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.