Artificial chemistry approach to exploring search spaces using Artificial Reaction Network agents

Advances in automation and data analytics can aid exploration of the complex chemistry of nanoparticles. Lead halide perovskite colloidal nanocrystals provide an interesting proving ground: there are reports of many different phases and transformations, which has made it hard to form a coherent conceptual framework for their controlled formation through traditional methods. In this work, we systematically explore the portion of Cs-Pb-Br synthesis space in which many optically distinguishable species are formed using high-throughput robotic synthesis to understand their formation reactions. We deploy an automated method that allows us to determine the relative amount of absorbance that can be attributed to each species in order to create maps of the synthetic space. These in turn facilitate improved understanding of the interplay between kinetic and thermodynamic factors that underlie which combination of species are likely to be prevalent under a given set of conditions. Based on these maps, we test potential transformation routes between perovskite nanocrystals of different shapes and phases. We find that shape is determined kinetically, but many reactions between different phases show equilibrium behavior. We demonstrate a dynamic equilibrium between complexes, monolayers and nanocrystals of lead bromide, with substantial impact on the reaction outcomes. This allows us to construct a chemical reaction network that qualitatively explains our results as well as previous reports and can serve as a guide for those seeking to prepare a particular composition and shape.

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Synthesis and Breakdown of the Universal Precursors to Biological Metabolism Promoted by Ferrous Iron

10.26434/chemrxiv.7178930.v1 ◽

2018 ◽

Cited By ~ 1

Author(s):

Kamila B. Muchowska ◽

Sreejith Jayasree VARMA ◽

Joseph Moran

Keyword(s):

Amino Acids ◽

Chemical Reaction ◽

Metabolic Pathways ◽

Ferrous Iron ◽

Reaction Network ◽

Tca Cycle ◽

Chemical Reaction Network ◽

Metabolic Precursors ◽

Tca Cycle Intermediates

How core biological metabolism initiated and why it uses the intermediates, reactions and pathways that it does remains unclear. Life builds its molecules from CO2 and breaks them down to CO2 again through the intermediacy of just five metabolites that act as the hubs of biochemistry. Here, we describe a purely chemical reaction network promoted by Fe2+ in which aqueous pyruvate and glyoxylate, two products of abiotic CO2 reduction, build up nine of the eleven TCA cycle intermediates, including all five universal metabolic precursors. The intermediates simultaneously break down to CO2 in a life-like regime resembling biological anabolism and catabolism. Introduction of hydroxylamine and Fe0 produces four biological amino acids. The network significantly overlaps the TCA/rTCA and glyoxylate cycles and may represent a prebiotic precursor to these core metabolic pathways.

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A flux-based stoichiometric model of enhanced biological phosphorus removal metabolism

Water Science & Technology ◽

10.2166/wst.1998.0727 ◽

1998 ◽

Vol 37 (4-5) ◽

pp. 609-613

Author(s):

J. Pramanik ◽

P. L. Trelstad ◽

J. D. Keasling

Keyword(s):

Phosphorus Removal ◽

Reaction Network ◽

Bacterial Biomass ◽

Enhanced Biological Phosphorus Removal ◽

Biological Phosphorus Removal ◽

Stoichiometric Model ◽

Aerobic Reactor ◽

Complete Set ◽

Biological Phosphorus

Enhanced biological phosphorus removal (EBPR) in wastewater treatment involves metabolic cycling through the biopolymers polyphosphate (polyP), polyhydroxybutyrate (PHB), and glycogen. This cycling is induced through treatment systems that alternate between carbon-rich anaerobic and carbon-poor aerobic reactor basins. While the appearance and disappearance of these biopolymers has been documented, the intracellular pressures that regulate their synthesis and degradation are not well understood. Current models of the EBPR process have examined a limited number of metabolic pathways that are frequently lumped into an even smaller number of “reactions.” This work, on the other hand, uses a stoichiometric model that contains a complete set of the pathways involved in bacterial biomass synthesis and energy production to examine EBPR metabolism. Using the stoichiometric model we were able to analyze the role of EBPR metabolism within the larger context of total cellular metabolism, as well as predict the flux distribution of carbon and energy fluxes throughout the total reaction network. The model was able to predict the consumption of PHB, the degradation of polyP, the uptake of acetate and the release of Pi. It demonstrated the relationship between acetate uptake and Pi release, and the effect of pH on this relationship. The model also allowed analysis of growth metabolism with respect to EBPR.

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ADAPTAÇÃO E APLICAÇÃO DE MÉTODOS DE INTELIGÊNCIA COMPUTACIONAL PARA A ESTIMAÇÃO DE UMA FONTE DE POLUENTES EM ESTUÁRIOS

Engevista ◽

10.22409/engevista.v17i2.688 ◽

2014 ◽

Vol 17 (2) ◽

pp. 152

Author(s):

Radael De Souza Parolin ◽

Pedro Paulo Gomes Watts Rodrigues ◽

Antônio J. Silva Neto

Keyword(s):

Computational Intelligence ◽

Computational Models ◽

Source Position ◽

Iterative Search ◽

Contaminant Source ◽

Resources Management ◽

Search Spaces ◽

Grid Points ◽

Computational Intelligence Methods

The quality of a given water body can be assessed through the analysis of a number of indicators. Mathematical and computational models can be built to simulate the behavior of these indicators (observable variables), in such a way that different scenarios can be generated, supporting decisions regarding water resources management. In this study, the transport of a conservative contaminant in an estuarine environment is simulated in order to identify the position and intensity of the contaminant source. For this, it was formulated an inverse problem, which was solved through computational intelligence methods. This approach required adaptations to these methods, which had to be modified to relate the source position to the discrete mesh points of the domain. In this context, two adaptive techniques were developed. In one, the estimated points are projected to the grid points, and in the other, points are randomly selected in the iterative search spaces of the methods. The results showed that the methodology here developed has a strong potential in water bodies’ management and simulation.

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Artificial Chemistry and Molecular Darwinian Evolution in silico

Collection of Czechoslovak Chemical Communications ◽

10.1135/cccc20030139 ◽

2003 ◽

Vol 68 (1) ◽

pp. 139-177 ◽

Cited By ~ 4

Author(s):

Vladimír Kvasnička ◽

Jiří Pospíchal

Keyword(s):

Graph Theory ◽

Molecular Level ◽

Stable State ◽

Chemical Reactor ◽

Darwinian Evolution ◽

Simplified Model ◽

Asymptotically Stable ◽

Artificial Chemistry ◽

Neutral Mutations ◽

Binary Strings

A simplified model of Darwinian evolution at the molecular level is studied by applying the methods of artificial chemistry. A chemical reactor (chemostat) contains molecules that are represented by binary strings, the strings being capable of replication with a probability proportional to their fitness. Moreover, the process of replication is not fully precise, sporadic mutations may produce new offspring strings, which are slightly different from their parent templates. The dynamics of such an autoreplicating system is described by Eigen's differential equations. These equations have a unique asymptotically stable state, which corresponds to those strings that have the highest rate constants (fitness). Fitness of binary string is calculated as a graph-theory similarity between a folding (phenotype) of respective string and the so-called required folding. The presented method offers a detailed view of mechanisms of the molecular Darwinian evolution, in particular of the meaning and importance of neutral mutations.

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Is There Life in Possible Worlds?

10.1093/oso/9780198803478.003.0007 ◽

2017 ◽

Author(s):

Mark Wilson

Keyword(s):

Possible Worlds ◽

Machine Design ◽

Lagrangian Mechanics ◽

Philosophical Investigations ◽

Search Spaces ◽

Dimensional Modeling ◽

Lower Dimensional

Scientists have developed various collections of specialized possibilities to serve as search spaces in which excessive reliance upon speculative forms of lower dimensional modeling or other unwanted details can be skirted. Two primary examples are discussed: the search spaces of machine design and the virtual variations utilized within Lagrangian mechanics. Contemporary appeals to “possible worlds” attempt to imbed these localized possibilities within fully enunciated universes. But not all possibilities are made alike and these reductive schemes should be resisted, on the grounds that they render the utilities of everyday counterfactuals and “possibility” talk incomprehensible. The essay also discusses whether Wittgenstein’s altered views in his Philosophical Investigations reflect similar concerns.

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Hidden in its color: A molecular-level analysis of the beer’s Maillard reaction network

Food Chemistry ◽

10.1016/j.foodchem.2021.130112 ◽

2021 ◽

pp. 130112

Author(s):

Stefan A. Pieczonka ◽

Daniel Hemmler ◽

Franco Moritz ◽

Marianna Lucio ◽

Martin Zarnkow ◽

...

Keyword(s):

Maillard Reaction ◽

Molecular Level ◽

Reaction Network ◽

Level Analysis

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Tandem synthesis of tetrahydroquinolines and identification of reaction network by operando NMR

Catalysis Science & Technology ◽

10.1039/d1cy00418b ◽

2021 ◽

Author(s):

Jingwen Chen ◽

Long Qi ◽

Biying Zhang ◽

Minda Chen ◽

Takeshi Kobayashi ◽

...

Keyword(s):

Reaction Mechanism ◽

Complex Network ◽

Reaction Network ◽

Tandem Reactions ◽

Organic P ◽

Design And Optimization ◽

Metal Organic ◽

Tandem Synthesis

The study of the reaction mechanism and complex network for heterogeneously catalyzed tandem reactions is challenging but can guide reaction design and optimization. Here, we describe using a bifunctional metal-organic...

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A CRISPR-Cas autocatalysis-driven feedback amplification network for supersensitive DNA diagnostics

Science Advances ◽

10.1126/sciadv.abc7802 ◽

2021 ◽

Vol 7 (5) ◽

pp. eabc7802

Author(s):

Kai Shi ◽

Shiyi Xie ◽

Renyun Tian ◽

Shuo Wang ◽

Qin Lu ◽

...

Keyword(s):

Nucleic Acid ◽

Genomic Dna ◽

Reaction Network ◽

Clinical Samples ◽

Great Promise ◽

Base Specificity ◽

Nucleotide Mutation ◽

Positive Feedback Circuit ◽

Stringent Target ◽

And Function

Artificial nucleic acid circuits with precisely controllable dynamic and function have shown great promise in biosensing, but their utility in molecular diagnostics is still restrained by the inability to process genomic DNA directly and moderate sensitivity. To address this limitation, we present a CRISPR-Cas–powered catalytic nucleic acid circuit, namely, CRISPR-Cas–only amplification network (CONAN), for isothermally amplified detection of genomic DNA. By integrating the stringent target recognition, helicase activity, and trans-cleavage activity of Cas12a, a Cas12a autocatalysis-driven artificial reaction network is programmed to construct a positive feedback circuit with exponential dynamic in CONAN. Consequently, CONAN achieves one-enzyme, one-step, real-time detection of genomic DNA with attomolar sensitivity. Moreover, CONAN increases the intrinsic single-base specificity of Cas12a, and enables the effective detection of hepatitis B virus infection and human bladder cancer–associated single-nucleotide mutation in clinical samples, highlighting its potential as a powerful tool for disease diagnostics.

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