A Minimal Model for Computational Bioelectronic Peptide ... A Minimal Model for Computational...

download A Minimal Model for Computational Bioelectronic Peptide ... A Minimal Model for Computational Bioelectronic

of 35

  • date post

    03-Jun-2020
  • Category

    Documents

  • view

    1
  • download

    0

Embed Size (px)

Transcript of A Minimal Model for Computational Bioelectronic Peptide ... A Minimal Model for Computational...

  • Wires Within Wires A Minimal Model for Computational Bioelectronic Peptide Design

    R. A. Mansbach1 A. L. Ferguson2

    1Physics Department

    2Materials Science Department University of Illinois at Urbana-Champaign

    Blue Waters Symposium, Sunriver, OR, June 4, 2018

  • Wires Within Wires

    Mansbach, Rachael

    Motivation

    Patchy Model

    Results

    Conclusions and Future Work

    π-conjugated self-assembling optoelectronic peptides

    Wall, Brian D., et al. “Supramolecular Polymorphism: Tunable Electronic Interactions within π-Conjugated Peptide Nanostructures Dictated by Primary Amino Acid Sequence.” Langmuir30.20 (2014): 5946-5956.

    www.imore.com/sites/imore.com/files/styles/large/

    public/topic_images/2015/

    Galagan, Y.,& Andriessen, R. (2012). “Organic photovoltaics: technologies and manufacturing.” INTECH Open AccessPublisher.

    topic-apple-watch-all.png?itok=OUtlCphV2 / 15

    www.imore.com/sites/imore.com/files/styles/large/public/topic_images/2015/ www.imore.com/sites/imore.com/files/styles/large/public/topic_images/2015/ topic-apple-watch-all.png?itok=OUtlCphV

  • Wires Within Wires

    Mansbach, Rachael

    Motivation

    Patchy Model

    Results

    Conclusions and Future Work

    π-conjugated self-assembling optoelectronic peptides

    Wall, Brian D., et al. “Supramolecular Polymorphism: Tunable Electronic Interactions within π-Conjugated Peptide Nanostructures Dictated by Primary Amino Acid Sequence.” Langmuir30.20 (2014): 5946-5956.

    www.imore.com/sites/imore.com/files/styles/large/

    public/topic_images/2015/

    Galagan, Y.,& Andriessen, R. (2012). “Organic photovoltaics: technologies and manufacturing.” INTECH Open AccessPublisher.

    topic-apple-watch-all.png?itok=OUtlCphV2 / 15

    www.imore.com/sites/imore.com/files/styles/large/public/topic_images/2015/ www.imore.com/sites/imore.com/files/styles/large/public/topic_images/2015/ topic-apple-watch-all.png?itok=OUtlCphV

  • Wires Within Wires

    Mansbach, Rachael

    Motivation

    Patchy Model

    Results

    Conclusions and Future Work

    π-conjugated self-assembling optoelectronic peptides

    Wall, Brian D., et al. “Supramolecular Polymorphism: Tunable Electronic Interactions within π-Conjugated Peptide Nanostructures Dictated by Primary Amino Acid Sequence.” Langmuir30.20 (2014): 5946-5956.

    www.imore.com/sites/imore.com/files/styles/large/

    public/topic_images/2015/

    Galagan, Y.,& Andriessen, R. (2012). “Organic photovoltaics: technologies and manufacturing.” INTECH Open AccessPublisher.

    topic-apple-watch-all.png?itok=OUtlCphV2 / 15

    www.imore.com/sites/imore.com/files/styles/large/public/topic_images/2015/ www.imore.com/sites/imore.com/files/styles/large/public/topic_images/2015/ topic-apple-watch-all.png?itok=OUtlCphV

  • Wires Within Wires

    Mansbach, Rachael

    Motivation

    Patchy Model

    Results

    Conclusions and Future Work

    DXXX series demonstrates hierarchical assembly

    Optical Clusters

    Contact Clusters

    3 / 15

  • Wires Within Wires

    Mansbach, Rachael

    Motivation

    Patchy Model

    Results

    Conclusions and Future Work

    DXXX series demonstrates hierarchical assembly

    Optical Clusters Contact Clusters

    3 / 15

  • Wires Within Wires

    Mansbach, Rachael

    Motivation

    Patchy Model

    Results

    Conclusions and Future Work

    Reaching longer time and length scales

    Minimal coarse-grained model

    Large computational infrastructure

    Do parameter sweep over well depths and radii to gain understanding of effect of different interaction parameters on assembly at mesoscale

    4 / 15

  • Wires Within Wires

    Mansbach, Rachael

    Motivation

    Patchy Model

    Results

    Conclusions and Future Work

    Reaching longer time and length scales

    Minimal coarse-grained model

    Large computational infrastructure

    Do parameter sweep over well depths and radii to gain understanding of effect of different interaction parameters on assembly at mesoscale

    4 / 15

  • Wires Within Wires

    Mansbach, Rachael

    Motivation

    Patchy Model

    Results

    Conclusions and Future Work

    Understanding chemical interactions at low resolution

    Minimal coarse-grained model

    Large computational infrastructure

    Do parameter sweep over well depths and radii to gain understanding of effect of different interaction parameters on assembly at mesoscale

    5 / 15

  • Wires Within Wires

    Mansbach, Rachael

    Motivation

    Patchy Model

    Results

    Conclusions and Future Work

    Aggregate shape and fractal dimension match previous work

    Ardona, Herdeline Ann M., and John D. Tovar. “Energy transfer within responsive π-conjugated coassembled peptide-based nanostructures in aqueous

    environments.” Chemical Science 6.2 (2015): 1474-1484. 6 / 15

  • Wires Within Wires

    Mansbach, Rachael

    Motivation

    Patchy Model

    Results

    Conclusions and Future Work

    Interaction parameters control aggregate morphology

    Increasing side chain stickiness increases disorder

    Side chain size controls transition between flat ribbon and twisted fibril

    7 / 15

  • Wires Within Wires

    Mansbach, Rachael

    Motivation

    Patchy Model

    Results

    Conclusions and Future Work

    Optical cluster growth is primarily controlled by side chain interactivity

    Optical Cluster Growth

    Increasing side chain well depth increases favorability of side chain–side chain interactions

    Biggest increase as side chain interactivity decreases below core–core interactivity

    8 / 15

  • Wires Within Wires

    Mansbach, Rachael

    Motivation

    Patchy Model

    Results

    Conclusions and Future Work

    Side chain radius affects contact cluster growth more strongly

    Contact Cluster Growth Fewer configurations

    Increasing cross-section

    9 / 15

  • Wires Within Wires

    Mansbach, Rachael

    Motivation

    Patchy Model

    Results

    Conclusions and Future Work

    Identification of optimal parameter sets

    Pareto frontier

    Tradeoff between different objectives 10 / 15

  • Wires Within Wires

    Mansbach, Rachael

    Motivation

    Patchy Model

    Results

    Conclusions and Future Work

    Five candidates flagged for future study

    11 / 15

  • Wires Within Wires

    Mansbach, Rachael

    Motivation

    Patchy Model

    Results

    Conclusions and Future Work

    Next steps: Active Learning

    Brochu, Eric, Vlad M. Cora, and Nando De Freitas. “A tutorial on Bayesian optimization of expensive cost functions, with application to active user modeling and

    hierarchical reinforcement learning.” arXiv preprint arXiv:1012.2599 (2010). 12 / 15

  • Wires Within Wires

    Mansbach, Rachael

    Motivation

    Patchy Model

    Results

    Conclusions and Future Work

    Next steps: Active Learning

    Brochu, Eric, Vlad M. Cora, and Nando De Freitas. “A tutorial on Bayesian optimization of expensive cost functions, with application to active user modeling and

    hierarchical reinforcement learning.” arXiv preprint arXiv:1012.2599 (2010). 12 / 15

  • Wires Within Wires

    Mansbach, Rachael

    Motivation

    Patchy Model

    Results

    Conclusions and Future Work

    Next steps: Active Learning

    Brochu, Eric, Vlad M. Cora, and Nando De Freitas. “A tutorial on Bayesian optimization of expensive cost functions, with application to active user modeling and

    hierarchical reinforcement learning.” arXiv preprint arXiv:1012.2599 (2010). 12 / 15

  • Wires Within Wires

    Mansbach, Rachael

    Motivation

    Patchy Model

    Results

    Conclusions and Future Work

    Why Blue Waters?

    Scale of problem

    300 simulations of 10,648 monomers Each simulation requires multiple GPU acceleration and produces 10-20 gigabytes of data to be analyzed

    Big data research infrastructure

    Access to broader big data community

    https://www.slideshare.net/sergejsgroskovs/

    pragmatism-philosophy-of-science-lecture-slides

    13 / 15

    https://www.slideshare.net/sergejsgroskovs/pragmatism-philosophy-of-science-lecture-slides https://www.slideshare.net/sergejsgroskovs/pragmatism-philosophy-of-science-lecture-slides

  • Wires Within Wires

    Mansbach, Rachael

    Motivation

    Patchy Model

    Results

    Conclusions and Future Work

    Why Blue Waters?

    Scale of problem

    300 simulations of 10,648 monomers Each simulation requires multiple GPU acceleration and produces 10-20 gigabytes of data to be analyzed

    Big data research infrastructure

    Access to broader big data community

    https://www.slideshare.net/sergejsgroskovs/

    pragmatism-philosophy-of-science-lecture-slides

    13 / 15

    https://www.slideshare.net/sergejsgroskovs/pragmatism-philosophy-of-science-lecture