Research Mentor(s): Yongqun He, Associate Professor
Research Mentor School/College/Department: Lab Animal Medicine, Microbiology and Immunology, & Bioinformatics, Michigan Medicine
Presentation Date: Thursday, April 22, 2021
Session: Session 1 (10am-10:50am)
Breakout Room: Room 19
Bioinformatics has been a powerful method to study COVID-19 and our project look at ontology-based application in rational drug design. In our previous study (https://www.nature.com/articles/s41597-021-00799-w), the Coronavirus Infectious Disease Ontology (CIDO) was used as an ontological platform to represent anti-coronaviral drugs, drug targets, host-coronavirus interaction (HCI), and their relations. A “HCI checkpoint cocktail” strategy was further proposed to interrupt the important checkpoints in the dynamic HCI network and ontologies support this design process. However, the users such as drug researchers might not have the required ontology knowledge to use the information represented by the CIDO. Therefore, our project aims to design and build a user-friendly tool/website to allow basic queries and facilitate rational drug design using “checkpoint cocktail” strategy. We have developed a MySQL relational database that systematically represent the drugs, bioentities, interactions, pathways, and their relations. A set of real life data were added to the database. MySQL queries were performed to demonstrate our capabilities to query different contents from the database to support the query of anti-coronaviral drug information. A web interface is being developed in order to further support online query and analysis of anti-coronaviral drugs, leading to rational anticoronaviral drug cocktail design.
Authors: Peiling Tan, Yongqun Oliver He
Research Method: Computer Programming