Integrating Molecular Dynamics and Machine Learning Algorithms to Predict the Functional Profile of Kinase Ligands.

The modulation of protein function via designed small molecules is providing new opportunities in chemical biology and medicinal chemistry. While drugs have traditionally been developed to block enzymatic activities through active site occupation, a growing number of strategies now aim to control protein functions in an allosteric fashion, allowing for the tuning of a target's activation or deactivation via the modulation of the populations of conformational ensembles that underlie its function. In the context of the discovery of new active leads, it would be very useful to generate hypotheses for the functional impact of new ligands. Since the discovery and design of allosteric modulators (inhibitors/activators) is still a challenging and often serendipitous target, the development of a rapid and robust approach to predict the functional profile of a new ligand would significantly speed up candidate selection. Herein, we present different machine learning (ML) classifiers to distinguish between potential orthosteric and allosteric binders. Our approach integrates information on the chemical fingerprints of the ligands with descriptors that recapitulate ligand effects on protein functional motions. The latter are derived from molecular dynamics (MD) simulations of the target protein in complex with orthosteric or allosteric ligands. In this framework, we train and test different ML architectures, which are initially probed on the classification of orthosteric versus allosteric ligands for cyclin-dependent kinases (CDKs). The results demonstrate that different ML methods can successfully partition allosteric versus orthosteric effectors (although to different degrees). Next, we further test the models with FDA-approved CDK drugs, not included in the original dataset, as well as ligands that target other kinases, to test the range of applicability of these models outside of the domain on which they were developed. Overall, the results show that enriching the training dataset with chemical physics-based information on the protein-ligand dynamic cross-talk can significantly expand the reach and applicability of approaches for the prediction and classification of the mode of action of small molecules.

Phosphorylation-driven epichaperome assembly is a regulator of cellular adaptability and proliferation.

The intricate network of protein-chaperone interactions is crucial for maintaining cellular function. Recent discoveries have unveiled the existence of specialized chaperone assemblies, known as epichaperomes, which serve as scaffolding platforms that orchestrate the reconfiguration of protein-protein interaction networks, thereby enhancing cellular adaptability and proliferation. This study explores the structural and regulatory aspects of epichaperomes, with a particular focus on the role of post-translational modifications (PTMs) in their formation and function. A key finding is the identification of specific PTMs on HSP90, particularly at residues Ser226 and Ser255 within an intrinsically disordered region, as critical determinants of epichaperome assembly. Our data demonstrate that phosphorylation of these serine residues enhances HSP90's interactions with other chaperones and co-chaperones, creating a microenvironment conducive to epichaperome formation. Moreover, we establish a direct link between epichaperome function and cellular physiology, particularly in contexts where robust proliferation and adaptive behavior are essential, such as in cancer and pluripotent stem cell maintenance. These findings not only provide mechanistic insights but also hold promise for the development of novel therapeutic strategies targeting chaperone assemblies in diseases characterized by epichaperome dysregulation, thereby bridging the gap between fundamental research and precision medicine.

High-throughput peptide array analysis and computational techniques for serological profiling of flavivirus infections: Implications for diagnostics and vaccine development.

Arthropod-borne viruses, such as dengue virus (DENV), pose significant global health threats, with DENV alone infecting around 400 million people annually and causing outbreaks beyond endemic regions. This study aimed to enhance serological diagnosis and discover new drugs by identifying immunogenic protein regions of DENV. Utilizing a comprehensive approach, the study focused on peptides capable of distinguishing DENV from other flavivirus infections through serological analyses. Over 200 patients with confirmed arbovirus infection were profiled using high-density pan flavivirus peptide arrays comprising 6253 peptides and the computational method matrix of local coupling energy (MLCE). Twenty-four peptides from nonstructural and structural viral proteins were identified as specifically recognized by individuals with DENV infection. Six peptides were confirmed to distinguish DENV from Zika virus (ZIKV), West Nile virus (WNV), Yellow Fever virus (YFV), Usutu virus (USUV), and Chikungunya virus (CHIKV) infections, as well as healthy controls. Moreover, the combination of two immunogenic peptides emerged as a potential serum biomarker for DENV infection. These peptides, mapping to highly accessible regions on protein structures, show promise for diagnostic and prophylactic strategies against flavivirus infections. The described methodology holds broader applicability in the serodiagnosis of infectious diseases.

Cracking the chaperone code through the computational microscope.

The heat shock protein 90 kDa (Hsp90) chaperone machinery plays a crucial role in maintaining cellular homeostasis. Beyond its traditional role in protein folding, Hsp90 is integral to key pathways influencing cellular function in health and disease. Hsp90 operates through the modular assembly of large multiprotein complexes, with their composition, stability, and localization adapting to the cell's needs. Its functional dynamics are finely tuned by ligand binding and post-translational modifications (PTMs). Here, we discuss how to disentangle the intricacies of the complex code that governs the crosstalk between dynamics, binding, PTMs, and the functions of the Hsp90 machinery using computer-based approaches. Specifically, we outline the contributions of computational and theoretical methods to the understanding of Hsp90 functions, ranging from providing atomic-level insights into its dynamics to clarifying the mechanisms of interactions with protein clients, cochaperones, and ligands. The knowledge generated in this framework can be actionable for the design and development of chemical tools and drugs targeting Hsp90 in specific disease-associated cellular contexts. Finally, we provide our perspective on how computation can be integrated into the study of the fine-tuning of functions in the highly complex Hsp90 landscape, complementing experimental methods for a comprehensive understanding of this important chaperone system.

Clinical and Economic Impact of Early Diagnosis of Chronic Kidney Disease in General Practice: The Endorse Study.

Introduction: The underdiagnosis of chronic kidney disease (CKD) remains a significant public health concern. The Early chroNic kiDney disease pOint of caRe Screening (ENDORSE) project aimed to evaluate the clinical and economic implications of a targeted training intervention for general practitioners (GPs) to enhance CKD awareness and early diagnosis. Methods: Data on estimated Glomerular Filtration Rate (eGFR) and Urinary Albumin-Creatinine Ratio (uACR) were collected by 53 Italian GPs from 112,178 patients at baseline and after six months. The intervention involved six months of hybrid training provided by 11 nephrologists, which included formal lectures, instant messaging support, and joint visits for complex cases. Results: The results demonstrated a substantial increase in the use of eGFR (+44.7%) and uACR (+95.2%) tests. This led to a 128.9% rise in the number of individuals screened for CKD using the KDIGO classification, resulting in a 62% increase in CKD diagnoses. The intervention's impact was particularly notable in high-risk groups, including patients with type 2 diabetes, hypertension, and heart failure. Discussion: A budget impact analysis projected cumulative five-year savings of €1.7 million for the study cohort. When these findings were extrapolated to the entire Italian CKD population, potential savings were estimated at €106.6 million, highlighting significant cost savings for the national health service. The clinical simulation assumed that early diagnosed CKD patients would be treated according to current indications for dapagliflozin, which slows disease progression. Conclusion: The ENDORSE model demonstrated that targeted training for GPs can significantly improve early CKD detection, leading to better patient outcomes and considerable economic benefits. This approach shows promise for broader implementation to address the underdiagnosis of CKD on a national and potentially international scale.

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.

N-Glycosylation-Induced Pathologic Protein Conformations as a Tool to Guide the Selection of Biologically Active Small Molecules.

Post-translational modifications such as protein N-glycosylation, significantly influence cellular processes. Dysregulated N-glycosylation, exemplified in Grp94, a member of the Hsp90 family, leads to structural changes and the formation of epichaperomes, contributing to pathologies. Targeting N-glycosylation-induced conformations offers opportunities for developing selective chemical tools and drugs for these pathologic forms of chaperones. We here demonstrate how a specific Grp94 conformation induced by N-glycosylation, identified previously via molecular dynamics simulations, rationalizes the distinct behavior of similar ligands. Integrating dynamic ligand unbinding information with SAR development, we differentiate ligands productively engaging the pathologic Grp94 conformers from those that are not. Additionally, analyzing binding site stereoelectronic properties and QSAR models using cytotoxicity data unveils relationships between chemical, conformational properties, and biological activities. These findings facilitate the design of ligands targeting specific Grp94 conformations induced by abnormal glycosylation, selectively disrupting pathogenic protein networks while sparing normal mechanisms.

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.

Conformational Dynamics, Energetics, and the Divergent Evolution of Allosteric Regulation: The Case of the Yeast MAPK Family.

Allosteric mechanisms provide finely-tuned control over signalling proteins. Proteins of the same family may share high sequence identity and structural similarity but show distinct traits of allosteric control and evolutionary divergent regulation. Revealing the determinants of such properties may be important to understand the molecular bases of different regulatory pathways. Herein, we investigate whether and how evolutionarily-divergent traits of allosteric regulation in homologous proteins can be decoded in terms of internal dynamics and interaction networks that support functionally oriented conformations. In this framework, we start from the comparative analysis of the dynamics and energetics of the yeast MAP Kinases (MAPKs) Fus3 and Kss1 in their native basins. Importantly, distinctive dynamic and energetic stabilization features emerge, which can be related to the two proteins' differential ability to be phosphorylated and engage with the allosteric activator Ste5. We then expanded our study to other evolutionarily-related MAPKs. We show that the dynamical and energetical traits defining the distinct regulatory profiles of Fus3 and Kss1 can be traced along their evolutionary tree. Overall, our approach is able to reconnect (latent) allostery with the principal elements of protein structural stabilization and dynamics, showing how allosteric regulation was encrypted in MAPKs structure well before Ste5 appearance.

Phosphorylation-Driven Epichaperome Assembly: A Critical Regulator of Cellular Adaptability and Proliferation.

The intricate protein-chaperone network is vital for cellular function. Recent discoveries have unveiled the existence of specialized chaperone complexes called epichaperomes, protein assemblies orchestrating the reconfiguration of protein-protein interaction networks, enhancing cellular adaptability and proliferation. This study delves into the structural and regulatory aspects of epichaperomes, with a particular emphasis on the significance of post-translational modifications in shaping their formation and function. A central finding of this investigation is the identification of specific PTMs on HSP90, particularly at residues Ser226 and Ser255 situated within an intrinsically disordered region, as critical determinants in epichaperome assembly. Our data demonstrate that the phosphorylation of these serine residues enhances HSP90's interaction with other chaperones and co-chaperones, creating a microenvironment conducive to epichaperome formation. Furthermore, this study establishes a direct link between epichaperome function and cellular physiology, especially in contexts where robust proliferation and adaptive behavior are essential, such as cancer and stem cell maintenance. These findings not only provide mechanistic insights but also hold promise for the development of novel therapeutic strategies targeting chaperone complexes in diseases characterized by epichaperome dysregulation, bridging the gap between fundamental research and precision medicine.

Cost-Utility Analysis Comparing Pegcetacoplan to Anti-C5 Monoclonal Antibodies in the Treatment of Paroxysmal Nocturnal Hemoglobinuria.

Background: Paroxysmal nocturnal hemoglobinuria is a rare, acquired disease characterized by hemolytic episodes and associated with significant clinical burden. The introduction of C5 inhibitory monoclonal antibodies (C5i) represented a major breakthrough in PNH treatment, effectively reducing intravascular hemolysis (IVH) but showing limited impact on extravascular hemolysis (EVH). In 2021, the C3 inhibitor pegcetacoplan was approved by EMA and recently reimbursed in Italy, which also has the advantages in the reduction of both IVH and EVH, increasing hemoglobin values and simultaneously improving the quality of life and fatigue of patients. A cost-utility analysis was developed to compare pegcetacoplan to C5i (eculizumab and ravulizumab) in the PNH population who remain anemic after treatment with C5i for at least 3 months. Materials and Methods: The analysis employed a Markov model with a 5-year time horizon whereby patients can transition among 3 PNH health states, adopting the perspective of the Italian NHS. Efficacy data were sourced from the PEGASUS study, with drug prices reflecting ex-factory costs. Additionally, costs associated with resource utilization, adverse events, and complications were estimated based on outpatient and hospital care rates, excluding indirect expenses. Utility and disutility values related to transfusions were also considered, with pegcetacoplan allowing for dose escalation. Results: The cumulative cost of treatment per individual patient at 5 years was estimated to be €1,483,454 for pegcetacoplan, €1,585,763 for eculizumab, and €1,574,826 for ravulizumab. Pegcetacoplan demonstrated a superior increase in quality-adjusted life years (QALYs) compared to both eculizumab (0.51 increase) and ravulizumab (0.27 increase). Furthermore, pegcetacoplan showed a reduction in complication management costs (€22,891 less compared to eculizumab and €22,611 less compared to ravulizumab) and lower transfusion-related expenses (€14,147 less than both C5i treatments). Conclusion: Pegcetacoplan emerged as the dominant strategy in this analysis, being more effective, less expensive and improves quality of life in the analyzed population affected by PNH.

N-Glycosylation as a Modulator of Protein Conformation and Assembly in Disease.

Glycosylation, a prevalent post-translational modification, plays a pivotal role in regulating intricate cellular processes by covalently attaching glycans to macromolecules. Dysregulated glycosylation is linked to a spectrum of diseases, encompassing cancer, neurodegenerative disorders, congenital disorders, infections, and inflammation. This review delves into the intricate interplay between glycosylation and protein conformation, with a specific focus on the profound impact of N-glycans on the selection of distinct protein conformations characterized by distinct interactomes-namely, protein assemblies-under normal and pathological conditions across various diseases. We begin by examining the spike protein of the SARS virus, illustrating how N-glycans regulate the infectivity of pathogenic agents. Subsequently, we utilize the prion protein and the chaperone glucose-regulated protein 94 as examples, exploring instances where N-glycosylation transforms physiological protein structures into disease-associated forms. Unraveling these connections provides valuable insights into potential therapeutic avenues and a deeper comprehension of the molecular intricacies that underlie disease conditions. This exploration of glycosylation's influence on protein conformation effectively bridges the gap between the glycome and disease, offering a comprehensive perspective on the therapeutic implications of targeting conformational mutants and their pathologic assemblies in various diseases. The goal is to unravel the nuances of these post-translational modifications, shedding light on how they contribute to the intricate interplay between protein conformation, assembly, and disease.

[Economic evaluation of a fixed-dose combination (acetylsalicylic acid and rosuvastatin) in the cardiovascular context]. / Valutazione farmacoeconomica di una combinazione a dose fissa (acido acetilsalicilico e rosuvastatina) in ambito cardiovascolare.

BACKGROUND: Cardiovascular diseases pose a significant challenge to the society and healthcare systems, with serious implications in terms of mortality and healthcare expenditure. The treatment of cardiovascular diseases, based on acetylsalicylic acid combined with statins in multi-pill regimens, is characterized by a lower adherence rate among patients compared to the single-pill combination. A potential solution lies in single-pill formulations, drugs that combine two or more active ingredients at a fixed dosage within the same dosage unit. METHODS: In order to assess the potential pharmacoeconomic impact of single-pill treatment, a budget impact model (BIM) was developed, considering the combination of 100 mg acetylsalicylic acid and 5 mg, 10 mg, or 20 mg rosuvastatin. RESULTS: The use of the single pill, according to the selected scenario, could result in savings in Italy compared to the use of multi-pill at 100%, ranging from € 951 201 in the case of using both single and multi-pill at 50%, to € 1 902 402 in the case of using the single pill exclusively. Sensitivity analysis confirmed the robustness of the results. CONCLUSIONS: The developed BIM allows observing the potential savings that single-pill treatment could generate, linked both to an increase in adherence rates and the consequent improvement in clinical outcomes for patients, as well as the lower cost of medications. The use of single pills represents a promising solution to enhance patient adherence and reduce costs in the management of cardiovascular diseases in Italy.

How to recognize pulmonary embolism in syncope patients: A simple rule.

BACKGROUND: Syncope can be the presenting symptom of Pulmonary Embolism (PE). It is not known wether using a standardized algorithm to rule-out PE in all patients with syncope admitted to the Emergency Departments (ED) is of value or can lead to overdiagnosis and overtreatment. METHODS: We tested if simple anamnestic and clinical parameters could be used as a rule to identify patients with syncope and PE in a multicenter observational study. The rule's sensitivity was tested on a cohort of patients that presented to the ED for syncopal episodes caused by PE. The clinical impact of the rule was assessed on a population of consecutive patients admitted for syncope in the ED. RESULTS: Patients were considered rule-positive in the presence of any of the following: hypotension, tachycardia, peripheral oxygen saturation ≤ 93 % (SpO2), chest pain, dyspnea, recent history of prolonged bed rest, clinical signs of deep vein thrombosis, history of previous venous thrombo-embolism and active neoplastic disease. The sensitivity of the rule was 90.3 % (95 % CI: 74.3 % to 98.0 %). The application of the rule to a population of 217 patients with syncope would have led to a 70 % reduction in the number of subjects needing additional diagnostic tests to exclude PE. CONCLUSIONS: Most patients with syncope due to PE present with anamnestic and clinical features indicative of PE diagnosis. A clinical decision rule can be used to identify patients who would benefit from further diagnostic tests to exclude PE, while reducing unnecessary exams that could lead to over-testing and over-diagnosis.

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.