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Progress in Chemistry 2015, Vol. 27 Issue (7): 841-847 DOI: 10.7536/PC150120 Previous Articles   Next Articles

• Review and comments •

Multisite Statistical Interactions in Supramolecular Chemistry: Design and Application

Chen Feng, Wan Decheng*   

  1. School of Materials Science and Engineering, Tongji University, Shanghai 201804, China
  • Received: Revised: Online: Published:
  • Supported by:
    The work was supported by the National Natural Science Foundation of China (No.51273149).
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Among supramolecular interaction styles, a multisite statistical interaction is fundamentally different from multivalent or multiligand interactions because the former has no rigorous requirement on the morphology, size and electronic environment of the host, thus is ready to realize. Multisite statistical interactions are dynamic and random in nature, with reasonable design of the electronic environment of a host, the host-guest interaction strength can be significantly enhanced.While by topology design, the competitive statistical interaction by other molecules can be weakened. This can similarly lead to enhanced host-guest complement, and the binding constant can be improved by 105-fold. With the aid of multisite statistical interactions, highly effective capture of the micro- and trace pollutants in water is realized, including small-sized heavy metals, dyes and the highly hydrophobic and carcinogenic aromatic compounds. It can also be applied in peptide extraction at sub-femtomolar level. Tuning the host-guest statistical probability can lead to thermodynamically well-controlled release of a guest from a nanocapsule. The feature and application of multisite statistical interactions are here reviewed in this article.

Contents
1 Introduction
2 Application of multisite statistical host-guest interactions
2.1 Eliminating micro- and trace pollutants in water by multisite statistical interaction promoted adsorption
2.2 Application of multisite statistical interactions on peptide extraction
2.3 Selective encapsulation, separation and controlled release promoted by multisite statistical interactions
3 Influencing factors on multisite statistical interactions and their design and applications
4 Conclusion

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