Diagnosis of acute aortic syndromes with ultrasound and d-dimer: the PROFUNDUS study.

BACKGROUND: In patients complaining common symptoms such as chest/abdominal/back pain or syncope, acute aortic syndromes (AAS) are rare underlying causes. AAS diagnosis requires urgent advanced aortic imaging (AAI), mostly computed tomography angiography. However, patient selection for AAI poses conflicting risks of misdiagnosis and overtesting. OBJECTIVES: We assessed the safety and efficiency of a diagnostic protocol integrating clinical data with point-of-care ultrasound (POCUS) and d-dimer (single/age-adjusted cutoff), to select patients for AAI. METHODS: This prospective study involved 12 Emergency Departments from 5 countries. POCUS findings were integrated with a guideline-compliant clinical score, to define the integrated pre-test probability (iPTP) of AAS. If iPTP was high, urgent AAI was requested. If iPTP was low and d-dimer was negative, AAS was ruled out. Patients were followed for 30 days, to adjudicate outcomes. RESULTS: Within 1979 enrolled patients, 176 (9 %) had an AAS. POCUS led to net reclassification improvement of 20 % (24 %/-4 % for events/non-events, P < 0.001) over clinical score alone. Median time to AAS diagnosis was 60 min if POCUS was positive vs 118 if negative (P = 0.042). Within 941 patients satisfying rule-out criteria, the 30-day incidence of AAS was 0 % (95 % CI, 0-0.41 %); without POCUS, 2 AAS were potentially missed. Protocol rule-out efficiency was 48 % (95 % CI, 46-50 %) and AAI was averted in 41 % of patients. Using age-adjusted d-dimer, rule-out efficiency was 54 % (difference 6 %, 95 % CI, 4-9 %, vs standard cutoff). CONCLUSIONS: The integrated algorithm allowed rapid triage of high-probability patients, while providing safe and efficient rule-out of AAS. Age-adjusted d-dimer maximized efficiency. CLINICAL TRIAL REGISTRATION: Clinicaltrials.gov, NCT04430400.

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.

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.

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.

Unveiling the role of PUS7-mediated pseudouridylation in host protein interactions specific for the SARS-CoV-2 RNA genome.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a positive single-stranded RNA virus, engages in complex interactions with host cell proteins throughout its life cycle. While these interactions enable the host to recognize and inhibit viral replication, they also facilitate essential viral processes such as transcription, translation, and replication. Many aspects of these virus-host interactions remain poorly understood. Here, we employed the catRAPID algorithm and utilized the RNA-protein interaction detection coupled with mass spectrometry technology to predict and validate the host proteins that specifically bind to the highly structured 5' and 3' terminal regions of the SARS-CoV-2 RNA. Among the interactions identified, we prioritized pseudouridine synthase PUS7, which binds to both ends of the viral RNA. Using nanopore direct RNA sequencing, we discovered that the viral RNA undergoes extensive post-transcriptional modifications. Modified consensus regions for PUS7 were identified at both terminal regions of the SARS-CoV-2 RNA, including one in the viral transcription regulatory sequence leader. Collectively, our findings offer insights into host protein interactions with the SARS-CoV-2 UTRs and highlight the likely significance of pseudouridine synthases and other post-transcriptional modifications in the viral life cycle. This new knowledge enhances our understanding of virus-host dynamics and could inform the development of targeted therapeutic strategies.

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.

How aberrant N-glycosylation can alter protein functionality and ligand binding: An atomistic view.

Protein-assembly defects due to an enrichment of aberrant conformational protein variants are emerging as a new frontier in therapeutics design. Understanding the structural elements that rewire the conformational dynamics of proteins and pathologically perturb functionally oriented ensembles is important for inhibitor development. Chaperones are hub proteins for the assembly of multiprotein complexes and an enrichment of aberrant conformers can affect the cellular proteome, and in turn, phenotypes. Here, we integrate computational and experimental tools to investigte how N-glycosylation of specific residues in glucose-regulated protein 94 (GRP94) modulates internal dynamics and alters the conformational fitness of regions fundamental for the interaction with ATP and synthetic ligands and impacts substructures important for the recognition of interacting proteins. N-glycosylation plays an active role in modulating the energy landscape of GRP94, and we provide support for leveraging the knowledge on distinct glycosylation variants to design molecules targeting GRP94 disease-associated conformational states and assemblies.

PhosY-secretome profiling combined with kinase-substrate interaction screening defines active c-Src-driven extracellular signaling.

c-Src tyrosine kinase is a renowned key intracellular signaling molecule and a potential target for cancer therapy. Secreted c-Src is a recent observation, but how it contributes to extracellular phosphorylation remains elusive. Using a series of domain deletion mutants, we show that the N-proximal region of c-Src is essential for its secretion. The tissue inhibitor of metalloproteinases 2 (TIMP2) is an extracellular substrate of c-Src. Limited proteolysis-coupled mass spectrometry and mutagenesis studies verify that the Src homology 3 (SH3) domain of c-Src and the P31VHP34 motif of TIMP2 are critical for their interaction. Comparative phosphoproteomic analyses identify an enrichment of PxxP motifs in phosY-containing secretomes from c-Src-expressing cells with cancer-promoting roles. Inhibition of extracellular c-Src using custom SH3-targeting antibodies disrupt kinase-substrate complexes and inhibit cancer cell proliferation. These findings point toward an intricate role for c-Src in generating phosphosecretomes, which will likely influence cell-cell communication, particularly in c-Src-overexpressing cancers.

Pre-Test Probability Assessment and d-Dimer Based Evaluation in Patients with Previous Acute Aortic Syndrome.

Background and Objectives. Acute aortic syndromes (AASs) are emergencies burdened by high morbidity and mortality. Guideline-recommended diagnostic workup is based on pre-test probability assessment (PPA) and d-dimer testing. However, the performance of PPA and d-dimer has never been studied in individuals with previous AAS (pAAS), which represent a challenging population. Materials and Methods. We analyzed a registry of patients with pAAS evaluated in two Emergency Departments (EDs) for suspected novel AAS (nAAS). Enrolment criteria were history of pAAS and the presence of truncal pain, syncope or perfusion deficit. All patients underwent advanced imaging. Clinical data were registered prospectively and PPA was performed by applying the aortic dissection detection (ADD) and an aorta simplified (AORTAs) score. Results. A total of 128 patients were enrolled, including 77 patients with previous Stanford type A aortic dissection and 45 patients with previous Stanford type B aortic dissection. The final diagnosis was nAAS in 40 (31%) patients. Clinical variables associated with nAAS were: aortic valve disease, thoracic aortic aneurysm, severe pain, sudden pain, ripping/tearing pain and hypotension/shock. ADD score ≥ 2 had a sensitivity of 65% and a specificity of 83% for nAAS; AORTAs score ≥ 2 had a sensitivity of 48% and a specificity of 88%. d-dimer (cutoff ≥ 500 ng/mL or age-adjusted cutoff) had a sensitivity of 97% and a specificity of 13%/14.7%, for diagnosis of nAAS. Patients that were candidates for guideline-compliant PPA/d-dimer integrated rule-out were: 5 (4.9%) with ADD ≤ 1/d-dimer and 8 (7.8%) with AORTAs ≤ 1/d-dimer < age-adjusted cutoff. None of them had a nAAS. Conclusions. Patients with pAAS evaluated in the ED for red-flag symptoms showed intermediate-to-high pre-test probability of nAAS. The ADD score had lower sensitivity and specificity than in unselected patients. d-dimer, alone and integrated with PPA, was highly sensitive for nAAS, but very unspecific. PPA/d-dimer integrated strategies are unlikely to significantly reduce the number of patients with pAAS undergoing advanced imaging.

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.

Acute aortic syndromes: An internist's guide to the galaxy.

Acute aortic syndromes (AASs) are severe conditions defined by dissection, hemorrhage, ulceration or rupture of the thoracic aorta. AASs share etiological and pathophysiological features, including long-term aortic tissue degeneration and mechanisms of acute aortic damage. The clinical signs and symptoms of AASs are unspecific and heterogeneous, requiring large differential diagnosis. When evaluating a patient with AAS-compatible symptoms, physicians need to integrate clinical probability assessment, bedside imaging techniques such as point-of-care ultrasound, and blood test results such as d-dimer. The natural history of AASs is dominated by engagement of ischemic, coagulative and inflammatory pathways at large, causing multiorgan damage. Medical treatment, multiorgan monitoring and outcome prognostication are therefore paramount, with internal medicine playing a key role in non-surgical management of AASs.

A Human Stem Cell-Derived Neurosensory-Epithelial Circuitry on a Chip to Model Herpes Simplex Virus Reactivation.

Both emerging viruses and well-known viral pathogens endowed with neurotropism can either directly impair neuronal functions or induce physio-pathological changes by diffusing from the periphery through neurosensory-epithelial connections. However, developing a reliable and reproducible in vitro system modeling the connectivity between the different human sensory neurons and peripheral tissues is still a challenge and precludes the deepest comprehension of viral latency and reactivation at the cellular and molecular levels. This study shows a stable topographic neurosensory-epithelial connection on a chip using human stem cell-derived dorsal root ganglia (DRG) organoids. Bulk and single-cell transcriptomics showed that different combinations of key receptors for herpes simplex virus 1 (HSV-1) are expressed by each sensory neuronal cell type. This neuronal-epithelial circuitry enabled a detailed analysis of HSV infectivity, faithfully modeling its dynamics and cell type specificity. The reconstitution of an organized connectivity between human sensory neurons and keratinocytes into microfluidic chips provides a powerful in vitro platform for modeling viral latency and reactivation of human viral pathogens.

Studying the Dynamics of a Complex G-Quadruplex System: Insights into the Comparison of MD and NMR Data.

Molecular dynamics (MD) simulations are coming of age in the study of nucleic acids, including specific tertiary structures such as G-quadruplexes. While being precious for providing structural and dynamic information inaccessible to experiments at the atomistic level of resolution, MD simulations in this field may still be limited by several factors. These include the force fields used, different models for ion parameters, ionic strengths, and water models. We address various aspects of this problem by analyzing and comparing microsecond-long atomistic simulations of the G-quadruplex structure formed by the human immunodeficiency virus long terminal repeat (HIV LTR)-III sequence for which nuclear magnetic resonance (NMR) structures are available. The system is studied in different conditions, systematically varying the ionic strengths, ion numbers, and water models. We comparatively analyze the dynamic behavior of the G-quadruplex motif in various conditions and assess the ability of each simulation to satisfy the nuclear magnetic resonance (NMR)-derived experimental constraints and structural parameters. The conditions taking into account K+-ions to neutralize the system charge, mimicking the intracellular ionic strength, and using the four-atom water model are found to be the best in reproducing the experimental NMR constraints and data. Our analysis also reveals that in all of the simulated environments residues belonging to the duplex moiety of HIV LTR-III exhibit the highest flexibility.

Sites of vulnerability in HCV E1E2 identified by comprehensive functional screening.

The E1 and E2 envelope proteins of hepatitis C virus (HCV) form a heterodimer that drives virus-host membrane fusion. Here, we analyze the role of each amino acid in E1E2 function, expressing 545 individual alanine mutants of E1E2 in human cells, incorporating them into infectious viral pseudoparticles, and testing them against 37 different monoclonal antibodies (MAbs) to ascertain full-length translation, folding, heterodimer assembly, CD81 binding, viral pseudoparticle incorporation, and infectivity. We propose a model describing the role of each critical residue in E1E2 functionality and use it to examine how MAbs neutralize infection by exploiting functionally critical sites of vulnerability on E1E2. Our results suggest that E1E2 is a surprisingly fragile protein complex where even a single alanine mutation at 92% of positions disrupts its function. The amino-acid-level targets identified are highly conserved and functionally critical and can be exploited for improved therapies and vaccines.

Nanopore ReCappable sequencing maps SARS-CoV-2 5' capping sites and provides new insights into the structure of sgRNAs.

The SARS-CoV-2 virus has a complex transcriptome characterised by multiple, nested subgenomic RNAsused to express structural and accessory proteins. Long-read sequencing technologies such as nanopore direct RNA sequencing can recover full-length transcripts, greatly simplifying the assembly of structurally complex RNAs. However, these techniques do not detect the 5' cap, thus preventing reliable identification and quantification of full-length, coding transcript models. Here we used Nanopore ReCappable Sequencing (NRCeq), a new technique that can identify capped full-length RNAs, to assemble a complete annotation of SARS-CoV-2 sgRNAs and annotate the location of capping sites across the viral genome. We obtained robust estimates of sgRNA expression across cell lines and viral isolates and identified novel canonical and non-canonical sgRNAs, including one that uses a previously un-annotated leader-to-body junction site. The data generated in this work constitute a useful resource for the scientific community and provide important insights into the mechanisms that regulate the transcription of SARS-CoV-2 sgRNAs.

Protein Allostery and Ligand Design: Computational Design Meets Experiments to Discover Novel Chemical Probes.

Herein we examine the determinants of the allosteric inhibition of the mitochondrial chaperone TRAP1 by a small molecule ligand. The knowledge generated is harnessed into the design of novel derivatives with interesting biological properties. TRAP1 is a member of the Hsp90 family of proteins, which work through sequential steps of ATP processing coupled to client-protein remodeling. Isoform selective inhibition of TRAP1 can provide novel information on the biomolecular mechanisms of molecular chaperones, as well as new insights into the development of small molecules with therapeutic potential. Our analysis of the interactions between an active first-generation allosteric ligand and TRAP1 shows how the small molecule induces long-range perturbations that influence the attainment of reactive poses in the active site. At the same time, the dynamic adaptation of the allosteric binding pocket to the presence of the first-generation compound sets the stage for the design of a set of second-generation ligands: the characterization of the formation/disappearance of pockets around the allosteric site that is used to guide optimize the ligands' fit for the allosteric site and improve inhibitory activities. The effects of the newly designed molecules are validated experimentally in vitro and in vivo. We discuss the implications of our approach as a promising strategy towards understanding the molecular determinants of allosteric regulation in chemical and molecular biology, and towards speeding up the design of allosteric small molecule modulators.

AlphaFold predicted structure of the Hsp90-like domains of the neurodegeneration linked protein sacsin reveals key residues for ATPase activity.

The ataxia-linked protein sacsin has three regions of partial homology to Hsp90's N-terminal ATP binding domain. Although a crystal structure for this Hsp90-like domain has been reported the precise molecular interactions required for ATP-binding and hydrolysis are unclear and it is debatable whether ATP biding is compatible with these domains. Furthermore, the Identification of a sacsin domain(s) equivalent to the middle domain of Hsp90 has been elusive. Here we present the superimposition of an AlphaFold structure of sacsin with yeast Hsp90, which provides novel insights into sacsin's structure. We identify residues within the sacsin Hsp90-like domains that are required for ATP binding and hydrolysis, including the putative catalytic arginine residues equivalent to that of the Hsp90 middle domain. Importantly, our analysis allows comparison of the Hsp90 middle domain with corresponding sacsin regions and identifies a shorter lid segment, in the sacsin ATP-binding domains, than the one found in the N-terminal domain of Hsp90. Our results show how a realignment of residues in the lid segment of sacsin that are involved in ATP binding can better match equivalent residues seen in Hsp90, which we then corroborated using molecular dynamic simulations. We speculate, from a structural viewpoint, why some ATP competitive inhibitors of Hsp90 may not bind sacsin, while others would. Together our analysis supports the hypothesis that sacsin's function is ATP-driven and would be consistent with it having a role as a super molecular chaperone. We propose that the SR1 regions of sacsin be renamed as HSP-NRD (Hsp90 N-Terminal Repeat Domain; residues 84-324) and the fragment immediately after as HSP-MRD (Hsp90 Middle Repeat Domain; residues 325-518).

New perspectives in cancer drug development: computational advances with an eye to design.

Computational chemistry has come of age in drug discovery. Indeed, most pharmaceutical development programs rely on computer-based data and results at some point. Herein, we discuss recent applications of advanced simulation techniques to difficult challenges in drug discovery. These entail the characterization of allosteric mechanisms and the identification of allosteric sites or cryptic pockets determined by protein motions, which are not immediately evident in the experimental structure of the target; the study of ligand binding mechanisms and their kinetic profiles; and the evaluation of drug-target affinities. We analyze different approaches to tackle challenging and emerging biological targets. Finally, we discuss the possible perspectives of future application of computation in drug discovery.

The tumor suppressor folliculin inhibits lactate dehydrogenase A and regulates the Warburg effect.

Aerobic glycolysis in cancer cells, also known as the 'Warburg effect', is driven by hyperactivity of lactate dehydrogenase A (LDHA). LDHA is thought to be a substrate-regulated enzyme, but it is unclear whether a dedicated intracellular protein also regulates its activity. Here, we identify the human tumor suppressor folliculin (FLCN) as a binding partner and uncompetitive inhibitor of LDHA. A flexible loop within the amino terminus of FLCN controls movement of the LDHA active-site loop, tightly regulating its enzyme activity and, consequently, metabolic homeostasis in normal cells. Cancer cells that experience the Warburg effect show FLCN dissociation from LDHA. Treatment of these cells with a decapeptide derived from the FLCN loop region causes cell death. Our data suggest that the glycolytic shift of cancer cells is the result of FLCN inactivation or dissociation from LDHA. Together, FLCN-mediated inhibition of LDHA provides a new paradigm for the regulation of glycolysis.