Exploring Mutation-Driven Changes in the ATP-ADP Conformational Cycle of Human Hsp70 by All-Atom MD Adaptive Sampling.

Hsp70 belongs to a family of molecular chaperones ubiquitous through organisms that assist client protein folding and prevent aggregation. It works through a tightly ATP-regulated allosteric cycle mechanism, which organizes its two NBD and SBD into alternate open and closed arrangements that facilitate loading and unloading of client proteins. The two cytosolic human isoforms Hsc70 and HspA1 are relevant targets for neurodegenerative diseases and cancer. Illuminating the molecular details of Hsp70 functional dynamics is essential to rationalize differences among the well-characterized bacterial homologue DnaK and the less explored human forms and develop subtype- or species-selective allosteric drugs. We present here a molecular dynamics-based analysis of the conformational dynamics of HspA1. By using an "allosterically impaired" mutant for comparison, we can reconstruct the impact of the ADP-ATP swap on interdomain contacts and dynamic coordination in full-length HspA1, supporting previous predictions that were, however, limited to the NBD. We model the initial onset of the conformational cycle by proposing a sequence of structural steps, which reveal the role of a specific human sequence insertion at the linker, and a modulation of the angle formed by the two NBD lobes during the progression of docking. Our findings pinpoint functionally relevant conformations and set the basis for a selective structure-based drug discovery approach targeting allosteric sites in human Hsp70.

Inhibition of the RNA-Dependent RNA-Polymerase from SARS-CoV-2 by 6-Chloropurine Isoxazoline-Carbocyclic Monophosphate Nucleotides.

Isoxazoline-carbocyclic monophosphate nucleotides were designed and synthesized through the chemistry of nitrosocarbonyl intermediates and stable anthracenenitrile oxide. Docking and molecular dynamics studies were first conducted for determining the best candidate for polymerase SARS-CoV-2 inhibition. The setup phosphorylation protocol afforded the nucleotides available for the biological tests. Preliminary inhibition and cytotoxicity assays were then performed, and the results showed a moderate activity of the nucleotides accompanied by cytotoxicity.

Gluten Exorphins Promote Cell Proliferation through the Activation of Mitogenic and Pro-Survival Pathways.

Celiac disease (CD) is a chronic and systemic autoimmune disorder that affects preferentially the small intestine of individuals with a genetic predisposition. CD is promoted by the ingestion of gluten, a storage protein contained in the endosperm of the seeds of wheat, barley, rye, and related cereals. Once in the gastrointestinal (GI) tract, gluten is enzymatically digested with the consequent release of immunomodulatory and cytotoxic peptides, i.e., 33mer and p31-43. In the late 1970s a new group of biologically active peptides, called gluten exorphins (GEs), was discovered and characterized. In particular, these short peptides showed a morphine-like activity and high affinity for the δ-opioid receptor (DOR). The relevance of GEs in the pathogenesis of CD is still unknown. Recently, it has been proposed that GEs could contribute to asymptomatic CD, which is characterized by the absence of symptoms that are typical of this disorder. In the present work, GEs cellular and molecular effects were in vitro investigated in SUP-T1 and Caco-2 cells, also comparing viability effects with human normal primary lymphocytes. As a result, GEs treatments increased tumor cell proliferation by cell cycle and Cyclins activation as well as by induction of mitogenic and pro-survival pathways. Finally, a computational model of GEs interaction with DOR is provided. Altogether, the results might suggest a possible role of GEs in CD pathogenesis and on its associated cancer comorbidities.

Cholesterol occupies the lipid translocation pathway to block phospholipid scrambling by a G protein-coupled receptor.

Class A (rhodopsin-like) G protein-coupled receptors (GPCRs) are constitutive phospholipid scramblases as evinced after their reconstitution into liposomes. Yet phospholipid scrambling is not detectable in the resting plasma membrane of mammalian cells that is replete with GPCRs. We considered whether cholesterol, a prominent component of the plasma membrane, limits the ability of GPCRs to scramble lipids. Our previous Markov State Model (MSM) analysis of molecular dynamics simulations of membrane-embedded opsin indicated that phospholipid headgroups traverse a dynamically revealed hydrophilic groove between transmembrane helices (TM) 6 and 7 while their tails remain in the bilayer. Here, we present comparative MSM analyses of 150-µs simulations of opsin in cholesterol-free and cholesterol-rich membranes. Our analyses reveal that cholesterol inhibits phospholipid scrambling by occupying the TM6/7 interface and stabilizing the closed groove conformation while itself undergoing flip-flop. This mechanism may explain the inability of GPCRs to scramble lipids at the plasma membrane.

The Answer Lies in the Energy: How Simple Atomistic Molecular Dynamics Simulations May Hold the Key to Epitope Prediction on the Fully Glycosylated SARS-CoV-2 Spike Protein.

SARS-CoV-2 is a health threat with dire socioeconomical consequences. As the crucial mediator of infection, the viral glycosylated spike protein (S) has attracted the most attention and is at the center of efforts to develop therapeutics and diagnostics. Herein, we use an original decomposition approach to identify energetically uncoupled substructures as antibody binding sites on the fully glycosylated S. Crucially, all that is required are unbiased MD simulations; no prior knowledge of binding properties or ad hoc parameter combinations is needed. Our results are validated by experimentally confirmed structures of S in complex with anti- or nanobodies. We identify poorly coupled subdomains that are poised to host (several) epitopes and potentially involved in large functional conformational transitions. Moreover, we detect two distinct behaviors for glycans: those with stronger energetic coupling are structurally relevant and protect underlying peptidic epitopes, and those with weaker coupling could themselves be prone to antibody recognition.

Simple Model of Protein Energetics To Identify Ab Initio Folding Transitions from All-Atom MD Simulations of Proteins.

A fundamental requirement to predict the native conformation, address questions of sequence design and optimization, and gain insights into the folding mechanisms of proteins lies in the definition of an unbiased reaction coordinate that reports on the folding state without the need to compare it to reference values, which might be unavailable for new (designed) sequences. Here, we introduce such a reaction coordinate, which does not depend on previous structural knowledge of the native state but relies solely on the energy partition within the protein: the spectral gap of the pair nonbonded energy matrix (ENergy Gap, ENG). This quantity can be simply calculated along unbiased MD trajectories. We show that upon folding the gap increases significantly, while its fluctuations are reduced to a minimum. This is consistently observed for a diverse set of systems and trajectories. Our approach allows one to promptly identify residues that belong to the folding core as well as residues involved in non-native contacts that need to be disrupted to guide polypeptides to the folded state. The energy gap and fluctuations criteria are then used to develop an automatic detection system which allows us to extract and analyze folding transitions from a generic MD trajectory. We speculate that our method can be used to detect conformational ensembles in dynamic and intrinsically disordered proteins, revealing potential preorganization for binding.

Tryptophan scanning mutagenesis as a way to mimic the compound-bound state and probe the selectivity of allosteric inhibitors in cells.

Understanding the selectivity of a small molecule for its target(s) in cells is an important goal in chemical biology and drug discovery. One powerful way to address this question is with dominant negative (DN) mutants, in which an active site residue in the putative target is mutated. While powerful, this approach is less straightforward for allosteric sites. Here, we introduce tryptophan scanning mutagenesis as an expansion of this idea. As a test case, we focused on the challenging drug target, heat shock cognate protein 70 (Hsc70), and its allosteric inhibitor JG-98. Structure-based modelling predicted that mutating Y149W in human Hsc70 or Y145W in the bacterial ortholog DnaK would place an indole side chain into the allosteric pocket normally occupied by the compound. Indeed, we found that the tryptophan mutants acted as if they were engaged with JG-98. We then used DnaK Y145W to suggest that this protein may be an anti-bacterial target. Indeed, we found that DnaK inhibitors have minimum inhibitory concentration (MIC) values <0.125 µg mL-1 against several pathogens, including multidrug-resistant Staphylococcus aureus (MRSA) strains. We propose that tryptophan scanning mutagenesis may provide a distinct way to address the important problem of target engagement.

A Machine Learning Approach for the Discovery of Ligand-Specific Functional Mechanisms of GPCRs.

G protein-coupled receptors (GPCRs) play a key role in many cellular signaling mechanisms, and must select among multiple coupling possibilities in a ligand-specific manner in order to carry out a myriad of functions in diverse cellular contexts. Much has been learned about the molecular mechanisms of ligand-GPCR complexes from Molecular Dynamics (MD) simulations. However, to explore ligand-specific differences in the response of a GPCR to diverse ligands, as is required to understand ligand bias and functional selectivity, necessitates creating very large amounts of data from the needed large-scale simulations. This becomes a Big Data problem for the high dimensionality analysis of the accumulated trajectories. Here we describe a new machine learning (ML) approach to the problem that is based on transforming the analysis of GPCR function-related, ligand-specific differences encoded in the MD simulation trajectories into a representation recognizable by state-of-the-art deep learning object recognition technology. We illustrate this method by applying it to recognize the pharmacological classification of ligands bound to the 5-HT2A and D2 subtypes of class-A GPCRs from the serotonin and dopamine families. The ML-based approach is shown to perform the classification task with high accuracy, and we identify the molecular determinants of the classifications in the context of GPCR structure and function. This study builds a framework for the efficient computational analysis of MD Big Data collected for the purpose of understanding ligand-specific GPCR activity.

Allosteric Modulators of HSP90 and HSP70: Dynamics Meets Function through Structure-Based Drug Design.

Molecular chaperones HSP90 and HSP70 are essential regulators of the folding and activation of a disparate ensemble of client proteins. They function through ATP hydrolysis and the assembly of multiprotein complexes with cochaperones and clients. While their therapeutic relevance is recognized, important details underlying the links between ATP-dependent conformational dynamics and clients/cochaperones recruitment remain elusive. Allosteric modulators represent fundamental tools to obtain molecular insights into functional regulation. By selective perturbation of different aspects of HSP90/HSP70 activities, allosteric drugs can tune rather than completely inhibit signaling cascades, providing information on the relationships between structure-dynamics and function. Herein, we review advances in the design of HSP90 and HSP70 allosteric modulators. We consider inhibitors and activators in different biochemical and disease models. We discuss these compounds as probes to decipher the complexity of the chaperone machinery and that at the same time represent starting leads for the development of drugs against cancer and neurodegeneration.

A Local Allosteric Network in Heat Shock Protein 70 (Hsp70) Links Inhibitor Binding to Enzyme Activity and Distal Protein-Protein Interactions.

Allosteric inhibitors can be more difficult to optimize without an understanding of how their binding influences the conformational motions of the target. Here, we used an integrated computational and experimental approach to probe the molecular mechanism of an allosteric inhibitor of heat shock protein 70 (Hsp70). The anticancer compound, MKT-077, is known to bind a conserved site in members of the Hsp70 family, which favors the ADP-bound state and interferes with a protein-protein interaction (PPI) at long range. However, the binding site does not overlap with either the nucleotide-binding cleft or the PPI contact surface, so its mechanism is unclear. To this end, we modeled Hsp70's internal dynamics and studied how MKT-077 alters local sampling of its allosteric states. The results pointed to a set of concerted motions between five loops in Hsp70's nucleotide-binding domain (NBD), surrounding the MKT-077 binding site. To test this prediction, we mutated key residues and monitored chaperone activities in vitro. Together, the results indicate that MKT-077 interacts with loop222 to favor a pseudo-ADP bound conformer of Hsp70's NBD, even when ATP is present. We used this knowledge to synthesize an analog of MKT-077 that would better prevent motions of loop222 and confirmed that it had improved antiproliferative activity in breast cancer cells. These results provide an example of how to unlock and leverage the complex mechanisms of allosteric inhibitors.

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).

Prediction and Targeting of Interaction Interfaces in G-protein Coupled Receptor Oligomers.

BACKGROUND: Communication within a protein complex is mediated by physical interactions made among the protomers. Evidence for both the allosteric regulation present among the protomers of the protein oligomer and of the direct effect of membrane composition on this regulation has made it essential to investigate the underlying molecular mechanism that drives oligomerization, the type of interactions present within the complex, and to determine the identity of the interaction interface. This knowledge allows a holistic understanding of dynamics and also modulation of the function of the resulting oligomers/signalling complexes. G-Protein-Coupled Receptors (GPCRs), which are targeted by 40% of currently prescribed drugs in the market, are widely involved in the formation of such physiological oligomers/signalling complexes. SCOPE: This review highlights the importance of studying Protein-Protein Interactions (PPI) by using a combination of data obtained from cutting-edge experimental and computational methods that were developed for this purpose. In particular, we focused on interaction interfaces found at GPCR oligomers as well as signalling complexes, since any problem associated with these interactions causes the onset of various crucial diseases. CONCLUSION: In order to have a holistic mechanistic understanding of allosteric PPIs that drive the formation of GPCR oligomers and also to determine the composition of interaction interfaces with respect to different membrane compositions, it is essential to combine both relevant experimental and computational data. In this way, efficient and specific targeting of these interaction interfaces in oligomers/ complexes can be achieved. Thus, effective therapeutic molecules with fewer side effects can be designed to modulate the function of these physiologically important receptor family.

Mechanisms of Lipid Scrambling by the G Protein-Coupled Receptor Opsin.

Several class-A G protein-coupled receptor (GPCR) proteins act as constitutive phospholipid scramblases catalyzing the transbilayer translocation of >10,000 phospholipids per second when reconstituted into synthetic vesicles. To address the molecular mechanism by which these proteins facilitate rapid lipid scrambling, we carried out large-scale ensemble atomistic molecular dynamics simulations of the opsin GPCR. We report that, in the process of scrambling, lipid head groups traverse a dynamically revealed hydrophilic pathway in the region between transmembrane helices 6 and 7 of the protein while their hydrophobic tails remain in the bilayer environment. We present quantitative kinetic models of the translocation process based on Markov State Model analysis. As key residues on the lipid translocation pathway are conserved within the class-A GPCR family, our results illuminate unique aspects of GPCR structure and dynamics while providing a rigorous basis for the design of variants of these proteins with defined scramblase activity.

Computational studies of G protein-coupled receptor complexes: Structure and dynamics.

G protein-coupled receptors (GPCRs) are ubiquitously expressed transmembrane proteins associated with a wide range of diseases such as Alzheimer's, Parkinson, schizophrenia, and also implicated in in several abnormal heart conditions. As such, this family of receptors is regarded as excellent drug targets. However, due to the high number of intracellular signaling partners, these receptors have a complex interaction networks and it becomes challenging to modulate their function. Experimentally determined structures give detailed information on the salient structural properties of these signaling complexes but they are far away from providing mechanistic insights into the underlying process. This chapter presents some of the computational tools, namely molecular dynamics, molecular docking, and molecular modeling and related analyses methods that have been used to complement experimental findings.

Role of Terahertz (THz) Fluctuations in the Allosteric Properties of the PDZ Domains.

With the aim of investigating the relationship between the fast fluctuations of proteins and their allosteric behavior, we perform molecular dynamics simulations of two model PDZ domains with differential allosteric responses. We focus on protein dynamics in the THz regime (0.1-3 THz) as opposed to lower frequencies. By characterizing the dynamic modulation of the protein backbone induced by ligand binding in terms of single residue and pairwise distance fluctuations, we identify a response nucleus modulated by the ligand that is visible only at THz frequencies. The residues of this nucleus undergo a significant stiffening and an increase in mutual coordination upon binding. Additionally, we find that the dynamic modulation is significantly more intense for the side chains, where it is also redistributed to distal regions not immediately in contact with the ligand allowing us to better define the response nucleus at THz frequencies. The overlap between the known allosterically responding residues of the investigated PDZ domains and the modulated region highlighted here suggests that fast THz dynamics could play a role in allosteric mechanisms.

Crystal Structure of the DFNKF Segment of Human Calcitonin Unveils Aromatic Interactions between Phenylalanines.

Although intensively studied, the high-resolution crystal structure of the peptide DFNKF, the core-segment of human calcitonin, has never been described. Here we report how the use of iodination as a strategy to promote crystallisation and facilitate phase determination, allowed us to solve, for the first time, the single-crystal X-ray structure of a DFNKF derivative. Computational studies suggest that both the iodinated and the wild-type peptides populate very similar conformations. Furthermore, the conformer found in the solid-state structure is one of the most populated in solution, making the crystal structure a reliable model for the peptide in solution. The crystal structure of DFNKF(I) confirms the overall features of the amyloid cross-ß spine and highlights how aromatic-aromatic interactions are important structural factors in the self-assembly of this peptide. A detailed analysis of such interactions is reported.

Allosteric Regulation Points Control the Conformational Dynamics of the Molecular Chaperone Hsp90.

Heat shock protein 90 (Hsp90) is an ATP-dependent molecular chaperone responsible for the activation, maturation, and trafficking of several hundred client proteins in the cell. It is well known that (but not understood how) residues far away from Hsp90's nucleotide binding pocket can regulate its ATPase activity, a phenomenon called allosteric regulation. Here, the computational design of allosteric mutations was combined with in vitro and in vivo experiments to unravel nucleotide-responsive hot spots in the regulation of Hsp90. With this approach, we identified both activating and inhibiting regulation points and show that changes in those amino acids affect the conformational dynamics and ATPase activity of Hsp90 in vitro. Our observations that activating mutations loosen and inhibiting mutations rigidify the protein explain for the first time how Hsp90 changes in response to allosteric mutations. Additionally, mutations of these allosteric regulation points can be controlled by the interplay with Hsp90 co-chaperones, thus providing cells with an efficient mechanism of modifying Hsp90's intrinsic properties via different layers of regulation. Altogether, our results show that a framework for transmitting conformational information exists in the Hsp90 structure.

Understanding the Differential Selectivity of Arrestins toward the Phosphorylation State of the Receptor.

Proteins in the arrestin family exhibit a conserved structural fold that nevertheless allows for significant differences in their selectivity for G-protein coupled receptors (GPCRs) and their phosphorylation states. To reveal the mechanism of activation that prepares arrestin for selective interaction with GPCRs, and to understand the basis for these differences, we used unbiased molecular dynamics simulations to compare the structural and dynamic properties of wild type Arr1 (Arr1-WT), Arr3 (Arr3-WT), and a constitutively active Arr1 mutant, Arr1-R175E, characterized by a perturbation of the phosphate recognition region called "polar core". We find that in our simulations the mutant evolves toward a conformation that resembles the known preactivated structures of an Arr1 splice-variant, and the structurally similar phosphopeptide-bound Arr2-WT, while this does not happen for Arr1-WT. Hence, we propose an activation allosteric mechanism connecting the perturbation of the polar core to a global conformational change, including the relative reorientation of N- and C-domains, and the emergence of electrostatic properties of putative binding surfaces. The underlying local structural changes are interpreted as markers of the evolution of an arrestin structure toward an active-like conformation. Similar activation related changes occur in Arr3-WT in the absence of any perturbation of the polar core, suggesting that this system could spontaneously visit preactivated states in solution. This hypothesis is proposed to explain the lower selectivity of Arr3 toward nonphosphorylated receptors. Moreover, by elucidating the allosteric mechanism underlying activation, we identify functionally critical regions on arrestin structure that can be targeted with drugs or chemical tools for functional modulation.