Automated Transition State Search and Its Application to Diverse Types of Organic Reactions

过渡(遗传学) 国家(计算机科学) 计算机科学 数据科学 化学 纳米技术 数据挖掘 材料科学 程序设计语言 生物化学 基因
作者
Leif D. Jacobson,Arteum D. Bochevarov,Mark A. Watson,Thomas F. Hughes,David Rinaldo,Stephan Ehrlich,Thomas Steinbrecher,S. Vaitheeswaran,Dean M. Philipp,Mathew D. Halls,Richard A. Friesner
出处
期刊:Journal of Chemical Theory and Computation [American Chemical Society]
卷期号:13 (11): 5780-5797 被引量:161
标识
DOI:10.1021/acs.jctc.7b00764
摘要

Transition state search is at the center of multiple types of computational chemical predictions related to mechanistic investigations, reactivity and regioselectivity predictions, and catalyst design. The process of finding transition states in practice is, however, a laborious multistep operation that requires significant user involvement. Here, we report a highly automated workflow designed to locate transition states for a given elementary reaction with minimal setup overhead. The only essential inputs required from the user are the structures of the separated reactants and products. The seamless workflow combining computational technologies from the fields of cheminformatics, molecular mechanics, and quantum chemistry automatically finds the most probable correspondence between the atoms in the reactants and the products, generates a transition state guess, launches a transition state search through a combined approach involving the relaxing string method and the quadratic synchronous transit, and finally validates the transition state via the analysis of the reactive chemical bonds and imaginary vibrational frequencies as well as by the intrinsic reaction coordinate method. Our approach does not target any specific reaction type, nor does it depend on training data; instead, it is meant to be of general applicability for a wide variety of reaction types. The workflow is highly flexible, permitting modifications such as a choice of accuracy, level of theory, basis set, or solvation treatment. Successfully located transition states can be used for setting up transition state guesses in related reactions, saving computational time and increasing the probability of success. The utility and performance of the method are demonstrated in applications to transition state searches in reactions typical for organic chemistry, medicinal chemistry, and homogeneous catalysis research. In particular, applications of our code to Michael additions, hydrogen abstractions, Diels-Alder cycloadditions, carbene insertions, and an enzyme reaction model involving a molybdenum complex are shown and discussed.

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