Sunday, May 11, 2025
5/11/2025
Theory and Modeling of Functional Conformational Changes of RNA Polymerases_Diversity Supplement - Project Summary: The operation of RNA polymerases (RNAPs) relies on numerous conformational changes. During eukaryotic transcription, RNA Polymerase II (Pol II) encountering oxidative lesions in its DNA template often leads to misincorporation and transcriptional stalling. These events contribute to tumor growth in skin cancer. Mycobacterium tuberculosis (Mtb) causes lethal tuberculosis and is responsible for over 1 million deaths per year. Transcription initiation complexes of Mtb RNAP, especially the DNA loading gate, are effective targets for the development of antibiotics. Revealing the dynamics of transcription initiation can thus provide novel mechanistic insights into prokaryotic transcription and greatly facilitate the understanding of inhibition mechanisms for antibiotics targeting Mtb RNAP. These two important biological problems in transcription drive us to develop novel methodology using the generalized master equation (GME) to model biomolecular conformational changes. My group has been successful in developing GME methods that explicitly consider the memory functions of biomolecular dynamics and outperform the popular Markov State Model (MSM) method. However, as an emerging approach, the current implementation of GME is prone to instability when estimating memory functions for complex RNAP systems. We here propose novel methods to build GME models. Our specific aims are: 1. To develop new GME methods to model conformational changes. Specifically, to derive a new theory (IGME) to solve the GME, to develop efficient implementations of the GME to enhance numerical stability when computing memory kernels from molecular dynamics (MD) simulation trajectories, and to create a protocol tailor-made for building GME models to study biomolecular conformational changes. Our preliminary work shows that the proposed IGME method greatly outperforms the original implementation of GME in yielding robust and accurate predictions of the biomolecular dynamics, especially for the complex RNAP system. 2. To reveal how the dynamic coupling of several key conformational changes (i.e., the loading of NTP, the rotation of the damaged DNA base, and the translocation of Pol II on the DNA template) leads to transcriptional mutagenesis and/or stalling. Specifically, to construct GME models to elucidate molecular mechanisms of 8-oxo- guanine (8OG) and Guanidinohydantoin (Gh) lesions induced ATP misincorporation and/or transcriptional stalling. 3. To elucidate the molecular mechanisms of transcriptional initiation and its inhibition of Mtb RNAP. Specifically, to construct GME models to reveal the dynamics of the Mtb RNAP’s loading gate without DNA, and to further reveal the dynamics for the transition from a partially formed transcription bubble to a fully formed bubble, a conformational change involving both Mtb RNAP’s gate opening and DNA unwinding. We further aim to understand the recognition mechanisms of multiple antibiotic compounds, including Myxopyronin (Myx) and Fidaxomicin (Fdx) that target the loading gate motion, and Sorangicin (Sor) that inhibits the formation of the full transcription bubble. These mechanistic insights will facilitate the rational design of new inhibitors fighting drug resistance of Mtb in the long term. Throughout our studies, we will work closely with our experimental collaborators to conduct biochemical, time-resolved X-ray, and Cryo-EM experiments to test and validate our predictions. Our innovative GME methods will provide a general computational framework to model functional conformational changes of biomolecules. Our developed protocol and associated code development in the MSMBuilder software will widely benefit the biophysics community.
HHS’ Tracking Accountability in Government Grants System (TAGGS) website provides access to detailed descriptions of grants, loans, aggregated direct payments and other types of financial assistance awarded by the HHS Operating Divisions (OPDIVs) and the Office of the Secretary Staff Divisions (STAFFDIVs).