bms 2010

Philip E. BourneSkaggs School of Pharmacy and

Pharmaceutical Sciencespbourne@ucsd.edu

http://www.sdsc.edu/pb

The BMS Bioinformatics Focus

Sept 27, 2010

The Bioinformatics/Comp. Biol. Distinction

• Bioinformatics – New tools and algorithms for the analysis and use of high throughput data

• See journal Bioinformatics or BMC Bioinformatics

• Computational Biology – Application of computational techniques to make new discoveries about living systems

• See journal PLoS Computational Biology

There are opportunities to study bothSept 27, 2010

Bioinformatics In General

Biological Experiment Data Information Knowledge Discovery

Collect Characterize Compare Model Infer

Sequence

Structure

Assembly

Sub-cellular

Cellular

Organ

Higher-life

Year90 05

Computing Power

SequencingTechnology

Data

1 10 100 1000 100000

95 00

E.ColiGenome

C.ElegansGenome

ESTs

YeastGenome

Gene Chips

Virus Structure Ribosome

Metaboloic Pathway of E.coli

Complexity Technology

Brain Mapping

Neuronal Modeling

Cardiac Modeling

Human Genome

# People/Web Site

(C) Copyright Phil Bourne 1998

106 102 1

10

1000000

.1

GWAS

4th Gen

Translational Medicine

Meta-genomics

Consider one Bioinformatics Growth Area Pioneered by a BMS Alumni

Sept 27, 2010

Metagenomics: First Look at the Challenges

• New type of genomics • New data (and lots of it) and new types of data– 17M new (predicted

proteins!) 4-5 x growth in just few months and much more coming

– New challenges and exacerbation of old challenges

• PLoS Biology 2007 5(3) e74

http://plos.cnpg.com/lsca/webinar/venter/20070306/index.htmlSept 27, 2010

What is Metagenomics?

• Technology– Sequencing DNA

extracted directly from the environment

– No cultures, no PCR

– Short reads• 500-800 bp• 80-100 bp (454)

– No assembly

• Concept– Direct study of

microbial communities– Minimal perturbation –

no cultures, no assumptions

– Fragmentary data, sampling rather than assembling

Sept 27, 2010

Metagenomics: first results

• More then 99.5% of DNA in every environment studied represent unknown organisms– Culturable organisms are

exceptions, not the rule

• Most genes represent distant homologs of known genes, but there are thousands of new families

• Everything we touch turns out to be a gold mine

• Environments studied:– Water (ocean, lakes)– Soil– Human body (gut, oral

cavity, human microbiome)

Sept 27, 2010

http://camera.calit2.net/

Sept 27, 2010

http://bioinformatics.ucsd.edu

• Emphasis on cross training and interdisciplinary activities

• Multiple departments• Over 40 faculty

Sept 27, 2010

Example Courses

http://bioinformatics.ucsd.edu/page/99/

Sept 27, 2010

Support Infrastructure

San Diego Supercomputer Center

California Institute for Telecommunications& Information Technology

Sept 27, 2010

Sample Mentors & Project Areas

• Phil Bourne – Drug discovery, evolution, structure and function of signaling molecules

• Ruben Abagyan – Molecular Biophysics

• Steve Briggs – Stem Cells

• Bing Ren – Gene regulatory networks

• Palmer Taylor – structure and function of molecules involved in neurotransmission

• Terry Gaasterland – Microbial Genomics

Sept 27, 2010

http://bioinformatics.ucsd.edu/faculty/

• Trey Ideker – Network construction and analysis• Pavel Pevzner – Genome rearrangements• J Andrew McCammon – Electrostatic interactions• Wei Wang – Inference of gene regulatory

networks• Bernhard Palsson – Systems biology• Shankar Subramaniam – Functional genomics

Sample Mentors & Project Areas

Sept 27, 2010

http://bioinformatics.ucsd.edu/faculty/

Rotation Projects

http://bioinformatics.ucsd.edu/page/53/

Sept 27, 2010

Questions?

pbourne@ucsd.edu

Example Projects from My Labhttp://www.sdsc.edu/pb/projects.htm

• Pharmaceutical Sciences - Competitive Binding of Major Pharmaceuticals

• From Physical Model of Nucleosome Organization Towards Genome Annotation

• Earth Sciences Meets Life Sciences• Scholarly Communication• Exploring the Flexibility versus Designability of

Protein Folds• What Makes Some Introns’ Positions Ultra-conserved? • Building a Meta-method for Assignment of Structural

Domains in Proteins

Sept 27, 2010

A Reverse Engineering Approach to Drug Discovery Across Gene Families

Characterize ligand binding site of primary target (Geometric Potential)

Identify off-targets by ligand binding site similarity(Sequence order independent profile-profile alignment)

Extract known drugs or inhibitors of the primary and/or off-targets

Search for similar small molecules

Dock molecules to both primary and off-targets

Statistics analysis of docking score correlations

…

Computational MethodologySept 27, 2010

Repositioning TB

• TB Infects 6M people and kills 2M people per year

• Entacapone and tolcapone shown to have potential as InhA inhibitors

• Direct mechanism of action avoids M.tuberculosis resistance mechanisms

• Possess excellent safety profiles with few side effects

• Commercially available and easy to make

• Further in vitro, in vivo and clinical studies required

• Can potentially be applied to clinical practice directly

S. Kinnings, L. Xie N. Buchmeier and P.E. BourneSept 27, 2010

A Systems Biology Approach to Explaining & Subsequently Minimizing Side Effects

PNAS Submitted

Strong BindingMedium Binding

Weak Binding

Positive Regulation

Negative Regulation

Positive & Negative RegulationSept 27, 2010

Bioinformatics Final Examples..

• Donepezil for treating Alzheimer’s shows positive effects against other neurological disorders

• Orlistat used to treat obesity has proven effective against certain cancer types

• Ritonavir used to treat AIDS effective against TB

• Nelfinavir used to treat AIDS effective against different types of cancers

Sept 27, 2010