single ligand to sequential docking of large datasets 64
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  • 66. Graph TheoryGraph Theory • Graph theory is a branch of mathematics that considers sets of objects, called nodesnodes, and the relationships, called edgesedges, between pairs of these objects • The definition is completely general, allowing graphs to be used in many different application domains as long as an appropriate representation can be derived 66
  • 68. Proposed courses for a DistanceProposed courses for a Distance learning Programlearning Program • Chemoinformatics Virtual ClassroomChemoinformatics Virtual Classroom 68
  • 69. At present there are no specific software tools for chemical information training in the IranIran. A number of commercial software products used in the pharmaceutical and biotechnology industry are either too expensive or of limited utility for training in either academic or business settings. By employing distance learningdistance learning through a web delivery system, the training software will provide an effective, low cost solution for academic institutions, whether they are offering a single course to students in a remote setting, or an entire program in cheminformatics. 69
  • 70. 70 In addition, such training tools will be very useful in industry settings with local area networks, where in a multidiscipline setting individuals need to receive training on the concepts employed by industrial chemoinformatics software's.
  • 71. Chemoinformatics: aimsChemoinformatics: aims • Develop an awareness of Informatics Management techniques used in the design and implementation of chemoinformatics systems • Enable students to demonstrate skills learned by carrying out a small-scale industrially relevant chemoinformatics research project • Basic structure – Three semesters of taught modules – One semester dissertation working at the site of one of the companies supporting the programme 71
  • 72. Proposed Cources ;Proposed Cources ; • An introduction to chemoinformatics. – Chemoinformatics (Fundamental) – Information Systems Modelling – Information Storage and Retrieval – Foundations of Object-Oriented Programming 72
  • 73. 73 • Chemoinformatics (Advance ; more programming) • Database Design • Research Methods and Dissertation Preparation • Two from a range of elective modules, including Molecular Modelling (Chemistry), Healthcare Information...etc
  • 74. ConclusionsConclusions Distance learning is becoming increasingly accepted by the professional bodies. The image of distance learning would need to be improved. The concept would have to be well presented as something new, modern and completely different from the old-style correspondence courses. Chemoinformatics can step in to assist in this effort. And it can do so in all fields of chemistry, inorganic, analytical, organic, physical, medicinal, and bio-chemistry. And it can reach beyond chemistry provide methods and information that can be used in biology, medicine, and physics. 74
  • 75. ReferencesReferences Journal Articles • Y. M. Alvarez-Ginarte,et al. Bioorganic & Medicinal Chemistry 16 (2008) 6448–6459. • S. D. Lindell, L. C. Pattenden, J. Shannon, Bioorganic & Medicinal Chemistry 17 (2009) 4035–4046. • J. Gasteiger, Chemometrics and Intelligent Laboratory Systems 82 (2006) 200 – 209. 75
  • 76. ReferencesReferences Books • An introduction to chemoinformatics. A.R. Leach & V.J. Gillet. Kluwer, 2003. • Chemoinformatics – A textbook. J. Gasteiger & T. Engel (eds). Wiley-VCH, 2003. • Handbook of chemoinformatics. J. Gasteiger (ed.). Wiley-VCH, 2003. • Chemoinformatics: Concepts, Methods, and Applications (Methods in Molecular Biology). J. Bajorath. Humana Press, 2004. • Molecular Modelling Principles and Applications. A. R. Leach. Longman, 1996. 76
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