Literature DB >> 23521272

Statistical mechanics approach to lock-key supramolecular chemistry interactions.

Gerardo Odriozola1, Marcelo Lozada-Cassou.   

Abstract

In the supramolecular chemistry field, intuitive concepts such as molecular complementarity and molecular recognition are used to explain the mechanism of lock-key associations. However, these concepts lack a precise definition, and consequently this mechanism is not well defined and understood. Here we address the physical basis of this mechanism, based on formal statistical mechanics, through Monte Carlo simulation and compare our results with recent experimental data for charged or uncharged lock-key colloids. We find that, given the size range of the molecules involved in these associations, the entropy contribution, driven by the solvent, rules the interaction, over that of the enthalpy. A universal behavior for the uncharged lock-key association is found. Based on our results, we propose a supramolecular chemistry definition.

Year:  2013        PMID: 23521272     DOI: 10.1103/PhysRevLett.110.105701

Source DB:  PubMed          Journal:  Phys Rev Lett        ISSN: 0031-9007            Impact factor:   9.161


  4 in total

1.  Understanding shape entropy through local dense packing.

Authors:  Greg van Anders; Daphne Klotsa; N Khalid Ahmed; Michael Engel; Sharon C Glotzer
Journal:  Proc Natl Acad Sci U S A       Date:  2014-10-24       Impact factor: 11.205

2.  The entropic bond in colloidal crystals.

Authors:  Eric S Harper; Greg van Anders; Sharon C Glotzer
Journal:  Proc Natl Acad Sci U S A       Date:  2019-08-02       Impact factor: 11.205

3.  Assembling oppositely charged lock and key responsive colloids: A mesoscale analog of adaptive chemistry.

Authors:  Adriana M Mihut; Björn Stenqvist; Mikael Lund; Peter Schurtenberger; Jérôme J Crassous
Journal:  Sci Adv       Date:  2017-09-15       Impact factor: 14.136

Review 4.  Insights into Protein-Ligand Interactions: Mechanisms, Models, and Methods.

Authors:  Xing Du; Yi Li; Yuan-Ling Xia; Shi-Meng Ai; Jing Liang; Peng Sang; Xing-Lai Ji; Shu-Qun Liu
Journal:  Int J Mol Sci       Date:  2016-01-26       Impact factor: 5.923

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.