Online platform explores virtual chemical reaction pathways
A new online platform to explore computationally calculated chemical reaction pathways has been released by Japanese researchers, allowing for in-depth understanding and design of chemical reactions.
Advances in computational chemistry have proven a great boon in the field of reaction design, leading to the discovery of new reaction pathways for the synthesis of high-value compounds. Computational chemistry generates much data, and the process of organising and visualising this data is vital to be able to utilise it for future research.
A team of researchers from Hokkaido University, led by Professor Keisuke Takahashi and Professor Satoshi Maeda, has now developed a centralised, interactive and user-friendly platform, Searching Chemical Action and Network (SCAN), to explore reaction pathways generated by computational chemistry. Their work has been published in the journal Digital Discovery.
“From a computational viewpoint, chemical reactions can be considered as extremely complex networks that consist of numerous molecular interactions,” Takahashi said. “Many tools have been developed to calculate these networks, such as the AFIR method we use at WPI-ICReDD [Hokkaido’s Institute for Chemical Reaction Design and Discovery]. However, tools to explore these calculated networks are also needed, which led us to the current study.”
In broad strokes, all the raw data from AFIR calculations forms a ‘data lake’. This data is then subjected to a pre-processing step, creating a ‘data warehouse’. Finally, the ‘data mart’ accesses and retrieves data from the data warehouse and provides tools to visualise, analyse and share the retrieved data.
“The pre-processing step is crucial,” Maeda said. “The raw data form AFIR contains an immense amount of information, from which the key data required for the SCAN platform must be extracted. This key data is sufficient to allow the creation of an interactive reaction pathway map which can be searched and viewed.”
SCAN is accessible online at https://scan.sci.hokudai.ac.jp/. The source code for SCAN is also publicly available.
“We have developed SCAN with a user-friendly graphic user interface,” Takahashi said. “Users can search and explore the chemical reaction path network generated by the first principle calculation (AFIR). It will aid in achieving a detailed understanding of complex chemical reaction pathways.”
AI camera tech could help quickly identify serious infections
A combination of camera technology, software and AI has the potential to assess the severity of...
Machine learning identifies 800,000+ antimicrobial peptides
An international research team has used machine learning to search for antibiotics in a vast...
AI platform makes microscopy image analysis more accessible
DL4MicEverywhere makes artificial intelligence (AI) accessible for analysing microscopy images,...