Resolving the fine structure in the energy landscapes of repeat proteins

Understanding the Energy Landscape of Intrinsically Disordered Protein Ensembles

A substantial portion of various organisms' proteomes comprises intrinsically disordered proteins (IDPs) that lack a defined three-dimensional structure. These IDPs exhibit a diverse array of conformations, displaying remarkable spatiotemporal heterogeneity and exceptional conformational flexibility. Characterizing the structure or structural ensemble of IDPs presents significant conceptual and methodological challenges owing to the absence of a well-defined native structure. While databases such as the Protein Ensemble Database (PED) provide IDP ensembles obtained through a combination of experimental data and molecular modeling, the absence of reaction coordinates poses challenges in comprehensively understanding pertinent aspects of the system. In this study, we leverage the energy landscape visualization method (JCTC, 6482, 2019) to scrutinize four IDP ensembles sourced from PED. ELViM, a methodology that circumvents the need for a priori reaction coordinates, aids in analyzing the ensembles. The specific IDP ensembles investigated are as follows: two fragments of nucleoporin (NUL: 884-993 and NUS: 1313-1390), yeast sic 1 N-terminal (1-90), and the N-terminal SH3 domain of Drk (1-59). Utilizing ELViM enables the comprehensive validation of ensembles, facilitating the detection of potential inconsistencies in the sampling process. Additionally, it allows for identifying and characterizing the most prevalent conformations within an ensemble. Moreover, ELViM facilitates the comparative analysis of ensembles obtained under diverse conditions, thereby providing a powerful tool for investigating the functional mechanisms of IDPs.

Helical Content Correlations and Hydration Structures of the Folding Ensemble of the B Domain of Protein A

The B domain of protein A (BdpA), a small three-helix bundle, folds on a time scale of a few microseconds with heterogeneous native and unfolded states. It is widely used as a model for understanding protein folding mechanisms. In this work, we use structure-based models (SBMs) and atomistic simulations to comprehensively investigate how BdpA folding is associated with the formation of its secondary structure. The energy landscape visualization method (ELViM) was used to characterize the pathways that connect the folded and unfolded states of BdpA as well as the sets of structures displaying specific ellipticity patterns. We show that the native state conformational diversity is due mainly to the conformational variability of helix I. Helices I, II, and III occur in a weakly correlated manner, with Spearman's rank correlation coefficients of 0.1539 (I and II), 0.1259 (I and III), and 0.2561 (II and III). These results, therefore, suggest the highest cooperativity between helices II and III. Our results allow the clustering of partially folded structures of folding of the B domain of protein A on the basis of its secondary structure, paving the way to an understanding of environmental factors in the relative stability of the basins of the folding ensemble, which are illustrated by the structural dependency of the protein hydration structures, as computed with minimum-distance distribution functions.

ELViM: Exploring Biomolecular Energy Landscapes through Multidimensional Visualization

Molecular dynamics (MD) simulations provide a powerful means of exploring the dynamic behavior of biomolecular systems at the atomic level. However, analyzing the vast data sets generated by MD simulations poses significant challenges. This article discusses the energy landscape visualization method (ELViM), a multidimensional reduction technique inspired by the energy landscape theory. ELViM transcends one-dimensional representations, offering a comprehensive analysis of the effective conformational phase space without the need for predefined reaction coordinates. We apply the ELViM to study the folding landscape of the antimicrobial peptide Polybia-MP1, showcasing its versatility in capturing complex biomolecular dynamics. Using dissimilarity matrices and a force-scheme approach, the ELViM provides intuitive visualizations, revealing structural correlations and local conformational signatures. The method is demonstrated to be adaptable, robust, and applicable to various biomolecular systems.

Exploring the folding landscape of leptin: Insights into threading pathways

The discovery of new protein topologies with entanglements and loop-crossings have shown the impact of local amino acid arrangement and global three-dimensional structures. This phenomenon plays a crucial role in understanding how protein structure relates to folding and function, affecting the global stability, and biological activity. Protein entanglements encompassing knots and non-trivial topologies add complexity to their folding free energy landscapes. However, the initial native contacts driving the threading event for entangled proteins remains elusive. The Pierced Lasso Topology (PLT) represents an entangled topology where a covalent linker creates a loop in which the polypeptide backbone is threaded through. Compared to true knotted topologies, PLTs are simpler topologies where the covalent-loop persists in all conformations. In this work, the PLT protein leptin, is used to visualize and differentiate the preference for slipknotting over plugging transition pathways along the folding route. We utilize the Energy Landscape Visualization Method (ELViM), a multidimensional projection technique, to visualize and distinguish early threaded conformations that cannot be observed in an in vitro experiment. Critical contacts for the leptin threading mechanisms were identified where the competing pathways are determined by the formation of a hairpin loop in the unfolded basin. Thus, prohibiting the dominant slipknotting pathway. Furthermore, ELViM offers insights into distinct folding pathways associated with slipknotting and plugging providing a novel tool for de novo design and in vitro experiments with residue specific information of threading events in silico.

Probing Mastoparan-like Antimicrobial Peptides Interaction with Model Membrane Through Energy Landscape Analysis

Antimicrobial Peptides (AMPs) have emerged as promising alternatives to conventional antibiotics due to their capacity to disrupt the lipid packing of bacterial cell membranes. This mechanism of action may prevent the development of resistance by bacteria. Understanding their role in lipid packing disruption and their structural properties upon interaction with bacterial membranes is highly desirable. In this study, we employed Molecular Dynamics simulations and the Energy Landscape Visualization Method (ELViM) to characterize and compare the conformational ensembles of mastoparan-like Polybia-MP1 and its analogous H-MP1, in which histidines replace lysine residues. Two situations were analyzed: (i) the peptides in their free state in an aqueous solution containing water and ions and (ii) the peptides spontaneously adsorbing onto an anionic lipid bilayer, used as a bacteria membrane mimetic. ELViM was used to project a single effective conformational phase space for both peptides, providing a comparative analysis. This projection enabled us to map the conformational ensembles of each peptide in an aqueous solution and assess the structural effects of substituting lysines with histidines in H-MP1. Furthermore, a single conformational phase space analysis was employed to describe structural changes during the adsorption process using the same framework. We show that ELViM provides a comprehensive analysis, able to identify discrepancies in the conformational ensembles of these peptides that may affect their affinity to the membrane and adsorption kinetics.

Characterizing the Folding Transition-State Ensembles in the Energy Landscape of an RNA Tetraloop

Molecular dynamics (MD) simulations have become increasingly powerful and can now describe the folding/unfolding of small biomolecules in atomic detail. However, a major challenge in MD simulations is to represent the complex energy landscape of biomolecules using a small number of reaction coordinates. In this study, we investigate the folding pathways of an RNA tetraloop, gcGCAAgc, using five classical MD simulations with a combined simulation time of approximately 120 μs. Our approach involves analyzing the tetraloop dynamics, including the folding transition state ensembles, using the energy landscape visualization method (ELViM). The ELViM is an approach that uses internal distances to compare any two conformations, allowing for a detailed description of the folding process without requiring root mean square alignment of structures. This method has previously been applied to describe the energy landscape of disordered β-amyloid peptides and other proteins. The ELViM results in a non-linear projection of the multidimensional space, providing a comprehensive representation of the tetraloop's energy landscape. Our results reveal four distinct transition-state regions and establish the paths that lead to the folded tetraloop structure. This detailed analysis of the tetraloop's folding process has important implications for understanding RNA folding, and the ELViM approach can be used to study other biomolecules.