Onset of natural selection in populations of autocatalytic heteropolymers.
Identifieur interne : 001F80 ( Ncbi/Curation ); précédent : 001F79; suivant : 001F81Onset of natural selection in populations of autocatalytic heteropolymers.
Auteurs : Alexei V. Tkachenko [États-Unis] ; Sergei Maslov [États-Unis]Source :
- The Journal of chemical physics [ 1089-7690 ] ; 2018.
Descripteurs français
- KwdFr :
- MESH :
English descriptors
- KwdEn :
- MESH :
- chemical , chemistry : Biopolymers.
- Algorithms, Catalysis, Computer Graphics, Computer Simulation, Entropy, Models, Chemical, Nucleic Acid Hybridization, Origin of Life, Polymerization.
Abstract
Reduction of information entropy along with ever-increasing complexity is among the key signatures of life. Understanding the onset of such behavior in the early prebiotic world is essential for solving the problem of the origin of life. Here we study a general problem of heteropolymers capable of template-assisted ligation based on Watson-Crick-like hybridization. The system is driven off-equilibrium by cyclic changes in the environment. We model the dynamics of 2-mers, i.e., sequential pairs of specific monomers within the heteropolymer population. While the possible number of them is Z2 (where Z is the number of monomer types), we observe that most of the 2-mers get extinct, leaving no more than 2Z survivors. This leads to a dramatic reduction of the information entropy in the sequence space. Our numerical results are supported by a general mathematical analysis of the competition of growing polymers for constituent monomers. This natural-selection-like process ultimately results in a limited subset of polymer sequences. Importantly, the set of surviving sequences depends on initial concentrations of monomers and remains exponentially large (2 L down from ZL for length L) in each of realizations. Thus, an inhomogeneity in initial conditions allows for a massively parallel search of the sequence space for biologically functional polymers, such as ribozymes. We also propose potential experimental implementations of our model in the contexts of either biopolymers or artificial nano-structures.
DOI: 10.1063/1.5048488
PubMed: 30292218
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Tkachenko</name><affiliation wicri:level="1"><nlm:affiliation>Center for Functional Nanomaterials, Brookhaven National Laboratory, Upton, New York 11973, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Center for Functional Nanomaterials, Brookhaven National Laboratory, Upton, New York 11973</wicri:regionArea><wicri:noRegion>New York 11973</wicri:noRegion></affiliation></author><author><name sortKey="Maslov, Sergei" sort="Maslov, Sergei" uniqKey="Maslov S" first="Sergei" last="Maslov">Sergei Maslov</name><affiliation wicri:level="1"><nlm:affiliation>Department of Bioengineering, University of Illinois at Urbana-Champaign, 1270 Digital Computer Laboratory, MC-278, Urbana, Illinois 61801, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Bioengineering, University of Illinois at Urbana-Champaign, 1270 Digital Computer Laboratory, MC-278, Urbana, Illinois 61801</wicri:regionArea><wicri:noRegion>Illinois 61801</wicri:noRegion></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2018">2018</date><idno type="RBID">pubmed:30292218</idno><idno type="pmid">30292218</idno><idno type="doi">10.1063/1.5048488</idno><idno type="wicri:Area/PubMed/Corpus">000765</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">000765</idno><idno type="wicri:Area/PubMed/Curation">000765</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Curation">000765</idno><idno type="wicri:Area/PubMed/Checkpoint">000819</idno><idno type="wicri:explorRef" wicri:stream="Checkpoint" wicri:step="PubMed">000819</idno><idno type="wicri:Area/Ncbi/Merge">001F80</idno><idno type="wicri:Area/Ncbi/Curation">001F80</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Onset of natural selection in populations of autocatalytic heteropolymers.</title><author><name sortKey="Tkachenko, Alexei V" sort="Tkachenko, Alexei V" uniqKey="Tkachenko A" first="Alexei V" last="Tkachenko">Alexei V. Tkachenko</name><affiliation wicri:level="1"><nlm:affiliation>Center for Functional Nanomaterials, Brookhaven National Laboratory, Upton, New York 11973, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Center for Functional Nanomaterials, Brookhaven National Laboratory, Upton, New York 11973</wicri:regionArea><wicri:noRegion>New York 11973</wicri:noRegion></affiliation></author><author><name sortKey="Maslov, Sergei" sort="Maslov, Sergei" uniqKey="Maslov S" first="Sergei" last="Maslov">Sergei Maslov</name><affiliation wicri:level="1"><nlm:affiliation>Department of Bioengineering, University of Illinois at Urbana-Champaign, 1270 Digital Computer Laboratory, MC-278, Urbana, Illinois 61801, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Bioengineering, University of Illinois at Urbana-Champaign, 1270 Digital Computer Laboratory, MC-278, Urbana, Illinois 61801</wicri:regionArea><wicri:noRegion>Illinois 61801</wicri:noRegion></affiliation></author></analytic><series><title level="j">The Journal of chemical physics</title><idno type="eISSN">1089-7690</idno><imprint><date when="2018" type="published">2018</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms</term><term>Biopolymers (chemistry)</term><term>Catalysis</term><term>Computer Graphics</term><term>Computer Simulation</term><term>Entropy</term><term>Models, Chemical</term><term>Nucleic Acid Hybridization</term><term>Origin of Life</term><term>Polymerization</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Algorithmes</term><term>Biopolymères ()</term><term>Catalyse</term><term>Entropie</term><term>Hybridation d'acides nucléiques</term><term>Infographie</term><term>Modèles chimiques</term><term>Origine de la vie</term><term>Polymérisation</term><term>Simulation numérique</term></keywords><keywords scheme="MESH" type="chemical" qualifier="chemistry" xml:lang="en"><term>Biopolymers</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Algorithms</term><term>Catalysis</term><term>Computer Graphics</term><term>Computer Simulation</term><term>Entropy</term><term>Models, Chemical</term><term>Nucleic Acid Hybridization</term><term>Origin of Life</term><term>Polymerization</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Algorithmes</term><term>Biopolymères</term><term>Catalyse</term><term>Entropie</term><term>Hybridation d'acides nucléiques</term><term>Infographie</term><term>Modèles chimiques</term><term>Origine de la vie</term><term>Polymérisation</term><term>Simulation numérique</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Reduction of information entropy along with ever-increasing complexity is among the key signatures of life. Understanding the onset of such behavior in the early prebiotic world is essential for solving the problem of the origin of life. Here we study a general problem of heteropolymers capable of template-assisted ligation based on Watson-Crick-like hybridization. The system is driven off-equilibrium by cyclic changes in the environment. We model the dynamics of 2-mers, i.e., sequential pairs of specific monomers within the heteropolymer population. While the possible number of them is <i>Z</i><sup>2</sup> (where <i>Z</i> is the number of monomer types), we observe that most of the 2-mers get extinct, leaving no more than 2<i>Z</i> survivors. This leads to a dramatic reduction of the information entropy in the sequence space. Our numerical results are supported by a general mathematical analysis of the competition of growing polymers for constituent monomers. This natural-selection-like process ultimately results in a limited subset of polymer sequences. Importantly, the set of surviving sequences depends on initial concentrations of monomers and remains exponentially large (2 <sup><i>L</i></sup> down from <i>Z</i><sup><i>L</i></sup> for length <i>L</i>) in each of realizations. Thus, an inhomogeneity in initial conditions allows for a massively parallel search of the sequence space for biologically functional polymers, such as ribozymes. We also propose potential experimental implementations of our model in the contexts of either biopolymers or artificial nano-structures.</div></front></TEI></record>Pour manipuler ce document sous Unix (Dilib)
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