Literature DB >> 26925858

Development of a True Transition State Force Field from Quantum Mechanical Calculations.

Ádám Madarász1, Dénes Berta1, Robert S Paton2,3.   

Abstract

Transition state force fields (TSFF) treated the TS structure as an artificial minimum on the potential energy surface in the past decades. The necessary parameters were developed either manually or by the Quantum-to-molecular mechanics method (Q2MM). In contrast with these approaches, here we propose to model the TS structures as genuine saddle points at the molecular mechanics level. Different methods were tested on small model systems of general chemical reactions such as protonation, nucleophilic attack, and substitution, and the new procedure led to more accurate models than the Q2MM-type parametrization. To demonstrate the practicality of our approach, transferrable parameters have been developed for Mo-catalyzed olefin metathesis using quantum mechanical properties as reference data. Based on the proposed strategy, any force field can be extended with true transition state force field (TTSFF) parameters, and they can be readily applied in several molecular mechanics programs as well.

Entities:  

Year:  2016        PMID: 26925858     DOI: 10.1021/acs.jctc.5b01237

Source DB:  PubMed          Journal:  J Chem Theory Comput        ISSN: 1549-9618            Impact factor:   6.006


  4 in total

1.  Application of Q2MM to predictions in stereoselective synthesis.

Authors:  Anthony R Rosales; Taylor R Quinn; Jessica Wahlers; Anna Tomberg; Xin Zhang; Paul Helquist; Olaf Wiest; Per-Ola Norrby
Journal:  Chem Commun (Camb)       Date:  2018-07-24       Impact factor: 6.222

2.  Machine learning and semi-empirical calculations: a synergistic approach to rapid, accurate, and mechanism-based reaction barrier prediction.

Authors:  Elliot H E Farrar; Matthew N Grayson
Journal:  Chem Sci       Date:  2022-06-14       Impact factor: 9.969

3.  Prediction of Stereochemistry using Q2MM.

Authors:  Eric Hansen; Anthony R Rosales; Brandon Tutkowski; Per-Ola Norrby; Olaf Wiest
Journal:  Acc Chem Res       Date:  2016-04-11       Impact factor: 22.384

4.  Automated fitting of transition state force fields for biomolecular simulations.

Authors:  Taylor R Quinn; Himani N Patel; Kevin H Koh; Brandon E Haines; Per-Ola Norrby; Paul Helquist; Olaf Wiest
Journal:  PLoS One       Date:  2022-03-10       Impact factor: 3.240

  4 in total

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