Michael Schnieders is a UI professor of biomedical engineering with expertise in molecular biophysics theory and high-performance computational algorithms.
Wednesday, April 16, 2025
Michael J. Schnieders
Schnieders

A University of Iowa engineering professor is creating new computer models that would speed up development of lifesaving drugs by better predicting how drugs crystallize into pharmaceutical tablets and their binding to protein targets when delivered to the human body. 

A key focus is understanding complex organic crystals, which are structures composed of molecules with unique properties, such as flexibility or the ability to change shape. Crystal structures are the foundation for many drugs, and they are at the heart of a new three-year, $600,000 National Science Foundation grant awarded to Michael Schnieders, UI professor of biomedical engineering and principal investigator of the project.

Being able to predict organic crystals’ solubility, stability, and bioavailability (how well it's absorbed in the body) is essential to developing safe and effective therapeutic drugs. 

Schnieders Lab
Nessler

While methods exist to predict properties and behaviors of simpler crystal structures, predictions become far more difficult with more complex crystals.

Schnieders, a renowned scholar of molecular biophysics theory and high-performance computational algorithms, plans to use software called "Force Field X" to simulate how crystals shift from one form to another. A second aspect of the study integrates chemistry to capture how proteins are influenced by pH, or acidity/basicity, in both aqueous solution and solid phases. Andrew Thiel and Aaron Nessler, who both recently earned PhDs in biomedical engineering, have been key contributors to the project as members of Schnieders' lab. 

These breakthroughs could speed up critical drug design calculations by as much as 100 times, reduce costs, and lead to new knowledge of how enzymes work, according to Schnieders' hypothesis.

Schnieders Lab
Thiel

The project will also engage high school science students through internships, train graduate students in advanced computational skills, and share Force Field X with the scientific community for free.

Learn more about the grant at https://www.nsf.gov/awardsearch/showAward?AWD_ID=2504153