Title: Computational Protein Topographics for Health Improvement
1Computational Protein Topographics for Health
Improvement Jie Liang, Ph.D. Bioengineering Prim
e Grant Support National Science Foundation
Career Award, National Institutes of Health R01,
Office of Naval Research, and the
Whitaker Foundation.
Protein surface matching
Problem Statement and Motivation
- The structure of proteins provide rich
information about how cells work. With the
success of structural genomics, soon we will have
all human proteins mapped to structures. - However, we need to develop computational tools
to extract information from these structures to
understand how cell works and how new diseases
can be treated. - Therefore, the development of computational tools
for surface matching and for function prediction
will open the door for many new development for
health improvement.
Evolution of function
Key Achievements and Future Goals
Technical Approach
- We have developed a web server CASTP (cast.engr.
uic.edu) that identify and measures protein
surfaces. It has been used by thousands of
scientists world wide. - We have built a protein surface library for
gt10,000 proteins, and have developed models to
characterize cross reactivities of enzymes. - We also developed methods for designing phage
library for discovery of peptide drugs. - We have developed methods for predicting
structures of beta-barrel membrane proteins. - Future Understand how protein fold and
assemble, and designing method for engineering
better proteins and drugs.
- We use geometric models and fast algorithm to
characterize surface properties of over thirty
protein structures. - We develop evolutionary models to understand how
proteins overall evolve to acquire different
functions using different combination of surface
textures. - Efficient search methods and statistical models
allow us to identify very similar surfaces on
totally different proteins - Probablistc models and sampling techniques help
us to understand how protein works to perform
their functions.
2Fluid Physics and Transport Phenomena in the
Human Brain Laboratory for Product and Process
Design, Director A. A. LINNINGER College of
Engineering, University of Illinois, Chicago, IL,
60607, U.S.A. Grant Support NSF, Susman and
Asher Foundation
- Problem Statement
- Prediction of large deformations of the brain
parenchyma based on Fluid-Structure Interaction
modeling. - Coupling of the brain parenchyma, vascular and
ventricular system in the human brain. - Motivation
- The therapeutic approach for hydrocephalus
treatment is very brutal (shunting) and many
revisions are needed. - Ultimate goal precise model of human brain
dynamics to design treatments without in vivo
test.
- Key Achievements
- 3D geometric reconstruction of patient-specific
brain dimensions based on MRI data - 3D patient-specific dynamic analysis of CSF flow
in the human brain - Future Goals
- Optimal Drug Delivery to the Human Brain.
- Feedback control systems to better treat
Hydrocephalus.
- Data from Magnetic Resonance Imaging.
- Use of MRI reconstruction tools for generation of
3D patient specific brain geometry. - Introduction of the geometry to Finite Volumes or
Finite Elements advanced solvers. - Post processing of the obtained results.
3Integrating Nanostructures with Biological
Structures Investigators M. Stroscio, ECE and
BioE M. Dutta, ECE Prime Grant Support ARO,
NSF, AFOSR, SRC, DARPA
Problem Statement and Motivation
Quantum Dot
- Coupling manmade nanostructures with biological
structures to monitor and control biological
processes. - For underlying concepts see Biological
Nanostructures and Applications of Nanostructures
in Biology Electrical, Mechanical, Optical
Properties, edited by Michael A. Stroscio and
Mitra Dutta (Kluwer, New York, 2004).
Cellular Membrane
Integrin
Technical Approach
Key Achievements and Future Goals
- Synthesis of nanostructures
- Binding nanostructures to manmade structures
- Modeling electrical, optical and mechanical
- properties of nanostructures
- Experimental characterization of intergated
manmade - nanostructure-biological structures
- Numerous manmade nanostructures have been
functionalized with biomolecules - Nanostructure-biomolecule complexes have been
used to study a variety of biological structures
including cells - Interactions between nanostructures with
biomolecules and with biological environments
have been modeled for a wide variety of systems - Ultimate goal is controlling biological systems
at the nanoscale
4Multimode Sonic Ultrasonic Diagnostic
Imaging Investigators Thomas J. Royston
Francis Loth, Mechanical Industrial
Engineering Prime Grant Support NIH
Problem Statement and Motivation
Bimodal image.
- Ultrasonic (US) imaging provides detailed
geometry - Geometric changes may indicate disease or injury
- Sonic imaging provides unique functional
information - Sounds associated with disease are sonic, not US
- Merge US and Sonics to harness strengths of each
- Initial application peripheral vascular
pathologies vessel constrictions (plaque and
intimal hyperplasia)
Blood vessel with constriction in soft tissue
phantom Grayscale of geometry from US
imaging Color overlay of acoustic field generated
by turbulence downstream of the constriction
Key Achievements and Future Goals
Technical Approach
- Sonic wave propagation in biological tissue is
more complex than US. - Requires new acoustic modeling developments
- Inverse modeling to extract acoustic image from
array - Novel acoustic sensor development
- Prototype US/Sonic system has been developed
- - conventional US system retrofitted with
- - electromagnetic position device for true
3D imaging - - acoustic sensor array pad that is
transparent to US so US imaging can be conducted
with the pad in place - Calibration of system on phantom models in
progress - Turbulence imaged downstream of vessel
constriction - Future plans Human subject studies, improved
prototype, better sensor array, improved imaging
software
Prototype 15 sensor sonic array pad on arm
- Merging multiple imaging modalities on same
platform
Biomedical Biotechnology