scholarly journals A mechanism of abiogenesis based on complex reaction networks organized by seed-dependent autocatalytic systems

2021 ◽  
Author(s):  
Zhen Peng ◽  
Jeff Linderoth ◽  
David Baum
Keyword(s):  
Reaction Networks ◽  
Food Utilization ◽  
Complex Reaction ◽  
Chemical Systems ◽  
Promising Strategy ◽  
Underlying Basis ◽  
Scientific Questions ◽  
Emergence Of Life

The complexity gap between the biotic and abiotic worlds has made explaining abiogenesis one of the hardest scientific questions. A promising strategy for addressing this problem is to identify features shared by abiotic and biotic chemical systems that permit the stepwise accretion of complexity. Therefore, we compared abiotic and biotic reaction networks in order to evaluate the presence of autocatalysis, the underlying basis of biological self-propagation, and to see if the organization of autocatalytic motifs permits stepwise complexification. We provide an algorithm to detect seed-dependent autocatalytic systems (SDASs), namely subnetworks that can use food chemicals to self-propagate but must be seeded by some non-food chemicals to become activated. We show that serial activation of SDASs can cause incremental complexification. Furthermore, we identify life-like features that emerge during the accretion of SDASs, including the emergence of new ecological opportunities and improvements in the efficiency of food utilization. The SDAS concept explains how driven abiotic environments, namely ones receiving an ongoing flux of food chemicals, can incrementally complexify without the need for genetic polymers. This framework also suggests experiments that have the potential to detect the spontaneous emergence of life-like features, such as self-propagation and adaptability, in driven chemical systems.

scholarly journals A mechanism of abiogenesis based on complex reaction networks organized by seed-dependent autocatalytic systems

2021 ◽  
Author(s):  
Zhen Peng ◽  
Jeff Linderoth ◽  
David Baum
Keyword(s):  
Reaction Networks ◽  
Food Utilization ◽  
Complex Reaction ◽  
Chemical Systems ◽  
Promising Strategy ◽  
Underlying Basis ◽  
Scientific Questions ◽  
Emergence Of Life

The complexity gap between the biotic and abiotic worlds has made explaining abiogenesis one of the hardest scientific questions. A promising strategy for addressing this problem is to identify features shared by abiotic and biotic chemical systems that permit the stepwise accretion of complexity. Therefore, we compared abiotic and biotic reaction networks in order to evaluate the presence of autocatalysis, the underlying basis of biological self-propagation, and to see if the organization of autocatalytic motifs permits stepwise complexification. We provide an algorithm to detect seed-dependent autocatalytic systems (SDASs), namely subnetworks that can use food chemicals to self-propagate but must be seeded by some non-food chemicals to become activated. We show that serial activation of SDASs can cause incremental complexification. Furthermore, we identify life-like features that emerge during the accretion of SDASs, including the emergence of new ecological opportunities and improvements in the efficiency of food utilization. The SDAS concept explains how driven abiotic environments, namely ones receiving an ongoing flux of food chemicals, can incrementally complexify without the need for genetic polymers. This framework also suggests experiments that have the potential to detect the spontaneous emergence of life-like features, such as self-propagation and adaptability, in driven chemical systems.

scholarly journals Autocatalytic and oscillatory reaction networks that form guanidines and products of their cyclization

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Alexander I. Novichkov ◽  
Anton I. Hanopolskyi ◽  
Xiaoming Miao ◽  
Linda J. W. Shimon ◽  
Yael Diskin-Posner ◽  
...  
Keyword(s):  
Chemical Cues ◽  
Native Chemical Ligation ◽  
Reaction Networks ◽  
Oscillatory Reaction ◽  
Experimental Conditions ◽  
Chemical Ligation ◽  
Chemical Systems ◽  
Life On Earth ◽  
Emergence Of Life ◽  
Equilibrium Chemical

AbstractAutocatalytic and oscillatory networks of organic reactions are important for designing life-inspired materials and for better understanding the emergence of life on Earth; however, the diversity of the chemistries of these reactions is limited. In this work, we present the thiol-assisted formation of guanidines, which has a mechanism analogous to that of native chemical ligation. Using this reaction, we designed autocatalytic and oscillatory reaction networks that form substituted guanidines from thiouronium salts. The thiouronium salt-based oscillator show good stability of oscillations within a broad range of experimental conditions. By using nitrile-containing starting materials, we constructed an oscillator where the concentration of a bicyclic derivative of dihydropyrimidine oscillates. Moreover, the mixed thioester and thiouronium salt-based oscillator show unique responsiveness to chemical cues. The reactions developed in this work expand our toolbox for designing out-of-equilibrium chemical systems and link autocatalytic and oscillatory chemistry to the synthesis of guanidinium derivatives and the products of their transformations including analogs of nucleobases.

scholarly journals A mechanism of abiogenesis based on complex reaction networks organized by seed-dependent autocatalytic systems

2021 ◽  
Author(s):  
Zhen Peng ◽  
Jeff Linderoth ◽  
David Baum
Keyword(s):  
Dissipative System ◽  
Trophic Levels ◽  
Reaction Networks ◽  
Chemical Systems ◽  
The Core ◽  
Lower Tier ◽  
Prebiotic Chemical ◽  
The Origin Of Life ◽  
Emergence Of Life ◽  
Over Time

The core of the origin-of-life problem is to explain how a complex dissipative system could emerge spontaneously from a simple environment, perpetuate itself, and complexify over time. This would only be possible, we argue, if prebiotic chemical reaction networks had autocatalytic features organized in a way that permitted the accretion of complexity even in the absence of genetic control. To evaluate this claim, we developed tools to analyze the autocatalytic organization of food-driven reaction networks and applied these tools to both abiotic and biotic networks. Both networks contained seed-dependent autocatalytic systems (SDASs), which are subnetworks that can use a flux of food chemicals to self-propagate if, and only if, they are first seeded by some non-food chemicals. Moreover, SDASs were organized such that the activation of a lower-tier SDAS could render new higher-tier SDASs accessible. The organization of SDASs is, thus, similar to trophic levels (producer, primary consumer, etc.) in a biological ecosystem. Furthermore, similar to ecological succession, we found that higher-tier SDASs may produce chemicals that enhance the ability of the entire chemical ecosystem to utilize food more efficiently. The SDAS concept explains how driven abiotic environments, namely ones receiving an ongoing flux of food chemicals, can incrementally complexify even without genetic polymers. This framework predicts that it ought to be possible to detect the spontaneous emergence of life-like features, such as self-propagation and adaptability, in driven chemical systems in the laboratory. Additionally, SDAS theory may be useful for exploring general properties of other complex systems.

scholarly journals Self-Reproduction and Darwinian Evolution in Autocatalytic Chemical Reaction Systems

Life ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 308
Author(s):  
Sandeep Ameta ◽  
Yoshiya J. Matsubara ◽  
Nayan Chakraborty ◽  
Sandeep Krishna ◽  
Shashi Thutupalli
Keyword(s):  
Experimental Evolution ◽  
Experimental Studies ◽  
Theoretical Work ◽  
Living System ◽  
Darwinian Evolution ◽  
Chemical System ◽  
Chemical Systems ◽  
Open Questions ◽  
Scientific Questions ◽  
Emergence Of Life

Understanding the emergence of life from (primitive) abiotic components has arguably been one of the deepest and yet one of the most elusive scientific questions. Notwithstanding the lack of a clear definition for a living system, it is widely argued that heredity (involving self-reproduction) along with compartmentalization and metabolism are key features that contrast living systems from their non-living counterparts. A minimal living system may be viewed as “a self-sustaining chemical system capable of Darwinian evolution”. It has been proposed that autocatalytic sets of chemical reactions (ACSs) could serve as a mechanism to establish chemical compositional identity, heritable self-reproduction, and evolution in a minimal chemical system. Following years of theoretical work, autocatalytic chemical systems have been constructed experimentally using a wide variety of substrates, and most studies, thus far, have focused on the demonstration of chemical self-reproduction under specific conditions. While several recent experimental studies have raised the possibility of carrying out some aspects of experimental evolution using autocatalytic reaction networks, there remain many open challenges. In this review, we start by evaluating theoretical studies of ACSs specifically with a view to establish the conditions required for such chemical systems to exhibit self-reproduction and Darwinian evolution. Then, we follow with an extensive overview of experimental ACS systems and use the theoretically established conditions to critically evaluate these empirical systems for their potential to exhibit Darwinian evolution. We identify various technical and conceptual challenges limiting experimental progress and, finally, conclude with some remarks about open questions.

scholarly journals Non-normality and non-monotonic dynamics in complex reaction networks

2020 ◽  
Vol 2 (4) ◽  
Author(s):  
Zachary G. Nicolaou ◽  
Takashi Nishikawa ◽  
Schuyler B. Nicholson ◽  
Jason R. Green ◽  
Adilson E. Motter
Keyword(s):  
Reaction Networks ◽  
Complex Reaction

scholarly journals Uncertainty quantification for quantum chemical models of complex reaction networks

2016 ◽  
Vol 195 ◽  
pp. 497-520 ◽  
Author(s):  
Jonny Proppe ◽  
Tamara Husch ◽  
Gregor N. Simm ◽  
Markus Reiher
Keyword(s):  
Free Energy ◽  
Electronic Structure ◽  
State Space ◽  
Time Scales ◽  
Reaction Network ◽  
Reaction Networks ◽  
Multiple Time Scales ◽  
Complex Reaction ◽  
Discrete State ◽  
Continuous State

For the quantitative understanding of complex chemical reaction mechanisms, it is, in general, necessary to accurately determine the corresponding free energy surface and to solve the resulting continuous-time reaction rate equations for a continuous state space. For a general (complex) reaction network, it is computationally hard to fulfill these two requirements. However, it is possible to approximately address these challenges in a physically consistent way. On the one hand, it may be sufficient to consider approximate free energies if a reliable uncertainty measure can be provided. On the other hand, a highly resolved time evolution may not be necessary to still determine quantitative fluxes in a reaction network if one is interested in specific time scales. In this paper, we present discrete-time kinetic simulations in discrete state space taking free energy uncertainties into account. The method builds upon thermo-chemical data obtained from electronic structure calculations in a condensed-phase model. Our kinetic approach supports the analysis of general reaction networks spanning multiple time scales, which is here demonstrated for the example of the formose reaction. An important application of our approach is the detection of regions in a reaction network which require further investigation, given the uncertainties introduced by both approximate electronic structure methods and kinetic models. Such cases can then be studied in greater detail with more sophisticated first-principles calculations and kinetic simulations.

scholarly journals More and Faster: Simultaneously Improving Reaction Coverage and Computational Cost in Automated Reaction Prediction Tasks

2020 ◽  
Author(s):  
Qiyuan Zhao ◽  
Brett Savoie
Keyword(s):  
Transition State ◽  
Domain Knowledge ◽  
Low Cost ◽  
Computational Cost ◽  
Chemical Degradation ◽  
Reaction Pathways ◽  
Reaction Networks ◽  
Complex Reaction ◽  
Success Rates ◽  
Reaction Prediction

<div> <div> <div> <p>Automated reaction prediction has the potential to elucidate complex reaction networks for applications ranging from combustion to materials degradation. Although substantial progress has been made in predicting specific reaction pathways and resolving mechanisms, the computational cost and inconsistent reaction coverage of automated prediction are still obstacles to exploring deep reaction networks without using heuristics. Here we show that cost can be reduced and reaction coverage can be increased simultaneously by relatively straight- forward modifications of the reaction enumeration, geometry initialization, and transition state convergence algorithms that are common to many emerging prediction methodologies. These changes are implemented in the context of Yet Another Reaction Program (YARP), our reaction prediction package, for which we report a head-to-head comparison with prevailing methods for two benchmark reaction prediction tasks. In all cases, we observe near perfect recapitulation of established reaction pathways and products by YARP, without the use of heuristics or other domain knowledge to guide reaction selection. In addition, YARP also discovers many new kinetically relevant pathways and products reported here for the first time. This is achieved while simultaneously reducing the cost of reaction characterization nearly 100-fold and increasing transition state success rates and intended rates over 2-fold and 10-fold, respectively, compared with recent benchmarks. This combination of ultra-low cost and high reaction-coverage creates opportunities to explore the reactivity of larger sys- tems and more complex reaction networks for applications like chemical degradation, where approaches based on domain heuristics fail. </p> </div> </div> </div>

Complex reaction networks in high temperature hydrocarbon chemistry

2015 ◽  
Vol 17 (12) ◽  
pp. 7972-7985 ◽  
Author(s):  
İbrahim Mutlay ◽  
Albeiro Restrepo
Keyword(s):  
High Temperature ◽  
Complex Network ◽  
Chemical Kinetics ◽  
Network Theory ◽  
Reaction Networks ◽  
Complex Reaction ◽  
Complex Network Theory ◽  
Kinetics Of ◽  
Hydrocarbon Chemistry

Complex network theory reveals novel insights into the chemical kinetics of high temperature hydrocarbon decomposition.

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