CRN++: Molecular Programming Language

TL;DR

CRN++ is a novel programming language designed for deterministic chemical kinetics, enabling the embedding of computational algorithms into molecular systems with minimized error, thus advancing molecular programming capabilities.

Contribution

It introduces a new language, CRN++, with syntax, semantics, and a compiler, facilitating the implementation of molecular algorithms with error analysis tools.

Findings

Successfully implemented classical algorithms in CRN++

Demonstrated minimized error in molecular computations

Provided a flexible framework for future molecular programming

Abstract

Synthetic biology is a rapidly emerging research area, with expected wide-ranging impact in biology, nanofabrication, and medicine. A key technical challenge lies in embedding computation in molecular contexts where electronic micro-controllers cannot be inserted. This necessitates effective representation of computation using molecular components. While previous work established the Turing-completeness of chemical reactions, defining representations that are faithful, efficient, and practical remains challenging. This paper introduces CRN++, a new language for programming deterministic (mass-action) chemical kinetics to perform computation. We present its syntax and semantics, and build a compiler translating CRN++ programs into chemical reactions, thereby laying the foundation of a comprehensive framework for molecular programming. Our language addresses the key challenge of embedding familiar imperative constructs into a set of chemical reactions happening simultaneously and manipulating real-valued concentrations. Although some deviation from ideal output value cannot be avoided, we develop methods to minimize the error, and implement error analysis tools. We demonstrate the feasibility of using CRN++ on a suite of well-known algorithms for discrete and real-valued computation. CRN++ can be easily extended to support new commands or chemical reaction implementations, and thus provides a foundation for developing more robust and practical molecular programs.