Decrypting Allostery in Membrane-Bound K-Ras4B Using Complementary In Silico Approaches Based on Unbiased Molecular Dynamics Simulations.

Protein functions are dynamically regulated by allostery, which enables conformational communication even between faraway residues, and expresses itself in many forms, akin to different "languages": allosteric control pathways predominating in an unperturbed protein are often unintuitively reshaped whenever biochemical perturbations arise (e.g., mutations). To accurately model allostery, unbiased molecular dynamics (MD) simulations require integration with a reliable method able to, e.g., detect incipient allosteric changes or likely perturbation pathways; this is because allostery can operate at longer time scales than those accessible by plain MD. Such methods are typically applied singularly, but we here argue their joint application─as a "multilingual" approach─could work significantly better. We successfully prove this through unbiased MD simulations (∼100 µs) of the widely studied, allosterically active oncotarget K-Ras4B, solvated and embedded in a phospholipid membrane, from which we decrypt allostery using four showcase "languages": Distance Fluctuation analysis and the Shortest Path Map capture allosteric hotspots at equilibrium; Anisotropic Thermal Diffusion and Dynamical Non-Equilibrium MD simulations assess perturbations upon, respectively, either superheating or hydrolyzing the GTP that oncogenically activates K-Ras4B. Chosen "languages" work synergistically, providing an articulate, mutually coherent, experimentally consistent picture of K-Ras4B allostery, whereby distinct traits emerge at equilibrium and upon GTP cleavage. At equilibrium, combined evidence confirms prominent allosteric communication from the membrane-embedded hypervariable region, through a hub comprising helix α5 and sheet ß5, and up to the active site, encompassing allosteric "switches" I and II (marginally), and two proposed pockets. Upon GTP cleavage, allosteric perturbations mostly accumulate on the switches and documented interfaces.

Gas Permeation through Mechanically Resistant Self-Standing Membranes of a Neat Amorphous Organic Cage.

The synthesis and characterization of a novel film-forming organic cage and of its smaller analogue are here described. While the small cage produced single crystals suitable for X-ray diffraction studies, the large one was isolated as a dense film. Due to its remarkable film-forming properties, this latter cage could be solution processed into transparent thin-layer films and mechanically stable dense self-standing membranes of controllable thickness. Thanks to these peculiar features, the membranes were also successfully tested for gas permeation, reporting a behavior similar to that found with stiff glassy polymers such as polymers of intrinsic microporosity or polyimides. Given the growing interest in the development of molecular-based membranes, for example for separation technologies and functional coatings, the properties of this organic cage were investigated by thorough analysis of their structural, thermal, mechanical and gas transport properties, and by detailed atomistic simulations.

Integrating Protein Interaction Surface Prediction with a Fragment-Based Drug Design: Automatic Design of New Leads with Fragments on Energy Surfaces.

Protein-protein interactions (PPIs) have emerged in the past years as significant pharmacological targets in the development of new therapeutics due to their key roles in determining pathological pathways. Herein, we present fragments on energy surfaces, a simple and general design strategy that integrates the analysis of the dynamic and energetic signatures of proteins to unveil the substructures involved in PPIs, with docking, selection, and combination of drug-like fragments to generate new PPI inhibitor candidates. Specifically, structural representatives of the target protein are used as inputs for the blind physics-based prediction of potential protein interaction surfaces using the matrix of low coupling energy decomposition method. The predicted interaction surfaces are subdivided into overlapping windows that are used as templates to direct the docking and combination of fragments representative of moieties typically found in active drugs. This protocol is then applied and validated using structurally diverse, important PPI targets as test systems. We demonstrate that our approach facilitates the exploration of the molecular diversity space of potential ligands, with no requirement of prior information on the location and properties of interaction surfaces or on the structures of potential lead compounds. Importantly, the hit molecules that emerge from our ab initio design share high chemical similarity with experimentally tested active PPI inhibitors. We propose that the protocol we describe here represents a valuable means of generating initial leads against difficult targets for further development and refinement.

The molecular chaperone TRAP1 in cancer: From the basics of biology to pharmacological targeting.

TRAP1, the mitochondrial component of the Hsp90 family of molecular chaperones, displays important bioenergetic and proteostatic functions. In tumor cells, TRAP1 contributes to shape metabolism, dynamically tuning it with the changing environmental conditions, and to shield from noxious insults. Hence, TRAP1 activity has profound effects on the capability of neoplastic cells to evolve towards more malignant phenotypes. Here, we discuss our knowledge on the biochemical functions of TRAP1 in the context of a growing tumor mass, and we analyze the possibility of targeting its chaperone functions for developing novel anti-neoplastic approaches.

SARS-CoV-2 Spike Protein Mutations and Escape from Antibodies: A Computational Model of Epitope Loss in Variants of Concern.

The SARS-CoV-2 spike (S) protein is exposed on the viral surface and is the first point of contact between the virus and the host. For these reasons it represents the prime target for Covid-19 vaccines. In recent months, variants of this protein have started to emerge. Their ability to reduce or evade recognition by S-targeting antibodies poses a threat to immunological treatments and raises concerns for their consequences on vaccine efficacy. To develop a model able to predict the potential impact of S-protein mutations on antibody binding sites, we performed unbiased multi-microsecond molecular dynamics of several glycosylated S-protein variants and applied a straightforward structure-dynamics-energy based strategy to predict potential changes in immunogenic regions on each variant. We recover known epitopes on the reference D614G sequence. By comparing our results, obtained on isolated S-proteins in solution, to recently published data on antibody binding and reactivity in new S variants, we directly show that modifications in the S-protein consistently translate into the loss of potentially immunoreactive regions. Our findings can thus be qualitatively reconnected to the experimentally characterized decreased ability of some of the Abs elicited against the dominant S-sequence to recognize variants. While based on the study of SARS-CoV-2 spike variants, our computational epitope-prediction strategy is portable and could be applied to study immunoreactivity in mutants of proteins of interest whose structures have been characterized, helping the development/selection of vaccines and antibodies able to control emerging variants.

Designing Molecular Spanners to Throw in the Protein Networks.

Proteins govern most aspects of cellular life and, through specific interfaces, are typically involved in intricate protein-protein interaction (PPI) networks and signaling pathways. Subtle up- or downregulation of key protein functions and PPIs results in disease; still, the preferred option to contrast the role of a protein in disease and healthy conditions alike remains its outright shutdown through orthosteric ligands that block its active site. Here, we explore subtler alternatives to modulate proteins and PPIs. Driven by a view of proteins as dynamic entities, we discuss ways to identify allosteric binding sites, which, when targeted by tailored ligands, can induce significant changes in the active site of a protein, and lead to agonistic or antagonistic effects. We also summarize the selective regulation of specific PPIs-either direct or allosteric-and show that effects can be stabilizing as well as destabilizing, depending on how the conformational equilibrium of a protein is shifted.

Chemical Perturbation of Oncogenic Protein Folding: from the Prediction of Locally Unstable Structures to the Design of Disruptors of Hsp90-Client Interactions.

Protein folding quality control in cells requires the activity of a class of proteins known as molecular chaperones. Heat shock protein-90 (Hsp90), a multidomain ATP driven molecular machine, is a prime representative of this family of proteins. Interactions between Hsp90, its co-chaperones, and client proteins have been shown to be important in facilitating the correct folding and activation of clients. Hsp90 levels and functions are elevated in tumor cells. Here, we computationally predict the regions on the native structures of clients c-Abl, c-Src, Cdk4, B-Raf and Glucocorticoid Receptor, that have the highest probability of undergoing local unfolding, despite being ordered in their native structures. Such regions represent potential ideal interaction points with the Hsp90-system. We synthesize mimics spanning these regions and confirm their interaction with partners of the Hsp90 complex (Hsp90, Cdc37 and Aha1) by Nuclear Magnetic Resonance (NMR). Designed mimics selectively disrupt the association of their respective clients with the Hsp90 machinery, leaving unrelated clients unperturbed and causing apoptosis in cancer cells. Overall, selective targeting of Hsp90 protein-protein interactions is achieved without causing indiscriminate degradation of all clients, setting the stage for the development of therapeutics based on specific chaperone:client perturbation.

Impact of Mutations on NPAC Structural Dynamics: Mechanistic Insights from MD Simulations.

NPAC is a cytokine-like nuclear factor involved in chromatin modification and regulation of gene expression. In humans, the C-terminal domain of NPAC has the conserved structure of the ß-hydroxyacid dehydrogenases (ß-HAD) protein superfamily, which forms a stable tetrameric core scaffold for demethylase enzymes and organizes multiple sites for chromatin interactions. In spite of the close structural resemblance to other ß-HAD family members, the human NPAC dehydrogenase domain lacks a highly conserved catalytic lysine, substituted by a methionine. The reintroduction of the catalytic lysine by M437 K mutation results in a significant decrease of stability of the tetramer. Here, we have computationally investigated the molecular determinants of the functional differences between methionine and lysine-containing NPAC proteins. We find that the single mutation can determine strong consequences in terms of dynamics, stability, and ultimately ability to assemble in supramolecular complexes: the higher stability and lower flexibility of the methionine variant structurally preorganizes the monomer for tetramerization, whereas lysine increases flexibility and favors conformations that, while catalytically active, are not optimal for tetrameric assembly. We combine structure-dynamics analysis to an evolutionary study of NPAC sequences, showing that the methionine mutation occurs in a specifically flexible region of the lysine-containing protein, flanked by two domains that concentrate most of the stabilizing interactions. In our model, such separation of stability nuclei and flexible regions appears to favor the functional innovability of the protein.

Electronic and relativistic contributions to ion-pairing in polyoxometalate model systems.

Ion pairs and solubility related to ion-pairing in water influence many processes in nature and in synthesis including efficient drug delivery, contaminant transport in the environment, and self-assembly of materials in water. Ion pairs are difficult to observe spectroscopically because they generally do not persist unless extreme solution conditions are applied. Here we demonstrate two advanced techniques coupled with computational studies that quantify the persistence of ion pairs in simple solutions and offer explanations for observed solubility trends. The system of study, ([(CH3)4N]+,Cs)8[M6O19] (M = Nb,Ta), is a set of unique polyoxometalate salts whose water solubility increases with increasing ion-pairing, contrary to most ionic salts. The techniques employed to characterize Cs+ association with [M6O19]8- and related clusters in simple aqueous media are 133Cs NMR (nuclear magnetic resonance) quadrupolar relaxation rate and PDF (pair distribution function) from X-ray scattering. The NMR measurements consistently showed more extensive ion-pairing of Cs+ with the Ta-analogue than the Nb-analogue, although the electrostatics of the ions should be identical. Computational studies also ascertained more persistent Cs+-[Ta6O19] ion pairs than Cs+-[Nb6O19] ion pairs, and bond energy decomposition analyses determined relativistic effects to be the differentiating factor between the two. These distinctions are likely responsible for many of the unexplained differences between aqueous Nb and Ta chemistry, while they are so similar in the solid state. The X-ray scattering studies show atomic level detail of this ion association that has not been prior observed, enabling confidence in our structures for calculations of Cs-cluster association energies. Moreover, detailed NMR studies allow quantification of the number of Cs+ associated with a single [Nb6O19]8- or [Ta6O19]8- anion which agrees with the PDF analyses.

Molecular Motion and Conformational Interconversion of Ir(I)·COD Included in Rebek's Self-Folding Octaamide Cavitand.

We report experimental and theoretical evidence of restrained axial rotation for heteroleptic L2·Ir(I)·1,5-cyclooctadiene (COD) complexes included in the aromatic cavity of Rebek's self-folding octaamide cavitand. At 298 K, the axial spinning motion of the included organometallic guests was slow on the (1)H NMR time scale and produced a proton spectrum for the bound host indicative of C2 symmetry. Signals corresponding to aromatic protons of the bound host coalesced at 323 K, indicating that the spinning process of the included guest became fast on the (1)H NMR time scale and that the complex approached C4 symmetry. Surprisingly, lowering the temperature of the solution to 193 K induced an additional splitting of the proton signals observed at room temperature for both the bound host and the included guest. We propose the emergence of a new element of chirality in the complexes, which was associated with a slow interconversion, on the (1)H NMR time scale between the two chiral twisted-boat conformers of the chelated COD included in the already chiral cavity of the container. This leads to the inclusion complexes existing in solution as pairs of two racemic diastereomers. We estimated that the racemization barrier for the two cyclochiral conformers of the Ir(I) chelated COD was 5 kcal mol(-1) higher as an included organometallic complex than as free in solution. Furthermore, we performed a van't Hoff plot and determined that the inclusion of the organometallic complex in the cavitand was endothermic and exclusively driven by entropy (ΔH = 5.9 kcal mol(-1) and ΔS = 33.9 cal mol(-1) K(-1)).

Ring-closing metathesis and nanoparticle formation based on diallyldithiocarbamate complexes of gold(I): synthetic, structural, and computational studies.

The gold(I) complexes [Au{S2CN(CH2CH═CH2)2}(L)] [L = PPh3, PCy3, PMe3, CN(t)Bu, IDip] are prepared from KS2CN(CH2CH═CH2)2 and [(L)AuCl]. The compounds [L2(AuCl)2] (L2 = dppa, dppf) yield [(L2){AuS2CN(CH2CH═CH2)2}2], while the cyclic complex [(dppm){Au2S2CN(CH2CH═CH2)2}]OTf is obtained from [dppm(AuCl)2] and AgOTf followed by KS2CN(CH2CH═CH2)2. The compound [Au2{S2CN(CH2CH═CH2)2}2] is prepared from [(tht)AuCl] (tht = tetrahydrothiophene) and the diallyldithiocarbamate ligand. This product ring-closes with [Ru(═CHPh)Cl2(SIMes)(PCy3)] to yield [Au2(S2CNC4H6)2], whereas ring-closing of [Au{S2CN(CH2CH═CH2)2}(PR3)] fails. Warming [Au2{S2CN(CH2CH═CH2)2}2] results in formation of gold nanoparticles with diallydithiocarbamate surface units, while heating [Au2(S2CNC4H6)2] with NaBH4 results in nanoparticles with 3-pyrroline dithiocarbamate surface units. Larger nanoparticles with the same surface units are prepared by citrate reduction of HAuCl4 followed by addition of the dithiocarbamate. The diallydithiocarbamate-functionalized nanoparticles undergo ring-closing metathesis using [Ru(═CHC6H4O(i)Pr-2)Cl2(SIMes)]. The interaction between the dithiocarbamate units and the gold surface is explored using computational methods to reveal no need for a countercation. Preliminary calculations indicate that the Au-S interactions are substantially different from those established in theoretical and experimental studies on thiolate-coated nanoparticles. Structural studies are reported for [Au{S2CN(CH2CH═CH2)2}(PPh3)] and [Au2{S2CN(CH2CH═CH2)2}2]. In the latter, exceptionally short intermolecular aurophilic interactions are observed.

Structures, dynamics, complexes, and functions: From classic computation to artificial intelligence.

Computational approaches can provide highly detailed insight into the molecular recognition processes that underlie drug binding, the assembly of protein complexes, and the regulation of biological functional processes. Classical simulation methods can bridge a wide range of length- and time-scales typically involved in such processes. Lately, automated learning and artificial intelligence methods have shown the potential to expand the reach of physics-based approaches, ushering in the possibility to model and even design complex protein architectures. The synergy between atomistic simulations and AI methods is an emerging frontier with a huge potential for advances in structural biology. Herein, we explore various examples and frameworks for these approaches, providing select instances and applications that illustrate their impact on fundamental biomolecular problems.

Assessing the preferred solution conformation of an interacting sense-antisense (complementary) peptide pair.

Sense peptides and corresponding antisense peptides, are capable of making specific interactions. Such interactions may result from inter-peptide side-chain/side-chain contacts or because peptides adopt mutually complementary three-dimensional shapes. Using a combined (1)H NMR spectroscopy/molecular modeling approach to study the interactions between one sense peptide and its corresponding antisense peptide, data are produced that provide clear support for the former hypothesis.

Computational Epitope Prediction and Design for Antibody Development and Detection.

The design of optimized protein antigens is a fundamental step in the development of new vaccine candidates and in the detection of therapeutic antibodies. A fundamental prerequisite is the identification of antigenic regions that are most prone to interact with antibodies, namely, B-cell epitopes. Here, we describe an efficient structure-based computational method for epitope prediction, called MLCE. In this approach, all that is required is the 3D structure of the antigen of interest. MLCE can be applied to glycosylated proteins, facilitating the identification of immunoreactive versus immune-shielding carbohydrates.

NLRP3 monomer functional dynamics: From the effects of allosteric binding to implications for drug design.

The protein NLRP3 and its complexes are associated with an array of inflammatory pathologies, among which neurodegenerative, autoimmune, and metabolic diseases. Targeting the NLRP3 inflammasome represents a promising strategy for easing the symptoms of pathologic neuroinflammation. When the inflammasome is activated, NLRP3 undergoes a conformational change triggering the production of pro-inflammatory cytokines IL-1ß and IL-18, as well as cell death by pyroptosis. NLRP3 nucleotide-binding and oligomerization (NACHT) domain plays a crucial role in this function by binding and hydrolysing ATP and is primarily responsible, together with conformational transitions involving the PYD domain, for the complex-assembly process. Allosteric ligands proved able to induce NLRP3 inhibition. Herein, we examine the origins of allosteric inhibition of NLRP3. Through the use of molecular dynamics (MD) simulations and advanced analysis methods, we provide molecular-level insights into how allosteric binding affects protein structure and dynamics, remodelling of the conformational ensembles populated by the protein, with key reverberations on how NLRP3 is preorganized for assembly and ultimately function. The data are used to develop a Machine Learning model to define the protein as Active or Inactive, only based on the analysis of its internal dynamics. We propose this model as a novel tool to select allosteric ligands.

Phosphorylation of the Hsp90 Co-Chaperone Hop Changes its Conformational Dynamics and Biological Function.

The molecular chaperones Hsp90 and Hsp70 and their regulatory co-chaperone Hop play a key role at the crossroads of the folding pathways of numerous client proteins by forming fine-tuned multiprotein complexes. Alterations of the biomolecules involved may functionally impact the chaperone machinery: here, we integrate simulations and experiments to unveil how Hop conformational fitness and interactions can be controlled by the perturbation of just one residue. Specifically, we unveil how mechanisms mediated by Hop residue Y354 control Hop open and closed states, which affect binding of Hsp70/Hsp90. Phosphorylation or mutation of Hop-Y354 are shown to favor structural ensembles that are indeed not optimal for stable interactions with Hsp90 and Hsp70. This disfavors cellular accumulation of the stringent Hsp90 clients glucocorticoid receptor and the viral tyrosine kinase v-Src, with detrimental effects on v-Src activity. Our results show how the post-translational modification of a specific residue in Hop provides a regulation mechanism for the larger chaperone complex of which it is part. In this framework, the effects of one single alteration are amplified at the cellular level through the perturbation of protein-interaction networks.

Conformational Behavior of SARS-Cov-2 Spike Protein Variants: Evolutionary Jumps in Sequence Reverberate in Structural Dynamic Differences.

SARS-CoV-2 has evolved rapidly in the first 3 years of pandemic diffusion. The initial evolution of the virus appeared to proceed through big jumps in sequence changes rather than through the stepwise accumulation of point mutations on already established variants. Here, we examine whether this nonlinear mutational process reverberates in variations of the conformational dynamics of the SARS-CoV-2 Spike protein (S-protein), the first point of contact between the virus and the human host. We run extensive microsecond-scale molecular dynamics simulations of seven distinct variants of the protein in their fully glycosylated state and set out to elucidate possible links between the mutational spectrum of the S-protein and the structural dynamics of the respective variant, at global and local levels. The results reveal that mutation-dependent structural and dynamic modulations mostly consist of increased coordinated motions in variants that acquire stability and in an increased internal flexibility in variants that are less stable. Importantly, a limited number of functionally important substructures (the receptor binding domain, in particular) share the same time of movements in all variants, indicating efficient preorganization for functional regions dedicated to host interactions. Our results support a model in which the internal dynamics of the S-proteins from different strains varies in a way that reflects the observed random and non-stepwise jumps in sequence evolution, while conserving the functionally oriented traits of conformational dynamics necessary to support productive interactions with host receptors.

Molecular mechanisms of chaperone-directed protein folding: Insights from atomistic simulations.

Molecular chaperones, a family of proteins of which Hsp90 and Hsp70 are integral members, form an essential machinery to maintain healthy proteomes by controlling the folding and activation of a plethora of substrate client proteins. This is achieved through cycles in which Hsp90 and Hsp70, regulated by task-specific co-chaperones, process ATP and become part of a complex network that undergoes extensive compositional and conformational variations. Despite impressive advances in structural knowledge, the mechanisms that regulate the dynamics of functional assemblies, their response to nucleotides, and their relevance for client remodeling are still elusive. Here, we focus on the glucocorticoid receptor (GR):Hsp90:Hsp70:co-chaperone Hop client-loading and the GR:Hsp90:co-chaperone p23 client-maturation complexes, key assemblies in the folding cycle of glucocorticoid receptor (GR), a client strictly dependent upon Hsp90/Hsp70 for activity. Using a combination of molecular dynamics simulation approaches, we unveil with unprecedented detail the mechanisms that underpin function in these chaperone machineries. Specifically, we dissect the processes by which the nucleotide-encoded message is relayed to the client and how the distinct partners of the assemblies cooperate to (pre)organize partially folded GR during Loading and Maturation. We show how different ligand states determine distinct dynamic profiles for the functional interfaces defining the interactions in the complexes and modulate their overall flexibility to facilitate progress along the chaperone cycle. Finally, we also show that the GR regions engaged by the chaperone machinery display peculiar energetic signatures in the folded state, which enhance the probability of partial unfolding fluctuations. From these results, we propose a model where a dynamic cross-talk emerges between the chaperone dynamics states and remodeling of client-interacting regions. This factor, coupled to the highly dynamic nature of the assemblies and the conformational heterogeneity of their interactions, provides the basis for regulating the functions of distinct assemblies during the chaperoning cycle.

The statistical significance of selected sense-antisense peptide interactions.

Sense and antisense peptides, encoded by sense and corresponding antisense DNA strands, are capable of specific interactions that could be a driving force to mediate protein-protein or protein-peptide binding associations. The complementary residue hypothesis suggests that these interactions are founded upon the sum of pairwise interactions between amino acids encoded by corresponding sense and antisense codons. Despite many successful experimental results obtained with the hypothesis, however, the physicochemical basis for these interactions is poorly understood. We examined the potential of the hypothesis for general identification of protein-protein interaction sites, and the possible role of the hypothesis in determining folding in a broad set of protein structures. In addition, we performed a structural study to investigate the binding of a complementary peptide to IL-1F2. Our results suggest that complementary residue pairs are no more frequent or conserved than average in protein-protein interfaces, and are statistically under-represented amongst contacting residue pairs in folded protein structures. Although our structural results matched experimental observations of binding between the peptide and IL-1F2, complementary residue interactions do not appear to be dominant in the bound structure. Overall, our data do not allow us to conclude that the complementary residue hypothesis accounts for specific sense-antisense peptide interactions.