Collaborating Authors

Design of a P System based Artificial Graph Chemistry Artificial Intelligence

Artificial Chemistries (ACs) are symbolic chemical metaphors for the exploration of Artificial Life, with specific focus on the origin of life. In this work we define a P system based artificial graph chemistry to understand the principles leading to the evolution of life-like structures in an AC set up and to develop a unified framework to characterize and classify symbolic artificial chemistries by devising appropriate formalism to capture semantic and organizational information. An extension of P system is considered by associating probabilities with the rules providing the topological framework for the evolution of a labeled undirected graph based molecular reaction semantics.

Thoughts on an Unified Framework for Artificial Chemistries Artificial Intelligence

Artificial Chemistries (ACs) are symbolic chemical metaphors for the exploration of Artificial Life, with specific focus on the problem of biogenesis or the origin of life. This paper presents authors thoughts towards defining a unified framework to characterize and classify symbolic artificial chemistries by devising appropriate formalism to capture semantic and organizational information. We identify three basic high level abstractions in initial proposal for this framework viz., information, computation, and communication. We present an analysis of two important notions of information, namely, Shannon's Entropy and Algorithmic Information, and discuss inductive and deductive approaches for defining the framework.

Origin-of-Life Study Points to Chemical Chimeras, Not RNA Quanta Magazine


Scientists studying how life arose from the primordial soup have been too eager to clean up the clutter. Four billion years ago, the prebiotic Earth was a messy place, a chaotic mélange of diverse starting materials. Even so, certain key molecules still somehow managed to emerge from that chemical mayhem -- RNA, DNA and proteins among them. But in the quest to understand how that happened, according to Ramanarayanan Krishnamurthy, a chemist at the Scripps Research Institute in California, researchers have been so myopic in their focus on reactions that generate molecules relevant to the planet's current inhabitants that they've overlooked other possibilities. "They are trying to impose biology today on prebiotic chemistry," he said.

Synthetic connectivity, emergence, and self-regeneration in the network of prebiotic chemistry


Chemists seeking to understand the origins of life have published a wide range of reactions that may have yielded the building blocks of proteins, nucleic acids, and lipids from simple precursors. Wołos et al. scoured the literature to document each such reaction class and then wrote software that applied the reactions first to the simplest compounds such as cyanide, water, and ammonia, and then iteratively to each successive generation of products. The resulting network predicted a variety of previously unappreciated routes to biochemically relevant compounds, several of which the authors validated experimentally. Science , this issue p. [eaaw1955][1] ### INTRODUCTION Although hundreds of organic reactions have been validated under consensus prebiotic conditions, we still have only a fragmentary understanding of how these individual steps combined into complete synthetic pathways to generate life’s building blocks, which other abiotic molecules might have also formed, how independent reactions gave rise to chemical systems, and how membranes encapsulating these systems came into being. Answering such questions requires consideration of very large numbers of possible synthetic pathways. Starting with even a few primordial substrates—e.g., H2O, N2, HCN, NH3, CH4, and H2S—the number of prebiotically synthesizable molecules grows rapidly into the tens of thousands. Detailed analysis of this space and its synthetic connectivity may be beyond the cognition of individual chemists but can be performed by smart computer algorithms. ### RATIONALE We harnessed the power of computer-assisted organic synthesis to map the network of molecules that are synthesizable from basic prebiotic feedstocks. This was done by encoding currently known prebiotic reactions in a machine-readable format, augmenting these reaction transforms with information about incompatible groups and reaction conditions, and then applying them iteratively to a set of basic prebiotic substrates. The reaction network thus created was queried by algorithms to identify complete synthetic routes as well as those tracing reaction systems—notably, reaction cycles. All calculations were supported by a software application that is freely available to the scientific community. ### RESULTS We demonstrate that this network comprises more abiotic molecules than biotic molecules. The biotic compounds differ from the abiotic compounds in several ways: They are more hydrophilic, more thermodynamically stable, and more balanced in terms of the hydrogen bond donors and acceptors they contain and are synthesizable along routes with fewer changes of conditions. The network contains not only all known syntheses of biotic compounds but also previously unidentified routes, several of which (e.g., prebiotic syntheses of acetaldehyde and diglycine, as well as malic, fumaric, citric, and uric acids) we validated by experiment. We also demonstrate three notable forms of chemical emergence: (i) that the molecules created within the network can themselves enable new types of prebiotic reactions; (ii) that within just a few synthetic generations, simple chemical systems (including self-regenerating cycles) begin to emerge; and (iii) that the network contains prebiotic routes to surfactant species, thus outlining a path to biological compartmentalization. We support these conclusions with experimental results, establishing previously undescribed prebiotic reactions and entire reaction systems—notably, a self-regenerating cycle of iminodiacetic acid. ### CONCLUSION Computer-generated reaction networks are useful in identifying synthetic routes to prebiotically relevant targets and are indispensable for the discovery of prebiotic chemical systems that are otherwise challenging to discern. As our network continues to grow by means of crowd-sourcing of newly validated prebiotic reactions, it will allow continued simulation of chemical genesis, beginning with molecules as simple as water, ammonia, and methane and leading to increasingly complex targets, including those of current interest in the chemical and pharmaceutical industries. ![Figure][2] Network of prebiotic chemistry. Computer simulation of plausible prebiotic reactions creates a network of molecules that are synthesizable from prebiotic feedstocks and establishes multiple unreported—but now experimentally validated—syntheses of prebiotic targets as well as self-regenerating cycles. In this schematic illustration, light blue nodes represent abiotic molecules, dark blue nodes represent molecules along newly discovered prebiotic syntheses of uric and citric acids, and red nodes represent other biotic molecules. The challenge of prebiotic chemistry is to trace the syntheses of life’s key building blocks from a handful of primordial substrates. Here we report a forward-synthesis algorithm that generates a full network of prebiotic chemical reactions accessible from these substrates under generally accepted conditions. This network contains both reported and previously unidentified routes to biotic targets, as well as plausible syntheses of abiotic molecules. It also exhibits three forms of nontrivial chemical emergence, as the molecules within the network can act as catalysts of downstream reaction types; form functional chemical systems, including self-regenerating cycles; and produce surfactants relevant to primitive forms of biological compartmentalization. To support these claims, computer-predicted, prebiotic syntheses of several biotic molecules as well as a multistep, self-regenerative cycle of iminodiacetic acid were validated by experiment. [1]: /lookup/doi/10.1126/science.aaw1955 [2]: pending:yes

Motility at the origin of life: Its characterization and a model Artificial Intelligence

Due to recent advances in synthetic biology and artificial life, the origin of life is currently a hot topic of research. We review the literature and argue that the two traditionally competing "replicator-first" and "metabolism-first" approaches are merging into one integrated theory of individuation and evolution. We contribute to the maturation of this more inclusive approach by highlighting some problematic assumptions that still lead to an impoverished conception of the phenomenon of life. In particular, we argue that the new consensus has so far failed to consider the relevance of intermediate timescales. We propose that an adequate theory of life must account for the fact that all living beings are situated in at least four distinct timescales, which are typically associated with metabolism, motility, development, and evolution. On this view, self-movement, adaptive behavior and morphological changes could have already been present at the origin of life. In order to illustrate this possibility we analyze a minimal model of life-like phenomena, namely of precarious, individuated, dissipative structures that can be found in simple reaction-diffusion systems. Based on our analysis we suggest that processes in intermediate timescales could have already been operative in prebiotic systems. They may have facilitated and constrained changes occurring in the faster- and slower-paced timescales of chemical self-individuation and evolution by natural selection, respectively.