Case ID: M25-009L^

Published: 2025-06-03 10:08:30

Last Updated: 1748945310


Inventor(s)

Jin Lu
Ismail Can Kazan
Sefika Banu Ozkan

Technology categories

Artificial Intelligence/Machine LearningLife Science (All LS Techs)Proteomic Assays/Reagents/Tools

Licensing Contacts

Jovan Heusser
Director of Licensing and Business Development
[email protected]

Dynamic-based Computational Drug Design Strategy for WW Domains

Understanding the relationship between protein sequence-structure and binding dynamics is not well understood. Of particular interest is the ability to relate foldability and function of a protein and the ability to characterize how foldability and binding change based on mutations in the protein sequence. WW domains are one of the most abundant independently folded protein domains in nature, mainly due to their important role in regulating transcription, apoptosis and ubiquitylation. Unfortunately, a significant proportion of artificially designed WW sequences fail to fold correctly.
 
Researchers at Arizona State University have developed a dynamic-based design and computational drug design strategy for WW domains, focusing on both local and distal sites to achieve nature-like binding affinity. This strategy provides valuable insights into predicting and manipulating protein-ligand interactions. By understanding the dynamics of protein structures, and implementing innovative strategies, new proteins can be designed with improved binding affinity and specificity. This novel computational approach restores functionality in underperforming WW domains to create gain-of-function mutants.
 
The present method paves the way for a new era of protein design that has the potential to significantly impact the field of biophysics.
 
Potential Applications
  • Protein drug design and development
  • Synthetic biology and bioengineering
  • Biotechnology research – tool for understanding protein dynamics and interactions
Benefits and Advantages
  • Provides approaches to rationally design proteins with altered binding affinity
  • Elucidates roles of dynamics and potential allosteric effects in determining binding
  • Allows proteins to be engineered for desired binding properties
  • Overcomes limitations in current protein design approaches by incorporating dynamic analysis
  • Addresses the challenges of enhancing protein functionality without compromising foldability or stability
For more information about this opportunity, please see
 
For more information about the inventor(s) and their research, please see