October 26, 2026
A Mizzou Engineering researcher’s NIH-funded project aspires to improve understanding of disease-causing mutations and accelerate drug discovery.
An ambitious new project from a leading Mizzou Engineering researcher will develop new artificial intelligence (AI) tools that can better determine the shapes and structures of large biological molecules, especially groups of proteins working together.
Scientists can predict the structure of individual proteins using AI, but figuring out more complex molecular assemblies remains difficult. This project will use AI to combine genetic information, cryogenic-electron microscopy images and existing 3D structural data to build more accurate models of complex biological molecules.
The goal is to help researchers understand how biological molecules work and change, including how disease-causing mutations alter protein structures and accelerate drug discovery.
Who is conducting the research?
Jianlin (Jack) Cheng is a leading researcher on predicting protein structure, function and interaction for precision medicines and other applications. He is a Curators’ Distinguished Professor and the Paul K. and Diane Shumaker Professor in Bioinformatics in the David L. Payne Department of Electrical Engineering and Computer Science.
Why is this research important?
Current AI methods have revolutionized protein structure prediction but still have important limitations. This project aims to develop AI methods to reconstruct large macromolecular structures from cryogenic-electron microscopy — which allows scientists to take extremely detailed pictures of biological molecules — and cryo-electron tomography data — which lets scientists create 3D images of the molecular machinery inside cells — helping them see how biological components are organized and interact.
Cheng will also develop AI models that predict the detailed structural changes caused by single or multiple protein mutations that existing methods generally cannot predict accurately.
“Applications of AI is one of the big pushes for the federal government, so this project aligns well with national priorities of AI and biomedical tech integration.” – Jianlin Cheng
Who benefits from this research?
Scientists studying disease, pharmaceutical companies developing new therapies, physicians pursuing precision medicine and, ultimately, patients could all benefit from AI tools that reveal the structures of complex biomolecules and develop more personalized therapies more quickly and accurately.
“These tools can be used by biological and medical researchers and practitioners to study proteins related to many aspects of life sciences such as disease, protein design, protein engineering, drug discovery, crop engineering and bioenergy.” – Jianlin Cheng
Who is funding the research?
Cheng’s study “AI methods for reconstructing protein complex structures from cryo-EM data and predicting mutated protein structures” is funded by a $2.3 million National Institutes for Health (NIH) Maximizing Investigators’ Research Award (MIRA).
Bottom line
Cheng’s NIH-funded project aims to leverage AI to help scientists see the structures of complex biological molecules more accurately, which could accelerate drug discovery, improve understanding of disease-causing mutations and advance precision medicine.
What can I study if I’m interested in this research?
Mizzou undergraduates can pursue a bachelor degree in computer science as well as an undergraduate certificate in artificial intelligence fundamentals and applications.
Computer science undergrads who have completed at least 90 credit hours and have a 3.0 GPA or higher are eligible to apply for the accelerated BS to MS program.
Graduate students can pursue a master’s degree in computer science or a master’s degree in artificial intelligence. Mizzou Engineering also offers a doctorate in computer science.