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Researchers create most complete model of complex protein machinery



 The researchers used the new model to accurately identify clusters of gene mutations (spheres), which helped them study the emergence of various genetic diseases. Credit: Ivaylo Ivanov, Georgia State University
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<p> Environmental conditions, lifestyle choices, chemical exposure, and foodborne and airborne pathogens are among the external factors that can cause disease. In contrast, internal genetic factors can be responsible for the onset and progression of diseases ranging from degenerative neurological disorders to some cancers.<br />
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The state-of-the-art smartest and most powerful supercomputer in the world, the world's smartest and most powerful supercomputer, is now developing an integrative model of the transcription preinitiation complex (PIC), a complex of protein vital to gene expression. Results of this work are published in Nature Structural & Molecular Biology .

Gene expression involves the conversion of genetic information that originates in DNA to produce functional molecules. through steps known as transcription and translation. Because of genetic mutations and genetic phenomena, biomedical scientists are also interested in making sense of the connection between a patient's unique genetic makeup, or genotype, and the external manifestation of a disease or phenotype.

A better understanding The complex relationship between a genotype and a phenotype could reveal how mutations cause genetic diseases and thus inform the development of more effective treatments.

"In a machine, mutationally changes the function of the defective protein, a process that involves alterations in both structure and dynamics," Ivanov said ,

Polynesis-play a., Polly II, and Pol III, referred to collectively as RNA polymerases-play a., Describe the complex and highly regulated process of gene transcription significant role. Pol II helps mediate protein synthesis, the process of transforming genetic information into proteins.

During initiation-the first step of transcription-Pol II and a host of general transcription factors (GTFs) assemble in a region of DNA called a promoter to form the PIC. Opening the promoter depends on transcription factor II human (TFIIH), a GTF consisting of multiple protein chains, which has the ability to unwind the double helix strands of DNA to initiate transcription. TFIIH also contributes to DNA repair.

Because the biochemical pathways responsible for gene expression and repair are intertwined, understanding the molecular mechanism behind this process is crucial to advancing biomedical applications. In short, the presence of mutations in three subunits of TFIIH directly leads to severe genetic diseases, including autoimmune and neurological disorders.

Previous attempts to characterize the PIC have been limited by incomplete models.

To develop their PIC model, the researchers combine data from cryo-electron microscopy (CryoEM) -a structural biology method that uses an electron beam to study cryogenically frozen protein and large-scale molecular dynamics simulations on Summit using the Nanoscale Molecular Dynamics (NAMD) code. The Oak Ridge Leadership Computing Facility (OLCF), a US Department of Energy's (DOE) Office of Science User Facility at Oak Ridge National Laboratory (ORNL).


A visualization of a new structure of the human PIC , The spheres correspond to the positions of patient-derived mutations color-coded by disease phenotype. Credit: Ivaylo Ivanov, Georgia State University.

"The new model gives us the most complete view of the structure of TFIIH, which explains the origins of patient-derived mutations, potentially The future of the structural mechanics of TFIIH, "Ivanov said.

The PIC and the how it explains its structural components function to modify DNA. By mapping 36 different patient-derived mutations to the PIC model, the team determined that the mutations tend to be clustered in critical areas of TFIIH, including a subunit known as XPD, which prevents the GTF from working properly and leads to disease.

"Computation is absolutely instrumental in providing a link between the structure, which comes from CryoEM data, and the disease phenotype, which is a high-level concept, which is based on traditional biochemistry and structural biology," Ivanov said. 19659005]

"In the presence of cancer, aging, and developmental defects, by means of their distinguishing molecular mechanisms." then you can potentially develop therapies for genetic diseases, but without a fundamental understanding of the underlying mechanism, "Ivanov said 9659005] This accomplishment provides a foundation for the genetic engineering research, expound on TFIIH's distinct contribution to transcription and DNA repair, and delves deeper into the mechanism of gene expression.

high-performance computing platforms, access to high-performance computing platforms.

"Running on Summit accelerates our research," Ivanov said.

This year, the team is going to make calculations on a summit through a 2019 Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program allocation. The researchers have studied pol II, but they plan to expand their project to investigate the functional dynamics of Pol I and Pol III as well, which could lead to more groundbreaking insights.

"We look forward to moving beyond describing the Mechanisms of transcription to elucidate their connection to genetic diseases, "Ivanov said.
                                                                                                                        


Zooming in on an inner-cell DNA repair shop


More information:
Chunli Yan et al., Transcription Preli- tation Complex Structure and Dynamics Intellec- tive Intellectual Diseases, Nature Structural & Molecular Biology (2019). DOI: 10.1038 / s41594-019-0220-3

Provided by
Oak Ridge National Laboratory




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                                                 Researchers create most complete model of complex protein machinery (2019, May 21)
                                                 retrieved 22 May 2019
                                                 from https://phys.org/news/2019-05-complex-protein-machinery.html
                                            

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