ATLANTA—A Georgia State University chemistry researcher and his collaborators have created a new structural model of the human transcription preinitiation complex (PIC), providing new insights into how genetic mutations lead to three inherited genetic diseases.
Genetic factors play an outsized role in the onset and progression of many diseases. Understanding how the patient’s unique genetic makeup (genotype) is linked to the external manifestations of the disease (phenotype) is a grand challenge in biomedical science. Making sense of the connection between genotype and phenotype could unravel the causes of many cancers, degenerative neurological and inherited genetic disorders, thus stimulating discovery of new treatments.
The team, led by Associate Professor of Chemistry Ivaylo Ivanov, developed a new, comprehensive model of the human transcription preinitiation complex (PIC), a complex assembly of proteins vital to gene expression. While structural knowledge of the PIC is beginning to emerge, little is understood about its molecular mechanism, which underlies gene expression regulation. At the same time, detailed mechanistic knowledge is essential to advance biomedical applications. Importantly, the biochemical pathways that orchestrate the expression and repair of genes are intricately intertwined. For instance, mutations in just three subunits of the general transcription factor TFIIH, a constituent of the PIC, result in severe human genetic disorders. Notably, the new model uncovered a critical connection between the locations of patient-derived mutations and disease phenotype.
“Basically, this new model provides a link all the way from the molecular architecture, through dynamics, all the way to phenotype or disease,” Ivanov said. “This will help us understand the dynamics of these proteins and let us map the origins of mutations, potentially enabling future biochemical experiments as well.”
To develop their PIC model, the researchers ran simulations of the process on the world’s most powerful supercomputer, located at the Oak Ridge Leadership Computing Facility, a US Department of Energy Office of Science User Facility at at Oak Ridge National Laboratory in Tennessee. Using the supercomputer allowed the research team to spend hours rather than months to perform the calculations needed for the study, Ivanov said.
“Computation is absolutely instrumental in providing a link between the structure and the disease phenotype, which is difficult to explain with answers purely based on traditional biochemistry and structural biology,” he said. “The speed of the Summit system allowed us to make rapid progress on this important research problem.”
The simulations revealed the hierarchical organization of the PIC and explained how its numerous structural components function to modify DNA during the early stages of transcription. From these findings, the team gained detailed insights into three distinct genetic disorders associated with cancer, aging, and developmental defects and their distinguishing molecular mechanisms.
“If you have a handle on which regions of a protein are affected, then you can potentially develop therapies for genetic diseases, but without a fundamental understanding of the underlying mechanism, all bets are off,” Ivanov said.
Ivanov’s coauthors include Chunli Yan and Thomas Dodd of Georgia State University, Yuan He of Northwestern University, John A. Tainer of the University of Texas M.D. Anderson Cancer Center and Lawrence Berkeley National Laboratory, and Susan E. Tsutakawa of Lawrence Berkeley National Laboratory.
The research was supported by the National Institutes of Health and is discussed in the article “Transcription preinitiation complex structure and dynamics provide insight into genetic diseases,” published in Nature Structural & Molecular Biology.
Image courtesy of Oak Ridge Leadership Computing Facility.