Intrinsic reaction coordinate: Calculation, bifurcation, and automated search
05 Mar 2015-International Journal of Quantum Chemistry (John Wiley & Sons, Ltd)-Vol. 115, Iss: 5, pp 258-269
TL;DR: The intrinsic reaction coordinate (IRC) approach has been used extensively in quantum chemical analysis and prediction of the mechanism of chemical reactions as mentioned in this paper, which gives a unique connection from a given transition structure to local minima of the reactant and product sides.
Abstract: The intrinsic reaction coordinate (IRC) approach has been used extensively in quantum chemical analysis and prediction of the mechanism of chemical reactions. The IRC gives a unique connection from a given transition structure to local minima of the reactant and product sides. This allows for easy understanding of complicated multistep mechanisms as a set of simple elementary reaction steps. In this article, three topics concerning the IRC approach are discussed. In the first topic, the first ab initio study of the IRC and a recent development of an IRC calculation algorithm for enzyme reactions are introduced. In the second topic, cases are presented in which dynamical trajectories bifurcate and corresponding IRC connections can be inaccurate. In the third topic, a recent development of an automated reaction path search method and its application to systematic construction of IRC networks are described. Finally, combining these three topics, future perspectives are discussed. © 2014 Wiley Periodicals, Inc.
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TL;DR: An efficient scheme for the in silico sampling for parts of the molecular chemical space by semiempirical tight-binding methods combined with a meta-dynamics driven search algorithm is proposed and discussed, opening many possible applications in modern computational chemistry and drug discovery.
Abstract: We propose and discuss an efficient scheme for the in silico sampling for parts of the molecular chemical space by semiempirical tight-binding methods combined with a meta-dynamics driven search algorithm. The focus of this work is set on the generation of proper thermodynamic ensembles at a quantum chemical level for conformers, but similar procedures for protonation states, tautomerism and non-covalent complex geometries are also discussed. The conformational ensembles consisting of all significantly populated minimum energy structures normally form the basis of further, mostly DFT computational work, such as the calculation of spectra or macroscopic properties. By using basic quantum chemical methods, electronic effects or possible bond breaking/formation are accounted for and a very reasonable initial energetic ranking of the candidate structures is obtained. Due to the huge computational speedup gained by the fast low-cost quantum chemical methods, overall short computation times even for systems with hundreds of atoms (typically drug-sized molecules) are achieved. Furthermore, specialized applications, such as sampling with implicit solvation models or constrained conformational sampling for transition-states, metal-, surface-, or noncovalently bound complexes are discussed, opening many possible applications in modern computational chemistry and drug discovery. The procedures have been implemented in a freely available computer code called CREST, that makes use of the fast and reliable GFNn-xTB methods.
671 citations
University of California, Irvine1, Technical University of Denmark2, Dassault Systèmes3, Ruhr University Bochum4, Karlsruhe Institute of Technology5, Technical University of Berlin6, Max Planck Society7, Forschungszentrum Jülich8, Case Western Reserve University9, University of North Carolina at Chapel Hill10, Aarhus University11, California State University, Long Beach12, Kaiserslautern University of Technology13, Tata Institute of Fundamental Research14
TL;DR: This review focuses on recent additions to TURBOMOLE’s functionality, including excited-state methods, RPA and Green's function methods, relativistic approaches, high-order molecular properties, solvation effects, and periodic systems.
Abstract: TURBOMOLE is a collaborative, multi-national software development project aiming to provide highly efficient and stable computational tools for quantum chemical simulations of molecules, clusters, periodic systems, and solutions. The TURBOMOLE software suite is optimized for widely available, inexpensive, and resource-efficient hardware such as multi-core workstations and small computer clusters. TURBOMOLE specializes in electronic structure methods with outstanding accuracy-cost ratio, such as density functional theory including local hybrids and the random phase approximation (RPA), GW-Bethe-Salpeter methods, second-order Moller-Plesset theory, and explicitly correlated coupled-cluster methods. TURBOMOLE is based on Gaussian basis sets and has been pivotal for the development of many fast and low-scaling algorithms in the past three decades, such as integral-direct methods, fast multipole methods, the resolution-of-the-identity approximation, imaginary frequency integration, Laplace transform, and pair natural orbital methods. This review focuses on recent additions to TURBOMOLE's functionality, including excited-state methods, RPA and Green's function methods, relativistic approaches, high-order molecular properties, solvation effects, and periodic systems. A variety of illustrative applications along with accuracy and timing data are discussed. Moreover, available interfaces to users as well as other software are summarized. TURBOMOLE's current licensing, distribution, and support model are discussed, and an overview of TURBOMOLE's development workflow is provided. Challenges such as communication and outreach, software infrastructure, and funding are highlighted.
489 citations
TL;DR: Several of these approaches, which are categorized based on their overarching TS finding strategies, have been described in this paper, and future advances are discussed that may revolutionize the ability of simulation to fully predict not just the reaction mechanism but reaction outcomes.
Abstract: The area of reaction mechanism discovery simulation has taken considerable strides in recent years. Novel methods that make hypotheses for elementary steps and complementary means for reaction path and transition state (TS) optimization are lowering the amount of chemical intuition and user effort required to explore reaction networks. The resulting networks lead from reactants to reactive intermediates and products, and are becoming closer representations of physical mechanisms involved in experiments. This review describes several of these approaches, which are categorized based on their overarching TS finding strategies. Future advances are discussed that may revolutionize the ability of simulation to fully predict not just the reaction mechanism but reaction outcomes.
For further resources related to this article, please visit the WIREs website.
157 citations
TL;DR: Investigation of minimum energy structures within the hypersurface in which two different electronic states degenerate, and an interface with the quantum mechanics/molecular mechanics method, are also described.
Abstract: This article reports implementation and performance of the artificial force induced reaction (AFIR) method in the upcoming 2017 version of GRRM program (GRRM17). The AFIR method, which is one of automated reaction path search methods, induces geometrical deformations in a system by pushing or pulling fragments defined in the system by an artificial force. In GRRM17, three different algorithms, that is, multicomponent algorithm (MC-AFIR), single-component algorithm (SC-AFIR), and double-sphere algorithm (DS-AFIR), are available, where the MC-AFIR was the only algorithm which has been available in the previous 2014 version. The MC-AFIR does automated sampling of reaction pathways between two or more reactant molecules. The SC-AFIR performs automated generation of global or semiglobal reaction path network. The DS-AFIR finds a single path between given two structures. Exploration of minimum energy structures within the hypersurface in which two different electronic states degenerate, and an interface with the quantum mechanics/molecular mechanics method, are also described. A code termed SAFIRE will also be available, as a visualization software for complicated reaction path networks. © 2017 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.
133 citations
TL;DR: In this article, the existence of post-transition state bifurcations on potential energy surfaces for organic and biological reaction mechanisms has been known for decades, but recently, new reports of bifurlcations have been occurring at a much higher rate.
Abstract: Abstract The existence of post-transition state bifurcations on potential energy surfaces for organic and biological reaction mechanisms has been known for decades, but recently, new reports of bifurcations have been occurring at a much higher rate. Beyond simply discovering bifurcations, computational chemists are developing techniques to understand what aspects of molecular structure and vibrations control the product selectivity in systems containing bifurcations. For example, the distribution of products seen in simulations has been found to be extremely sensitive to the local environment of the reacting system (i.e. the presence of a catalyst, enzyme, or explicit solvent molecules). The outlook for the future of this field is discussed, with an eye towards the application of the principles discussed here by experimental chemists to design a reaction setup to efficiently generate desired products.
114 citations
References
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01 Jan 1993TL;DR: This article presents bootstrap methods for estimation, using simple arguments, with Minitab macros for implementing these methods, as well as some examples of how these methods could be used for estimation purposes.
Abstract: This article presents bootstrap methods for estimation, using simple arguments. Minitab macros for implementing these methods are given.
37,183 citations
TL;DR: In this article, a modification of the nudged elastic band method for finding minimum energy paths is presented, where one of the images is made to climb up along the elastic band to converge rigorously on the highest saddle point.
Abstract: A modification of the nudged elastic band method for finding minimum energy paths is presented. One of the images is made to climb up along the elastic band to converge rigorously on the highest saddle point. Also, variable spring constants are used to increase the density of images near the top of the energy barrier to get an improved estimate of the reaction coordinate near the saddle point. Applications to CH4 dissociative adsorption on Ir~111! and H2 on Si~100! using plane wave based density functional theory are presented. © 2000 American Institute of Physics. @S0021-9606~00!71246-3#
14,071 citations
TL;DR: Statistical theory attacks the problem from both ends as discussed by the authors, and provides optimal methods for finding a real signal in a noisy background, and also provides strict checks against the overinterpretation of random patterns.
Abstract: Statistics is the science of learning from experience, especially experience that arrives a little bit at a time. The earliest information
science was statistics, originating in about 1650. This century has
seen statistical techniques become the analytic methods of choice
in biomedical science, psychology, education, economics, communications theory, sociology, genetic studies, epidemiology, and other
areas. Recently, traditional sciences like geology, physics, and astronomy have begun to make increasing use of statistical methods
as they focus on areas that demand informational efficiency, such as
the study of rare and exotic particles or extremely distant galaxies.
Most people are not natural-born statisticians. Left to our own
devices we are not very good at picking out patterns from a sea
of noisy data. To put it another way, we are all too good at picking out non-existent patterns that happen to suit our purposes.
Statistical theory attacks the problem from both ends. It provides
optimal methods for finding a real signal in a noisy background,
and also provides strict checks against the overinterpretation of
random patterns.
6,361 citations
TL;DR: In this article, a second order algorithm for finding points on a steepest descent path from the transition state of the reactants and products is presented. But the points are optimized so that the segment of the reaction path between any two adjacent points is given by an arc of a circle, and the gradient at each point is tangent to the path.
Abstract: A new algorithm is presented for obtaining points on a steepest descent path from the transition state of the reactants and products. In mass‐weighted coordinates, this path corresponds to the intrinsic reaction coordinate. Points on the reaction path are found by constrained optimizations involving all internal degrees of freedom of the molecule. The points are optimized so that the segment of the reaction path between any two adjacent points is given by an arc of a circle, and so that the gradient at each point is tangent to the path. Only the transition vector and the energy gradients are needed to construct the path. The resulting path is continuous, differentiable and piecewise quadratic. In the limit of small step size, the present algorithm is shown to take a step with the correct tangent vector and curvature vector; hence, it is a second order algorithm. The method has been tested on the following reactions: HCN→CNH, SiH2+H2→SiH4, CH4+H→CH3+H2, F−+CH3F→FCH3+F−, and C2H5F→C2H4+HF. Reaction paths calculated with a step size of 0.4 a.u. are almost identical to those computed with a step size of 0.1 a.u. or smaller.
5,487 citations
5,052 citations