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Automated exploration of the conformational degrees of freedom along reaction profiles - driving a FASTCAR.

Oscar GayraudBastien CourbièreFrédéric Guegan
Published in: Physical chemistry chemical physics : PCCP (2024)
This publication aims at presenting a Python-based workflow designed to enable a fully automatised and exhaustive exploration of the conformational degrees of freedom within the calculation of reaction paths in molecular systems. The proposed strategy focuses on effectively representing the lowest energy conformers for intricate, highly rotatable, and non-intuitive transition states, reagents and products, using existing computational tools. The article presents a workflow that is demonstrated through the application of five chemical reactions, chosen to be representative of the diversity and complexity of actual experimental studies, and which often prove to be challenging to study "by hand". The proposed methodology is expected to be of a great help in the modelling of state-of-the art organic chemistry reactions, whose complexity is ever increasing.
Keyphrases
  • single molecule
  • molecular dynamics
  • molecular dynamics simulations
  • electronic health record
  • machine learning
  • deep learning
  • high throughput
  • case report
  • electron transfer
  • drug discovery
  • water soluble