Computational Methods for Efficient Sampling of Protein Landscapes and Disclosing Allosteric Regions

Allosteric modulation of fluorescence revealed by hydrogen bond dynamics in a genetically encoded maltose biosensor

Genetically encoded fluorescent biosensors (GEFBs) proved to be reliable tracers for many metabolites and cellular processes. In the simplest case, a fluorescent protein (FP) is genetically fused to a sensing protein which undergoes a conformational change upon ligand binding. This drives a rearrangement in the chromophore environment and changes the spectral properties of the FP. Structural determinants of successful biosensors are revealed only in hindsight when the crystal structures of both ligand-bound and ligand-free forms are available. This makes the development of new biosensors for desired analytes a long trial-and-error process. In the current study, we conducted μs-long all atom molecular dynamics (MD) simulations of a maltose biosensor in both the apo (dark) and holo (bright) forms. We performed detailed hydrogen bond occupancy analyses to shed light on the mechanism of ligand induced conformational change in the sensor protein and its allosteric effect on the chromophore environment. We find that two strong indicators for distinguishing bright and dark states of biosensors are due to substantial changes in hydrogen bond dynamics in the system and solvent accessibility of the chromophore.

Scipion-EM-ProDy: A Graphical Interface for the ProDy Python Package within the Scipion Workflow Engine Enabling Integration of Databases, Simulations and Cryo-Electron Microscopy Image Processing

Macromolecular assemblies, such as protein complexes, undergo continuous structural dynamics, including global reconfigurations critical for their function. Two fast analytical methods are widely used to study these global dynamics, namely elastic network model normal mode analysis and principal component analysis of ensembles of structures. These approaches have found wide use in various computational studies, driving the development of complex pipelines in several software packages. One common theme has been conformational sampling through hybrid simulations incorporating all-atom molecular dynamics and global modes of motion. However, wide functionality is only available for experienced programmers with limited capabilities for other users. We have, therefore, integrated one popular and extensively developed software for such analyses, the ProDy Python application programming interface, into the Scipion workflow engine. This enables a wider range of users to access a complete range of macromolecular dynamics pipelines beyond the core functionalities available in its command-line applications and the normal mode wizard in VMD. The new protocols and pipelines can be further expanded and integrated into larger workflows, together with other software packages for cryo-electron microscopy image analysis and molecular simulations. We present the resulting plugin, Scipion-EM-ProDy, in detail, highlighting the rich functionality made available by its development.

Explicit versus implicit consideration of binding partners in protein-protein complex to elucidate intrinsic dynamics

The binding of many proteins to their protein partners is tightly regulated via control of their relative intrinsic dynamics during the binding process, a phenomenon which can in turn be modulated. Therefore, investigating the intrinsic dynamics of proteins is necessary to understand function in a comprehensive way. By intrinsic dynamics herein, we principally refer to the vibrational signature of a protein molecule popularly obtained from normal modes or essential modes. For normal modes, one often considers that the molecule under investigation is a collection of springs in a solvent-free or implicit-solvent medium. In the context of a protein-binding partner, the analysis of vibration of the target protein is often complicated due to molecular interaction within the complex. Generally, it is assumed that the isolated bound conformation of the target protein captures the implicit effect of the binding partner on the intrinsic dynamics, therefore suggesting that any influence of the partner molecule is also already integrated. Such an assumption allows large-scale studies of the conservation of protein flexibility. However, in cases where a partner protein directly influences the vibration of the target via critical contacts at the protein-protein interface, the above assumption falls short of providing a detailed view. In this review article, we discuss the implications of considering the dynamics of a protein in a protein-protein complex, as modelled implicitly and explicitly with methods dependent on elastic network models. We further propose how such an explicit consideration can be applied to understand critical protein-protein contacts that can be targeted in future studies.

Exploring the Conformational Impact of Glycine Receptor TM1-2 Mutations Through Coarse-Grained Analysis and Atomistic Simulations

Pentameric ligand-gated ion channels (PLGICs) are a family of proteins that convert chemical signals into ion fluxes through cellular membranes. Their structures are highly conserved across all kingdoms from bacteria to eukaryotes. Beyond their classical roles in neurotransmission and neurological disorders, PLGICs have been recently related to cell proliferation and cancer. Here, we focus on the best characterized eukaryotic channel, the glycine receptor (GlyR), to investigate its mutational patterns in genomic-wide tumor screens and compare them with mutations linked to hyperekplexia (HPX), a Mendelian neuromotor disease that disrupts glycinergic currents. Our analysis highlights that cancer mutations significantly accumulate across TM1 and TM2, partially overlapping with HPX changes. Based on 3D-clustering, conservation, and phenotypic data, we select three mutations near the pore, expected to impact GlyR conformation, for further study by molecular dynamics (MD). Using principal components from experimental GlyR ensembles as framework, we explore the motions involved in transitions from the human closed and desensitized structures and how they are perturbed by mutations. Our MD simulations show that WT GlyR spontaneously explores opening and re-sensitization transitions that are significantly impaired by mutations, resulting in receptors with altered permeability and desensitization properties in agreement with HPX functional data.

Dynamic Community Composition Unravels Allosteric Communication in PDZ3

The third domain of PSD-95 (PDZ3) is a model for investigating allosteric communication in protein and ligand interactions. While motifs contributing to its binding specificity have been scrutinized, a conformational dynamical basis is yet to be established. Despite the miniscule structural changes due to point mutants, the observed significant binding affinity differences have previously been assessed with a focus on two α-helices located at the binding groove (α₂) and the C-terminus (α₃). Here, we employ a new computational approach to develop a generalized view on the molecular basis of PDZ3 binding selectivity and interaction communication for a set of point mutants of the protein (G330T, H372A, G330T-H372A) and its ligand (CRIPT, named L₁, and its T-2F variant, L₂) along with the wild type (WT). To analyze the dynamical aspects hidden in the conformations that are produced by molecular dynamics simulations, we utilize variations in community composition calculated based on the betweenness centrality measure from graph theory. We find that the highly charged N-terminus, which is located far from the ligand, has the propensity to share the same community with the ligand in the biologically functional complexes, indicating a distal segment might mediate the binding dynamics. N- and C-termini of PDZ3 share communities, and α₃ acts as a hub for the whole protein by sustaining the communication with all structural segments, albeit being a trait not unique to the functional complexes. Moreover, α₂ which lines the binding cavity frequently parts communities with the ligand and is not a controller of the binding but is rather a slave to the overall dynamics coordinated by the N-terminus. Thus, ligand binding fate in PDZ3 is traced to the population of community compositions extracted from dynamics despite the lack of significant conformational changes.

A Coarse-Grained Methodology Identifies Intrinsic Mechanisms That Dissociate Interacting Protein Pairs

We address the problem of triggering dissociation events between proteins that have formed a complex. We have collected a set of 25 non-redundant, functionally diverse protein complexes having high-resolution three-dimensional structures in both the unbound and bound forms. We unify elastic network models with perturbation response scanning (PRS) methodology as an efficient approach for predicting residues that have the propensity to trigger dissociation of an interacting protein pair, using the three-dimensional structures of the bound and unbound proteins as input. PRS reveals that while for a group of protein pairs, residues involved in the conformational shifts are confined to regions with large motions, there are others where they originate from parts of the protein unaffected structurally by binding. Strikingly, only a few of the complexes have interface residues responsible for dissociation. We find two main modes of response: In one mode, remote control of dissociation in which disruption of the electrostatic potential distribution along protein surfaces play the major role; in the alternative mode, mechanical control of dissociation by remote residues prevail. In the former, dissociation is triggered by changes in the local environment of the protein, e.g., pH or ionic strength, while in the latter, specific perturbations arriving at the controlling residues, e.g., via binding to a third interacting partner is required for decomplexation. We resolve the observations by relying on an electromechanical coupling model which reduces to the usual elastic network result in the limit of the lack of coupling. We validate the approach by illustrating the biological significance of top residues selected by PRS on select cases where we show that the residues whose perturbation leads to the observed conformational changes correspond to either functionally important or highly conserved residues in the complex.

Towards gaining sight of multiscale events: utilizing network models and normal modes in hybrid methods

With the explosion of normal mode analyses (NMAs) based on elastic network models (ENMs) in the last decade, and the proven precision of MD simulations for visualizing interactions at atomic scale, many hybrid methods have been proposed in recent years. These aim at exploiting the best of both worlds: the atomic precision of MD that often fall short of exploring time and length scales of biological interest, and the capability of ENM-NMA to predict the cooperative and often functional rearrangements of large structures and assemblies, albeit at low resolution. We present an overview of recent progress in the field with examples of successful applications highlighting the utility of such hybrid methods and pointing to emerging future directions guided by advances in experimental characterization of biomolecular systems structure and dynamics.

Perturb-Scan-Pull: A Novel Method Facilitating Conformational Transitions in Proteins

Conformational transitions in proteins facilitate precise physiological functions. Therefore, it is crucial to understand the mechanisms underlying these processes to modulate protein function. Yet, studying structural and dynamical properties of proteins is notoriously challenging due to the complexity of the underlying potential energy surfaces (PES). We have previously developed the perturbation-response scanning (PRS) method to identify key residues that participate in the communication network responsible for specific conformational transitions. PRS is based on a residue-by-residue scan of the protein to determine the subset of residues/forces which provide the closest conformational change leading to a target conformational state, inasmuch as linear response theory applies to these motions. Here, we develop a novel method to further evaluate if conformational transitions may be triggered on the PES. We aim to study functionally relevant conformational transitions in proteins by using results obtained from PRS and feeding them as inputs to steered molecular dynamics simulations. The success and the transferability of the method are evaluated on three protein systems having different complexities of motion on the PES: calmodulin, adenylate kinase, and bacterial ferric binding protein. We find that the method captures the target conformation, while providing key residues and the optimum paths with relatively low free energy profiles.

Role of protein-protein interactions in allosteric drug design for DNA methyltransferases

DNA methyltransferases (DNMTs) not only play key roles in epigenetic gene regulation, but also serve as emerging targets for several diseases, especially for cancers. Due to the multi-domains of DNMT structures, targeting allosteric sites of protein-protein interactions (PPIs) is becoming an attractive strategy in epigenetic drug discovery. This chapter aims to review the major contemporary approaches utilized for the drug discovery based on PPIs in different dimensions, from the enumeration of allosteric mechanism to the identification of allosteric pockets. These include the construction of protein structure networks (PSNs) based on molecular dynamics (MD) simulations, performing elastic network models (ENMs) and perturbation response scanning (PRS) calculation, the sequence-based conservation and coupling analysis, and the allosteric pockets identification. Furthermore, we complement this methodology by highlighting the role of computational approaches in promising practical applications for the computer-aided drug design, with special focus on two DNMTs, namely, DNMT1 and DNMT3A.