Information Technology
Predicting Protein Hot Spot Residues
WARF: P140357US01
Inventors: Julie Mitchell, Xiaolei Zhu, Steven Darnell
The Wisconsin Alumni Research Foundation (WARF) is seeking commercial partners interested in developing the most accurate software to date for modeling hot spot mutagenesis in proteins.
Overview
Most biological processes involve multiple proteins interacting with each other. While the principles governing protein-protein interactions are not fully understood, it is known that a small subset of ‘hot spot’ residues play a key role in binding.
In practice, the site-directed mutation of hot spots is an effective means of disrupting and studying protein interactions. This typically involves replacing the amino acid of interest with an alanine. The process requires major time and resources to identify hot spots in a systemic fashion.
Predictive models can dramatically improve efficiency.
In practice, the site-directed mutation of hot spots is an effective means of disrupting and studying protein interactions. This typically involves replacing the amino acid of interest with an alanine. The process requires major time and resources to identify hot spots in a systemic fashion.
Predictive models can dramatically improve efficiency.
The Invention
UW–Madison researchers have created the most accurate program ever developed to predict hot spot residues in proteins and model the effects of alanine substitution on each of the amino acids. The program uses a modified Knowledge-based FADE and Contacts (or KFC2) approach.
Applications
- Software for predicting hot spots and alanine mutagenesis
- Determining sites to target with small molecule drug design
Key Benefits
- Outperforms other programs
- Makes experimental design more efficient
Stage of Development
The program currently is in use.
Additional Information
For More Information About the Inventors
Tech Fields
For current licensing status, please contact Jennifer Gottwald at [javascript protected email address] or 608-960-9854