Biology subjects

Pietrek, L. M.

Publications and source records attributed to Pietrek, L. M..

4 recordsLinked to original sources

bioRxiv2023

Hierarchical assembly of single-stranded RNA

Single-stranded RNA (ssRNA) plays a major role in the flow of genetic information- most notably in the form of messenger RNA (mRNA)-and in the regulation of biological processes. The highly dynamic nature of chains of unpaired nucleobases challenges structural characterizations of ssRNA by experiments or molecular dynamics (MD) simulations alike. Here we use hierarchical chain growth (HCG) to construct ensembles of ssRNA chains. HCG assembles the structures of protein and nucleic acid chains from fragment libraries created by MD simulations. Applied to homo- and heteropolymeric ssRNAs of different lengths, we find that HCG produces structural ensembles that overall are in good agreement with diverse experiments including nuclear magnetic resonance (NMR), small-angle X-ray scattering (SAXS), and single-molecule Forster resonance energy transfer (FRET). The agreement can be further improved by ensemble refinement using Bayesian inference of ensembles (BioEn). HCG can also be used to assemble RNA structures that combine base-paired and unpaired regions, as illustrated for the 51 untranslated region (UTR) of SARS-CoV-2 mRNA.

biophysics↗

bioRxiv2021

Global Structure of the Intrinsically Disordered Protein Tau Emerges from its Local Structure

The paradigmatic disordered protein tau plays an important role in neuronal function and neurodegenerative diseases. To disentangle the factors controlling the balance between functional and disease-associated conformational states, we build a structural ensemble of the tau K18 fragment containing the four pseudorepeat domains involved in both microtubule binding and amyloid fibril formation. We assemble 129-residue-long tau K18 chains at atomic resolution from an extensive fragment library constructed with molecular dynamics simulations. We introduce a reweighted hierarchical chain growth (RHCG) algorithm that integrates experimental data reporting on the local structure into the assembly process in a systematic manner. By combining Bayesian ensemble refinement with importance sampling, we obtain well-defined ensembles and overcome the problem of exponentially varying weights in the integrative modeling of long-chain polymeric molecules. The resulting tau K18 ensembles capture nuclear magnetic resonance (NMR) chemical shift and J-coupling measurements. Without further fitting, we achieve excellent agreement with measurements of NMR residual dipolar couplings. The good agreement with experimental measures of global structures such as singlemolecule Forster resonance energy transfer (FRET) efficiencies is improved further by ensemble refinement. By comparing wild-type and mutant ensembles, we show that pathogenic single-point P301 mutations shift the population from the turn-like conformations of the functional microtubule-bound state to the extended conformations of disease-associated tau fibrils. RHCG thus provides us with an atomically resolved view of the population equilibrium between functional and aggregation-prone states of tau K18, and demonstrates that global structural characteristics of this intrinsically disordered protein emerge from its local structure.

biophysics↗

bioRxiv2021

Disease-linked TDP-43 hyperphosphorylation suppresses TDP-43 condensation and aggregation

Post-translational modifications (PTMs) have emerged as key modulators of protein phase separation and have been linked to protein aggregation in neurodegenerative disorders. The major aggregating protein in amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), the RNA-binding protein TDP-43, is hyperphosphorylated in disease on several C-terminal serine residues, which is generally believed to promote TDP-43 aggregation. Here, we show that hyperphosphorylation by Casein kinase 1{delta} or C-terminal phosphomimetic mutations surprisingly reduce TDP-43 phase separation and aggregation and render TDP-43 condensates more liquid-like and dynamic. Multi-scale simulations reveal reduced homotypic interactions of TDP-43 low complexity domains through enhanced solvation of phosphomimetic residues. Cellular experiments show that phosphomimetic substitutions do not affect nuclear import or RNA regulatory functions of TDP-43, but suppress accumulation of TDP-43 in membrane-less organelles and promote its solubility in neurons. We propose that TDP-43 hyperphosphorylation may be a protective cellular response to counteract TDP-43 aggregation.

biochemistry↗

bioRxiv2019

Hierarchical Ensembles of Intrinsically Disordered Proteins at Atomic Resolution in Molecular Dynamics Simulations

Intrinsically disordered proteins (IDPs) constitute a large fraction of the human proteome and are critical in the regulation of cellular processes. A detailed understanding of the conformational dynamics of IDPs could help to elucidate their roles in health and disease. However the inherent flexibility of IDPs makes structural studies and their interpretation challenging. Molecular dynamics (MD) simulations could address this challenge in principle, but inaccuracies in the simulation models and the need for long simulations have stymied progress. To overcome these limitations, we adopt an hierarchical approach that builds on the \"flexible meccano\" model of Bernado et al. (J. Am. Chem. Soc. 2005, 127, 17968-17969). First, we exhaustively sample small IDP fragments in all-atom simulations to capture local structure. Then, we assemble the fragments into full-length IDPs to explore the stereochemically possible global structures of IDPs. The resulting ensembles of three-dimensional structures of full-length IDPs are highly diverse, much more so than in standard MD simulation. For the paradigmatic IDP -synuclein, our ensemble captures both local structure, as probed by nuclear magnetic resonance (NMR) spectroscopy, and its overall dimension, as obtained from small-angle X-ray scattering (SAXS) in solution. By generating representative and meaningful starting ensembles, we can begin to exploit the massive parallelism afforded by current and future high-performance computing resources for atomic-resolution characterization of IDPs.

biophysics↗