Open flow non-enzymatic template catalysis and replication

Literature Information

Publication Date 2018-05-11
DOI 10.1039/C8CP01828F
Impact Factor 3.676
Authors

Larwsk H. Gonçalves da Silva, David Hochberg


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Abstract

Template induced replication is the basis of multiplication and reproduction in nature and underlies the importance of gaining a detailed understanding of its mechanisms in terms of chemical reaction networks. We analyze numerically the stationary state solutions for a class of autocatalytic reactions based on reversible template assisted ligation with first and second order catalysis and governed by mass-action kinetics. Chemical thermodynamics leads to constraints on the reaction rate constants which result in very low template yield in systems subject to fixed external concentrations. When however the network is driven out of equilibrium via open flow in a well-mixed reactor, the template yield can be increased significantly for very small fluid flow rates. This can be understood in terms of driven unidirectional pathways, as determined by stoichiometric network analysis.

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Source Journal

Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
Articles per Year: 3036

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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