A microiterative intrinsic reaction coordinate method for large QM/MM systems

Literature Information

Publication Date 2013-05-31
DOI 10.1039/C3CP51669E
Impact Factor 3.676
Authors

Iakov Polyak, Eliot Boulanger, Kakali Sen, Walter Thiel


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Abstract

Intrinsic reaction coordinate (IRC) computations are a valuable tool in theoretical studies of chemical reactions, but they can usually not be applied in their current form to handle large systems commonly described by quantum mechanics/molecular mechanics (QM/MM) methods. We report on a development that tackles this problem by using a strategy analogous to microiterative transition state optimization. In this approach, the IRC equations only govern the motion of a core region that contains at least the atoms directly involved in the reaction, while the remaining degrees of freedom are relaxed after each IRC step. This strategy can be used together with any existing IRC procedure. The present implementation covers the stabilized Euler, local quadratic approximation, and Hessian predictor–corrector algorithms for IRC calculations. As proof of principle, we perform tests at the QM level on small gas-phase systems and validate the results by comparisons with standard IRC procedures. The broad applicability of the method is demonstrated by IRC computations for two enzymatic reactions using standard QM/MM setups.

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Source Journal

Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
Articles per Year: 3036

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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