CHEMISTRY IN EVERYDAY LIFE

1. Chemistry in every day Life

2. Chemistry in every day Life
Chemistry and Chemicals
Prof . AJAL A. J
8907305642
Head of Academics

4. Chemistry is the study of substances in terms of
Composition What a material it made of
Structure How the elementary particles are put
together
Properties The characteristics of the material
Reactions How it behave with other substances
What is chemistry?

5. 3 Major Groupings of Chemical
Reactions
1. Precipitation
Reactions
2. Oxidation-Reduction
Reactions
3. Acid-Base
Neutralization
Reactions

6. Precipitation Reactions
Precipitation reactions: When
an insoluble solid called a
precipitate forms when
reactants are formed
together.
For example, when Carbon
Dioxide is mixed with
Calcium Hydroxide
(limewater), the precipitate
Calcium carbonate is
formed.
Ca(OH)2+CO2→H2O+Ca
C03
Calcium Carbonate is found
in chalk!

7. Oxidation/Reduction Reactions
• A reaction in which
electrons are transferred
from one atom to
another.
• Oxidation: The loss of
electrons by an atom
• Reduction: The gain of
electrons by an atom.
EXAMPLE:
Take a penny, file of the copper to
expose the zinc in the inside.
Place it in HCl, and zinc is oxidized.
Zn(s) + HCl(aq) Zn2+(aq) + Cl -
(aq) + H2(g)
Zinc gains a positive charge, and is
oxidized.

8. Chemical reactions happen when
• a car is started
• tarnish is removed from silver
• fertilizer is added to help plants
grow
• food is digested
• electricity is produced from
burning natural gas
• rust is formed on iron nails

9. Everything in our lives from materials
to life involve chemistry
• glass (SiO2)n
• metal alloys
• chemically treated water
• plastics and polymers
• baking soda, NaHCO3
• foods
• fertilizers and pesticides
• living beings

10. Chemicals in Toothpaste

11. The Scientific Method
The scientific method is the
process used to explain
observations in nature.
The method involves:
• making observations
• forming a hypothesis
• doing experiments to test
the hypothesis

12. In chemistry:
quantities are measured
experiments are performed
results are calculated
use numbers to report measurements,
results are compared to standards.

13. Scientific notation
 is used to write very large or very small numbers
 the width of a human hair (0.000 008 m) is written
8 x 10-6 m
 a large number such as 4 500 000 s is written
4.5 x 106 s

14. If the thickness of the skin fold at the
waist indicates an 11% body fat, how
much fat is in a person with a mass
of 86 kg?
11 % fat means 11kg/100kg body weight
86 kg x 11 kg fat = 9.5 kg of fat
100 kg

15. • The density of the zinc object
can be calculated from its
mass and volume.
d = 68.6g/(45.0-35.5)mL; 68.6g/9.5 mL
d = 7.2 g/mL

16. Physical vs. Chemical Changes
Physical changes occur when substances or
objects undergo a change without changing into
another substance
Chemical changes are changes substances undergo
when they become new or different substances.

17. Physical Change
- Involves heat
Melting of ice cream is an
example of a physical change.
YOUR TURN: Can you think of other examples of
physical changes?
Image available at
http://www.icecreamclubonline.com/

18. Chemical Change
At the molecular level: The
wax molecule changes to
carbon dioxide and water
molecules.
Burning of a candle is an
example of a chemical
change.
Image available at Colin Baird, “Chemistry in Your Life”. 2nd ed.,
(ISBN 0-7167-7042-3) New York: W.H. Freeman, 2006.

19. Other examples of chemical changes
Can you think of another term for chemical
changes?
YOUR TURN: Can you think of other examples of
everyday life chemical reactions?
Chemical change = chemical reaction

20. Collecting and Preserving Evidence
Physical and chemical changes are sometimes
involved in the collection of physical evidence from
a crime scene
Reference: M. Johll, “Investigating Chemistry: A Forensic Science Perspective.”
W.H.Freeman: New York, 2007. p. 26.
Ex. Latent fingerprints (invisible to the naked eye) are
treated with chemicals to become visible (= chemical
change)
Developing latent fingerprints
Image source:
http://www.clpex.com/images/Articles/RT
X/s-Dsc_0025.jpg

21. Collecting and Preserving Evidence
Ex. Bloody clothes are dried out to prevent the blood from
decomposing.
 Identify the underlined words above as either a
physical or chemical change.
Reference: M. Johll, 2007, p. 25
Question: Why are evidence collected in separate containers?

22. Everyday life chemical changes/reactions
 Acid-base reactions
Q. Do you know where in our body do we have acids?
Q. Can you give some examples of acids? Bases?
Q. Can you give an example of acid-base reaction?

23. Everyday life chemical changes/reactions
 Oxidation reactions
Q. Can you tell which gas is used or produced during
oxidation?
Q. What could be an observable sign of oxidation
reaction?

24. ACID and BASES
of everyday life

25. Image available at C. Baird and W. Gloffke, “Chemistry In Your Life.”
New York: Freeman, 2003. (p. 437)
Acidic soil Alkaline (basic) soil

26. Acidic and basic are two extremes that describe chemicals, just like hot and cold are
two extremes that describe temperature.
Mixing acids and bases can cancel out their extreme effects; much like mixing hot and
cold water can even out the water temperature.
A substance that is neither acidic nor basic is neutral.
http://www.epa.gov/acidrain/measure/ph.html

27. Highly corrosive!
Highly corrosive!
Remember:
Low pH = high acidity
Image available at
http://www.phsciences.com/about_p
h/ph_scale.asp

28. Learning objectives
• Know the stages of drug development
• Explain why animals are used in research
• Analyse why new drugs may fail
Starter:
1. List 5-10 medications
that you have taken.
2. What symptoms were
they treating?
Developing medicines

29. What information do you need before you take a
medicine?
Write down 3 things that you would want to know
about a medicine that you were about to take.

30. What information do you need before you take a
medicine?
Are
there
any side
effects?
Does it
work?
How
often
should I
take it?
Should I
take it with
food/water?
How
much
should I
take?
What is
the dose?
Will it make
me better?
What
are the
side
effects?
Is it safe?
Is it toxic?
Is it
poisonous?
Is it
addictive?
Will it
cure
me?

31. Think, Pair, Share
You are faced with a new, untested drug
1. Pick one of the questions below.
2. How could you find the answer to your
question?
Are there any side effects?
Does it work?
What is the correct dose?
Is it safe?
What information do you need before you take a
medicine?

32. 1. Look at the Drug
Development Process
worksheet
2. Put them in the correct
order, first to last.
3. Animals are used in two
of the stages. Which
stages do you think
these are?
The Drug Development Process

33. Scientists study bodies and diseases to see how they work. They try to find ‘targets’ for
medicines to aim at. Targets are things that cause diseases such as tiny protein molecules.
Computers and cell samples are used to find chemicals that seem to work on the target. Tens
of thousands of known chemicals are tested like this.
The most promising treatments are tested to see how much is safe and how much is
poisonous. Scientists need to know how quickly and where the body absorbs the chemical and
how quickly it flushes it out.
The second clinical trial involves a much bigger group of patients, to see if the drug works on
the disease it is designed for.
If a medicine passes all the clinical trials it can get a licence from the government which means
doctors can use it.
Double blind randomised trials involve large numbers of patients. Some are given the new
medicine and some a placebo that does nothing at all. Neither the patients nor the people
giving them the medicine know which group is which.
Doctors prescribe licensed medicines, but they continue to monitor the effects on patients. This
is sometimes called the ‘phase 4’ clinical trial.
The first clinical trial is where new medicines are tested on healthy people to make sure there
are no unexpected side effects.
Correct Answers

34. What is a scientific model?
Models are used in scientific
research when we cannot
study the real thing. They help
us to predict what will happen.
There are 3 kinds of models
used in developing a new
medicine:
• Non-animal/non-human
• Living humans
• Living animals

35. Computers can be programmed
with information about a disease
and a treatment to try and
predict what will happen when
the treatment is given.
Tissue samples show the effect
that a treatment has on a group
of cells. These cells are alive but
are not part of a whole organism.
The effects of a medicine can
also be looked at in bacteria.
Non-animal and non-human models
Computer model of artery
Tissue sample

36. Think, Pair, Share
Consider each of the following models. Why might
they not provide all the information needed to
confirm if a new drug is safe and effective for us?
A human tissue sample to study if a new
chemical causes cancer
(test if the drug is carcinogenic)
Computer model of how a drug is
metabolised in the body
Yeast cells used to check if a new drug is
toxic to parts of a cell.
Non-animal and non-human models

37. Animal models
Even if we give a new medicine to some
human cells, this cannot tell us how it will
affect the whole body. We also need to
know if the medicine will reach the part of
the body it needs to.
Living animals, most commonly mice, rats
and fish, are used to see how a medicine
affects a whole body. It can tell us about
the toxicity and will also indicate what
dosage is necessary for humans.
The government requires new medicines to be
tested on two species. Why do you think this is?

38. Human models
In the clinical trial stages of developing a new
medicine, small groups of humans are used as a
model for other humans. We cannot test a medicine
on every human so we use the tests on these groups
to predict the effects in everyone else.
Some patients will receive the drug and some will
receive a placebo (sugar pill). The patient does not
know which he has been given; this is called a blind
trial.

39. Human models
Stage I
Testing at
low doses on
healthy
volunteers.
Usually
young males
Stage III
Testing on a large number
of patients to gather data
from larger populations
Stage II
Testing on ill patients
to test efficacy of drug
and calculate
appropriate dosages

40. Important Points in Drug Design based on
Bioinformatics Tools
History of Drug/Vaccine development
– Plants or Natural Product
• Plant and Natural products were source for medical substance
• Example: foxglove used to treat congestive heart failure
• Foxglove contain digitalis and cardiotonic glycoside
• Identification of active component
– Accidental Observations
• Penicillin is one good example
• Alexander Fleming observed the effect of mold
• Mold(Penicillium) produce substance penicillin
• Discovery of penicillin lead to large scale screening
• Soil micoorganism were grown and tested
• Streptomycin, neomycin, gentamicin, tetracyclines etc.
http://www.geocities.com/bioinformaticsweb/drugdiscovery.html

41. Important Points in Drug Design based on
Bioinformatics Tools
• Chemical Modification of Known Drugs
– Drug improvement by chemical modification
– Pencillin G -> Methicillin; morphine->nalorphine
• Receptor Based drug design
– Receptor is the target (usually a protein)
– Drug molecule binds to cause biological effects
– It is also called lock and key system
– Structure determination of receptor is important
• Ligand-based drug design
– Search a lead ocompound or active ligand
– Structure of ligand guide the drug design process

42. Important Points in Drug Design based on
Bioinformatics Tools
• Identify Target Disease
– Identify and study the lead compounds
– Marginally useful and may have severe side effects
• Refinement of the chemical structures
– Detect the Molecular Bases for Disease
– Detection of drug binding site
– Tailor drug to bind at that site
– Protein modeling techniques
– Traditional Method (brute force testing)

43. Genetics Review
TACGCTTCCGGATTCAA
transcription
AUGCGAAGGCCUAAGUU
DNA:
RNA:
translation
PIRLMQTS
Protein
Amino Acids:

44. Overview Continued –
A simple example
Protein
Small molecule
drug

45. Overview Continued –
A simple example
Protein
Small molecule
drug
Protein
Protein disabled
… disease
cured

46. Chemoinformatics
ProteinSmall molecule
drug
Bioinformatics
•Large databases •Large databases

47. Chemoinformatics
ProteinSmall molecule
drug
Bioinformatics
•Large databases
•Not all can be drugs
•Large databases
•Not all can be drug targets

48. Chemoinformatics
ProteinSmall molecule
drug
Bioinformatics
•Large databases
•Not all can be drugs
•Opportunity for data mining
techniques
•Large databases
•Not all can be drug targets
•Opportunity for data mining
techniques

49. Important Points in Drug Design based on
Bioinformatics Tools
• Application of Genome
– 3 billion bases pair
– 30,000 unique genes
– Any gene may be a potential drug target
– ~500 unique target
– Their may be 10 to 100 variants at each target gene
– 1.4 million SNP
– 10200 potential small molecules

50. Important Points in Drug Design based on
Bioinformatics Tools
• Detect the Molecular Bases for Disease
– Detection of drug binding site
– Tailor drug to bind at that site
– Protein modeling techniques
– Traditional Method (brute force testing)
• Rational drug design techniques
– Screen likely compounds built
– Modeling large number of compounds (automated)
– Application of Artificial intelligence
– Limitation of known structures

51. Important Points in Drug Design based on
Bioinformatics Tools
• Refinement of compounds
– Refine lead compounds using laboratory techniques
– Greater drug activity and fewer side effects
– Compute change required to design better drug
• Quantitative Structure Activity Relationships (QSAR)
– Compute functional group in compound
– QSAR compute every possible number
– Enormous curve fitting to identify drug activity
– chemical modifications for synthesis and testing.
• Solubility of Molecule
• Drug Testing

52. Drug Discovery & Development
Identify disease
Isolate protein
involved in
disease (2-5 years)
Find a drug effective
against disease protein
(2-5 years)
Preclinical testing
(1-3 years)
Formulation
Human clinical trials
(2-10 years)
Scale-up
FDA approval
(2-3 years)

53. Techology is impacting this process
Identify disease
Isolate protein
Find drug
Preclinical testing
GENOMICS, PROTEOMICS & BIOPHARM.
HIGH THROUGHPUT SCREENING
MOLECULAR MODELING
VIRTUAL SCREENING
COMBINATORIAL CHEMISTRY
IN VITRO & IN SILICO ADME MODELS
Potentially producing many more targets
and “personalized” targets
Screening up to 100,000 compounds a
day for activity against a target protein
Using a computer to
predict activity
Rapidly producing vast numbers
of compounds
Computer graphics & models help improve activity
Tissue and computer models begin to replace animal testing

54. 1. Gene Chips
• “Gene chips” allow us
to look for changes in
protein expression for
different people with a
variety of conditions,
and to see if the
presence of drugs
changes that expression
• Makes possible the
design of drugs to
target different
phenotypes
compounds administered
people / conditions
e.g. obese, cancer,
caucasian
expression profile
(screen for 35,000 genes)

55. Biopharmaceuticals
• Drugs based on proteins, peptides or natural
products instead of small molecules (chemistry)
• Pioneered by biotechnology companies
• Biopharmaceuticals can be quicker to discover
than traditional small-molecule therapies
• Biotechs now paring up with major
pharmaceutical companies

56. 2. High-Throughput Screening
Screening perhaps millions of compounds in a corporate
collection to see if any show activity against a certain disease
protein

57. High-Throughput Screening
• Drug companies now have millions of samples of
chemical compounds
• High-throughput screening can test 100,000
compounds a day for activity against a protein target
• Maybe tens of thousands of these compounds will
show some activity for the protei
• The chemist needs to intelligently select the 2 - 3
classes of compounds that show the most promise for
being drugs to follow-up

58. Informatics Implications
• Need to be able to store chemical structure and biological data for
millions of datapoints
– Computational representation of 2D structure
• Need to be able to organize thousands of active compounds into
meaningful groups
– Group similar structures together and relate to activity
• Need to learn as much information as possible from the data (data
mining)
– Apply statistical methods to the structures and related information

59. 3. Computational Models of Activity
• Machine Learning Methods
– E.g. Neural nets, Bayesian nets, SVMs, Kahonen nets
– Train with compounds of known activity
– Predict activity of “unknown” compounds
• Scoring methods
– Profile compounds based on properties related to target
• Fast Docking
– Rapidly “dock” 3D representations of molecules into 3D
representations of proteins, and score according to how well
they bind

60. 4. Combinatorial Chemistry
• By combining molecular “building blocks”, we
can create very large numbers of different
molecules very quickly.
• Usually involves a “scaffold” molecule, and sets
of compounds which can be reacted with the
scaffold to place different structures on
“attachment points”.

61. Combinatorial Chemistry Issues
• Which R-groups to choose
• Which libraries to make
– “Fill out” existing compound collection?
– Targeted to a particular protein?
– As many compounds as possible?
• Computational profiling of libraries can help
– “Virtual libraries” can be assessed on computer

62. 5. Molecular Modeling
• 3D Visualization of interactions between compounds and proteins
• “Docking” compounds into proteins computationally

63. 3D Visualization
• X-ray crystallography and NMR Spectroscopy can
reveal 3D structure of protein and bound
compounds
• Visualization of these “complexes” of proteins and
potential drugs can help scientists understand the
mechanism of action of the drug and to improve
the design of a drug
• Visualization uses computational “ball and stick”
model of atoms and bonds, as well as surfaces
• Stereoscopic visualization available

64. “Docking” compounds into proteins
computationally

65. 6. In Vitro & In Silico ADME
models
• Traditionally, animals were used for pre-human testing.
However, animal tests are expensive, time consuming and
ethically undesirable
• ADME (Absorbtion, Distribution, Metabolism, Excretion)
techniques help model how the drug will likely act in the
body
• These methods can be experemental (in vitro) using
cellular tissue, or in silico, using computational models

66. In Silico ADME Models
• Computational methods can predict compound
properties important to ADME, e.g.
– LogP, a liphophilicity measure
– Solubility
– Permeability
– Cytochrome p450 metabolism
• Means estimates can be made for millions of
compouds, helping reduce “atrittion” – the failure
rate of compounds in late stage

67. Size of databases
• Millions of entries in databases
– CAS : 23 million
– GeneBank : 5 million
• Total number of drugs worldwide: 60,000
• Fewer than 500 characterized molecular
targets
• Potential targets : 5,000-10,000