nCoVDock2: a docking server to predict the binding modes between COVID-19 targets and its potential ligands.

The rapid emergence of SARS-CoV-2 variants with multi-sites mutations is considered as a major obstacle for the development of drugs and vaccines. Although most of the functional proteins essential for SARS-CoV-2 have been determined, the understanding of the COVID-19 target-ligand interactions remains a key challenge. The old version of this COVID-19 docking server was built in 2020, and free and open to all users. Here, we present nCoVDock2, a new docking server to predict the binding modes for targets from SARS-CoV-2. First, the new server supports more targets. We replaced the modeled structures with newly resolved structures and added more potential targets of COVID-19, especially for the variants. Second, for small molecule docking, Autodock Vina was upgraded to the latest version 1.2.0, and a new scoring function was added for peptide or antibody docking. Third, the input interface and molecular visualization were updated for a better user experience. The web server, together with an extensive help and tutorial, are freely available at: https://ncovdock2.schanglab.org.cn.

Machine Learning Radiomics Liver Function Model for Prognostic Prediction After Radical Resection of Advanced Gastric Cancer: A Retrospective Study.

PURPOSE: We aimed to establish a machine learning radiomics liver function model to explore how liver function affects the prognosis of patients with gastric cancer (GC). METHODS: Patients with advanced GC were retrospectively enrolled in this study. Eight machine learning radiomic models were constructed by extracting radiomic features from portal-vein-phase contrast-enhanced computed tomography (CE-CT) images. Clinicopathological features were determined using univariate and multifactorial Cox regression analyses. These features were used to construct a GC survival nomogram. RESULTS: A total of 510 patients with GC were split into training and test cohorts in an 8:2 ratio. Kaplan-Meier analysis showed that patients with type I liver function had a better prognosis. Fifteen significant features were retained to establish the machine learning model. LightBGM showed the best predictive performance in the training (area under the receiver operating characteristic curve [AUC] 0.978) and test cohorts (AUC 0.714). Multivariate analysis revealed that gender, age, liver function, Nutritional Risk Screening 2002 (NRS-2002) score, tumor-lymph node-metastasis stage, tumor size, and tumor differentiation were independent risk factors for GC prognosis. The survival nomogram based on machine learning radiomics, instead of liver biochemical indicators, still had high accuracy (C-index of 0.771 vs. 0.773). CONCLUSION: The machine learning radiomics liver function model has high diagnostic value in predicting the influence of liver function on prognosis in patients with GC.

CoDock-Ligand: combined template-based docking and CNN-based scoring in ligand binding prediction.

For ligand binding prediction, it is crucial for molecular docking programs to integrate template-based modeling with a precise scoring function. Here, we proposed the CoDock-Ligand docking method that combines template-based modeling and the GNINA scoring function, a Convolutional Neural Network-based scoring function, for the ligand binding prediction in CASP15. Among the 21 targets, we obtained successful predictions in top 5 submissions for 14 targets and partially successful predictions for 4 targets. In particular, for the most complicated target, H1114, which contains 56 metal cofactors and small molecules, our docking method successfully predicted the binding of most ligands. Analysis of the failed systems showed that the predicted receptor protein presented conformational changes in the backbone and side chains of the binding site residues, which may cause large structural deviations in the ligand binding prediction. In summary, our hybrid docking scheme was efficiently adapted to the ligand binding prediction challenges in CASP15.

Impact of AlphaFold on structure prediction of protein complexes: The CASP15-CAPRI experiment.

We present the results for CAPRI Round 54, the 5th joint CASP-CAPRI protein assembly prediction challenge. The Round offered 37 targets, including 14 homodimers, 3 homo-trimers, 13 heterodimers including 3 antibody-antigen complexes, and 7 large assemblies. On average ~70 CASP and CAPRI predictor groups, including more than 20 automatics servers, submitted models for each target. A total of 21 941 models submitted by these groups and by 15 CAPRI scorer groups were evaluated using the CAPRI model quality measures and the DockQ score consolidating these measures. The prediction performance was quantified by a weighted score based on the number of models of acceptable quality or higher submitted by each group among their five best models. Results show substantial progress achieved across a significant fraction of the 60+ participating groups. High-quality models were produced for about 40% of the targets compared to 8% two years earlier. This remarkable improvement is due to the wide use of the AlphaFold2 and AlphaFold2-Multimer software and the confidence metrics they provide. Notably, expanded sampling of candidate solutions by manipulating these deep learning inference engines, enriching multiple sequence alignments, or integration of advanced modeling tools, enabled top performing groups to exceed the performance of a standard AlphaFold2-Multimer version used as a yard stick. This notwithstanding, performance remained poor for complexes with antibodies and nanobodies, where evolutionary relationships between the binding partners are lacking, and for complexes featuring conformational flexibility, clearly indicating that the prediction of protein complexes remains a challenging problem.

Prediction of protein assemblies, the next frontier: The CASP14-CAPRI experiment.

We present the results for CAPRI Round 50, the fourth joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of twelve targets, including six dimers, three trimers, and three higher-order oligomers. Four of these were easy targets, for which good structural templates were available either for the full assembly, or for the main interfaces (of the higher-order oligomers). Eight were difficult targets for which only distantly related templates were found for the individual subunits. Twenty-five CAPRI groups including eight automatic servers submitted ~1250 models per target. Twenty groups including six servers participated in the CAPRI scoring challenge submitted ~190 models per target. The accuracy of the predicted models was evaluated using the classical CAPRI criteria. The prediction performance was measured by a weighted scoring scheme that takes into account the number of models of acceptable quality or higher submitted by each group as part of their five top-ranking models. Compared to the previous CASP-CAPRI challenge, top performing groups submitted such models for a larger fraction (70-75%) of the targets in this Round, but fewer of these models were of high accuracy. Scorer groups achieved stronger performance with more groups submitting correct models for 70-80% of the targets or achieving high accuracy predictions. Servers performed less well in general, except for the MDOCKPP and LZERD servers, who performed on par with human groups. In addition to these results, major advances in methodology are discussed, providing an informative overview of where the prediction of protein assemblies currently stands.

Mutant breeding of Starmerella bombicola by atmospheric and room-temperature plasma (ARTP) for improved production of specific or total sophorolipids.

To enhance specific or total sophorolipids (SLs) production by Starmerella bombicola for specific application, mutant library consisting of 106 mutants from 7 batches was constructed via atmospheric and room-temperature plasma (ARTP). When compared to the wild strain, 11, 36 and 12 mutants performed increases over 30% in lactonic, acidic or total SLs production. Genetic stability investigation showed that 8, 7, and 4 mutants could maintain the improved SLs production capacity. Mutants of A6-9 and A2-8 were selected out for enhanced specific SLs and total SLs production in fed-batch cultivation in flask. Without optimization, A6-9 obtained the highest reported lactonic SLs production of 51.95 g/l and A2-8 performed comparable acidic and total SLs production of 68.75 g/l and 100.33 g/l with all the reported stains. The structural composition of the obtained SLs was analyzed by HPLC and LC/MS, and the results confirmed the enhancement of SLs and certain SL components. These mutants would be important in industrial applications because the production and purification costs of SLs could be greatly reduced. Besides, the acquisition of these mutants also provided materials for the investigation of regulation mechanism of SLs biosynthesis for further genetic engineering of S. bombicola. Furthermore, critical micelle concentration (CMC), minimum surface tension (STmin) and hydrophilic-lipophilic balance (HLB) of the SLs obtained from the wild and mutant strains were also examined and compared. These results demonstrated the feasibility of obtaining SLs with different properties from different strains and the high efficiency of mutation breeding of S. bombicola by ARTP.

Circulating monocytes accelerate acute liver failure by IL-6 secretion in monkey.

Acute liver failure (ALF) is associated with high mortality, and a poor understanding of the underlying pathophysiology has resulted in a lack of effective treatments so far. Here, using an amatoxin-induced rhesus monkey model of ALF, we panoramically revealed the cellular and molecular events that lead to the development of ALF. The challenged monkeys with toxins underwent a typical course of ALF including severe hepatic injury, systemic inflammation and eventual death. Adaptive immune was not noticeably disturbed throughout the progress of ALF. A systematic examination of serum factors and cytokines revealed that IL-6 increase was the most rapid and drastic. Interestingly, we found that IL-6 was mainly produced by circulating monocytes. Furthermore, ablation of monocyte-derived IL-6 in mice decreased liver injury and systemic inflammation following chemical injection. Our findings reveal a critical role of circulating monocytes in initiating and accelerating ALF, indicating a potential therapeutic target in clinical treatment for ALF.

Elevated expression of Gsα in intrahepatic cholangiocarcinoma associates with poor prognosis.

BACKGROUND: The stimulatory G protein a subunit (Gsα) plays important roles in diverse cell processes including tumorigenesis. Activating mutations in Gsα gene (GNAS) have been reported to be associated with poor prognosis in various human carcinomas. Furthermore, Gsα signaling is crucial in promoting liver regeneration by interacting with growth factor signaling, indicating that Gsα might play a promoting role in cancer development. However, little is known about the correlation between Gsα levels and clinicopathological parameters in intrahepatic cholangiocarcinoma (ICC). METHODS: We performed immunoblotting to examine the expression levels of Gsα and Ki67 proteins in tumor tissues and the corresponding adjacent tissues. A total of 74 pair of specimens resected from 74 ICC patients were examined. The association between Gsα levels and clinicopathological findings and prognosis of the patients was evaluated. RESULTS: Western blotting demonstrated that the expression of Gsα was significantly higher in ICC tissues compared with that in their corresponding adjacent tissues. Gsα protein was highly expressed in about half of ICC tissues (48.6%, 36/74) while only 28.4% (21/74) of tumor adjacent tissues showed Gsα high expression (P=0.011). High Gsα expression in ICC was significantly associated with the numbers of tumor nodules (P=0.037) and lymph node metastases (P=0.010). Moreover, the level of Gsα was significantly and positively correlated with Ki67 expression (P<0.001). In addition, the recurrence-free survival rate and overall survival rate in the Gsα high group were significantly lower than those in the Gsα low group (P=0.004 and P=0.005, respectively). CONCLUSIONS: High Gsα expression is correlated with poor prognosis in ICC patients. Gsα might serve as a potential prognostic indicator of ICC.

MiR-17~92 ablation impairs liver regeneration in an estrogen-dependent manner.

As one of the most important post-transcriptional regulators, microRNAs (miRNAs) participate in diverse biological processes, including the regulation of cell proliferation. MiR-17~92 has been found to act as an oncogene, and it is closely associated with cell proliferation. However, its role in liver regeneration is still unclear. We generated a hepatocyte-specific miR-17~92-deficient mouse and used a mouse model with 70% partial hepatectomy (PH) or intraperitoneal injection of carbon tetrachloride to demonstrate the role of MiR-17~92 in liver regeneration. In quiescent livers, the expression of the miR-17~92 cluster showed a gender disparity, with much higher expression in female mice. The expression of four members of this cluster was found to be markedly reduced after 70% PH. The ablation of miR-17~92 led to obvious regeneration impairment during the early-stage regeneration in the female mice. Ovariectomy greatly reduced miR-17~92 expression but significantly promoted liver regeneration in wild-type mice. In addition, early regeneration impairment in miR-17~92-deficient livers could be largely restored following ovariectomy. The proliferation suppressors p21 and Pten were found to be the target effectors of miR-17~92. MiR-17~92 disruption resulted in elevated protein levels of p21 and Pten in regenerating livers. MiR-17~92 functions as a proliferation stimulator and acts in an oestrogen-dependent manner. The loss of this miRNA results in increases in p21 and Pten expression and therefore impairs liver regeneration in female mice.

Loss of Gsα impairs liver regeneration through a defect in the crosstalk between cAMP and growth factor signaling.

BACKGROUND & AIMS: The stimulatory G protein α subunit (Gsα) activates the cAMP-dependent pathway by stimulating the production of cAMP and participates in diverse cell processes. Aberrant expression of Gsα results in various pathophysiological disorders, including tumorigenesis, but little is known about its role in liver regeneration. METHODS: We generated a hepatocyte-specific Gsα gene knockout mouse to demonstrate the essential role of Gsα in liver regeneration using a mouse model with 70% partial hepatectomy (PH) or an intraperitoneal injection of carbon tetrachloride (CCl4). RESULTS: Gsα inactivation dramatically impaired liver regeneration and blocked proliferating hepatocytes in G1/S transition due to the simultaneous depression of cyclin-dependent kinase 2 (CDK2) and cyclin E1. Loss of Gsα led to a fundamental alteration in gene profiles. Among the altered signaling cascades, the MAPK/Erk pathway, which is downstream of growth factor signaling, was disrupted secondary to a defect in phosphorylated Raf1 (pRaf1), resulting in a deficiency in phosphorylated CREB (pCREB) and CDK2 ablation. The lack of pRaf1 also resulted in a failure to phosphorylate retinoblastoma, which releases and activates E2F1, and a decrease in cyclin E1. Although these factors could be phosphorylated through both Gsα and growth factor signaling, the unique function of Raf1 in the growth factor cascade collapsed in response to the lack of Gsα. CONCLUSION: The growth factor signaling pathway that promotes hepatocyte proliferation is dependent on Gsα signaling. Loss of Gsα leads to a breakdown of the crosstalk between cAMP and growth factor signaling and dramatically impairs liver regeneration.