GRRM23

AFIR and ADDF algorithm for automatic exploration of all potential molecules and reaction paths

Global reaction route mapping (GRRM) program empowers users to do their treasure hunt of unknown molecules and reactions through automatic reaction path exploration from one starting point (equilibrium), driven by two core algorithms that collaborate with quantum chemistry calculation: artificial force induced reaction (AFIR) and anharmonic downward distortion following (ADDF). The power of ADDF and AFIR opens unknown chemistry of all four types of chemical reactions shown below [1], which leads users to explore possible output (molecules and reaction paths) comprehensively just by one single input of molecules.

(1) A → X (Isomerization)
(2) A → X+Y (Dissociation)
(3) A+B → X (Combining synthesis)
(4) A+B → X+Y (Exchanging synthesis)

Kinetic analysis by RCMC method to evaluate population of chemical species and accelerate reaction path search

Kinetic simulation and kinetics-based navigation using rate constant matrix contraction (RCMC) method became available from GRRM20 to enhance the automated reaction search function of GRRM, being applicable to complex reaction path networks. The kinetic simulation enables users to evaluate population of chemical species which exist beyond specified lifetime condition, while the kinetics-based navigation contributes to dramatic speedups of the reaction path search (SC-AFIR search of GRRM) by restricting the search areas to extract kinetically feasible paths from initial structures under given reaction temperatures and lifetimes [2].

Retrosynthetic analysis for exploring chemical reactants and yields by QCaRA

In GRRM23, the new function for reverse reaction kinetics analysis was implemented based on RCMC method (above-mentioned) for complex reaction path network analysis. This function predicts yields of target chemical products regarding all reactions starting from other chemical species on reaction path networks [3]. By utilizing this function as a kinetics navigation tool, quantum chemistry-aided retrosynthetic analysis (QCaRA) is performed. So far, QCaRA, which takes structures of products as its sole input, has already demonstrated the ability to correctly identify reactants for various known reactions, including the synthesis of small natural products [4].

Utilities to easily implement user-developed tools

GRRM23 provides functions to control structure optimization and exploration using externally developed modules. These modules can modify search order near local minima, change exploration routes from local minima, and apply external bias potentials to the system. These options are used in combination with rapidly exploring random tree algorithm [5] and graph neural network-based reaction path selection algorithm [6] in order to accelerate the reaction path exploration (SC-AFIR search of GRRM) for specific purposes. Moreover, they are also used for the development and application of virtual ligands for transition metal catalysts [7].

Applicable for various R&D

GRRM23 can be used to simulate various reaction systems, so far having already been applied in organic reaction, organometallic catalysis, cluster catalysis, radical reaction, photoreaction involving electronic excited states, crystal phase transition under periodic boundary conditions, enzyme catalysis reaction by QM/MM-ONIOM method, etc.

For example, in drug synthesis, GRRM program can be utilized for catalyst design targeting rate-determining reactions and for suppression of by-products by elucidating all reaction paths capable of synthesizing desired drug molecules.

For example, in combustion reaction, it is possible to meet the accuracy of reaction rates in CAE design of automotive and rocket engine because thousands to tens of thousands of elementary reactions can be obtained based on highly precise quantum chemistry calculations.