CS 790 – Bioinformatics CS790 – Bioinformatics CS790 – Bioinformatics Introduction and overview
CS 790 – Bioinformatics
CS790 – BioinformaticsCS790 – Bioinformatics
Introduction and overview
Course Overview 2CS 790 – Bioinformatics
What is Bioinformatics?What is Bioinformatics?DNA (and RNA) Proteins
Course Overview 3CS 790 – Bioinformatics
What is Bioinformatics?What is Bioinformatics?Computational
Biology
Bioinformatics
Genomics
Proteomics
Functionalgenomics
Structuralbioinformatics
Course Overview 4CS 790 – Bioinformatics
Why is Bioinformatics Important?Why is Bioinformatics Important? Applications areas include
• Medicine• Pharmaceutical drug design• Toxicology• Molecular evolution• Biosensors• Biomaterials• Biological computing models• DNA computing
Course Overview 5CS 790 – Bioinformatics
The Role of The Role of ComputationalComputational Biology Biology
1 2 3 5 10 16 24 35 49 72 101 157217
385652
1,160
2,009
3,841
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
Millions
82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99
Source: GenBank
3D StructuresGrowth:
Source: http://www.rcsb.org/pdb/holdings.html
GenBank BASEPAIR GROWTH
Course Overview 6CS 790 – Bioinformatics
Fighting Human DiseaseFighting Human Disease Genetic / Inherited
• Diabetes
Viral• Flu, common cold
Bacterial• Meningitis, Strep throat
Drug Development Life CycleDrug Development Life Cycle
Years
0 2 4 6 8 10 12 14 16
Discovery (2 to 10 Years)
Preclinical Testing(Lab and Animal Testing)
Phase I(20-30 Healthy Volunteers used to check for safety and dosage)
Phase II(100-300 Patient Volunteers used to check for efficacy and side effects)
Phase III(1000-5000 Patient Volunteers used to monitor reactions to long-term drug use)
FDA Review & Approval
Post-Marketing Testing
$600-700 Million!$600-700 Million!
7 – 15 Years!7 – 15 Years!
Course Overview 8CS 790 – Bioinformatics
Drug lead screeningDrug lead screening
5,000 to 10,000 compounds screened
250 Lead Candidates in Preclinical Testing5 Drug Candidates
enter Clinical Testing; 80% Pass Phase I
One drug approved by the FDAOne drug approved by the FDA
30%Pass Phase II
80% Pass Phase III
Course Overview 9CS 790 – Bioinformatics
What are we going to learn?What are we going to learn? DNA, Proteins, life, and disease: an overview Basic chemistry introduction/review Basic biochemistry: proteins Basic biochemistry: DNA, genes, and
molecular evolution (Dr. Dan Krane, Biological Sciences)
Drug docking and screening, dealing with water molecules: Dr. Raymer
Student presentations: techniques in bioinformatics
Course Overview 10CS 790 – Bioinformatics
Student PresentationsStudent Presentations Students will each make 1 or 2 one-hour presentations
on topics in bioinformatics• Tutorial
• Survey
• Research Paper
Each class, we’ll turn in either:• A one-page summary of the previous presentation, or
• A mini-project assigned as part of the presentation.
We’ll talk more about this next time Web page
Course Overview 11CS 790 – Bioinformatics
DNA is the blueprint for lifeDNA is the blueprint for life Every cell in
your body has 23 chromosomes in the nucleus
The genes in these chromosomes determine all of your physical attributes.
Image source: Crane digital, http://www.cranedigital.com/
Course Overview 12CS 790 – Bioinformatics
Mapping the GenomeMapping the Genome The human genome project has provided us
with a draft of the entire human genome.
• Four bases:A, T, C, G
• 3.12 billion base-pairs
• 99% of these are the same
• Polymorphisms = where they differ
Course Overview 13CS 790 – Bioinformatics
How does the code work?How does the code work? Template for construction of proteins
Course Overview 14CS 790 – Bioinformatics
Proteins: Molecular machineryProteins: Molecular machinery
Proteins in your muscles allows you to move:
myosinandactin
Course Overview 15CS 790 – Bioinformatics
Proteins: Molecular machineryProteins: Molecular machinery Enzymes
(digestion, catalysis) Structure (collagen)
Course Overview 16CS 790 – Bioinformatics
Proteins: Molecular machineryProteins: Molecular machinery
Signaling(hormones, kinases)
Transport(energy, oxygen)
Image source: Crane digital, http://www.cranedigital.com/
Course Overview 17CS 790 – Bioinformatics
Example Case: HIV ProteaseExample Case: HIV Protease
1. Exposure & infection
2. HIV enters your cell3. Your own cell reads
the HIV “code” and creates the HIV proteins.
4. New viral proteins prepare HIV for infection of other cells.
http://whyfiles.org/035aids/index.html© George Eade, Eade Creative Services, Inc.
Course Overview 18CS 790 – Bioinformatics
HIV Protease & InhibitionHIV Protease & Inhibition
Course Overview 19CS 790 – Bioinformatics
HIV Protease as a drug targetHIV Protease as a drug target Many drugs bind to
protein active sites. This HIV protease
can no longer prepare HIV proteins for infection, because an inhibitor is already bound in its active site.
HIV Protease + Peptidyl inhibitor (1A8G.PDB)
Course Overview 20CS 790 – Bioinformatics
Drug DiscoveryDrug Discovery Target Identification
• What protein can we attack to stop the disease from progressing?
Lead discovery & optimization• What sort of molecule will bind to this protein?
Toxicology• Does it kill the patient?• Does it have side effects?• Does it get to the problem spots?
Course Overview 21CS 790 – Bioinformatics
Drug discovery: past & presentDrug discovery: past & present Put some of the infectious agent into thousands
of tiny wells Add a known drug lead compound into each
well.• Try nearly every drug lead known.
See which ones kill the agent…• To small to see, so we have to use chemical tests
called assays
Course Overview 22CS 790 – Bioinformatics
Finding drug leadsFinding drug leads Once we have a target, how do we find some
compounds that might bind to it? The old way: exhaustive screening The new way: computational screening!
Course Overview 23CS 790 – Bioinformatics
Drug Lead Screening & DockingDrug Lead Screening & Docking
Complementarity• Shape• Chemical• Electrostatic
??
Course Overview 24CS 790 – Bioinformatics
Problems in BioinformatcsProblems in Bioinformatcs Genomics
• Gene finding• Annotation
Sequence alignment and database search• Functional genomics
Microarray expression, “gene chips” Proteomics
• Structure prediction Comparative modeling
• Function prediction Structural bioinformatics
• Molecular docking, screening, etc.