Molecular recognition and self-replication

1992 ◽  
Vol 5 (3) ◽  
pp. 83-88 ◽  
Author(s):  
Julius Rebek
2019 ◽  
Author(s):  
Haralampos N. Miras ◽  
Cole Mathis ◽  
Weimin Xuan ◽  
De-Liang Long ◽  
Robert Pow ◽  
...  

Biological self-replication is driven by complex machinery requiring large amounts of sequence information too complex to have formed spontaneously. This presents a fundamental problem for understanding the origins self-replication and by extension, life. One route for the emergence of self-replicators is via autocatalytic sets, but experimentally these have been based on RNA and require sequence information. Showing an example outside of biology, would give insights into how the universal ‘life-like’ chemistry can be. Here we show how a simple inorganic salt can spontaneously form information-rich, autocatalytic sets of replicating inorganic molecules that work via molecular recognition based on the {PMo12} Keggin ion, and {Mo36} cluster. These small clusters are involved in an autocatalytic network, where the assembly of gigantic molybdenum blue wheel (Mo154-blue), {Mo132} ball containing 154 and 132 molybdenum atoms, and a new {PMo12}Ì{Mo124 Ce4} nanostructure are templated by the smaller clusters which are themselves able to catalyse their own formation. Kinetic investigations revealed key traits of autocatalytic systems including molecular recognition and kinetic saturation. A stochastic model confirms the presence of an autocatalytic network driven by molecular recognition, where the larger clusters are the only products stabilised by information contained in the cycle, isolated due to a critical transition in the network. This study demonstrates how information-rich autocatalytic sets, based on simple inorganic salts, can spontaneously emerge which are capable of collective self-reproduction outside of biology.<br>


Author(s):  
Haralampos N. Miras ◽  
Cole Mathis ◽  
Weimin Xuan ◽  
De-Liang Long ◽  
Robert Pow ◽  
...  

Biological self-replication is driven by complex machinery requiring large amounts of sequence information too complex to have formed spontaneously. This presents a fundamental problem for understanding the origins self-replication and by extension, life. One route for the emergence of self-replicators is via autocatalytic sets, but experimentally these have been based on RNA and require sequence information. Showing an example outside of biology, would give insights into how the universal ‘life-like’ chemistry can be. Here we show how a simple inorganic salt can spontaneously form information-rich, autocatalytic sets of replicating inorganic molecules that work via molecular recognition based on the {PMo12} Keggin ion, and {Mo36} cluster. These small clusters are involved in an autocatalytic network, where the assembly of gigantic molybdenum blue wheel (Mo154-blue), {Mo132} ball containing 154 and 132 molybdenum atoms, and a new {PMo12}Ì{Mo124 Ce4} nanostructure are templated by the smaller clusters which are themselves able to catalyse their own formation. Kinetic investigations revealed key traits of autocatalytic systems including molecular recognition and kinetic saturation. A stochastic model confirms the presence of an autocatalytic network driven by molecular recognition, where the larger clusters are the only products stabilised by information contained in the cycle, isolated due to a critical transition in the network. This study demonstrates how information-rich autocatalytic sets, based on simple inorganic salts, can spontaneously emerge which are capable of collective self-reproduction outside of biology.<br>


2020 ◽  
Vol 29 (4) ◽  
pp. 741-757
Author(s):  
Kateryna Hazdiuk ◽  
◽  
Volodymyr Zhikharevich ◽  
Serhiy Ostapov ◽  
◽  
...  

This paper deals with the issue of model construction of the self-regeneration and self-replication processes using movable cellular automata (MCAs). The rules of cellular automaton (CA) interactions are found according to the concept of equilibrium neighborhood. The method is implemented by establishing these rules between different types of cellular automata (CAs). Several models for two- and three-dimensional cases are described, which depict both stable and unstable structures. As a result, computer models imitating such natural phenomena as self-replication and self-regeneration are obtained and graphically presented.


2020 ◽  
Author(s):  
Junxia Ren ◽  
Yaozu Liu ◽  
Xin Zhu ◽  
Yangyang Pan ◽  
Yujie Wang ◽  
...  

<p><a></a><a></a><a></a><a></a><a></a><a></a><a></a><a>The development of highly-sensitive recognition of </a><a></a><a></a><a></a><a></a><a>hazardous </a>chemicals, such as volatile organic compounds (VOCs) and polycyclic aromatic hydrocarbons (PAHs), is of significant importance because of their widespread social concerns related to environment and human health. Here, we report a three-dimensional (3D) covalent organic framework (COF, termed JUC-555) bearing tetraphenylethylene (TPE) side chains as an aggregation-induced emission (AIE) fluorescence probe for sensitive molecular recognition.<a></a><a> </a>Due to the rotational restriction of TPE rotors in highly interpenetrated framework after inclusion of dimethylformamide (DMF), JUC-555 shows impressive AIE-based strong fluorescence. Meanwhile, owing to the large pore size (11.4 Å) and suitable intermolecular distance of aligned TPE (7.2 Å) in JUC-555, the obtained material demonstrates an excellent performance in the molecular recognition of hazardous chemicals, e.g., nitroaromatic explosives, PAHs, and even thiophene compounds, via a fluorescent quenching mechanism. The quenching constant (<i>K</i><sub>SV</sub>) is two orders of magnitude better than those of other fluorescence-based porous materials reported to date. This research thus opens 3D functionalized COFs as a promising identification tool for environmentally hazardous substances.</p>


2018 ◽  
Author(s):  
Yingqian Wang ◽  
Xiaoxia Hu ◽  
Lingling Zhang ◽  
Chunli Zhu ◽  
Jie Wang ◽  
...  

Extracellular vesicles (EVs) are involved in the regulation of cell physiological activity and the reconstruction of extracellular environment. Matrix vesicles (MVs) are a type of EVs, and they participate in the regulation of cell mineralization. Herein, bioinspired MVs embedded with black phosphorus are functionalized with cell-specific aptamer (denoted as Apt-bioinspired MVs) for stimulating biomineralization. The aptamer can direct bioinspired MVs to targeted cells, and the increasing concentration of inorganic phosphate originated from the black phosphorus can facilitate cell biomineralization. The photothermal effect of the Apt-bioinspired MVs also positively affects mineralization. In addition, the Apt-bioinspired MVs display outstanding bone regeneration performance. Considering the excellent behavior of the Apt-bioinspired MVs for promoting biomineralization, our strategy provides a way of designing bionic tools for studying the mechanisms of biological processes and advancing the development of medical engineering.<br>


2019 ◽  
Author(s):  
Meifeng Wang ◽  
Gan Zhu ◽  
Yiqun Li ◽  
Liuqun Gu

Arylboronic acids were widely used as efficient catalysts in direct amide formation and other organic transformations. Surprisingly, reports on their use as catalysts in carbohydrates synthesis are very rare even though boron acid-diol complexation was extensively investigated in molecular recognition for saccharides and so on. Here we developed an efficient arylboronic acids catalyzed dimerization of glucosamines forming deoxyfructosazine which is important compound in pharmaceutical and food industries, against a commonly held belief that excess amount of phenyl boronic acid (or boric acid) is a must. A catalytic mechanism was also proposed and arylboronic acids instead of their boronates was identified as catalysts.


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