Exploration of Reaction Pathways and Chemical Transformation Networks

2018/10/31 by Gregor N. C. Simm, Gregor N. Simm, Alain C. Vaucher +1 · 258 citations
Biochemistry, Genetics and Molecular Biology · Chemistry · Computer Science · Engineering · Materials Science · Mathematics · Physics and Astronomy · #Artificial intelligence #Biology #Chemistry #Completeness (order theory) #Computational Drug Discovery Methods #Computer science #Data science #Engineering #Gene Regulatory Network Analysis #Heuristics #Identification (biology) #Machine Learning in Materials Science #Mathematics #Range (aeronautics) #Theoretical computer science #Transformation (genetics) #cond-mat.mtrl-sci #physics.chem-ph #physics.comp-ph

paper · pdf · open access · doi:10.1021/acs.jpca.8b10007

published in The Journal of Physical Chemistry A 123(2), 385-399 (American Chemical Society) · 48 pages, 4 figures

openalex publication_date 2018/11/13 · arxiv created 2018/12/03 · arxiv updated 2019/05/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06

Abstract

For the investigation of chemical reaction networks, the identification of all relevant intermediates and elementary reactions is mandatory. Many algorithmic approaches exist that perform explorations efficiently and in an automated fashion. These approaches differ in their application range, the level of completeness of the exploration, and the amount of heuristics and human intervention required. Here, we describe and compare the different approaches based on these criteria. Future directions leveraging the strengths of chemical heuristics, human interaction, and physical rigor are discussed.

Citations

• A dimer method for finding saddle points on high dimensional potential surfaces using only first derivatives
• Ammonia Synthesis from First-Principles Calculations

Cited by

• Transferable Learning of Reaction Pathways from Geometric Priors
• Finding Pathways in Reaction Networks guided by Energy Barriers using Integer Linear Programming