Covalent modification of proteins by ubiquitin or ubiquitin chains is one of the most prevalent post-translational modifications in eukaryotes. Different types of ubiquitin chains are assumed to selectively signal respectively modified proteins for different fates. In support of this hypothesis, structural studies have shown that the eight possible ubiquitin dimers adopt different conformations. However, at least in some cases, these structures cannot sufficiently explain the molecular basis of the selective signaling mechanisms. This indicates that the available structures represent only a few distinct conformations within the entire conformational space adopted by a ubiquitin dimer. Here, molecular simulations on different levels of resolution can complement the structural information. We have combined exhaustive coarse grained and atomistic simulations of all eight possible ubiquitin dimers with a suitable dimensionality reduction technique and a new method to characterize protein-protein interfaces and the conformational landscape of protein conjugates. We found that ubiquitin dimers exhibit characteristic linkage type-dependent properties in solution, such as interface stability and the character of contacts between the subunits, which can be directly correlated with experimentally observed linkage-specific properties.
One of the approaches to improve our ability to characterize biologically important processes and to map out an underlying free energy landscape is to direct MD simulations to explore molecular conformational phase space faster. Intrinsically disordered systems with shallow free energy landscapes of a huge number of metastable minima pose a particular challenge in this regard. Both characterization of the often ill-defined conformational states as well as the assessment of the degree of convergence of phase space exploration are problematic. We have used a multidimensional scaling-like embedding (sketch-map) to describe the energetically accessible regions of phase space for a peptide fragment of the intrinsically disordered protein α-synuclein. Using sketch-map coordinates from a short initial simulation, we guided additional MD simulations to efficiently expand sampling of the conformational space. The sketch-map projections are very well suited to detect rare but possibly functionally relevant events, metastable intermediates, and transition states in the vast amount of data.
One ongoing topic of research in MD simulations is how to enable sampling to chemically and biologically relevant time scales. We address this question by introducing a back-mapping based sampling (BMBS) that combines multiple aspects of different sampling techniques. BMBS uses coarse grained (CG) free energy surfaces (FESs) and dimensionality reduction to initiate new atomistic simulations. These new simulations are started from atomistic conformations that were back-mapped from CG points all over the FES in order to sample the entire accessible phase space as fast as possible. In the context of BMBS, we address relevant back-mapping related questions like where to start the back-mapping from and how to judge the atomistic ensemble that results from the BMBS. The latter is done with the use of the earth mover's distance, which allows us to quantitatively compare distributions of CG and atomistic ensembles. By using this metric, we can also show that the BMBS is able to correct inaccuracies of the CG model. In this paper, BMBS is applied to a just recently introduced neural network (NN) based approach for a radical coarse graining to predict free energy surfaces for oligopeptides. The BMBS scheme back-maps these FESs to the atomistic scale, justifying and complementing the proposed NN based CG approach. The efficiency benefit of the algorithm scales with the length of the oligomer. Already for the heptamers, the algorithm is about one order of magnitude faster in sampling compared to a standard MD simulation.
Proteins that influence nucleation, growth, or polymorph selection during biomineralization processes are often rich in glutamic-or aspartic acid. Here, the interactions between carboxylate side chains and ions lead to an interplay of peptide conformations and ion structuring in solution. Molecular dynamics simulations are an ideal tool to mechanistically investigate these processes. Unfortunately, the formation of strong ion-peptide contacts and ion bridges drastically impedes structural reorganization of ionic bonds and conformational transitions of the polymers. Thus, to obtain a complete thermodynamical picture of such systems, enhanced sampling techniques become necessary as well as the methods to characterize the conformational states of these partially disordered polymer-ion systems. Here, we propose a new set of Hamiltonian replica exchange (HRE) parameters for efficient simulations of peptide−ion systems, with an aspartic acid trimer in the presence of Ca 2+ and Cl − ions as a test system. We introduce dimensionality reduction and clustering strategies to characterize the states of such a multicomponent system and to analyze the outcome of the proposed HRE with different reweighting methods.
Regulation of gene expression via riboswitches is a widespread mechanism in bacteria. Here, we investigate ligand binding of a member of the guanidine sensing riboswitch family, the guanidine-II riboswitch (Gd-II). It consists of two stem–loops forming a dimer upon ligand binding. Using extensive molecular dynamics simulations we have identified conformational states corresponding to ligand-bound and unbound states in a monomeric stem–loop of Gd-II and studied the selectivity of this binding. To characterize these states and ligand-dependent conformational changes we applied a combination of dimensionality reduction, clustering, and feature selection methods. In absence of a ligand, the shape of the binding pocket alternates between the conformation observed in presence of guanidinium and a collapsed conformation, which is associated with a deformation of the dimerization interface. Furthermore, the structural features responsible for the ability to discriminate against closely related analogs of guanidine are resolved. Based on these insights, we propose a mechanism that couples ligand binding to aptamer dimerization in the Gd-II system, demonstrating the value of computational methods in the field of nucleic acids research.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.