Optimization of Enzymatic Biochemical Logic for Noise Reduction and Scalability: How Many Biocomputing Gates Can Be Interconnected in a Circuit?

TL;DR

This paper experimentally evaluates biochemical AND gates, models their behavior, and proposes an optimization approach to minimize noise, demonstrating potential for scalable biochemical computing up to ten concatenated gates.

Contribution

It introduces a rate-equation model for biochemical logic gates and identifies optimal parameters for noise reduction, enabling scalable gate concatenation.

Findings

Biochemical AND gates can be concatenated for up to 10 steps under optimized conditions.

A rate-equation model effectively describes the gate's input-output behavior.

The study highlights the need for new paradigms beyond 10 gates to prevent noise accumulation.

Abstract

We report an experimental evaluation of the "input-output surface" for a biochemical AND gate. The obtained data are modeled within the rate-equation approach, with the aim to map out the gate function and cast it in the language of logic variables appropriate for analysis of Boolean logic for scalability. In order to minimize "analog" noise, we consider a theoretical approach for determining an optimal set for the process parameters to minimize "analog" noise amplification for gate concatenation. We establish that under optimized conditions, presently studied biochemical gates can be concatenated for up to order 10 processing steps. Beyond that, new paradigms for avoiding noise build-up will have to be developed. We offer a general discussion of the ideas and possible future challenges for both experimental and theoretical research for advancing scalable biochemical computing.