Energetic redistribution in allostery to execute protein function

Molecular mechanism of regulation of RhoA GTPase by phosphorylation of RhoGDI

Rho-specific guanine nucleotide dissociation inhibitors (RhoGDIs) play a crucial role in the regulation of Rho family GTPases. They act as negative regulators that prevent the activation of Rho GTPases by forming complexes with the inactive GDP-bound state of GTPase. Release of Rho GTPase from the RhoGDI-bound complex is necessary for Rho GTPase activation. Biochemical studies provide evidence of a "phosphorylation code," where phosphorylation of some specific residues of RhoGDI selectively releases its GTPase partner (RhoA, Rac1, Cdc42, etc.). This work attempts to understand the molecular mechanism behind this specific phosphorylation-induced reduction in binding affinity. Using several microseconds long atomistic molecular dynamics simulations of the wild-type and phosphorylated states of the RhoA-RhoGDI complex, we propose a molecular-interaction-based mechanistic model for the dissociation of the complex. Phosphorylation induces major structural changes, particularly in the positively charged polybasic region (PBR) of RhoA and the negatively charged N-terminal region of RhoGDI that contribute most to the binding affinity. Molecular mechanics Poisson-Boltzmann surface area binding energy calculations show a significant weakening of interaction on phosphorylation at the RhoA-specific site of RhoGDI. In contrast, phosphorylation at a Rac1-specific site does not affect the overall binding affinity significantly, which confirms the presence of a phosphorylation code. RhoA-specific phosphorylation leads to a reduction in the number of contacts between the PBR of RhoA and the N-terminal region of RhoGDI, which manifests a reduction of the binding affinity. Using hydrogen bond occupancy analysis and energetic perturbation network, we propose a mechanistic model for the allosteric response, i.e., long-range signal propagation from the site of phosphorylation to the PBR and buried geranylgeranyl group in the form of rearrangement and rewiring of hydrogen bonds and salt bridges. Our results highlight the crucial role of specific electrostatic interactions in manifestation of the phosphorylation code.

Allosteric Signaling in PDZ Energetic Networks: Embedding Error Analysis

Allosteric signaling in proteins has been known for some half a century, yet how the signal traverses the protein remains an active area of research. Recently, the importance of electrostatics to achieve long-range signaling has become increasingly appreciated. Our laboratory has been working on developing network approaches to capture such interactions. In this study, we turn our attention to the well-studied allosteric model protein, PDZ. We study the allosteric dynamics on a per-residue basis in key constructs involving the PDZ domain, its allosteric effector, and its peptide ligand. We utilize molecular dynamics trajectories to create the networks for the constructs to explore the allosteric effect by plotting the heat kernel results onto axes defined by principal components. We introduce a new metric to quantitate the volume sampled by a residue in the latent space. We relate our findings to PDZ and the greater field of allostery.

Network Analysis of Molecular Dynamics Sectors in the p53 Protein

Design of allosteric regulators is an emergent field in the area of drug discovery holding promise for currently untreated diseases. Allosteric regulators bind to a protein in one location and affect a distant site. The ubiquitous presence of allosteric effectors in biology and the success of serendipitously identified allosteric compounds point to the potential they hold. Although the mechanism of transmission of an allosteric signal is not unequivocally determined, one hypothesis suggests that groups of evolutionarily covarying residues within a protein, termed sectors, are conduits. A long-term goal of our lab is to allosterically modulate the activity of proteins by binding small molecules at points of allosteric control. However, methods to consistently identify such points remain unclear. Sector residues on the surfaces of proteins are a promising source of allosteric targets. Recently, we introduced molecular dynamics (MD)-based sectors; MD sectors capitalize on covariance of motion, in place of evolutionary covariance. By focusing on motional covariance, MD sectors tap into the framework of statistical mechanics afforded by the Boltzmann ensemble of structural conformations comprising the underlying data set. We hypothesized that the method of MD sectors can be used to identify a cohesive network of motionally covarying residues capable of transmitting an allosteric signal in a protein. While our initial qualitative results showed promise for the method to predict sectors, that a network of cohesively covarying residues had been produced remained an untested assumption. In this work, we apply network theory to rigorously analyze MD sectors, allowing us to quantitatively assess the biologically relevant property of network cohesiveness of sectors in the context of the tumor suppressor protein, p53. We revised the methodology for assessing and improving MD sectors. Specifically, we introduce a metric to calculate the cohesive properties of the network. Our new approach separates residues into two categories: sector residues and non-sector residues. The relatedness within each respective group is computed with a distance metric. Cohesive sector networks are identified as those that have high relatedness among the sector residues which exceeds the relatedness of the residues to the non-sector residues in terms of the correlation of motions. Our major finding was that the revised means of obtaining sectors was more efficacious than previous iterations, as evidenced by the greater cohesion of the networks. These results are discussed in the context of the development of allosteric regulators of p53 in particular and the expected applicability of the method to the drug design field in general.

Molecular Insights into Phosphorylation-Induced Allosteric Conformational Changes in a β2-Adrenergic Receptor

The large conformational flexibility of G protein-coupled receptors (GPCRs) has been a puzzle in structural and pharmacological studies for the past few decades. Apart from structural rearrangements induced by ligands, enzymatic phosphorylations by GPCR kinases (GRKs) at the carboxy-terminal tail (C-tail) of a GPCR also make conformational alterations to the transmembrane helices and facilitates the binding of one of its transducer proteins named β-arrestin. The phosphorylation-induced conformational transition of the receptor that causes specific binding to β-arrestin but prevents the association of other transducers such as G proteins lacks atomistic understanding and is elusive to experimental studies. Using microseconds of all-atom conventional and Gaussian accelerated molecular dynamics (GaMD) simulations, we investigate the allosteric mechanism of phosphorylation induced-conformational changes in β₂-adrenergic receptor, a well-characterized GPCR model system. Free energy profiles reveal that the phosphorylated receptor samples a new conformational state in addition to the canonical active state corroborating with recent nuclear magnetic resonance experimental findings. The new state has a smaller intracellular cavity that is likely to accommodate β-arrestin better than G protein. Using contact map and inter-residue interaction energy calculations, we found the phosphorylated C-tail adheres to the cytosolic surface of the transmembrane domain of the receptor. Transfer entropy calculations show that the C-tail residues drive the correlated motions of TM residues, and the allosteric signal is relayed via several residues at the cytosolic surface. Our results also illustrate how the redistribution of inter-residue nonbonding interaction couples with the allosteric communication from the phosphorylated C-tail to the transmembrane. Atomistic insight into phosphorylation-induced β-arrestin specific conformation is therapeutically important to design drugs with higher efficacy and fewer side effects. Our results, therefore, open novel opportunities to fine-tune β-arrestin bias in GPCR signaling.

Design of novel cyanovirin-N variants by modulation of binding dynamics through distal mutations

We develop integrated co-evolution and dynamic coupling (ICDC) approach to identify, mutate, and assess distal sites to modulate function. We validate the approach first by analyzing the existing mutational fitness data of TEM-1 β-lactamase and show that allosteric positions co-evolved and dynamically coupled with the active site significantly modulate function. We further apply ICDC approach to identify positions and their mutations that can modulate binding affinity in a lectin, cyanovirin-N (CV-N), that selectively binds to dimannose, and predict binding energies of its variants through Adaptive BP-Dock. Computational and experimental analyses reveal that binding enhancing mutants identified by ICDC impact the dynamics of the binding pocket, and show that rigidification of the binding residues compensates for the entropic cost of binding. This work suggests a mechanism by which distal mutations modulate function through dynamic allostery and provides a blueprint to identify candidates for mutagenesis in order to optimize protein function.

Allosteric Type and Pathways Are Governed by the Forces of Protein-Ligand Binding

Allostery is central to many cellular processes, by up- or down-regulating target function. However, what determines the allosteric type remains elusive and currently it is impossible to predict whether the allosteric compounds would activate or inhibit target function before experimental studies. We demonstrated that the allosteric type and allosteric pathways are governed by the forces imposed by ligand binding to target protein using the anisotropic network model and developed an allosteric type prediction method (AlloType). AlloType correctly predicted 13 of the 16 allosteric systems in the data set with experimentally determined protein and complex structures as well as verified allosteric types, which was also used to identify allosteric pathways. When applied to glutathione peroxidase 4, a protein with no complex structure information, AlloType could still be able to predict the allosteric type of the recently reported allosteric activators, demonstrating its potential application in designing specific allosteric drugs and uncovering allosteric mechanisms.

Dynamic energy correlation analysis of E. coli aspartokinase III and alteration of allosteric regulation by manipulating energy transduction pathways

Conformational change associated with allosteric regulation in a protein is ultimately driven by energy transformation. However, little is known about the latter process. In this work, we combined steered molecular dynamics simulations and sequence conservation analysis to investigate the conformational changes and energy transformation in the allosteric enzyme aspartokinase III (AK III) from Escherichia coli. Correlation analysis of energy change at residue level indicated significant transformation between electrostatic energy and dihedral angle energy during the allosteric regulation. Key amino acid residues located in the corresponding energy transduction pathways were identified by dynamic energy correlation analysis. To verify their functions, residues with a high energy correlation in the pathways were altered and their effects on allosteric regulation of AKIII were determined. This study sheds new insights into energy transformation during allosteric regulation of AK III and proposes a strategy to identify key residues that are involved in intramolecular energy transduction and thus in driving the allosteric process.

Substrates Modulate Charge-Reorganization Allosteric Effects in Protein-Protein Association

Protein function may be modulated by an event occurring far away from the functional site, a phenomenon termed allostery. While classically allostery involves conformational changes, we recently observed that charge redistribution within an antibody can also lead to an allosteric effect, modulating the kinetics of binding to target antigen. In the present work, we study the association of a polyhistidine tagged enzyme (phosphoglycerate kinase, PGK) to surface-immobilized anti-His antibodies, finding a significant Charge-Reorganization Allostery (CRA) effect. We further observe that PGK's negatively charged nucleotide substrates modulate CRA substantially, even though they bind far away from the His-tag-antibody interaction interface. In particular, binding of ATP reduces CRA by more than 50%. The results indicate that CRA is affected by the binding of charged molecules to a protein and provide further insight into the significant role that charge redistribution can play in protein function.

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.

Protein folding stability and binding interactions through the lens of evolution: a dynamical perspective

While the function of a protein depends heavily on its ability to fold into a correct 3D structure, billions of years of evolution have tailored proteins from highly stable objects to flexible molecules as they adapted to environmental changes. Nature maintains the fine balance of protein folding and stability while still evolving towards new function through generations of fine-tuning necessary interactions with other proteins and small molecules. Here we focus on recent computational and experimental studies that shed light onto how evolution molds protein folding and the functional landscape from a conformational dynamics' perspective. Particularly, we explore the importance of dynamic allostery throughout protein evolution and discuss how the protein anisotropic network can give rise to allosteric and epistatic interactions.

Machine Learning of Allosteric Effects: The Analysis of Ligand-Induced Dynamics to Predict Functional Effects in TRAP1

Allosteric molecules provide a powerful means to modulate protein function. However, the effect of such ligands on distal orthosteric sites cannot be easily described by classical docking methods. Here, we applied machine learning (ML) approaches to expose the links between local dynamic patterns and different degrees of allosteric inhibition of the ATPase function in the molecular chaperone TRAP1. We focused on 11 novel allosteric modulators with similar affinities to the target but with inhibitory efficacy between the 26.3 and 76%. Using a set of experimentally related local descriptors, ML enabled us to connect the molecular dynamics (MD) accessible to ligand-bound (perturbed) and unbound (unperturbed) systems to the degree of ATPase allosteric inhibition. The ML analysis of the comparative perturbed ensembles revealed a redistribution of dynamic states in the inhibitor-bound versus inhibitor-free systems following allosteric binding. Linear regression models were built to quantify the percentage of experimental variance explained by the predicted inhibitor-bound TRAP1 states. Our strategy provides a comparative MD–ML framework to infer allosteric ligand functionality. Alleviating the time scale issues which prevent the routine use of MD, a combination of MD and ML represents a promising strategy to support in silico mechanistic studies and drug design.

N-Terminus of the Third PDZ Domain of PSD-95 Orchestrates Allosteric Communication for Selective Ligand Binding

PDZ domains constitute common models to study single-domain allostery without significant structural changes. The third PDZ domain of PSD-95 (PDZ3) is known to have selective structural features that confer unique modulatory roles to this unit. In this model system, two residues, H372 directly connected to the binding site and G330 holding an off-binding-site position, were designated to assess the effect of mutations on binding selectivity. It has been observed that the H372A and G330T-H372A mutations change ligand preferences from class I (T/S amino acid at position -2 of the ligand) to class II (hydrophobic amino acid at the same position). Alternatively, the G330T single mutation leads to the recognition of both ligand classes. We have performed a series of molecular dynamics (MD) simulations for wild-type, H372A, and G330T single mutants and a double mutant of PDZ3 in the absence and presence of both types of ligands. With the combination of free-energy difference calculations and a detailed analysis of MD trajectories, "class switching" and "class bridging" behavior of PDZ3 mutants, as well as their effects on ligand selection and binding affinities are explained. We show that the dynamics of the charged N-terminus plays a fundamental role in determining the binding preferences in PDZ3 by altering the electrostatic energy. These findings are corroborated by simulations on N-terminus-truncated versions of these systems. The dynamical allostery orchestrated by the N-terminus offers a fresh perspective to the study of communication pathways in proteins.

Discovery of cryptic allosteric sites using reversed allosteric communication by a combined computational and experimental strategy

Allostery, which is one of the most direct and efficient methods to fine-tune protein functions, has gained increasing recognition in drug discovery. However, there are several challenges associated with the identification of allosteric sites, which is the fundamental cornerstone of drug design. Previous studies on allosteric site predictions have focused on communication signals propagating from the allosteric sites to the orthosteric sites. However, recent biochemical studies have revealed that allosteric coupling is bidirectional and that orthosteric perturbations can modulate allosteric sites through reversed allosteric communication. Here, we proposed a new framework for the prediction of allosteric sites based on reversed allosteric communication using a combination of computational and experimental strategies (molecular dynamics simulations, Markov state models, and site-directed mutagenesis). The desirable performance of our approach was demonstrated by predicting the known allosteric site of the small molecule MDL-801 in nicotinamide dinucleotide (NAD⁺)-dependent protein lysine deacetylase sirtuin 6 (Sirt6). A potential novel cryptic allosteric site located around the L116, R119, and S120 residues within the dynamic ensemble of Sirt6 was identified. The allosteric effect of the predicted site was further quantified and validated using both computational and experimental approaches. This study proposed a state-of-the-art computational pipeline for detecting allosteric sites based on reversed allosteric communication. This method enabled the identification of a previously uncharacterized potential cryptic allosteric site on Sirt6, which provides a starting point for allosteric drug design that can aid the identification of candidate pockets in other therapeutic targets.

Using reversed allosteric communication, we performed MD simulations, MSMs, and mutagenesis experiments, to discover allosteric sites. It reproduced the known allosteric site for MDL-801 on Sirt6 and uncovered a novel cryptic allosteric Pocket X.

Supertertiary protein structure affects an allosteric network

Protein function can be allosterically regulated by changes in structure or dynamics. PDZ domains are classic examples for studies of allostery in single protein domains. However, PDZ domains are often found in multidomain proteins; in particular, PDZ3 is located in a supramodule containing three domains. The allosteric network in PDZ3 has never been studied in the presence of the adjacent domains. Here we map the allosteric network for a PDZ3:ligand complex, both in isolation and in the context of a supramodule. We demonstrate that the allosteric network is highly dependent on this supertertiary structure, with broad implications for studies of allostery in single domains.

The notion that protein function is allosterically regulated by structural or dynamic changes in proteins has been extensively investigated in several protein domains in isolation. In particular, PDZ domains have represented a paradigm for these studies, despite providing conflicting results. Furthermore, it is still unknown how the association between protein domains in supramodules, consitituting so-called supertertiary structures, affects allosteric networks. Here, we experimentally mapped the allosteric network in a PDZ:ligand complex, both in isolation and in the context of a supramodular structure, and show that allosteric networks in a PDZ domain are highly dependent on the supertertiary structure in which they are present. This striking sensitivity of allosteric networks to the presence of adjacent protein domains is likely a common property of supertertiary structures in proteins. Our findings have general implications for prediction of allosteric networks from primary and tertiary structures and for quantitative descriptions of allostery.

PI3K inhibitors: review and new strategies

The search is on for effective specific inhibitors for PI3Kα mutants. PI3Kα, a critical lipid kinase, has two subunits, catalytic and inhibitory. PIK3CA, the gene that encodes the p110α catalytic subunit is a highly mutated protein in cancer. Dysregulation of PI3Kα signalling is commonly associated with tumorigenesis and drug resistance. Despite its vast importance, only recently the FDA approved the first drug (alpelisib by Novartis) for breast cancer. A second (GDC0077), classified as PI3Kα isoform-specific, is undergoing clinical trials. Not surprisingly, these ATP-competitive drugs commonly elicit severe concentration-dependent side effects. Here we briefly review PI3Kα mutations, focus on PI3K drug repertoire and propose new, to-date unexplored PI3Kα therapeutic strategies. These include (1) an allosteric and orthosteric inhibitor combination and (2) taking advantage of allosteric rescue mutations to guide drug discovery.

Adenosine A2A-dopamine D2 receptor-receptor interaction in neurons and astrocytes: Evidence and perspectives

The discovery of receptor-receptor interactions in the early 1980s, together with a more accurate focusing of allosteric mechanisms in proteins, expanded the knowledge on the G protein-coupled receptor (GPCR)-mediated signaling processes. GPCRs were seen to operate not only as monomers, but also as quaternary structures shaped by allosteric interactions. These integrative mechanisms can change the function of the GPCRs involved, leading to a sophisticated dynamic of the receptor assembly in terms of modulation of recognition and signaling. In this context, the heterodimeric complex formed by the adenosine A_2A and the dopamine D₂ receptors likely represents a prototypical example. The pharmacological evidence obtained, together with the tissue distribution of the A_2A-D₂ heteromeric complexes, suggested they could represent a target for new therapeutic strategies addressing significant disorders of the central nervous system. The research findings and the perspectives they offer from the therapeutic standpoint are the focus of the here presented discussion.

Intrinsic dynamics is evolutionarily optimized to enable allosteric behavior

Allosteric behavior is central to the function of many proteins, enabling molecular machinery, metabolism, signaling and regulation. Recent years have shown that the intrinsic dynamics of allosteric proteins defined by their 3-dimensional architecture or by the topology of inter-residue contacts favors cooperative motions that bear close similarity to structural changes they undergo during their allosteric actions. These conformational motions are usually driven by energetically favorable or soft modes at the low frequency end of the mode spectrum, and they are evolutionarily conserved among orthologs. These observations brought into light evolutionary adaptation mechanisms that help maintain, optimize or regulate allosteric behavior as the evolution from bacterial to higher organisms introduces sequential heterogeneities and structural complexities.

Does Ras Activate Raf and PI3K Allosterically?

The mechanism through which oncogenic Ras activates its effectors is vastly important to resolve. If allostery is at play, then targeting allosteric pathways could help in quelling activation of MAPK (Raf/MEK/ERK) and PI3K (PI3K/Akt/mTOR) cell proliferation pathways. On the face of it, allosteric activation is reasonable: Ras binding perturbs the conformational ensembles of its effectors. Here, however, we suggest that at least for Raf, PI3K, and NORE1A (RASSF5), that is unlikely. Raf's long disordered linker dampens effective allosteric activation. Instead, we suggest that the high-affinity Ras–Raf binding relieves Raf's autoinhibition, shifting Raf's ensemble from the inactive to the nanocluster-mediated dimerized active state, as Ras also does for NORE1A. PI3K is recruited and allosterically activated by RTK (e.g., EGFR) at the membrane. Ras restrains PI3K's distribution and active site orientation. It stabilizes and facilitates PIP₂ binding at the active site and increases the PI3K residence time at the membrane. Thus, RTKs allosterically activate PI3Kα; however, merging their action with Ras accomplishes full activation. Here we review their activation mechanisms in this light and draw attention to implications for their pharmacology.

Probing Protein Allostery as a Residue-Specific Concept via Residue Response Maps

Allosteric regulation is a well-established phenomenon defined as a distal conformational or dynamical change of the protein upon allosteric effector binding. Here, we developed a novel approach to delineate allosteric effects in proteins. In this approach, we applied robust machine learning methods, including deep neural network and random forest, on extensive molecular dynamics (MD) simulations to distinguish otherwise similar allosteric states of proteins. Using the PDZ3 domain of PDS-95 as a model protein, we demonstrated that the allosteric effects could be represented as residue-specific properties through two-dimensional property-residue maps, which we refer to as "residue response maps". These maps were constructed through two machine learning methods and could accurately describe how different properties of various residues are affected upon allosteric perturbation on protein. Based on the "residue response maps", we propose allostery as a residue-specific concept, suggesting that all residues could be considered as allosteric residues because each residue "senses" the allosteric events through changing its single or multiple attributes in a quantitatively unique way. The "residue response maps" could be used to fingerprint a protein based on the unique patterns of residue responses upon binding events, providing a novel way to systematically describe the protein allosteric effects of each residue upon perturbation.

A Ca2+/CaM-regulated transcriptional switch modulates stomatal development in response to water deficit

Calcium (Ca²⁺) signals are decoded by the Ca²⁺-sensor protein calmodulin (CaM) and are transduced to Ca²⁺/CaM-binding transcription factors to directly regulate gene expression necessary for acclimation responses in plants. The molecular mechanisms of Ca²⁺/CaM signal transduction processes and their functional significance remains enigmatic. Here we report a novel Ca²⁺/CaM signal transduction mechanism that allosterically regulates DNA-binding activity of GT2-LIKE 1 (GTL1), a transrepressor of STOMATAL DENSITY AND DISTRIBUTION 1 (SDD1), to repress stomatal development in response to water stress. We demonstrated that Ca²⁺/CaM interaction with the 2^nd helix of the GTL1 N-terminal trihelix DNA-binding domain (GTL1N) destabilizes a hydrophobic core of GTL1N and allosterically inhibits 3^rd helix docking to the SDD1 promoter, leading to osmotic stress-induced Ca²⁺/CaM-dependent activation (de-repression) of SDD1 expression. This resulted in GTL1-dependent repression of stomatal development in response to water-deficit stress. Together, our results demonstrate that a Ca²⁺/CaM-regulated transcriptional switch on a trihelix transrepressor directly transduces osmotic stress to repress stomatal development to improve plant water-use efficiency as an acclimation response.

Chokepoints in Mechanical Coupling Associated with Allosteric Proteins: The Pyruvate Kinase Example

Although the critical role of allostery in controlling enzymatic processes is well appreciated, there is a current dearth in our understanding of its underlying mechanisms, including communication between binding sites. One potential key aspect of intersite communication is the mechanical coupling between residues in a protein. Here, we introduce a graph-based computational approach to investigate the mechanical coupling between distant parts of a protein, highlighting effective pathways via which protein motion can transfer energy between sites. In this method, each residue is treated as a node on a weighted, undirected graph, in which the edges are defined by locally correlated motions of those residues and weighted by the strength of the correlation. The method was validated against experimental data on allosteric regulation in the human liver pyruvate kinase as obtained from full-protein alanine-scanning mutagenesis (systematic mutation) studies, as well as computational data on two G-protein-coupled receptors. The method provides semiquantitative information on the regulatory importance of specific structural elements. It is shown that these elements are key for the mechanical coupling between distant parts of the protein by providing effective pathways for energy transfer. It is also shown that, although there are a multitude of energy transfer pathways between distant parts of a protein, these pathways share a few common nodes that represent effective "chokepoints" for the communication.

Dissecting a novel allosteric mechanism of cruzain: A computer-aided approach

Trypanosoma cruzi is the causative agent of Chagas disease, a neglected infection affecting millions of people in tropical regions. There are several chemotherapeutic agents for the treatment of this disease, but most of them are highly toxic and generate resistance. Currently, the development of allosteric inhibitors constitutes a promising research field, since it can improve the accessibility to more selective and less toxic medicines. To date, the allosteric drugs prediction is a state-of-the-art topic in rational structure-based computational design. In this work, a simulation strategy was developed for computational discovery of allosteric inhibitors, and it was applied to cruzain, a promising target and the major cysteine protease of T. cruzi. Molecular dynamics simulations, binding free energy calculations and network-based modelling of residue interactions were combined to characterize and compare molecular distinctive features of the apo form and the cruzain-allosteric inhibitor complexes. By using geometry-based criteria on trajectory snapshots, we predicted two main allosteric sites suitable for drug targeting. The results suggest dissimilar mechanisms exerted by the same allosteric site when binding different potential allosteric inhibitors. Finally, we identified the residues involved in suboptimal paths linking the identified site and the orthosteric site. The present study constitutes the first approximation to the design of cruzain allosteric inhibitors and may serve for future pharmacological intervention. Here, no major effects on active site structure were observed due to compound binding (modification of distance and angles between catalytic residues), which indicates that allosteric regulation in cruzain might be mediated via alterations of its dynamical properties similarly to allosteric inhibition of human cathepsin K (HCatK). The current findings are particularly relevant for the design of allosteric modulators of papain-like cysteine proteases.

Receptor-Receptor Interactions as a Widespread Phenomenon: Novel Targets for Drug Development?

The discovery of receptor-receptor interactions (RRI) has expanded our understanding of the role that G protein-coupled receptors (GPCRs) play in intercellular communication. The finding that GPCRs can operate as receptor complexes, and not only as monomers, suggests that several different incoming signals could already be integrated at the plasma membrane level via direct allosteric interactions between the protomers that form the complex. Most research in this field has focused on neuronal populations and has led to the identification of a large number of RRI. However, RRI have been seen to occur not only in neurons but also in astrocytes and, outside the central nervous system, in cells of the cardiovascular and endocrine systems and in cancer cells. Furthermore, RRI involving the formation of macromolecular complexes are not limited to GPCRs, being also observed in other families of receptors. Thus, RRI appear as a widespread phenomenon and oligomerization as a common mechanism for receptor function and regulation. The discovery of these macromolecular assemblies may well have a major impact on pharmacology. Indeed, the formation of receptor complexes significantly broadens the spectrum of mechanisms available to receptors for recognition and signaling, which may be implemented through modulation of the binding sites of the adjacent protomers and of their signal transduction features. In this context, the possible appearance of novel allosteric sites in the receptor complex structure may be of particular relevance. Thus, the existence of RRI offers the possibility of new therapeutic approaches, and novel pharmacological strategies for disease treatment have already been proposed. Several challenges, however, remain. These include the accurate characterization of the role that the receptor complexes identified so far play in pathological conditions and the development of ligands specific to given receptor complexes, in order to efficiently exploit the pharmacological properties of these complexes.

How the Ligand-Induced Reorganization of Protein Internal Energies Is Coupled to Conformational Events

Here, we introduce a novel computational method to identify the protein substructures most likely to support the functionally oriented structural deformations that occur upon ligand-binding. To this aim, we study the modulation of protein energetics along the trajectory of a molecular dynamics simulation of different proteins in the presence and in the absence of their respective ligands, namely, human FGF, human second PDZ from human PTP1E/PTPL1, and the N terminal domain of human Hsp90. The method is based on the idea that a subset of protein residues (hotspots) may initiate the global response via the disassembly and reassembly of interactions, which is reflected in the modulation of the overall protein energetics. To identify structural hotspots and dynamic states linked to the onset of functionally relevant conformational transitions, we define an energy profile to monitor the protein energetics, based on a previously introduced approach that highlights the essential nonbonded couplings among all residues. The energy profiles are calculated along the trajectory to yield a time-dependent evolution, and their relative population in the presence and absence of the ligand is evaluated by means of a clustering procedure. It is found that interconversion between clusters, as well as their population and the density of specific energy profiles in the vicinity of structural transitions, provides specific information on the impact of the ligand in driving the protein conformational response. This analysis also highlights the hotspot residues that are most responsive to the presence of the ligand. Importantly, identified hotspots are in agreement with experimental evidence in the three considered systems. We propose that this approach can be generally used in the prediction of "allosteric hotspots" and ligand-induced conformational responses, as well as to select conformations more likely to support functional transitions (e.g., in the framework of adaptive sampling approaches).

Autoinhibition in Ras effectors Raf, PI3Kα, and RASSF5: a comprehensive review underscoring the challenges in pharmacological intervention

Autoinhibition is an effective mechanism that guards proteins against spurious activation. Despite its ubiquity, the distinct organizations of the autoinhibited states and their release mechanisms differ. Signaling is most responsive to the cell environment only if a small shift in the equilibrium is required to switch the system from an inactive (occluded) to an active (exposed) state. Ras signaling follows this paradigm. This underscores the challenge in pharmacological intervention to exploit and enhance autoinhibited states. Here, we review autoinhibition and release mechanisms at the membrane focusing on three representative Ras effectors, Raf protein kinase, PI3Kα lipid kinase, and NORE1A (RASSF5) tumor suppressor, and point to the ramifications to drug discovery. We further touch on Ras upstream and downstream signaling, Ras activation, and the Ras superfamily in this light, altogether providing a broad outlook of the principles and complexities of autoinhibition.

Theoretical analysis of inducer and operator binding for cyclic-AMP receptor protein mutants

Allosteric transcription factors undergo binding events at inducer binding sites as well as at distinct DNA binding domains, and it is difficult to disentangle the structural and functional consequences of these two classes of interactions. We compare the ability of two statistical mechanical models—the Monod-Wyman-Changeux (MWC) and the Koshland-Némethy-Filmer (KNF) models of protein conformational change—to characterize the multi-step activation mechanism of the broadly acting cyclic-AMP receptor protein (CRP). We first consider the allosteric transition resulting from cyclic-AMP binding to CRP, then analyze how CRP binds to its operator, and finally investigate the ability of CRP to activate gene expression. We use these models to examine a beautiful recent experiment that created a single-chain version of the CRP homodimer, creating six mutants using all possible combinations of the wild type, D53H, and S62F subunits. We demonstrate that the MWC model can explain the behavior of all six mutants using a small, self-consistent set of parameters whose complexity scales with the number of subunits, providing a significant benefit over previous models. In comparison, the KNF model not only leads to a poorer characterization of the available data but also fails to generate parameter values in line with the available structural knowledge of CRP. In addition, we discuss how the conceptual framework developed here for CRP enables us to not merely analyze data retrospectively, but has the predictive power to determine how combinations of mutations will interact, how double mutants will behave, and how each construct would regulate gene expression.

Functional Role of Solvent Entropy and Conformational Entropy of Metal Binding in a Dynamically Driven Allosteric System

Allostery is a regulatory phenomenon whereby ligand binding to one site influences the binding of the same or a different ligand to another site on a macromolecule. The physical origins of allosteric regulation remain under intense investigation. In general terms, ligand-induced structural changes, perturbations of residue-specific dynamics, and surrounding solvent molecules all potentially contribute to the global energetics of allostery. While the role of solvent is generally well understood in regulatory events associated with major protein structural rearrangements, the degree to which protein dynamics impact solvent degrees of freedom is unclear, particularly in cases of dynamically driven allostery. With the aid of new crystal structures, extensive calorimetric and residue-specific dynamics studies over a range of time scales and temperatures, we dissect for the first time the relative degree to which changes in solvent entropy and residue-specific dynamics impact dynamically driven, allosteric inhibition of DNA binding by Zn in the zinc efflux repressor, CzrA (chromosomal zinc-regulated repressor). We show that non-native residue-specific dynamics in allosterically impaired CzrA mutants are accompanied by significant perturbations in solvent entropy that cannot be predicted from crystal structures. We conclude that functional dynamics are not necessarily restricted to protein residues but involve surface water molecules that may be responding to ligand (Zn)-mediated perturbations in protein internal motions that define the conformational ensemble, rather than major structural rearrangements.

Long-range coupling between ATP-binding and lever-arm regions in myosin via dielectric allostery

A protein molecule is a dielectric substance, so the binding of a ligand is expected to induce dielectric response in the protein molecule, considering that ligands are charged or polar in general. We previously reported that binding of adenosine triphosphate (ATP) to molecular motor myosin actually induces such a dielectric response in myosin due to the net negative charge of ATP. By this dielectric response, referred to as "dielectric allostery," spatially separated two regions in myosin, the ATP-binding region and the actin-binding region, are allosterically coupled. In this study, from the statistically stringent analyses of the extensive molecular dynamics simulation data obtained in the ATP-free and the ATP-bound states, we show that there exists the dielectric allostery that transmits the signal of ATP binding toward the distant lever-arm region. The ATP-binding-induced electrostatic potential change observed on the surface of the main domain induced a movement of the converter subdomain from which the lever arm extends. The dielectric response was found to be caused by an underlying large-scale concerted rearrangement of the electrostatic bond network, in which highly conserved charged/polar residues are involved. Our study suggests the importance of the dielectric property for molecular machines in exerting their function.

Crystal structures of a pentameric ion channel gated by alkaline pH show a widely open pore and identify a cavity for modulation

Pentameric ligand-gated ion channels (pLGICs) constitute a widespread class of ion channels, present in archaea, bacteria, and eukaryotes. Upon binding of their agonists in the extracellular domain, the transmembrane pore opens, allowing ions to go through, via a gating mechanism that can be modulated by a number of drugs. Even though high-resolution structural information on pLGICs has increased in a spectacular way in recent years, both in bacterial and in eukaryotic systems, the structure of the open channel conformation of some intensively studied receptors whose structures are known in a nonactive (closed) form, such as Erwinia chrysanthemi pLGIC (ELIC), is still lacking. Here we describe a gammaproteobacterial pLGIC from an endo-symbiont of Tevnia jerichonana (sTeLIC), whose sequence is closely related to the pLGIC from ELIC with 28% identity. We provide an X-ray crystallographic structure at 2.3 Å in an active conformation, where the pore is found to be more open than any current conformation found for pLGICs. In addition, two charged restriction rings are present in the vestibule. Functional characterization shows sTeLIC to be a cationic channel activated at alkaline pH. It is inhibited by divalent cations, but not by quaternary ammonium ions, such as tetramethylammonium. Additionally, we found that sTeLIC is allosterically potentiated by aromatic amino acids Phe and Trp, as well as their derivatives, such as 4-bromo-cinnamate, whose cocrystal structure reveals a vestibular binding site equivalent to, but more deeply buried than, the one already described for benzodiazepines in ELIC.

G protein-coupled receptor-receptor interactions give integrative dynamics to intercellular communication

The proposal of receptor-receptor interactions (RRIs) in the early 1980s broadened the view on the role of G protein-coupled receptors (GPCR) in the dynamics of the intercellular communication. RRIs, indeed, allow GPCR to operate not only as monomers but also as receptor complexes, in which the integration of the incoming signals depends on the number, spatial arrangement, and order of activation of the protomers forming the complex. The main biochemical mechanisms controlling the functional interplay of GPCR in the receptor complexes are direct allosteric interactions between protomer domains. The formation of these macromolecular assemblies has several physiologic implications in terms of the modulation of the signaling pathways and interaction with other membrane proteins. It also impacts on the emerging field of connectomics, as it contributes to set and tune the synaptic strength. Furthermore, recent evidence suggests that the transfer of GPCR and GPCR complexes between cells via the exosome pathway could enable the target cells to recognize/decode transmitters and/or modulators for which they did not express the pertinent receptors. Thus, this process may also open the possibility of a new type of redeployment of neural circuits. The fundamental aspects of GPCR complex formation and function are the focus of the present review article.