Abstract
Hybrid biomimetic nanosensors use selective polymeric and biological materials that integrate flexible recognition moieties with nanometer size transducers. These sensors have the potential to offer the building blocks for a universal sensing platform. Their vast range of chemistries and high conformational flexibility present both a problem and an opportunity. Nonetheless, it has been shown that oligopeptide aptamers from sequenced genes can be robust substrates for the selective recognition of specific chemical species. Here we present first principles molecular modeling approaches tailored to peptide sequences suitable for the selective discrimination of small molecules on nanowire arrays. The modeling strategy is fully atomistic. The excellent performance of these sensors, their potential biocompatibility combined with advanced mechanistic modeling studies, could potentially lead to applications such as: unobtrusive implantable medical sensors for disease diagnostics, light weight multi-purpose sensing devices for aerospace applications, ubiquitous environmental monitoring devices in urban and rural areas, and inexpensive smart packaging materials for active in-situ food safety labeling.
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References
McAlpine, M. C.; Ahmad, H.; Wang, D.; Heath, J. R., Highly ordered nanowire arrays on plastic substrates for ultrasensitive flexible chemical sensors, Nat. Mat. 2007, 6, 379–384
McAlpine, M. C.; Agnew, H. D.; Rohde, R. D.; Blanco, M.; Ahmad, H.; Stuparu, A. D.; Goddard, W. A.; Heath, J. R., Peptide-nanowire hybrid materials for selective sensing of small molecules, J. Am. Chem. Soc. 2008, 130, 9583–9589
Chan, W. C.; White, P. D., Fmoc Solid Phase Peptide Synthesis: A Practical Approach; Oxford University Press, Oxford, 2000
Belmares, M.; Blanco, M.; Goddard, W. A.; Ross, R. B.; Caldwell, G.; Chou, S. H.; Pham, J.; Olofson, P. M.; Thomas, C., Hildebrand and Hansen solubility parameters from molecular dynamics with applications to electronic nose polymer sensors, J. Comput. Chem. 2004, 25, 1814–1826
Cozmuta, I.; Blanco, M.; Goddard, W. A., Gas sorption and barrier properties of polymeric membranes from molecular dynamics and Monte Carlo simulations, J. Phys. Chem. B 2007, 111, 3151–3166
Wu, T.-Z.; Lo, Y.-R.; Chan, E.-C., Exploring the recognized bio-mimicry materials for gas sensing Biosens. Bioelectron. 2001, 16, 945–953
Mayo, S. L.; Olafson, B. D.; Goddard, W. A., Dreiding – A generic force-field for molecular simulations. J. Phys. Chem. 1990, 94, 8897–8909
Lee, C. T.; Yang, W. T.; Parr, R. G., Development of the colle-salvetti correlation-energy formula into a functional of the electron-density, Phys. Rev. B 1988, 37, 785–789
Becke, A. D., Density-functional thermochemistry 3. The role of exact exchange. J. Chem. Phys. 1993, 98, 5648–5652
Venkatchalam, C. M., Cerius2 User' Manual, 4.10 edn.; Accelrys, Inc., San Diego, CA, 2005
Blanco, M., Molecular silverware. I. General solutions to excluded volume constrained problems, J. Comput. Chem. 1991, 12, 237–247
Accelrys, I.; 4.01 edn.; Accelrys, Inc., San Diego, CA, 2005
Hu, G. Q.; Quaranta, V.; Li, D. Q., Modeling of effects of nutrient gradients on cell proliferation in microfluidic bioreactor, Biotechnol. Prog. 2007, 23, 1347–1354
McAlpine, M.C.; Agnew, H.D.; Rohde, R.D.; Mario Blanco, M.; Ahmad, H.; Stuparu, A.D.; Goddard, W.A.; and Heath, J.R., J. Am. Chem. Soc. 2008, 130 (29), 9583–9589
Acknowledgments
This work was partly supported by the Materials and Process Simulation Center, Beckman Institute at the California Institute of Technology.
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Blanco, M., McAlpine, M.C., Heath, J.R. (2009). First Principles Molecular Modeling of Sensing Material Selection for Hybrid Biomimetic Nanosensors. In: Ryan, M., Shevade, A., Taylor, C., Homer, M., Blanco, M., Stetter, J. (eds) Computational Methods for Sensor Material Selection. Integrated Analytical Systems. Springer, New York, NY. https://doi.org/10.1007/978-0-387-73715-7_6
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DOI: https://doi.org/10.1007/978-0-387-73715-7_6
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