Identifying Small Molecule Drugs to Modulate the Biological Processes
Dr. Bin Chen works in the Departments of Pediatrics & Human Development and Pharmacology & Toxicology at Michigan State University. His lab has been using big data and artificial intelligence to discover new therapeutics for COVID-19 since the outbreak in late January. In particular, they are interested in identifying small-molecule drugs (including FDA approved drugs) that can target the host cells of the SARS-CoV-2 virus.
Currently, many researchers are trying to identify small molecule drugs to modulate one single protein. However, Dr. Chen and his team are working to identify small molecule drugs that modulate multiple biological processes. Their work uses gene expression to model the multiple biological processes involved in the virus-host interaction, and then develops new ways to pinpoint small molecules that reverse global gene expression of host cells. Using this approach, Dr. Chen and his fellow researchers are able to screen all FDA approved drugs and determine whether they have the potential to treat COVID-19.
Their research is currently moving in a few directions. When some of their newly-discovered potential drug candidates were found to be toxic, Dr. Chen and his team began developing a model to predict drug candidates’ toxicity. Another facet of their work focuses on using real world data from hospitals’ electronic medical records to determine whether certain drugs would be effective on patients. And finally together with Dr. Jiayu Zhou’s lab, they are developing deep learning methods to screen over 7 million commercially available compounds for drug discovery.
Very early on in the pandemic’s timeline, Dr. Chen’s team saw a great opportunity to use their resources and expertise in big data and artificial intelligence to help combat the virus. Nevertheless, they had to find ways to work around the twin challenges of accessing large volumes of patient data and the group’s limited resources. The lack of data presented difficulties with validating hypotheses for using certain drug candidates to treat COVID-19. Fortunately, working in collaboration with other scientists, the team is making progress in their effort to validate potential drug candidates in the bench. Moreover, with more and more COVID-19 data becoming available to the group, processing this large volume of data would not have been otherwise possible without access to MSU’s HPCC. Dr. Chen's lab assistant Shreya Paithankar routinely uses HPCC to process raw SARS-CoV-2 RNASeq data collected from public databases.
Dr. Chen has a positive outlook about the group’s ability to leverage the resources available, locally at Michigan State University and wider afield, to contribute to the efforts of combating COVID-19. He encourages anyone who has an idea or wants to make a difference in this time where all contributions matter: “If you have an idea, go out and pursue it! This is a global effort and I think many will be willing to help you.”
