Equilibrium analysis of the efficiency of an autonomous molecular computer

John A. Rose, Russell J. Deaton, Masami Hagiya, and Akira Suyama
Phys. Rev. E 65, 021910 – Published 25 January 2002
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Abstract

In the whiplash polymerase chain reaction (WPCR), autonomous molecular computation is implemented in vitro by the recursive, self-directed polymerase extension of a mixture of DNA hairpins. Although computational efficiency is known to be reduced by a tendency for DNAs to self-inhibit by backhybridization, both the magnitude of this effect and its dependence on the reaction conditions have remained open questions. In this paper, the impact of backhybridization on WPCR efficiency is addressed by modeling the recursive extension of each strand as a Markov chain. The extension efficiency per effective polymerase-DNA encounter is then estimated within the framework of a statistical thermodynamic model. Model predictions are shown to provide close agreement with the premature halting of computation reported in a recent in vitro WPCR implementation, a particularly significant result, given that backhybridization had been discounted as the dominant error process. The scaling behavior further indicates completion times to be sufficiently long to render WPCR-based massive parallelism infeasible. A modified architecture, PNA-mediated WPCR (PWPCR) is then proposed in which the occupancy of backhybridized hairpins is reduced by targeted PNA2/DNA triplex formation. The efficiency of PWPCR is discussed using a modified form of the model developed for WPCR. Predictions indicate the PWPCR efficiency is sufficient to allow the implementation of autonomous molecular computation on a massive scale.

  • Received 1 November 2000

DOI:https://doi.org/10.1103/PhysRevE.65.021910

©2002 American Physical Society

Authors & Affiliations

John A. Rose*

  • Institute of Physics, The University of Tokyo, Tokyo 153-8902, Japan

Russell J. Deaton

  • Department of Computer Science and Computer Engineering, The University of Arkansas, Fayetteville, Arkansas 72701

Masami Hagiya

  • Department of Computer Science, The University of Tokyo, Tokyo 113-0033, Japan

Akira Suyama§

  • Institute of Physics, The University of Tokyo, Tokyo 153-8902, Japan

  • *Electronic address: johnrose@genta.c.u-tokyo.ac.jp; URL:http://hagi.is.s.u-tokyo.ac.jp/johnrose
  • Electronic address: rdeaton@uark.edu;URL:http://csce.uark.edu/~rdeaton/
  • Electronic address: hagiya@is.s.u-tokyo.ac.jp; URL:http://hagi.is.s.u-tokyo.ac.jp/
  • §Electronic address: suyama@dna.c.u-tokyo.ac.jp; URL:http://talent.c.u-tokyo.ac.jp/suyama/

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Issue

Vol. 65, Iss. 2 — February 2002

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