Semi‐Automated Pipeline for Transition State Search of Molecular Photoswitches

2025/07/21 by Roman Yu. Peshkov, Jorn D. Steen, Stefano Crespi · 1 voice
Materials Science · Computer Science · Chemistry · #Photochromic and Fluorescence Chemistry #Computational Drug Discovery Methods #Various Chemistry Research Topics

paper · pdf · doi:10.1002/cptc.202500126

Abstract

In this work, a semi‐automated pipeline for the transition state search of molecular switches (PiTS 3 ) is reported, which facilitates the search, optimization, and conformational analysis of transition states of user‐generated molecular structures. This tool is oriented towards the casual user interested in simulating the thermal properties of photochemical switches. Hence, the pipeline can easily read the commonly used .cdxml files as input, and leverages different established packages such as ORCA, xTB, CREST, and pysisyphus. Additional scripts are provided to combine different inputs to create libraries of compounds from chemical drawings, to explore large chemical spaces of photoswitches based on the stilbene, imine, aza‐diarylethene, and norbornadiene structures.

Citations

• A generally applicable atomic-charge dependent London dispersion correction
• An improved chain of spheres for exchange algorithm
• CREST—A program for the exploration of low-energy molecular chemical space
• Efficient implementation of the analytic second derivatives of Hartree–Fock and hybrid DFT energies: a detailed analysis of different approximations

Discussions

• Our pipeline to compute thermal barriers of photoswitches💡 is out!🥳 We especially focused on NBDs for MOST🔋 and imines, but also stilbenes and DAEs. Try it out! You need just chemdraws and freeware [bsky, 18 points, 0 comments]

Related

• An automated photo-isomerisation and kinetics characterisation system for molecular photoswitches
• Data-Driven Discovery of Molecular Photoswitches with Multioutput Gaussian Processes
• Thermal half-lives of azobenzene derivatives: virtual screening based on intersystem crossing using a machine learning potential
• Photoswitches beyond azobenzene: a beginner’s guide
• Automated exploration of the low-energy chemical space with fast quantum chemical methods