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An open source computational workflow for the discovery of autocatalytic networks in abiotic reactions

Arya, Aayush and Ray, Jessica and Sharma, Siddhant and Cruz Simbron, Romulo and Lozano, Alejandro and Smith, Harrison B. and Andersen, Jacob L. and Chen, Huan and Meringer, Markus and Cleaves, H. James (2022) An open source computational workflow for the discovery of autocatalytic networks in abiotic reactions. Chemical Science, 13 (17), pp. 4838-4853. Royal Society of Chemistry. doi: 10.1039/D2SC00256F. ISSN 2041-6520.

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Official URL: https://pubs.rsc.org/en/content/articlelanding/2022/SC/D2SC00256F


A central question in origins of life research is how non-entailed chemical processes, which simply dissipate chemical energy because they can do so due to immediate reaction kinetics and thermodynamics, enabled the origin of highly-entailed ones, in which concatenated kinetically and thermodynamically favorable processes enhanced some processes over others. Some degree of molecular complexity likely had to be supplied by environmental processes to produce entailed self-replicating processes. The origin of entailment, therefore, must connect to fundamental chemistry that builds molecular complexity. We present here an open-source chemoinformatic workflow to model abiological chemistry to discover such entailment. This pipeline automates generation of chemical reaction networks and their analysis to discover novel compounds and autocatalytic processes. We demonstrate this pipeline's capabilities against a well-studied model system by vetting it against experimental data. This workflow can enable rapid identification of products of complex chemistries and their underlying synthetic relationships to help identify autocatalysis, and potentially self-organization, in such systems. The algorithms used in this study are open-source and reconfigurable by other user-developed workflows.

Item URL in elib:https://elib.dlr.de/186074/
Document Type:Article
Title:An open source computational workflow for the discovery of autocatalytic networks in abiotic reactions
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Arya, AayushLPU, Phagwara, Indiahttps://orcid.org/0000-0001-6782-407X
Sharma, SiddhantDU, New Delhi, Indiahttps://orcid.org/0000-0003-1768-1802
Cruz Simbron, RomuloUNI, Lima, Peruhttps://orcid.org/0000-0001-5942-9918
Lozano, AlejandroIPN, Mexico City, MexicoUNSPECIFIED
Smith, Harrison B.ELSI, Tokyo, Japanhttps://orcid.org/0000-0001-8806-9659
Andersen, Jacob L.SDU, Odense, DenmarkUNSPECIFIED
Chen, HuanNational High Magnetic Field Laboratory, Tallahassee, USAhttps://orcid.org/0000-0002-6032-6569
Meringer, MarkusUNSPECIFIEDhttps://orcid.org/0000-0001-8526-2429
Cleaves, H. JamesEarth-Life Science Institute, Tokyo Institute of TechnologyUNSPECIFIED
Date:23 March 2022
Journal or Publication Title:Chemical Science
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In ISI Web of Science:Yes
Page Range:pp. 4838-4853
Publisher:Royal Society of Chemistry
Keywords:origin of life, chemical reaction network, autocatalysis, mass spectrometry, computational modeling, algorithm
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space Exploration
DLR - Research area:Raumfahrt
DLR - Program:R EW - Space Exploration
DLR - Research theme (Project):R - Planetary Evolution and Life
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Atmospheric Processors
Deposited By: Meringer, Dr.rer.nat. Markus
Deposited On:09 May 2022 10:56
Last Modified:09 May 2022 10:56

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