Unveiling Metastable Ensembles of GRB2 and the Relevance of Interdomain Communication during Folding

Grb2 Y160F mutant mimics the wild-type monomeric state dynamics and the monomer-dimer equilibrium

The Growth factor receptor-bound protein 2 (Grb2) participates in early signaling complexes and regulates tyrosine kinase-mediated signal transduction through a monomer-dimer equilibrium. Grb2 dimeric state inhibits signal transduction whereas the monomer promotes signaling downstream. Since Grb2 dimer KD is ∼0.8 μM, studies focused on the monomer are still challenging and require mutations or interaction with phosphotyrosine peptides. However, these mutants were never characterized considering their effects on protein structure and dynamics in solution. Here, we present the biophysical characterization of Grb2Y160F, the first Grb2 mutant to induce protein monomerization without disrupting its native behavior in solution due to net charge modifications or interaction with peptides. We also identified that Grb2Y160F exists in a monomer-dimer equilibrium. Grb2Y160F ability to dimerize implies that different dimerization interfaces might regulate signaling pathways in distinct ways and raises an important question about the role of the Y160 residue in other dimerization interfaces.

GRB2: A dynamic adaptor protein orchestrating cellular signaling in health and disease

GRB2, or Growth Factor Receptor-Bound Protein 2, is a pivotal adaptor protein in intracellular signal transduction pathways, particularly within receptor tyrosine kinase (RTK) signaling cascades. Its crystal structure reveals a modular architecture comprising a single Src homology 2 (SH2) domain flanked by two Src homology 3 (SH3) domains, facilitating dynamic interactions critical for cellular signaling. While SH2 domains recognize phosphorylated tyrosines, SH3 domains bind proline-rich sequences, enabling GRB2 to engage with various downstream effectors. Folding and binding studies of GRB2 in its full-length form and isolated domains highlight a complex interplay between its protein-protein interaction domains on the folding energy landscape and in driving its function. Being at the crosslink of many key molecular pathways in the cell, GRB2 possesses a role in cancer pathogenesis, particularly in mediating the Ras-mitogen activated protein kinase (MAPK) pathway. Thus, pharmacological targeting of GRB2 domains is a promising field in cancer therapy, with efforts focused on disrupting protein-protein interactions. However, the dynamic interplay driving GRB2 function suggests the presence of allosteric sites at the interface between domains that could be targeted to modulate the binding properties of its constituent domains. We propose that the analysis of GRB2 proteins from other species may provide additional insights to make the allosteric pharmacological targeting of GRB2 a more feasible strategy.

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.