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Computational Exploration of Lipid Chemical Space: Predicting Assembly Using QSPR Models

Forget, Selene and Cleaves, H. James and Jia, Tony and Gillams, Richard J. and Meringer, Markus (2020) Computational Exploration of Lipid Chemical Space: Predicting Assembly Using QSPR Models. Molecular Origins of Life, Munich 2020 (MOM 2020), 08.-10. July 2020, Munich, Germany.

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Official URL: https://indico.physik.uni-muenchen.de/event/24/


Compartmentalization is likely to have been essential for the emergence of life. Compartmentalization allows for the creation of unique chemical conditions that can be maintained out of equilibrium with the environment and the exclusion of parasites. Confining organic molecules also helps limit diffusion, increases concentration and can thus influence both the thermodynamics and kinetics of prebiotic reactions. Biology currently predominantly uses phospholipids to construct cell membranes. However, there are many other types of organic compounds that can form stable compartments in water, and many of these may have been abundant in the prebiotic environment. In this study we explore this alternative lipid chemical space by using structure enumeration algorithms to compute an exhaustive combinatorial library of surfactant molecules. We then predict the propensity of these compounds to self-assemble into membranes using quantitative structure-property relationship (QSPR) models on critical micelle concentration (CMC). Combined with critical packing parameter calculations, these models can allow identification of novel molecule types which can be experimentally assayed as candidates for the emergence of protocells.

Item URL in elib:https://elib.dlr.de/135529/
Document Type:Conference or Workshop Item (Poster)
Title:Computational Exploration of Lipid Chemical Space: Predicting Assembly Using QSPR Models
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Forget, SeleneEcole Normale SupérieureUNSPECIFIED
Cleaves, H. JamesEarth-Life Science Institute, Tokyo Institute of TechnologyUNSPECIFIED
Jia, TonyEarth-Life Science Institute, Tokyo Institute of TechnologyUNSPECIFIED
Gillams, Richard J.Electronics and Computer Science, University of SouthamptonUNSPECIFIED
Meringer, MarkusMarkus.Meringer (at) dlr.dehttps://orcid.org/0000-0001-8526-2429
Date:July 2020
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:No
Keywords:combinatorial library, surfactant molecules, quantitative structure-property relationship, surfactant molecules, critical micelle concentration, machine learning
Event Title:Molecular Origins of Life, Munich 2020 (MOM 2020)
Event Location:Munich, Germany
Event Type:international Conference
Event Dates:08.-10. July 2020
Organizer:CRC 235 - Emergence of Life
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 - Explorationsstudien (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Atmospheric Processors
Deposited By: Meringer, Dr.rer.nat. Markus
Deposited On:04 Aug 2020 13:53
Last Modified:04 Aug 2020 13:53

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