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A VB/MM view of the identity S(N)2 valence-bond state correlation diagram in aqueous solution
Avital Sharir-Ivry1, Avital Shurki
1Department of Medicinal Chemistry and Natural Products, School of Pharmacy, The Lise Meitner-Minerva Center for Computational Quantum Chemistry, The Hebrew University of Jerusalem, Jerusalem 91120, Israel.
Abstract:
The valence-bond state correlation diagram (VBSCD), which was developed by Shaik and co-workers is an excellent tool to understand reactivity patterns in chemical reactions. The strength of the model is in its ability to describe the whole spectrum of reaction types and unify them under a single general paradigm. Moreover, it allows one to understand, conceptualize, and predict chemical reactivity in a general as well as specific manner. As such, VBSCD is a valuable model. The model has been largely tested on various systems in the gas phase both qualitatively and quantitatively. However, its application to reactions in solution was given less attention because of the difficulties to represent solvent reorganization and estimate non-equilibrium solvation effects, which, on the basis of the model, are expected to be fundamental. The recently developed valence-bond molecular mechanics (VB/MM) method overcomes these difficulties because it involves explicit solvent molecules and thus allows quantitative examination of these solvent effects. This work presents a study of the identity S(N)2 reaction X(-) + H(3)CX --> XCH(3) + X(-); (X = F, Cl, Br, I) in aqueous solution. The various parameters that form the VBSCD model are calculated and compared with the corresponding model's estimated values. A relatively good agreement between the calculated and estimated values is found. It is shown that when facing quantitative considerations, the picture may not be as simplistic as in the qualitative study; yet, the fundamental nature of the description is unaffected. This indicates that combined together, the VB/MM approach and the VBSCD model offer a very powerful tool to study reactions in complex systems and understand their reactivity patterns.
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