Structure and function of a ligand-free GPCR-Gαßγ intermediate complex.

Unraveling the signaling roles of intermediate complexes is pivotal for G protein-coupled receptor (GPCR) drug development. Despite hundreds of GPCR-Gαßγ structures, these snapshots primarily capture the fully activated complex. Consequently, the functions of intermediate GPCR-G protein complexes remain elusive. Guided by a conformational landscape visualized via 19F quantitative NMR and molecular dynamics (MD) simulation, we determined the structure of an intermediate GPCR-mini-Gαsßγ complex at 2.8 Å using cryo-EM, by blocking its transition to the fully activated complex. Furthermore, we presented direct evidence that the intermediate complex initiates a rate-limited nucleotide exchange without progressing to the fully activated complex, in which the α-helical domain (AHD) of the Gα is partially open engaged by a second nucleotide. Our MD simulation supported the pose of the AHD domain. These advances bridge a significant gap in our understanding the complexity of GPCR signaling.

Ligand Gaussian Accelerated Molecular Dynamics 3 (LiGaMD3): Improved Calculations of Binding Thermodynamics and Kinetics of Both Small Molecules and Flexible Peptides.

Binding thermodynamics and kinetics play critical roles in drug design. However, it has proven challenging to efficiently predict ligand binding thermodynamics and kinetics of small molecules and flexible peptides using conventional molecular dynamics (cMD), due to limited simulation time scales. Based on our previously developed ligand Gaussian accelerated molecular dynamics (LiGaMD) method, we present a new approach, termed "LiGaMD3″, in which we introduce triple boosts into three individual energy terms that play important roles in small-molecule/peptide dissociation, rebinding, and system conformational changes to improve the sampling efficiency of small-molecule/peptide interactions with target proteins. To validate the performance of LiGaMD3, MDM2 bound by a small molecule (Nutlin 3) and two highly flexible peptides (PMI and P53) were chosen as the model systems. LiGaMD3 could efficiently capture repetitive small-molecule/peptide dissociation and binding events within 2 µs simulations. The predicted binding kinetic constant rates and free energies from LiGaMD3 were in agreement with the available experimental values and previous simulation results. Therefore, LiGaMD3 provides a more general and efficient approach to capture dissociation and binding of both small-molecule ligands and flexible peptides, allowing for accurate prediction of their binding thermodynamics and kinetics.

Spectral CT for preoperative diagnosis of N2 station lymph node metastasis in solid T1 non-small cell lung cancer.

PURPOSE: To evaluate the diagnostic value of spectral CT for the preoperative diagnosis of N2 station lymph nodes metastasis in solid T1 non-small cell lung cancer (NSCLC). METHOD: For this retrospective study, dual-phase contrast agent-enhanced CT was performed in patients with NSCLC from September 2019 to June 2023. Quantitative spectral CT parameters measurements were performed by 2 radiologists independently. Logistic regression analysis and Delong test were performed. RESULTS: 60 NSCLC patients (mean age, 62.85 years ± 8.49, 44men) were evaluated. A total of 121 lymph nodes (38 with metastasis) were enrolled. There was no significant difference in the slope of the spectral Hounsfield unit curve (λHu) on arterial phase (AP) or venous phase (VP) between primary lesions and metastatic lymph nodes (P > 0.05), but significant difference in VP λHu between primary lesions and non-metastatic lymph nodes (P < 0.001). The CT40KeV, λHu, normalized iodine concentration (nIC), normalized effective atomic number (nZeff) measured during both AP and VP were lower in metastatic lymph nodes than in non-metastatic lymph nodes (all P < 0.05). Short-axis diameter (S) of metastatic lymph nodes was higher than non-metastatic lymph nodes (P < 0.001). Area under the curve (AUC) for S performed the highest (0.788) in diagnosing metastatic lymph nodes. When combined with VP λHu, VP nZeff, AUC increased to 0.871. CONCLUSION: Spectral CT is a complementary means for the preoperative diagnosis of N2 station lymph nodes metastasis in solid T1 NSCLC. The combined parameters have higher diagnostic efficiency.

Generation of virtual monoenergetic images at 40 keV of the upper abdomen and image quality evaluation based on generative adversarial networks.

BACKGROUND: Abdominal CT scans are vital for diagnosing abdominal diseases but have limitations in tissue analysis and soft tissue detection. Dual-energy CT (DECT) can improve these issues by offering low keV virtual monoenergetic images (VMI), enhancing lesion detection and tissue characterization. However, its cost limits widespread use. PURPOSE: To develop a model that converts conventional images (CI) into generative virtual monoenergetic images at 40 keV (Gen-VMI40keV) of the upper abdomen CT scan. METHODS: Totally 444 patients who underwent upper abdominal spectral contrast-enhanced CT were enrolled and assigned to the training and validation datasets (7:3). Then, 40-keV portal-vein virtual monoenergetic (VMI40keV) and CI, generated from spectral CT scans, served as target and source images. These images were employed to build and train a CI-VMI40keV model. Indexes such as Mean Absolute Error (MAE), Peak Signal-to-Noise Ratio (PSNR), and Structural Similarity (SSIM) were utilized to determine the best generator mode. An additional 198 cases were divided into three test groups, including Group 1 (58 cases with visible abnormalities), Group 2 (40 cases with hepatocellular carcinoma [HCC]) and Group 3 (100 cases from a publicly available HCC dataset). Both subjective and objective evaluations were performed. Comparisons, correlation analyses and Bland-Altman plot analyses were performed. RESULTS: The 192nd iteration produced the best generator mode (lower MAE and highest PSNR and SSIM). In the Test groups (1 and 2), both VMI40keV and Gen-VMI40keV significantly improved CT values, as well as SNR and CNR, for all organs compared to CI. Significant positive correlations for objective indexes were found between Gen-VMI40keV and VMI40keV in various organs and lesions. Bland-Altman analysis showed that the differences between both imaging types mostly fell within the 95% confidence interval. Pearson's and Spearman's correlation coefficients for objective scores between Gen-VMI40keV and VMI40keV in Groups 1 and 2 ranged from 0.645 to 0.980. In Group 3, Gen-VMI40keV yielded significantly higher CT values for HCC (220.5HU vs. 109.1HU) and liver (220.0HU vs. 112.8HU) compared to CI (p < 0.01). The CNR for HCC/liver was also significantly higher in Gen-VMI40keV (2.0 vs. 1.2) than in CI (p < 0.01). Additionally, Gen-VMI40keV was subjectively evaluated to have a higher image quality compared to CI. CONCLUSION: CI-VMI40keV model can generate Gen-VMI40keV from conventional CT scan, closely resembling VMI40keV.

Impact of the Alberta Stroke Program CT Score subregions on long-term functional outcomes in acute ischemic stroke: Results from two multicenter studies in China.

Background and Objectives: The Alberta Stroke Program CT Score (ASPECTS) is a widely used rating system for assessing infarct extent and location. We aimed to investigate the prognostic value of ASPECTS subregions' involvement in the long-term functional outcomes of acute ischemic stroke (AIS). Materials and Methods: Consecutive patients with AIS and anterior circulation large-vessel stenosis and occlusion between January 2019 and December 2020 were included. The ASPECTS score and subregion involvement for each patient was assessed using posttreatment magnetic resonance diffusion-weighted imaging. Univariate and multivariable regression analyses were conducted to identify subregions related to 3-month poor functional outcome (modified Rankin Scale scores, 3-6) in the reperfusion and medical therapy cohorts, respectively. In addition, prognostic efficiency between the region-based ASPECTS and ASPECTS score methods were compared using receiver operating characteristic curves and DeLong's test. Results: A total of 365 patients (median age, 64 years; 70% men) were included, of whom 169 had poor outcomes. In the reperfusion therapy cohort, multivariable regression analyses revealed that the involvement of the left M4 cortical region in left-hemisphere stroke (adjusted odds ratio [aOR] 5.39, 95% confidence interval [CI] 1.53-19.02) and the involvement of the right M3 cortical region in right-hemisphere stroke (aOR 4.21, 95% CI 1.05-16.78) were independently associated with poor functional outcomes. In the medical therapy cohort, left-hemisphere stroke with left M5 cortical region (aOR 2.87, 95% CI 1.08-7.59) and caudate nucleus (aOR 3.14, 95% CI 1.00-9.85) involved and right-hemisphere stroke with right M3 cortical region (aOR 4.15, 95% CI 1.29-8.18) and internal capsule (aOR 3.94, 95% CI 1.22-12.78) affected were related to the increased risks of poststroke disability. In addition, region-based ASPECTS significantly improved the prognostic efficiency compared with the conventional ASPECTS score method. Conclusion: The involvement of specific ASPECTS subregions depending on the affected hemisphere was associated with worse functional outcomes 3 months after stroke, and the critical subregion distribution varied by clinical management. Therefore, region-based ASPECTS could provide additional value in guiding individual decision making and neurological recovery in patients with AIS.

Understanding the impact of binding free energy and kinetics calculations in modern drug discovery.

INTRODUCTION: For rational drug design, it is crucial to understand the receptor-drug binding processes and mechanisms. A new era for the use of computer simulations in predicting drug-receptor interactions at an atomic level has begun with remarkable advances in supercomputing and methodological breakthroughs. AREAS COVERED: End-point free energy calculation methods such as Molecular Mechanics/Poisson Boltzmann Surface Area (MM/PBSA) or Molecular-Mechanics/Generalized Born Surface Area (MM/GBSA), free energy perturbation (FEP), and thermodynamic integration (TI) are commonly used for binding free energy calculations in drug discovery. In addition, kinetic dissociation and association rate constants (koff and kon) play critical roles in the function of drugs. Nowadays, Molecular Dynamics (MD) and enhanced sampling simulations are increasingly being used in drug discovery. Here, the authors provide a review of the computational techniques used in drug binding free energy and kinetics calculations. EXPERT OPINION: The applications of computational methods in drug discovery and design are expanding, thanks to improved predictions of the binding free energy and kinetic rates of drug molecules. Recent microsecond-timescale enhanced sampling simulations have made it possible to accurately capture repetitive ligand binding and dissociation, facilitating more efficient and accurate calculations of ligand binding free energy and kinetics.

Ligand Gaussian accelerated Molecular Dynamics 3 (LiGaMD3): Improved Calculations of Binding Thermodynamics and Kinetics of Both Small Molecules and Flexible Peptides.

Binding thermodynamics and kinetics play critical roles in drug design. However, it has proven challenging to efficiently predict ligand binding thermodynamics and kinetics of small molecules and flexible peptides using conventional Molecular Dynamics (cMD), due to limited simulation timescales. Based on our previously developed Ligand Gaussian accelerated Molecular Dynamics (LiGaMD) method, we present a new approach, termed "LiGaMD3", in which we introduce triple boosts into three individual energy terms that play important roles in small-molecule/peptide dissociation, rebinding and system conformational changes to improve the sampling efficiency of small-molecule/peptide interactions with target proteins. To validate the performance of LiGaMD3, MDM2 bound by a small molecule (Nutlin 3) and two highly flexible peptides (PMI and P53) were chosen as model systems. LiGaMD3 could efficiently capture repetitive small-molecule/peptide dissociation and binding events within 2 microsecond simulations. The predicted binding kinetic constant rates and free energies from LiGaMD3 agreed with available experimental values and previous simulation results. Therefore, LiGaMD3 provides a more general and efficient approach to capture dissociation and binding of both small-molecule ligand and flexible peptides, allowing for accurate prediction of their binding thermodynamics and kinetics.

Colour-coded collateral and venous outflow patterns in estimating infarct progression and predicting functional independence for stroke patients in late time window.

OBJECTIVES: To investigate whether cerebral collateral and venous outflow (VO) patterns on colour-coded multi-phase computed tomography angiography (mCTA) can estimate ischaemic core growth rate (IGR) and predict 90-day functional independence for patients with late-presenting acute ischaemic stroke (AIS). METHODS: The retrospective analysis included 127 AIS patients with a late time window. All patients underwent baseline mCTA with colour-coded reconstruction and computed tomography perfusion. Both collateral score and VO score on colour-coded mCTA maps were analysed and recorded. The IGR was calculated as ischaemic core volume divided by the time from onset to imaging. A 90-day modified Rankin Scale score of 0-2 was defined as functional independence. Kendall's Tau-b analysis was used for nonparametric correlation analysis. Propensity scores, logistic regressions, and receiver operator characteristic (ROC) curves were applied to construct the prediction model. RESULTS: Moderate correlations were found between collateral delay and IGR (Tau-b = -0.554) and between VO and IGR (Tau-b = -0.501). High collateral score (odds ratio = 3.01) and adequate VO (odds ratio = 4.89) remained independent predictors for 90-day functional independence after adjustment. The joint predictive model, which integrated the VO score and clinical features, demonstrated an area under the ROC curve (AUC) of 0.878. The AUCs of collateral score and VO score were 0.836 and 0.883 for outcome prediction after adjustment. CONCLUSIONS: Cerebral collateral and VO patterns based on colour-coded mCTA can effectively predict infarct progression and 90-day clinical outcomes, even for AIS patients beyond the routine time window. ADVANCES IN KNOWLEDGE: Colour-coded mCTA is a readily understandable post-processing technique for the rapid assessment of collateral circulation and VO status in stroke imaging. A moderate correlation was observed between the characteristics of collateral delay/VO on colour-coded mCTA and IGR in patients with AIS. Both high-quality collateral circulation and "red superficial middle cerebral vein sign" can predict 90-day functional independence even for patients beyond the routine time window.

Structure and function of an intermediate GPCR-Gαßγ complex.

Unraveling the signaling roles of intermediate complexes is pivotal for G protein-coupled receptor (GPCR) drug development. Despite hundreds of GPCR-Gαßγ structures, these snapshots primarily capture the fully activated end-state complex. Consequently, a comprehensive understanding of the conformational transitions during GPCR activation and the roles of intermediate GPCR-G protein complexes in signaling remain elusive. Guided by a conformational landscape profiled by 19 F quantitative NMR ( 19 F-qNMR) and Molecular Dynamics (MD) simulations, we resolved the structure of an unliganded GPCR-G protein intermediate complex by blocking its transition to the fully activated end-state complex. More importantly, we presented direct evidence that the intermediate GPCR-Gαsßγ complex initiates a rate-limited nucleotide exchange without progressing to the fully activated end-state complex, thereby bridging a significant gap in our understanding the complexity of GPCR signaling. Understanding the roles of individual conformational states and their complexes in signaling efficacy and bias will help us to design drugs that discriminately target a disease-related conformation.

Mechanistic insights into ligand dissociation from the SARS-CoV-2 spike glycoprotein.

The COVID-19 pandemic, driven by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spurred an urgent need for effective therapeutic interventions. The spike glycoprotein of the SARS-CoV-2 is crucial for infiltrating host cells, rendering it a key candidate for drug development. By interacting with the human angiotensin-converting enzyme 2 (ACE2) receptor, the spike initiates the infection of SARS-CoV-2. Linoleate is known to bind the spike glycoprotein, subsequently reducing its interaction with ACE2. However, the detailed mechanisms underlying the protein-ligand interaction remain unclear. In this study, we characterized the pathways of ligand dissociation and the conformational changes associated with the spike glycoprotein by using ligand Gaussian accelerated molecular dynamics (LiGaMD). Our simulations resulted in eight complete ligand dissociation trajectories, unveiling two distinct ligand unbinding pathways. The preference between these two pathways depends on the gate distance between two α-helices in the receptor binding domain (RBD) and the position of the N-linked glycan at N343. Our study also highlights the essential contributions of K417, N121 glycan, and N165 glycan in ligand unbinding, which are equally crucial in enhancing spike-ACE2 binding. We suggest that the presence of the ligand influences the motions of these residues and glycans, consequently reducing accessibility for spike-ACE2 binding. These findings enhance our understanding of ligand dissociation from the spike glycoprotein and offer significant implications for drug design strategies in the battle against COVID-19.

Mechanism of Ligand Binding to Theophylline RNA Aptamer.

Studying RNA-ligand interactions and quantifying their binding thermodynamics and kinetics are of particular relevance in the field of drug discovery. Here, we combined biochemical binding assays and accelerated molecular simulations to investigate ligand binding and dissociation in RNA using the theophylline-binding RNA as a model system. All-atom simulations using a Ligand Gaussian accelerated Molecular Dynamics method (LiGaMD) have captured repetitive binding and dissociation of theophylline and caffeine to RNA. Theophylline's binding free energy and kinetic rate constants align with our experimental data, while caffeine's binding affinity is over 10,000 times weaker, and its kinetics could not be determined. LiGaMD simulations allowed us to identify distinct low-energy conformations and multiple ligand binding pathways to RNA. Simulations revealed a "conformational selection" mechanism for ligand binding to the flexible RNA aptamer, which provides important mechanistic insights into ligand binding to the theophylline-binding model. Our findings suggest that compound docking using a structural ensemble of representative RNA conformations would be necessary for structure-based drug design of flexible RNA.

Deep Learning Dynamic Allostery of G-Protein-Coupled Receptors.

G-protein-coupled receptors (GPCRs) make up the largest superfamily of human membrane proteins and represent primary targets of ∼1/3 of currently marketed drugs. Allosteric modulators have emerged as more selective drug candidates compared with orthosteric agonists and antagonists. However, many X-ray and cryo-EM structures of GPCRs resolved so far exhibit negligible differences upon the binding of positive and negative allosteric modulators (PAMs and NAMs). The mechanism of dynamic allosteric modulation in GPCRs remains unclear. In this work, we have systematically mapped dynamic changes in free energy landscapes of GPCRs upon binding of allosteric modulators using the Gaussian accelerated molecular dynamics (GaMD), deep learning (DL), and free energy prOfiling Workflow (GLOW). GaMD simulations were performed for a total of 66 µs on 44 GPCR systems in the presence and absence of the modulator. DL and free energy calculations revealed significantly reduced dynamic fluctuations and conformational space of GPCRs upon modulator binding. While the modulator-free GPCRs often sampled multiple low-energy conformational states, the NAMs and PAMs confined the inactive and active agonist-G-protein-bound GPCRs, respectively, to mostly only one specific conformation for signaling. Such cooperative effects were significantly reduced for binding of the selective modulators to "non-cognate" receptor subtypes. Therefore, GPCR allostery exhibits a dynamic "conformational selection" mechanism. In the absence of available modulator-bound structures as for most current GPCRs, it is critical to use a structural ensemble of representative GPCR conformations rather than a single structure for compound docking ("ensemble docking"), which will potentially improve structure-based design of novel allosteric drugs of GPCRs.

Adjuvant therapy with Jianpi Huayu decoction improves overall and recurrence-free survival after hepatectomy for hepatocellular carcinoma: a retrospective propensity score-matching study.

Hepatocellular carcinoma (HCC) patients experience high rates of recurrence following hepatectomy. Many herbal preparations used in traditional Chinese medicine have been shown to improve the postoperative condition of cancer patients. This retrospective study examined the efficacy and safety of Jianpi Huayu decoction (JPHYD) as adjuvant therapy for HCC following hepatectomy. HCC patients received postoperative management according to Chinese Society of Clinical Oncology recommendations, either alone (Control group) or in addition to daily JPHYD (1 week in hospital and 3 months after release). To reduce selection bias, we performed 1:1 propensity score matching between the Control and JPHYD groups. The main endpoint was recurrence-free survival (RFS), and secondary endpoints included overall survival (OS) and adverse event frequency. A total of 207 patients meeting inclusion criteria were enrolled, 127 in the Control group and 80 in the JPHYD group. Patients were then propensity score-matched, yielding each group of 80. Recurrence-free survival rate was significantly higher in the JPHYD group than in the Control group at 1 year (67.9% vs. 38.1%), 2 years (39.1% vs. 26.2%), and 3 years (31.3% vs. 26.2%) following hepatectomy (HR 0.5666 [95%CI, 0.3655 to 0.8784]; p = 0.0066). Additionally, OS was significantly higher in the JPHYD group than the Control group at 1 year (94.3% vs. 81.9%), 2 years (76.4% vs. 58.8%), and 3 years (66.3% vs. 51.4%) following hepatectomy (HR 0.5199 [95%CI, 0.2849 to 0.9490]; p = 0.027). Adverse events frequencies did not differ between the two groups. In conclusion, JPHYD can safely improve RFS and OS following hepatectomy for HCC.

Structural basis of agonist specificity of α1A-adrenergic receptor.

α1-adrenergic receptors (α1-ARs) play critical roles in the cardiovascular and nervous systems where they regulate blood pressure, cognition, and metabolism. However, the lack of specific agonists for all α1 subtypes has limited our understanding of the physiological roles of different α1-AR subtypes, and led to the stagnancy in agonist-based drug development for these receptors. Here we report cryo-EM structures of α1A-AR in complex with heterotrimeric G-proteins and either the endogenous common agonist epinephrine or the α1A-AR-specific synthetic agonist A61603. These structures provide molecular insights into the mechanisms underlying the discrimination between α1A-AR and α1B-AR by A61603. Guided by the structures and corresponding molecular dynamics simulations, we engineer α1A-AR mutants that are not responsive to A61603, and α1B-AR mutants that can be potently activated by A61603. Together, these findings advance our understanding of the agonist specificity for α1-ARs at the molecular level, opening the possibility of rational design of subtype-specific agonists.

An advanced treatment process for 3-high wastewater discharged from crude oil storage tanks.

The wastewater discharged from crude oil storage tanks (WCOST) contains high concentrations of salt and metal iron ions, and high chemical oxygen demand (COD). It belongs to "3-high" wastewater, which is difficult for purification. In this study, WCOST treatments were comparatively investigated via an advanced pretreatment and the traditional coagulation-microfiltration (CMF) processes. After WCOST was purified through the conventional CMF process, fouling occurred in the microfiltration (MF) membrane, which is rather harmful to the following reverse osmosis (RO) membrane unit, and the effluent featured high COD and UV254 values. The analysis confirmed that the MF fouling was due to the oxidation of ferrous ions, and the high COD and UV254 values were mainly attributable to the organic compounds with small molecular sizes, including aromatic-like and fulvic-like compounds. After the pretreatment of the advanced process consisting of aeration, manganese sand filtration, and activated carbon adsorption in combination with CMF process, the removal efficiencies of organic matter and total iron ions reached 97.3% and 99.8%, respectively. All the water indexes of the effluent, after treatment by the advanced multi-unit process, meet well the corresponding standard. The advanced pretreatment process reported herein displayed a great potential for alleviating the MF membrane fouling and enhanced the lifetime of the RO membrane system in the 3-high WCOST treatment.

Pharmacological hallmarks of allostery at the M4 muscarinic receptor elucidated through structure and dynamics.

Allosteric modulation of G protein-coupled receptors (GPCRs) is a major paradigm in drug discovery. Despite decades of research, a molecular-level understanding of the general principles that govern the myriad pharmacological effects exerted by GPCR allosteric modulators remains limited. The M4 muscarinic acetylcholine receptor (M4 mAChR) is a validated and clinically relevant allosteric drug target for several major psychiatric and cognitive disorders. In this study, we rigorously quantified the affinity, efficacy, and magnitude of modulation of two different positive allosteric modulators, LY2033298 (LY298) and VU0467154 (VU154), combined with the endogenous agonist acetylcholine (ACh) or the high-affinity agonist iperoxo (Ipx), at the human M4 mAChR. By determining the cryo-electron microscopy structures of the M4 mAChR, bound to a cognate Gi1 protein and in complex with ACh, Ipx, LY298-Ipx, and VU154-Ipx, and applying molecular dynamics simulations, we determine key molecular mechanisms underlying allosteric pharmacology. In addition to delineating the contribution of spatially distinct binding sites on observed pharmacology, our findings also revealed a vital role for orthosteric and allosteric ligand-receptor-transducer complex stability, mediated by conformational dynamics between these sites, in the ultimate determination of affinity, efficacy, cooperativity, probe dependence, and species variability. There results provide a holistic framework for further GPCR mechanistic studies and can aid in the discovery and design of future allosteric drugs.

Deep Learning Dynamic Allostery of G-Protein-Coupled Receptors.

G-protein-coupled receptors (GPCRs) are the largest superfamily of human membrane proteins and represent primary targets of ~ 1/3 of currently marketed drugs. Allosteric modulators have emerged as more selective drug candidates compared with orthosteric agonists and antagonists. However, many X-ray and cryo-EM structures of GPCRs resolved so far exhibit negligible differences upon binding of positive and negative allosteric modulators (PAMs and NAMs). Mechanism of dynamic allosteric modulation in GPCRs remains unclear. In this work, we have systematically mapped dynamic changes in free energy landscapes of GPCRs upon binding of allosteric modulators using the Gaussian accelerated molecular dynamics (GaMD), Deep Learning (DL) and free energy prOfiling Workflow (GLOW). A total of 18 available high-resolution experimental structures of allosteric modulator-bound class A and B GPCRs were collected for simulations. A number of 8 computational models were generated to examine selectivity of the modulators by changing their target receptors to different subtypes. All-atom GaMD simulations were performed for a total of 66 µs on 44 GPCR systems in the presence/absence of the modulator. DL and free energy calculations revealed significantly reduced conformational space of GPCRs upon modulator binding. While the modulator-free GPCRs often sampled multiple low-energy conformational states, the NAMs and PAMs confined the inactive and active agonist-G protein-bound GPCRs, respectively, to mostly only one specific conformation for signaling. Such cooperative effects were significantly reduced for binding of the selective modulators to "non-cognate" receptor subtypes in the computational models. Therefore, comprehensive DL of extensive GaMD simulations has revealed a general dynamic mechanism of GPCR allostery, which will greatly facilitate rational design of selective allosteric drugs of GPCRs.

Predicting Biomolecular Binding Kinetics: A Review.

Biomolecular binding kinetics including the association (kon) and dissociation (koff) rates are critical parameters for therapeutic design of small-molecule drugs, peptides, and antibodies. Notably, the drug molecule residence time or dissociation rate has been shown to correlate with their efficacies better than binding affinities. A wide range of modeling approaches including quantitative structure-kinetic relationship models, Molecular Dynamics simulations, enhanced sampling, and Machine Learning has been developed to explore biomolecular binding and dissociation mechanisms and predict binding kinetic rates. Here, we review recent advances in computational modeling of biomolecular binding kinetics, with an outlook for future improvements.

GPMeta: a GPU-accelerated method for ultrarapid pathogen identification from metagenomic sequences.

Metagenomic sequencing (mNGS) is a powerful diagnostic tool to detect causative pathogens in clinical microbiological testing owing to its unbiasedness and substantially reduced costs. Rapid and accurate classification of metagenomic sequences is a critical procedure for pathogen identification in dry-lab step of mNGS test. However, clinical practices of the testing technology are hampered by the challenge of classifying sequences within a clinically relevant timeframe. Here, we present GPMeta, a novel GPU-accelerated approach to ultrarapid pathogen identification from complex mNGS data, allowing users to bypass this limitation. Using mock microbial community datasets and public real metagenomic sequencing datasets from clinical samples, we show that GPMeta has not only higher accuracy but also significantly higher speed than existing state-of-the-art tools such as Bowtie2, Bwa, Kraken2 and Centrifuge. Furthermore, GPMeta offers GPMetaC clustering algorithm, a statistical model for clustering and rescoring ambiguous alignments to improve the discrimination of highly homologous sequences from microbial genomes with average nucleotide identity >95%. GPMetaC exhibits higher precision and recall rate than others. GPMeta underlines its key role in the development of the mNGS test in infectious diseases that require rapid turnaround times. Further study will discern how to best and easily integrate GPMeta into routine clinical practices. GPMeta is freely accessible to non-commercial users at https://github.com/Bgi-LUSH/GPMeta.

Hepatectomy versus transcatheter arterial chemoembolization for resectable BCLC stage A/B hepatocellular carcinoma beyond Milan criteria: A randomized clinical trial.

Background: Hepatectomy is the recommended option for radical treatment of BCLC stage A/B hepatocellular carcinoma (HCC) that has progressed beyond the Milan criteria. This study evaluated the efficacy and safety of preoperative neoadjuvant transcatheter arterial chemoembolization (TACE) for these patients. Methods: In this prospective, randomized, open-label clinical study, BCLC stage A/B HCC patients beyond the Milan criteria were randomly assigned (1:1) to receive either neoadjuvant TACE prior to hepatectomy (NT group) or hepatectomy alone (OP group). The primary outcome was overall survival (OS), while the secondary outcomes were progression-free survival (PFS) and adverse events (AEs). Results: Of 249 patients screened, 164 meeting the inclusion criteria were randomly assigned to either the NT group (n = 82) or OP group (n = 82) and completed follow-up requirements. Overall survival was significantly greater in the NT group compared to the OP group at 1 year (97.2% vs. 82.4%), two years (88.4% vs. 60.4%), and three years (71.6% vs. 45.7%) (p = 0.0011) post-treatment. Similarly, PFS was significantly longer in the NT group than the OP group at 1 year (60.1% vs. 39.9%), 2 years (53.4% vs. 24.5%), and 3 years (42.2% vs. 24.5%) (p = 0.0003). No patients reported adverse events of grade 3 or above in either group. Conclusions: Neoadjuvant TACE prolongs the survival of BCLC stage A/B HCC patients beyond the Milan criteria without increasing severe adverse events frequency. Clinical trial registration: https://www.chictr.org.cn/, identifier ChiCTR2200055618.