random lessons from nano-bio for nsf materials science cyberinfrastructure eric jakobsson university...

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Random Lessons from Nano-bio for NSF Materials Science Cyberinfrastructure Eric Jakobsson University of Illinois at Urbana- Champaign Director, NIH Roadmap National Center for the Design of Biomimetic Nanoconductors Founder, Biology Student Workbench Former Director, NIGMS Center for Bioinformatics and Computational Biology, Former Chair, NIH Biomedical Information Science and Technology Initiative Consortium

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Page 1: Random Lessons from Nano-bio for NSF Materials Science Cyberinfrastructure Eric Jakobsson University of Illinois at Urbana-Champaign Director, NIH Roadmap

Random Lessons from Nano-bio for NSF Materials Science

CyberinfrastructureEric Jakobsson

University of Illinois at Urbana-ChampaignDirector, NIH Roadmap National Center for the Design of Biomimetic Nanoconductors

Founder, Biology Student WorkbenchFormer Director, NIGMS Center for

Bioinformatics and Computational Biology, Former Chair, NIH Biomedical Information

Science and Technology Initiative Consortium

Page 2: Random Lessons from Nano-bio for NSF Materials Science Cyberinfrastructure Eric Jakobsson University of Illinois at Urbana-Champaign Director, NIH Roadmap

Google: Nanoconductors—1st hit

Page 3: Random Lessons from Nano-bio for NSF Materials Science Cyberinfrastructure Eric Jakobsson University of Illinois at Urbana-Champaign Director, NIH Roadmap

Official Organization Chart of the University of Washington—a typical official research university organization--guaranteed to fail if functional relationships followed the chart. The system only works at all because people create other connections not reflected in the official chart, but the system works poorly because the institution does not reward the creation of the other connections.

Page 4: Random Lessons from Nano-bio for NSF Materials Science Cyberinfrastructure Eric Jakobsson University of Illinois at Urbana-Champaign Director, NIH Roadmap

An organization chart that needs work

Page 5: Random Lessons from Nano-bio for NSF Materials Science Cyberinfrastructure Eric Jakobsson University of Illinois at Urbana-Champaign Director, NIH Roadmap

Organization charts that actually work (from Tong et al, Global mapping of the yeast genetic interaction network, Science, 2-6-04…). Typically, there are multiple paths between each pair of nodes.

Page 6: Random Lessons from Nano-bio for NSF Materials Science Cyberinfrastructure Eric Jakobsson University of Illinois at Urbana-Champaign Director, NIH Roadmap

An organization chart that we think is working---the interaction network of participating investigators at The National Center for the Design of Biomimetic

Nanoconductors. The Principal Investigator (Jakobsson) is at the center rather than the top. There are multiple alternative pathways to getting things done. It looks a

lot more like the gene interaction network than a typical research institution,

Page 7: Random Lessons from Nano-bio for NSF Materials Science Cyberinfrastructure Eric Jakobsson University of Illinois at Urbana-Champaign Director, NIH Roadmap

Bridging the Experimental-Computational-Design Divides—General Principles

• Theory and computation in the Center will be validated by experiment in the Center.

• Experiment in the Center will be guided by theory and computation in the Center.

• Computation and theory in the Center will be focused on support of device design.

Page 8: Random Lessons from Nano-bio for NSF Materials Science Cyberinfrastructure Eric Jakobsson University of Illinois at Urbana-Champaign Director, NIH Roadmap

Bridging the Experimental-Computational-Design Divides—Specific Example 1

• We would like to fabricate nano/micro scale “cells” with a self-assembled membrane supported by semipermeable (permeable to water but not ions) silica or other thin films---essentially fabricated aquaporins. We know from electrostatics theory that this should be possible by adjusting the image force barrier in nanopores.

• Brinker lab (experimentalists) have devised an electrolytic deposition technique that enables him to closely control the size of nanopores in a thin film.

• Aluru lab (computationalists) are doing molecular dynamics simulations to determine range of nanopore dimensions for the materials from the Brinker lab that will be semipermeable; i.e., pass water but not ions.

Page 9: Random Lessons from Nano-bio for NSF Materials Science Cyberinfrastructure Eric Jakobsson University of Illinois at Urbana-Champaign Director, NIH Roadmap

Bridging the Experimental-Computational-Design Divides—Specific Example 2

• We want to design robust ion channels from beta-barrels that will have properties of our specification for membrane-based devices we design

• Bayley lab (experimentalists) have developed the ability to insert cyclodextrin into alpha-hemolysin pore, in a position where it could act as a selectivity filter.

• Roux lab (computationalists) are doing free energy/molecular dynamics simulations to determine selectivity of chemically decorated cyclodextrins to be synthesized in Bayley lab

Page 10: Random Lessons from Nano-bio for NSF Materials Science Cyberinfrastructure Eric Jakobsson University of Illinois at Urbana-Champaign Director, NIH Roadmap

Bridging the Experimental-Computational-Design Divides—Specific Example 3

• We would like to design and fabricate nanoscale batteries from supported membranes—biomimesis based on the organ of the electric eel as a proof of concept.

• Jakobsson lab (computationalists) developed a dynamic model describing ion and water flow across the airway epithelium

• LaVan lab (device design/experimentalists) have adapted the epithelial model as a template to do a first draft model of the electric organ, as a foundation for nano-battery design.

• Plimpton lab (computationalists) are building the LaVan first draft model into a full 3-dimensional model of the electric organ.

Page 11: Random Lessons from Nano-bio for NSF Materials Science Cyberinfrastructure Eric Jakobsson University of Illinois at Urbana-Champaign Director, NIH Roadmap
Page 12: Random Lessons from Nano-bio for NSF Materials Science Cyberinfrastructure Eric Jakobsson University of Illinois at Urbana-Champaign Director, NIH Roadmap

Bridging time and length scales in understanding membrane dynamics and organization

• Problem: No supercomputer that we can foresee will be able to simulate, from atomistic molecular dynamics, domain formation and phase relationships in heterogeneous membranes

• Our labs’ (Scott/Grama/Jakobsson) approach is to use atomistic molecular dynamics simulations to parameterize Mean Field Langevin Dynamics simulations that can span large distances and long time scales.

• In our specific implementation, cholesterol molecules are discrete particles, while other membrane lipids are represented by continuous fields of concentration and order parameter. Field evolution dynamics are derived directly from analysis of molecular dynamics output of corresponding membrane, specifically from correlation analysis of neighbor interactions.

• Method has been validated by successfully reproducing heat capacity through phase transitions, and phase boundary tie lines, for dppc-cholesterol mixtures. (ms. under review)

Page 13: Random Lessons from Nano-bio for NSF Materials Science Cyberinfrastructure Eric Jakobsson University of Illinois at Urbana-Champaign Director, NIH Roadmap

Suggested dissemination guidelines for software developed under CI (adapted from NIH guidelines and taking account

of discussion at NSF workshop)

• 1) The software should be freely (or at very nominal cost) available to researchers and educators in the non-profit sector, such as institutions of education, research institutes, and government laboratories.

• 2) The terms of software availability should permit the commercialization of enhanced or customized versions of the software, or incorporation of the software or pieces of it into other software packages.

• 3) The terms of software availability should include the ability of researchers outside the supported project to modify the source code and to share modifications with other colleagues, with obligation to share modifications also with original developers.

• 4) The software must be in a form such that if the development team loses interest in the software subsequent to the life of the project another individual or team can make use of previous work to continue development and maintenance.

Page 14: Random Lessons from Nano-bio for NSF Materials Science Cyberinfrastructure Eric Jakobsson University of Illinois at Urbana-Champaign Director, NIH Roadmap

User Web Browser

Application Programs

(May have varyinginterfaces and be written in different

languages)

Information Sources(May be of

varying formats)

Format Translator, Query Engine and Program Driver

Results

Instructions

Information

Queries

Output to User

Results to User

User Input

User Instructions and queries

THE INFORMATION WORKBENCH -- AN ARCHITECTURE FOR WEB-BASED COMPUTING

(NCSA COMPUTATIONAL BIOLOGY GROUP)

Page 15: Random Lessons from Nano-bio for NSF Materials Science Cyberinfrastructure Eric Jakobsson University of Illinois at Urbana-Champaign Director, NIH Roadmap
Page 16: Random Lessons from Nano-bio for NSF Materials Science Cyberinfrastructure Eric Jakobsson University of Illinois at Urbana-Champaign Director, NIH Roadmap

A question that emerged at a biology education meeting in North Carolina

Could homo sapiens interbreed, or have interbred, with other species?

Page 17: Random Lessons from Nano-bio for NSF Materials Science Cyberinfrastructure Eric Jakobsson University of Illinois at Urbana-Champaign Director, NIH Roadmap
Page 18: Random Lessons from Nano-bio for NSF Materials Science Cyberinfrastructure Eric Jakobsson University of Illinois at Urbana-Champaign Director, NIH Roadmap
Page 19: Random Lessons from Nano-bio for NSF Materials Science Cyberinfrastructure Eric Jakobsson University of Illinois at Urbana-Champaign Director, NIH Roadmap
Page 20: Random Lessons from Nano-bio for NSF Materials Science Cyberinfrastructure Eric Jakobsson University of Illinois at Urbana-Champaign Director, NIH Roadmap

Bottom Lines• NSF CI (and all research institutions) should consider reorganization

along lines proved to work in biological interaction networks and suggested by leading edge social network theory

• CI should nurture interactions among experimentalists, computationalists, theoreticians, and designers.

• CI should nurture development, implementation, and dissemination of efficient multiscale.

• NSF CI should adopt software dissemination guidelines similar to NIH roadmap BISTI National Centers for Biomedical Computing.

• NSF CI should promote portal development that provides unified access to multiple data sources and computational analysis tools for research and problem-based education. Translation between data and interface formats should be done by the portal developers.