Evaluation of clinical and imaging features for differentiating rhabdomyosarcoma from neuroblastoma in pediatric soft tissue.

Background: In this study, we developed a nomogram predictive model based on clinical, CT, and MRI parameters to differentiate soft tissue rhabdomyosarcoma (RMS) from neuroblastoma (NB) in children preoperatively. Materials and methods: A total of 103 children with RMS (n=37) and NB (n=66) were enrolled in the study from December 2012 to July 2023. The clinical and imaging data (assessed by two experienced radiologists) were analyzed using univariate analysis, and significant factors were further analyzed by multivariable logistic regression using the forward LR method to develop the clinical model, radiological model, and integrated nomogram model, respectively. The diagnostic performances, goodness of fit, and clinical utility of the integrated nomogram model were assessed using the area under the curve (AUC) of the receiver operator characteristics curve (ROC) with a 95% confidence interval (95% CI), calibration curve, and decision curve analysis (DCA) curves, respectively. Diagnostic efficacy between the model and radiologists' interpretations was examined. Results: The median age at diagnosis in the RMS group was significantly older than the NB group (36.0 months vs. 14.5 months; P=0.003); the fever rates in RMS patients were significantly lower than in patients with NB (0.0% vs.16.7%; P=0.022), and the incidence of palpable mass was higher in patients with RMS compared with the NB patients (89.2% vs. 34.8%; P<0.001). Compare NB on image features: RMS occurred more frequently in the head and neck and displayed homogeneous density on non-enhanced CT than NB (48.6% vs. 9.1%; 35.3% vs. 13.8%, respectively; all P<0.05), and the occurrence of characteristics such as calcification, encasing vessels, and intraspinal tumor extension was significantly less frequent in RMS children compared to children with NB (18.9% vs. 84.8%; 13.5% vs. 34.8%; 2.7% vs. 50.0%, respectively; all P <0.05). Two, three, and four features were identified as independent parameters by multivariate logistic regression analysis to develop the clinical, radiological, and integrated nomogram models, respectively. The AUC value (0.962), calibration curve, and DCA showed that the integrated nomogram model may provide better diagnostic performance, good agreement, and greater clinical net benefits than the clinical model, radiological model, and radiologists' subjective diagnosis. Conclusion: The clinical and imaging features-based nomogram has potential for helping radiologists distinguish between pediatric soft tissue RMS and NB patients preoperatively, and reduce unnecessary interventions.

Performance and Analysis of the Alchemical Transfer Method for Binding-Free-Energy Predictions of Diverse Ligands.

The Alchemical Transfer Method (ATM) is herein validated against the relative binding-free energies (RBFEs) of a diverse set of protein-ligand complexes. We employed a streamlined setup workflow, a bespoke force field, and AToM-OpenMM software to compute the RBFEs of the benchmark set prepared by Schindler and collaborators at Merck KGaA. This benchmark set includes examples of standard small R-group ligand modifications as well as more challenging scenarios, such as large R-group changes, scaffold hopping, formal charge changes, and charge-shifting transformations. The novel coordinate perturbation scheme and a dual-topology approach of ATM address some of the challenges of single-topology alchemical RBFE methods. Specifically, ATM eliminates the need for splitting electrostatic and Lennard-Jones interactions, atom mapping, defining ligand regions, and postcorrections for charge-changing perturbations. Thus, ATM is simpler and more broadly applicable than conventional alchemical methods, especially for scaffold-hopping and charge-changing transformations. Here, we performed well over 500 RBFE calculations for eight protein targets and found that ATM achieves accuracy comparable to that of existing state-of-the-art methods, albeit with larger statistical fluctuations. We discuss insights into the specific strengths and weaknesses of the ATM method that will inform future deployments. This study confirms that ATM can be applied as a production tool for RBFE predictions across a wide range of perturbation types within a unified, open-source framework.

Taming multiple binding poses in alchemical binding free energy prediction: the ß-cyclodextrin host-guest SAMPL9 blinded challenge.

We apply the Alchemical Transfer Method (ATM) and a bespoke fixed partial charge force field to the SAMPL9 bCD host-guest binding free energy prediction challenge that comprises a combination of complexes formed between five phenothiazine guests and two cyclodextrin hosts. Multiple chemical forms, competing binding poses, and computational modeling challenges pose significant obstacles to obtaining reliable computational predictions for these systems. The phenothiazine guests exist in solution as racemic mixtures of enantiomers related by nitrogen inversions that bind the hosts in various binding poses, each requiring an individual free energy analysis. Due to the large size of the guests and the conformational reorganization of the hosts, which prevent a direct absolute binding free energy route, binding free energies are obtained by a series of absolute and relative binding alchemical steps for each chemical species in each binding pose. Metadynamics-accelerated conformational sampling was found to be necessary to address the poor convergence of some numerical estimates affected by conformational trapping. Despite these challenges, our blinded predictions quantitatively reproduced the experimental affinities for the ß-cyclodextrin host and, to a lesser extent, those with a methylated derivative. The work illustrates the challenges of obtaining reliable free energy data in in silico drug design for even seemingly simple systems and introduces some of the technologies available to tackle them.

CT and MR imaging features of soft tissue rhabdoid tumor: compared with rhabdomyosarcoma in children.

Objective: To assess the computed tomography (CT) and magnetic resonance (MR) imaging characteristics of soft tissue rhabdoid tumors (RT) and compare them with those of rhabdomyosarcoma (RMS). Methods: We conducted a retrospective analysis of 49 pediatric patients from 2011 to 2022, comprising 16 patients with soft tissue RT and 33 patients with RMS who underwent CT or MRI scans. Key imaging features, as well as clinical and pathological data, were compared between the two groups. The multivariate logistic regression analysis was used to determine independent differential factors for distinguishing soft tissue RT from RMS, and the model was established. The final prediction model was visualized by nomograms and verified internally by using a bootstrapped resample 1,000 times. The diagnostic accuracy of the combined model was assessed in terms of discrimination, calibration, and clinical utility. Results: Age, sex, number of lesions, and primary locations were similar in both groups. The imaging characteristics, including margin, calcification, surrounding blood vessels, and rim enhancement, were associated with the two groups of soft tissue tumors, as determined by univariate analysis (all p < 0.05). On multivariate logistic regression analysis, the presence of unclear margin (p-value, adjusted odds ratio [95% confidence interval]: 0.03, 7.96 [1.23, 51.67]) and calcification (0.012, 30.37 [2.09, 440.70]) were independent differential factors for predicting soft tissue RT over RMS. The presence of rim enhancement (0.007, 0.05 [0.01, 0.43]) was an independent differential factor for predicting RMS over soft tissue RT. The comprehensive model established by logistic regression analysis showed an AUC of 0.872 with 81.8% specificity and 81.3% sensitivity. The decision curve analysis (DCA) curve displayed that the model achieved a better net clinical benefit. Conclusion: Our study revealed that the image features of calcification, indistinct margins, and a lack of rim enhancement on CT and MRI might be reliable to distinguish soft tissue RT from RMS.

Molecular Latent Space Simulators for Distributed and Multimolecular Trajectories.

All atom molecular dynamics (MD) simulations offer a powerful tool for molecular modeling, but the short time steps required for numerical stability of the integrator place many interesting molecular events out of reach of unbiased simulations. The popular and powerful Markov state modeling (MSM) approach can extend these time scales by stitching together multiple short discontinuous trajectories into a single long-time kinetic model but necessitates a configurational coarse-graining of the phase space that entails a loss of spatial and temporal resolution and an exponential increase in complexity for multimolecular systems. Latent space simulators (LSS) present an alternative formalism that employs a dynamical, as opposed to configurational, coarse graining comprising three back-to-back learning problems to (i) identify the molecular system's slowest dynamical processes, (ii) propagate the microscopic system dynamics within this slow subspace, and (iii) generatively reconstruct the trajectory of the system within the molecular phase space. A trained LSS model can generate temporally and spatially continuous synthetic molecular trajectories at orders of magnitude lower cost than MD to improve sampling of rare transition events and metastable states to reduce statistical uncertainties in thermodynamic and kinetic observables. In this work, we extend the LSS formalism to short discontinuous training trajectories generated by distributed computing and to multimolecular systems without incurring exponential scaling in computational cost. First, we develop a distributed LSS model over thousands of short simulations of a 264-residue proteolysis-targeting chimera (PROTAC) complex to generate ultralong continuous trajectories that identify metastable states and collective variables to inform PROTAC therapeutic design and optimization. Second, we develop a multimolecular LSS architecture to generate physically realistic ultralong trajectories of DNA oligomers that can undergo both duplex hybridization and hairpin folding. These trajectories retain thermodynamic and kinetic characteristics of the training data while providing increased precision of folding populations and time scales across simulation temperature and ion concentration.

Modeling the Effect of Cooperativity in Ternary Complex Formation and Targeted Protein Degradation Mediated by Heterobifunctional Degraders.

Chemically induced proximity between certain endogenous enzymes and a protein of interest (POI) inside cells may cause post-translational modifications to the POI with biological consequences and potential therapeutic effects. Heterobifunctional (HBF) molecules that bind with one functional part to a target POI and with the other to an E3 ligase induce the formation of a target-HBF-E3 ternary complex, which can lead to ubiquitination and proteasomal degradation of the POI. Targeted protein degradation (TPD) by HBFs offers a promising approach to modulate disease-associated proteins, especially those that are intractable using other therapeutic approaches, such as enzymatic inhibition. The three-way interactions among the HBF, the target POI, and the ligase-including the protein-protein interaction between the POI and the ligase-contribute to the stability of the ternary complex, manifested as positive or negative binding cooperativity in its formation. How such cooperativity affects HBF-mediated degradation is an open question. In this work, we develop a pharmacodynamic model that describes the kinetics of the key reactions in the TPD process, and we use this model to investigate the role of cooperativity in the ternary complex formation and in the target POI degradation. Our model establishes the quantitative connection between the ternary complex stability and the degradation efficiency through the former's effect on the rate of catalytic turnover. We also develop a statistical inference model for determining cooperativity in intracellular ternary complex formation from cellular assay data and demonstrate it by quantifying the change in cooperativity due to site-directed mutagenesis at the POI-ligase interface of the SMARCA2-ACBI1-VHL ternary complex. Our pharmacodynamic model provides a quantitative framework to dissect the complex HBF-mediated TPD process and may inform the rational design of effective HBF degraders.

The slow but steady rise of binding free energy calculations in drug discovery.

Binding free energy calculations are increasingly used in drug discovery research to predict protein-ligand binding affinities and to prioritize candidate drug molecules accordingly. It has taken decades of collective effort to transform this academic concept into a technology adopted by the pharmaceutical and biotech industry. Having personally witnessed and taken part in this transformation, here I recount the (incomplete) list of problems that had to be solved to make this computational tool practical and suggest areas of future development.

Predicting the structural basis of targeted protein degradation by integrating molecular dynamics simulations with structural mass spectrometry.

Targeted protein degradation (TPD) is a promising approach in drug discovery for degrading proteins implicated in diseases. A key step in this process is the formation of a ternary complex where a heterobifunctional molecule induces proximity of an E3 ligase to a protein of interest (POI), thus facilitating ubiquitin transfer to the POI. In this work, we characterize 3 steps in the TPD process. (1) We simulate the ternary complex formation of SMARCA2 bromodomain and VHL E3 ligase by combining hydrogen-deuterium exchange mass spectrometry with weighted ensemble molecular dynamics (MD). (2) We characterize the conformational heterogeneity of the ternary complex using Hamiltonian replica exchange simulations and small-angle X-ray scattering. (3) We assess the ubiquitination of the POI in the context of the full Cullin-RING Ligase, confirming experimental ubiquitinomics results. Differences in degradation efficiency can be explained by the proximity of lysine residues on the POI relative to ubiquitin.

Twisted Gaussian Schell-model breathers and solitons in strongly nonlocal nonlinear media.

Based on the Snyder-Mitchell linear model and the cross-spectral density (CSD) function, the analytical propagation formula of twisted Gaussian Schell-model (TGSM) beams in strongly nonlocal nonlinear medium (SNNM) is derived. Then the propagation characteristics of TGSM beam are studied. It is found that the soliton radius is jointly determined by the initial power, coherence length, and twist factor; the degree of spatial coherence is adjusted by changing the twist factor without affecting the soliton intensity. In the case of non-soliton properties, there is a threshold of coherence length which makes partially coherent beams have the same evolution law as completely coherent beams. Furthermore, increasing the twist factor, decreasing the coherence length and initial power can improve the beam quality of the beam propagating in SNNM.

Superimposed Hermite-Gaussian-correlated Schell-model beam with multiple off-axis vortices.

We first introduce a class of a superimposed Hermite-Gaussian-correlated Schell model with a multiple off-axis vortices beam, with the side lobe of the beam carrying one to four vortex singularities at the source plane. Subsequently, the variation laws of this beam after being focused by a thin lens are studied theoretically to obtain the optimal beam parameters. The numerical simulation results show that the beam possesses a unique multiple vortex structure, phase structure, and orbital angular momentum. Its intensity resembles a spiral staircase rotating around the axes. The rotational symmetry property of the transverse energy flow along the z axis was broken by the vortices. The hot spot position can be adjusted flexibly by changing the off-axis distance of vortices. This study is of great significance for nondestructive capture and manipulation of multiple particles or cells.

Whole-volume ADC histogram of the brain as an image biomarker in evaluating disease severity of neonatal hypoxic-ischemic encephalopathy.

Purpose: To examine the diagnostic significance of the apparent diffusion coefficient (ADC) histogram in quantifying neonatal hypoxic ischemic encephalopathy (HIE). Methods: An analysis was conducted on the MRI data of 90 HIE patients, 49 in the moderate-to-severe group, and the other in the mild group. The 3D Slicer software was adopted to delineate the whole brain region as the region of interest, and 22 ADC histogram parameters were obtained. The interobserver consistency of the two radiologists was assessed by the interclass correlation coefficient (ICC). The difference in parameters (ICC > 0.80) between the two groups was compared by performing the independent sample t-test or the Mann-Whitney U test. In addition, an investigation was conducted on the correlation between parameters and the neonatal behavioral neurological assessment (NBNA) score. The ROC curve was adopted to assess the efficacy of the respective significant parameters. Furthermore, the binary logistic regression was employed to screen out the independent risk factors for determining the severity of HIE. Results: The ADCmean, ADCmin, ADCmax,10th-70th, 90th percentile of ADC values of the moderate-to-severe group were smaller than those of the mild group, while the group's variance, skewness, kurtosis, heterogeneity, and mode-value were higher than those of the mild group (P < 0.05). All the mentioned parameters, the ADCmean, ADCmin, and 10th-70th and 90th percentile of ADC displayed positive correlations with the NBNA score, mode-value and ADCmax displayed no correlations with the NBNA score, the rest showed negative correlations with the NBNA score (P < 0.05). The area under the curve (AUC) of variance was the largest (AUC = 0.977; cut-off 972.5, sensitivity 95.1%; specificity 87.8%). According to the logistic regression analysis, skewness, kurtosis, variance, and heterogeneity were independent risk factors for determining the severity of HIE (OR > 1, P < 0.05). Conclusions: The ADC histogram contributes to the HIE diagnosis and is capable of indicating the diffusion information of the brain objectively and quantitatively. It refers to a vital method for assessing the severity of HIE.

Characterizing Receptor Flexibility to Predict Mutations That Lead to Human Adaptation of Influenza Hemagglutinin.

A key step in the emergence of human pandemic influenza strains has been a switch in binding preference of the viral glycoprotein hemagglutinin (HA) from avian to human sialic acid (SA) receptors. The conformation of the bound SA varies substantially with HA sequence, and crystallographic evidence suggests that the bound SA is flexible, making it difficult to predict which mutations are responsible for changing HA-binding preference. We performed molecular dynamics (MD) simulations of SA analogues binding to various HAs and observed a dynamic equilibrium among structurally diverse receptor conformations, including conformations that have not been experimentally observed. Using one such novel conformation, we predicted─and experimentally confirmed─a set of mutations that substantially increased an HA's affinity for a human SA analogue. This prediction could not have been inferred from the existing crystal structures, suggesting that MD-generated HA-SA conformational ensembles could help researchers predict human-adaptive mutations, aiding surveillance of emerging pandemic threats.

Non-Equilibrium Protein Folding and Activation by ATP-Driven Chaperones.

Recent experimental studies suggest that ATP-driven molecular chaperones can stabilize protein substrates in their native structures out of thermal equilibrium. The mechanism of such non-equilibrium protein folding is an open question. Based on available structural and biochemical evidence, I propose here a unifying principle that underlies the conversion of chemical energy from ATP hydrolysis to the conformational free energy associated with protein folding and activation. I demonstrate that non-equilibrium folding requires the chaperones to break at least one of four symmetry conditions. The Hsp70 and Hsp90 chaperones each break a different subset of these symmetries and thus they use different mechanisms for non-equilibrium protein folding. I derive an upper bound on the non-equilibrium elevation of the native concentration, which implies that non-equilibrium folding only occurs in slow-folding proteins that adopt an unstable intermediate conformation in binding to ATP-driven chaperones. Contrary to the long-held view of Anfinsen's hypothesis that proteins fold to their conformational free energy minima, my results predict that some proteins may fold into thermodynamically unstable native structures with the assistance of ATP-driven chaperones, and that the native structures of some chaperone-dependent proteins may be shaped by their chaperone-mediated folding pathways.

IL-31 expression in HIV-infected patients with different routes of disease transmission.

ABSTRACT: Acquired immunodeficiency syndrome (AIDS) is caused by the human immunodeficiency virus (HIV). AIDS is characterized by an impaired immune system and low cellular immunity. The main manifestation of AIDS is a reduction in the number of CD4+ T cells and alteration in cytokine concentration. The present work aimed to explore the expression of IL-31 in HIV infection and disease progression.Serum samples were collected from HIV-infected patients with different routes of disease transmission. The subjects included 24 patients who were infected with HIV upon blood transmission and 36 patients who had acquired the disease through sexual transmission (21 cases of homosexual transmission and 15 cases of heterosexual transmission). In addition, 20 normal healthy individuals were included to serve as the control group. The levels of IL-31 in the collected serum samples were estimated using the human IL-31 Platinum ELISA kit.The serum analysis results revealed that the concentration of IL-31 in the serum samples for the blood transmission, sexually transmission, and normal group patients was 4.07 ±â€Š1.63 pg/L, 7.43 ±â€Š1.15 pg/L, and 2.87 ±â€Š1.04 pg/L, respectively. The statistical analysis revealed that the concentration of IL-31 in HIV-1 infection was higher than that in the normal control. In addition, the expression of IL-31 was significantly higher in the sexual transmission group compared to the blood transmission group (P < .05).IL-31 could have an important role in HIV infection, although the role of IL-31 in disease progression in HIV-infected individuals requires further research.

Evolution properties of twisted Hermite Gaussian Schell-model beams in non-Kolmogorov turbulence.

A general form of twisted Hermite Gaussian Schell-model (THGSM) beams is introduced; analytical expressionsare obtained for cross-spectral density and M2-factor using the extended Huygens-Fresnel principle and Wigner function. The evolution of THGSM beams during propagation in non-Kolmogorov turbulence is shown numerically; the beams exhibit self-splitting and twist into two lobes. The intensity distribution evolves into a Gaussian shape and beam quality worsens with increasing distance; the intensity distribution and M2-factor are determined by the twist factor, beam orders, and other beam parameters. THGSM beams provide more degrees of freedom to regulate beam parameters, thereby enriching the types of partially coherent beams.

Precise Binding Free Energy Calculations for Multiple Molecules Using an Optimal Measurement Network of Pairwise Differences.

Alchemical binding free energy (BFE) calculations offer an efficient and thermodynamically rigorous approach to in silico binding affinity predictions. As a result of decades of methodological improvements and recent advances in computer technology, alchemical BFE calculations are now widely used in drug discovery research. They help guide the prioritization of candidate drug molecules by predicting their binding affinities for a biomolecular target of interest (and potentially selectivity against undesirable antitargets). Statistical variance associated with such calculations, however, may undermine the reliability of their predictions, introducing uncertainty both in ranking candidate molecules and in benchmarking their predictive accuracy. Here, we present a computational method that substantially improves the statistical precision in BFE calculations for a set of ligands binding to a common receptor by dynamically allocating computational resources to different BFE calculations according to an optimality objective established in a previous work from our group and extended in this work. Our method, termed Network Binding Free Energy (NetBFE), performs adaptive BFE calculations in iterations, re-optimizing the allocations in each iteration based on the statistical variances estimated from previous iterations. Using examples of NetBFE calculations for protein binding of congeneric ligand series, we demonstrate that NetBFE approaches the optimal allocation in a small number (≤5) of iterations and that NetBFE reduces the statistical variance in the BFE estimates by approximately a factor of 2 when compared to a previously published and widely used allocation method at the same total computational cost.

Linc8986 and linc0597 in plasma are novel biomarkers for systemic lupus erythematosus.

Despite increasing evidence that large intergenic non-coding RNAs (lincRNAs) are widely involved in human disease, the role of lincRNAs in the development of systemic lupus erythematosus (SLE) has remained largely elusive. The purpose of the present study was to investigate the expression of three lincRNAs (linc0597, linc8986 and linc7190) in the plasma of patients with SLE and their potential use as biomarkers for the diagnosis and treatment of SLE. Plasma samples were obtained from 54 patients with SLE, 24 patients with rheumatoid arthritis (RA), 24 patients with Sjogren's syndrome (SS) and 22 healthy controls. LincRNA expression levels were measured by reverse transcription-quantitative PCR. Compared with those in the healthy controls, the plasma levels of linc0597 and linc8986 were significantly increased in the patients with SLE (P<0.001), while the difference in the level of linc7190 was not significant (P=0.052). In addition, there was no significant difference in the levels of linc0597 and linc8986 among patients with RA, patients with SS and the healthy controls (P>0.05). Compared with patients with SLE without lupus nephritis (LN), the levels of linc0597 were significantly higher in patients with LN (P=0.044). For linc7190 and linc8986, there was no significant difference between patients with and without LN (P>0.05). Furthermore, complement component 3 (C3) levels were used to evaluate whether the expression of linc8986 and linc0597 is related to the activity of SLE. The results indicated that the levels of linc8986 and linc0597 were negatively correlated with the level of C3 (P<0.001 and P=0.004, respectively). Further analysis suggested that linc0597 and linc8986 were able to specifically identify patients with SLE and that a combination of linc0597 and linc8986 may improve the diagnostic accuracy. Therefore, the plasma levels of linc0597 and linc8986 may be suitable biomarkers for diagnosing SLE.

The genotype analysis of the hepatitis C virus in Heilongjiang Province, China.

ABSTRACT: Introduction: Hepatitis C virus (HCV) infection is a major public health issue. HCV genotype identification is clinically important to tailor the dosage and duration of treatment, and recombination in intra-patient populations of HCV may lead to the generation of escape mutants, as previously observed for other RNA viruses. Up to now, there is no study assessing HCV genotypes and subtypes in Heilongjiang Province, China.Methods: To determine genotype and phylogenetic analysis of HCV in Heilongjiang Province is crucial. In this study, we amplified 3 genome regions (5'UTR, E1, and NS5B) of 30 HCV patients in Heilongjiang Province, amplified products were analyzed by bioinformatics.Results: We found that 23 specimens had concordant subtypes in the 3 gene regions (2a and 1b), 7 HCV patients were considered the recombinants, the recombination pattern of the 7 HCV patients in the 5'UTR, E1, and NS5B region as followed: 1b/2a/1b, 2a/2a/1b, 1b/2a/2a, 1b/2a/1b, 1b/2a/1b, 1b/2a/1b, 2a/2a/1b.Conclusions: The findings in the present study showed that a higher recombination rate (23%) than other researches, and the recombination of 2a/1b in the 5'UTR, E1, and NS5B region was only found in the present study up to now.

Shaping the focal intensity distribution using a partially coherent radially polarized beam with multiple off-axis vortices.

A new kind of partially coherent vector vortex beam, namely, the partially coherent radially polarized (PCRP) beam with multiple off-axis vortices, is introduced, and the average intensity distributions of such vortex beam focused by a thin lens are investigated theoretically. It is novelty that the off-axis vortices will induce the focal intensity redistribution and reconstruction, while this remarkable characteristic will be vanished in the case of a very low coherence. In view of this distinctive feature, a new method has been put forward to shape or modulate the focal intensity distribution by elaborately tailoring the multiple off-axis vortices as well as the coherence length. More importantly, some peculiar focal fields with novel structures, such as bar-shaped, triangle-shaped, square-shaped, and pentagon-shaped hollow profiles or flat-top foci, are obtained. Our results indicate that modulating the multiple off-axis vortices provides an additional degree of freedom for focus shaping.

ATP-Driven Nonequilibrium Activation of Kinase Clients by the Molecular Chaperone Hsp90.

The molecular chaperone 90-kDa heat-shock protein (Hsp90) assists the late-stage folding and activation of diverse types of protein substrates (called clients), including many kinases. Previous studies have established that the Hsp90 homodimer undergoes an ATP-driven cycle through open and closed conformations. Here, I propose a model of client activation by Hsp90 that predicts that this cycle enables Hsp90 to use ATP energy to drive a client out of thermodynamic equilibrium toward its active conformation. My model assumes that an Hsp90-bound client can transition between a deactivating conformation and an activating conformation. It suggests that the cochaperone Cdc37 aids Hsp90 to activate kinase clients by differentiating between these two intermediate conformations. My model makes experimentally testable predictions, including how modulating the stepwise kinetics of the Hsp90 cycle-for example, by various cochaperones-affects the activation of different clients. My model may inform client-specific and cell-type-specific therapeutic intervention of Hsp90-mediated protein activation.