Research Highlights

A new study by Iowa State researchers Aayushi Singh, Daniel Burns, Sergey Sedinkin, Sayan Das, Davit Potoyan, and Vincenzo Venditti, published September 16 in PNAS, reveals how substrate binding drives a major conformational change in bacterial Enzyme I. By integrating solution NMR with molecular simulations, the team identified a distributed network of interactions that connects the substrate-binding site to distant protein domains, providing a broadly applicable strategy for understanding allostery in complex biomolecular systems.

A new study by Iowa State researchers Divyanshu Shukla and Davit Potoyan, in collaboration with researchers from the University of Texas at Dallas, uses generative AI to connect the sequence and structural “languages” of proteins. Published October 2 in PNAS, the study compares maps of protein families built from amino acid sequences and three-dimensional shapes, revealing how each captures different aspects of protein function and evolution. The approach uncovers relationships that sequence comparisons alone can miss and could help scientists predict the functions of unknown proteins and design new proteins adapted to different environments. 

Prof. Yuan Zhang and co-workers, including postdoctoral researcher Dr. Jingqiang Han and graduate student Erin Jacobsen, report a new strategy, termed “Core-Regenerating Atom-Pair Exchange,” that enables the selective replacement of a carbon atom in pyridine molecules with ¹³C, a stable isotope of carbon that can be used to trace molecules in biological systems. Pyridines are among the most common building blocks in medicines, and carbon-isotope labeling provides a valuable way to study how drug molecules move through and are processed by the body. The Zhang group anticipates that this method could provide a broadly useful approach for developing ¹³C-labeled drug molecules and advance research in drug discovery.