Biology subjects

Duc, K. D.

Publications and source records attributed to Duc, K. D..

3 recordsLinked to original sources

bioRxiv2025

Advanced coarse-grained model for fast simulation of nascent polypeptide chain dynamics within the ribosome

The nascent polypeptide exit tunnel (NPET) is a sub-compartment of the ribosome that constrains the dynamics of nascent polypeptide chains during protein translation. Simulating these dynamics has been limited due by the spatial scale of the ribosome and the temporal scale of elongation. Here, we present an automated pipeline to extract the geometry of the NPET and the ribosome surface at high resolution from any ribosome structure. We further convert this into a coarse-grained (CG) bead model that can be used in molecular simulations. This CG model more accurately captures NPET geometry than previous representations and allows for the simulation of co- and post-translational processes that are computationally prohibitive with all-atom approaches. In particular, we illustrate how the CG model may be used to simulate the elongation dynamics of the nascent polypeptide and its escape post-translation, as well as evaluate free energy landscapes and examine the influence of electrostatics on the nascent polypeptide escape. SIGNIFICANCEThe translation of nascent polypeptide chains is mediated by the ribosome, with interactions between the protein and the nascent polypeptide exit tunnel (NPET) impacting the process. However, modeling and simulating protein elongation and its escape from the NPET remain challenging due to computational limitations in spatial and temporal resolution. Here, we develop a computational pipeline for generating coarse-grained (CG) models of the NPET and ribosome surface from any ribosome structure that allow for both effective and accurate computer simulations. We demonstrate how the model can be implemented for various simulations, including the elongation dynamics of the nascent polypeptide and escape of the chain post-translation, as well as in estimating free energy landscapes and examining the impact of the charged environment on the escape time.

biophysics↗

bioRxiv2025

Detection of archaeal- and prokaryotic-like ribosome exit tunnels within eukaryotic kingdoms

The ribosome exit tunnel is a critical sub-compartment that actively regulates the folding and dynamics of nascent polypeptide chains during protein translation. In this study, we systematically examined tunnel structures of 725 ribosome models obtained through cryo-EM and X-ray crystallography, to quantify structural variations across different species and biological domains. Hierarchical clustering revealed significant geometric differences between prokaryotic and eukaryotic ribosomes, with a surprising discovery: six eukaryotic protist species display tunnel structures remarkably similar to those of archaea and bacteria. By analyzing the sequences and structures of ribosomal components forming the tunnel walls, we identified four specific sequence modifications in ribosomal proteins and ribosomal RNAs (rRNA) responsible for these unique geometric variations, and detected these modifications in additional protist species lacking existing 3D structural data. Overall, our findings highlights some complex evolutionary mechanisms governing ribosomal protein and large subunit rRNA, providing novel insights into the tunnels regulatory role in protein translation.

molecular biology↗

bioRxiv2025

A comprehensive survey and benchmark of deep learning-based methods for atomic model building from cryo-EM density maps

Advancements in deep learning (DL) have recently led to new methods for automated construction of atomic models of proteins, from single-particle cryogenic electron microscopy (cryo-EM) density maps. We conduct a comprehensive survey of these methods, distinguishing between direct model building approaches that only use density maps, and indirect ones that integrate sequence-to-structure predictions from AlphaFold. To evaluate them with better precision, we refine standard existing metrics, and benchmark a subset of representative DLmethods against traditional physics-based approaches using 50 cryo-EM density maps at varying resolutions. Our findings demonstrate that overall, DL-based methods outperform traditional physics-based methods. Our benchmark also shows the benefit of integrating AlphaFold as it improved the completeness and accuracy of the model, although its dependency on available sequence information and limited training data may limit its usage.

molecular biology↗