Genome sequencing of pancreatic cancer: differential expression by location

The results demonstrated that pancreatic ductal carcinoma (PDAC) of the body/tail was associated with more transcriptional and genomic changes, and correlated with worse prognosis, than PDAC of the pancreatic head. The different mutation types and gene expression of tumour locations provide deep insight into the carcinogenesis or metastasis of PDAC, and suggest different early diagnostic and therapeutic strategies. SNV, single-nucleotide variations; NLS, Nuclear localization sequence; MB, million base-pairs; UTR, untranslated region.

[Amentoflavone inhibits M1 polarization of THP-1-derived foam cells by activating PPAR-α/γ]

OBJECTIVE

To investigate the mechanism by which amentoflavone inhibits polarization of THP-1-derived foam cells to M1 phenotype.

OBJECTIVE

Human monocyte cell line THP-1 was stimulated to differentiate into M1-type macrophages using phorbol 12-myrislate13-acetate (PMA) combined with lipopolysaccharide (LPS) and recombinant human interferon-γ (rhlFN-γ). M1 polarization of THP-1-derived macrophages was confirmed by observing morphological changes of the cells and detecting the mRNA expression of L-6 and TNF-α with RT-qPCR. THP-1-derived foam cells treated with 5 or 10 μmol/L amentoflavone for 24 h were examined for cytokines using ELISA. The mRNA and protein expressions of IL-6, IL-10, TNF-α, TGF-β, PPAR-α/γ, Arg-1 and Fizz1 in the cells were detected using RT-qPCR and Western blotting.

OBJECTIVE

Amentoflavone prevented induced M1 polarization of THP-1 cells. Amentoflavone down-regulated the mRNA expressions of IL-6 and TNF-α, up-regulated mRNA expressions of IL-8 and TGF-β mRNA (P < 0.05), and increased the protein expressions of PPAR-α/γ, Arg-1 and Fizz1. Molecular docking simulation showed that amentoflavone could bind to the surface of PPARα/γ.

OBJECTIVE

Amentoflavone can inhibit the differentiation of macrophages into M1 type by activating PPAR-α/γ and restoring the expressions of the gene Arg-1 and Fizz1.

The chromosome-level genome of dragon fruit reveals whole-genome duplication and chromosomal co-localization of betacyanin biosynthetic genes

Dragon fruits are tropical fruits economically important for agricultural industries. As members of the family of Cactaceae, they have evolved to adapt to the arid environment. Here we report the draft genome of Hylocereus undatus, commercially known as the white-fleshed dragon fruit. The chromosomal level genome assembly contains 11 longest scaffolds corresponding to the 11 chromosomes of H. undatus. Genome annotation of H. undatus found ~29,000 protein-coding genes, similar to Carnegiea gigantea (saguaro). Whole-genome duplication (WGD) analysis revealed a WGD event in the last common ancestor of Cactaceae followed by extensive genome rearrangements. The divergence time between H. undatus and C. gigantea was estimated to be 9.18 MYA. Functional enrichment analysis of orthologous gene clusters (OGCs) in six Cactaceae plants found significantly enriched OGCs in drought resistance. Fruit flavor-related functions were overrepresented in OGCs that are significantly expanded in H. undatus. The H. undatus draft genome also enabled the discovery of carbohydrate and plant cell wall-related functional enrichment in dragon fruits treated with trypsin for a longer storage time. Lastly, genes of the betacyanin (a red-violet pigment and antioxidant with a very high concentration in dragon fruits) biosynthetic pathway were found to be co-localized on a 12 Mb region of one chromosome. The consequence may be a higher efficiency of betacyanin biosynthesis, which will need experimental validation in the future. The H. undatus draft genome will be a great resource to study various cactus plants.

Protocol for a gallbladder cancer registry study in China: the Chinese Research Group of Gallbladder Cancer (CRGGC) study

INTRODUCTION

Gallbladder cancer (GBC), the sixth most common gastrointestinal tract cancer, poses a significant disease burden in China. However, no national representative data are available on the clinical characteristics, treatment and prognosis of GBC in the Chinese population.

METHODS AND ANALYSIS

The Chinese Research Group of Gallbladder Cancer (CRGGC) study is a multicentre retrospective registry cohort study. Clinically diagnosed patient with GBC will be identified from 1 January 2008 to December, 2019, by reviewing the electronic medical records from 76 tertiary and secondary hospitals across 28 provinces in China. Patients with pathological and radiological diagnoses of malignancy, including cancer in situ, from the gallbladder and cystic duct are eligible, according to the National Comprehensive Cancer Network 2019 guidelines. Patients will be excluded if GBC is the secondary diagnosis in the discharge summary. The demographic characteristics, medical history, physical examination results, surgery information, pathological data, laboratory examination results and radiology reports will be collected in a standardised case report form. By May 2021, approximately 6000 patient with GBC will be included. The clinical follow-up data will be updated until 5 years after the last admission for GBC of each patient. The study aimed (1) to depict the clinical characteristics, including demographics, pathology, treatment and prognosis of patient with GBC in China; (2) to evaluate the adherence to clinical guidelines of GBC and (3) to improve clinical practice for diagnosing and treating GBC and provide references for policy-makers.

ETHICS AND DISSEMINATION

The protocol of the CRGGC has been approved by the Committee for Ethics of Xinhua Hospital, Shanghai Jiao Tong University School of Medicine (SHEC-C-2019-085). All results of this study will be published in peer-reviewed journals and presented at relevant conferences.

TRIAL REGISTRATION NUMBER

NCT04140552, Pre-results.

LncRNA TTTY15 regulates hypoxia-induced vascular endothelial cell injury via targeting miR-186-5p in cardiovascular disease

OBJECTIVE

Dysfunction of vascular endothelial cells was associated with diverse human diseases, including cardiovascular disease. Long noncoding RNAs (LncRNAs) were involved in the regulation of cell injury. We aimed to investigate the role of lncRNA testis-specific transcript, Y-linked 15 (TTTY15) in hypoxia-induced cell injury in human umbilical vein endothelial cells (HUVECs).

MATERIALS AND METHODS

Cell counting kit-8 (CCK8) assay was used to check cell viability. Lactate dehydrogenase (LDH) assay kit and flow cytometry were utilized to evaluate the leakage rate of LDH and cell apoptosis, respectively. The protein levels of Cyclin D1 and B-cell lymphoma-2-Associated X (Bax) in hypoxia-induced HUVECs were measured by Western blot. Quantitative Real-time polymerase chain reaction (qRT-PCR) was conducted to detect the expression levels of TTTY15 and miR-186-5p in hypoxia-induced HUVECs. The starBase was utilized to predict the binding sites between TTTY15 and miR-186-5p and the dual-luciferase reporter assay was performed to verify the interaction.

RESULTS

Hypoxia inhibited cell viability and promoted the release of LDH and cell apoptosis in HUVECs. Besides, hypoxia significantly decreased the protein level of Cyclin D1 and increased the protein level of Bax in HUVECs. In addition, the expression level of TTTY15 was obviously upregulated in hypoxia-induced HUVECs, opposite to the level of miR-186-5p. Meanwhile, knockdown of TTTY15 or upregulation of miR-186-5p mitigated hypoxia-induced cell injury in HUVECs. Further studies suggested that TTTY15 targeted miR-186-5p and regulated hypoxia-induced cell injury via interacting with miR-186-5p in HUVECs.

CONCLUSIONS

Downregulation of TTTY15 ameliorated hypoxia-induced cell injury by targeting miR-186-5p in HUVECs.

ECT2 overexpression promotes the polarization of tumor-associated macrophages in hepatocellular carcinoma via the ECT2/PLK1/PTEN pathway

Hepatocellular carcinoma (HCC) is a common high-mortality cancer, mainly due to diagnostic difficulties during its early clinical stages. In this study, we aimed to identify genes that are important for HCC diagnosis and treatment, and we investigated the underlying mechanism of prognostic differences. Differentially expressed genes (DEGs) were identified by using the limma package, and receiver operating characteristic curve analysis was performed to identify diagnostic markers for HCC. Bioinformatics and clinical specimens were used to assess epithelial cell transforming 2 (ECT2) in terms of expression, prognostic value, pathways, and immune correlations. In vitro experiments were used to investigate the underlying mechanism and function of ECT2, and the results were confirmed through in vivo experiments. The integrated analysis revealed 53 upregulated DEGs, and one candidate biomarker for diagnosis (ECT2) was detected. High expression of ECT2 was found to be an independent prognostic risk factor for HCC. ECT2 expression showed a strong correlation with tumor-associated macrophages. We found that ECT2 overexpression increased the migration and proliferation of HCC cells. It also promoted the expression of PLK1, which subsequently interacted with PTEN and interfered with its nuclear translocation, ultimately enhancing aerobic glycolysis and promoting M2 macrophage polarization. M2 macrophages suppress the functions of NK cells and T cells, and this was confirmed in the in vivo experiments. Overall, ECT2 may promote the polarization of M2 macrophages by enhancing aerobic glycolysis and suppressing the functions of immune cells. ECT2 could serve as a candidate diagnostic and prognostic biomarker for HCC.

Inhibition of Bone Morphogenetic Protein 2 Suppresses the Stemness Maintenance of Cancer Stem Cells in Hepatocellular Carcinoma via the MAPK/ERK Pathway

Background

Hepatocellular carcinoma (HCC) remains a life-threatening malignant tumor. Cancer stem cells (CSCs) harbor tumor-initiating capacity and can be used as a therapeutic target for human malignancies. Bone morphogenetic proteins (BMPs) play a regulatory role in CSCs. This study investigated the role and mechanism of BMP2 in CSCs in HCC.

Methods

BMP2 expression in HCC tissues and cells, and CSCs from HepG2 cells and SMMC7721 cells (HepG2-CSCs and SMMC7721-CSCs) was measured. The association between BMP2 expression and prognosis of HCC patients was analyzed. CSCs were interfered with BMP2 to evaluate the abilities of colony and tumor sphere formation, levels of stemness-related markers, epithelial-mesenchymal transition (EMT), and invasion and migration. Levels of MAPK/ERK pathway-related proteins in HepG2-CSCs were detected after BMP2 knockdown. The effect of the activated MAPK/ERK pathway on HepG2-CSCs was assessed. Finally, the effect of BMP2 inhibition on CSCs in HCC was verified in vivo.

Results

BMP2 showed obvious upregulation in HCC tissues and cells and was further upregulated in CSCs in HCC, with its higher expression indicative of worse prognosis. Silencing BMP2 inhibited colony and tumor sphere formation, levels of stemness-related markers, as well as EMT, invasion and migration of HepG2-CSCs and SMMC7721-CSCs. The MAPK/ERK pathway was suppressed after BMP2 knockdown, and its activation reversed the inhibitory effect of shBMP2 on hepatic CSCs. BMP2 accelerated tumor growth and EMT of CSCs in HCC in vivo.

Conclusion

We concluded that BMP2 knockdown inhibited the EMT, proliferation and invasion of CSCs in HCC, thereby hindering the stemness maintenance via suppressing the MAPK/ERK pathway.

dbCAN-PUL: a database of experimentally characterized CAZyme gene clusters and their substrates

PULs (polysaccharide utilization loci) are discrete gene clusters of CAZymes (Carbohydrate Active EnZymes) and other genes that work together to digest and utilize carbohydrate substrates. While PULs have been extensively characterized in Bacteroidetes, there exist PULs from other bacterial phyla, as well as archaea and metagenomes, that remain to be catalogued in a database for efficient retrieval. We have developed an online database dbCAN-PUL (http://bcb.unl.edu/dbCAN_PUL/) to display experimentally verified CAZyme-containing PULs from literature with pertinent metadata, sequences, and annotation. Compared to other online CAZyme and PUL resources, dbCAN-PUL has the following new features: (i) Batch download of PUL data by target substrate, species/genome, genus, or experimental characterization method; (ii) Annotation for each PUL that displays associated metadata such as substrate(s), experimental characterization method(s) and protein sequence information, (iii) Links to external annotation pages for CAZymes (CAZy), transporters (UniProt) and other genes, (iv) Display of homologous gene clusters in GenBank sequences via integrated MultiGeneBlast tool and (v) An integrated BLASTX service available for users to query their sequences against PUL proteins in dbCAN-PUL. With these features, dbCAN-PUL will be an important repository for CAZyme and PUL research, complementing our other web servers and databases (dbCAN2, dbCAN-seq).

MTIF2 impairs 5 fluorouracil-mediated immunogenic cell death in hepatocellular carcinoma in vivo: Molecular mechanisms and therapeutic significance

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related morbidity and mortality; it has been reported that immune cell infiltration is a prognosis factor. Here we identified genes that associated with tumor immune cell infiltrate; the underlying mechanism was verified by in vivo and in vitro experiment. In this study, Weighted correlation network analysis (WGCNA) and CIBERSORT tool were used to identify MTIF2 as the hub tumor immune infiltrating gene in HCC. To investigate the underlying role played by MTIF2, MTIF2 was knocked down by transfection of shRNA targeting MTIF2, CCK8, and EdU incorporation assay was used to evaluate the effect of MTIF2 on proliferation, wound heal assay and transwell assay was used to confirm its effect on cell migration. Ecto-calreticulin on the cell surface was evaluated by flow cytometry, ATP, and HMGB1 secretion were tested to the investigated effect of MTIF2 on the immunogenic cell death (ICD) process. We found that down-regulation of MTIF2 impaired proliferation and migration capacity of HCC cells, chemoresistance to 5-Fluorouracil (5-FU) weakened after MTIF2 was knocked down. Reduced release of damage-associated molecular patterns (DAMP) was observed after MTIF2 was overexpressed, which subsequently impaired dendritic cell (DC) maturation and proliferation of CD8 + T cells. Mechanically, the co-IP experiment confirmed that MTIF2 could interact with AIFM1, prevents AIFM1 induced transcription of caspase3, and finally suppress apoptosis. In vivo experiment also used to confirm our previously conclusion, our result indicated that MTIF2 overexpression suppresses tumor apoptosis and immune cell activity in the 5-FU therapy in vivo model, by suppression maturation of tumor-infiltrated DC. Collectively, our study confirmed that MTIF2 impair drug-induced immunogenic cell death in hepatocellular carcinoma cells.

Development and clinical validation of a novel 9-gene prognostic model based on multi-omics in pancreatic adenocarcinoma

The prognoses of patients with pancreatic adenocarcinoma (PAAD) remain poor due to the lack of biomarkers for early diagnosis and effective prognosis prediction. RNA sequencing, single nucleotide polymorphism, and copy number variation data were downloaded from The Cancer Genome Atlas (TCGA). Univariate Cox regression was used to identify prognosis-related genes. GISTIC 2.0 was used to identify significantly amplified or deleted genes, and Mutsig 2.0 was used to analyze the mutation data. The Lasso method was used to construct a risk prediction model. The Rms package was used to evaluate the overall predictive performance of the signature. Finally, Western blot and polymerase chain reaction were performed to evaluate gene expression. A total of 54 candidate genes were obtained after integrating the genomic mutated genes and prognosis-related genes. The Lasso method was used to ascertain 9 characteristic genes, including UNC13B, TSPYL4, MICAL1, KLHDC7B, KLHL32, AIM1, ARHGAP18, DCBLD1, and CACNA2D4. The 9-gene signature model was able to help stratify samples at risk in the training and external validation cohorts. In addition, the overall predictive performance of our model was found to be superior to that of other models. KLHDC7B, AIM1, DCBLD1, TSPYL4, and MICAL1 were significantly highly expressed in tumor tissues compared to normal tissues. ARHGAP18 and CACNA2D4 had no difference in expression between tumor and normal tissues. UNC13B and KLHL32 expression in the normal group was higher than in the tumor group. The 9-gene signature constructed in this study can be used as a novel prognostic marker to predict the survival of patients with pancreatic adenocarcinoma.

Using deep-learning algorithms to classify fetal brain ultrasound images as normal or abnormal

OBJECTIVES

To evaluate the feasibility of using deep-learning algorithms to classify as normal or abnormal sonographic images of the fetal brain obtained in standard axial planes.

METHODS

We included in the study images retrieved from a large hospital database from 10 251 normal and 2529 abnormal pregnancies. Abnormal cases were confirmed by neonatal ultrasound, follow-up examination or autopsy. After a series of pretraining data processing steps, 15 372 normal and 14 047 abnormal fetal brain images in standard axial planes were obtained. These were divided into training and test datasets (at case level rather than image level), at a ratio of approximately 8:2. The training data were used to train the algorithms for three purposes: performance of image segmentation along the fetal skull, classification of the image as normal or abnormal and localization of the lesion. The accuracy was then tested on the test datasets, with performance of segmentation being assessed using precision, recall and Dice's coefficient (DICE), calculated to measure the extent of overlap between human-labeled and machine-segmented regions. We assessed classification accuracy by calculating the sensitivity and specificity for abnormal images. Additionally, for 2491 abnormal images, we determined how well each lesion had been localized by overlaying heat maps created by an algorithm on the segmented ultrasound images; an expert judged these in terms of how satisfactory was the lesion localization by the algorithm, classifying this as having been done precisely, closely or irrelevantly.

RESULTS

Segmentation precision, recall and DICE were 97.9%, 90.9% and 94.1%, respectively. For classification, the overall accuracy was 96.3%. The sensitivity and specificity for identification of abnormal images were 96.9% and 95.9%, respectively, and the area under the receiver-operating-characteristics curve was 0.989 (95% CI, 0.986-0.991). The algorithms located lesions precisely in 61.6% (1535/2491) of the abnormal images, closely in 24.6% (614/2491) and irrelevantly in 13.7% (342/2491).

CONCLUSIONS

Deep-learning algorithms can be trained for segmentation and classification of normal and abnormal fetal brain ultrasound images in standard axial planes and can provide heat maps for lesion localization. This study lays the foundation for further research on the differential diagnosis of fetal intracranial abnormalities. Copyright © 2020 ISUOG. Published by John Wiley & Sons Ltd.

MiR-574-3p exerts as a tumor suppressor in ovarian cancer through inhibiting MMP3 expression

OBJECTIVE

The mortality rate of ovarian cancer (OC) has always been the highest among all female reproductive system malignant tumors. Currently, miRNAs have been verified to participate in the tumorigenesis and prognosis of OC. However, the expression and function of miR-574-3p in OC have not been fully elucidated.

PATIENTS AND METHODS

The expression level of miR-574-3p in OC tissues and cells was detected using quantitative Real Time-Polymerase Chain Reaction (qRT-PCR). By transfection of miR-574-3p mimics or inhibitor, the expression of miR-574-3p in SW626 or A2780 cells was up-regulated or down-regulated, respectively. Cell counting kit-8 (CCK-8) and colony formation assays were used to measure the proliferation of transfected OC cells. Meanwhile, the transwell assay was applied to detect the migration and invasion abilities of OC cells. Furthermore, dual-luciferase reporter gene analysis and Western blot were utilized to explore the underlying downstream molecules for miR-574-3p in OC.

RESULTS

MiR-574-3p was lowly expressed in OC tissue samples when compared with para-tumor tissues. Meanwhile, the expression of miR-574-3p in OC-derived cells was significantly lower than normal control HOSE cells. The overexpression of miR-574-3p markedly reduced the proliferation, invasion, and migration of SW626 cells. However, the inhibition of miR-574-3p remarkably accelerated the growth and metastasis of A2780 cells. MMP3 was verified as a direct target for miR-574-3p in OC. In addition, miR-574-3p could reduce the protein expression of MMP3 by binding to its 3'-untranslated region (3'-UTR).

CONCLUSIONS

MiR-574-3p functioned as a tumor suppressor in OC, which might be served as a potential target for the diagnosis and therapy for OC.

eCAMI: simultaneous classification and motif identification for enzyme annotation

MOTIVATION

Carbohydrate-active enzymes (CAZymes) are extremely important to bioenergy, human gut microbiome, and plant pathogen researches and industries. Here we developed a new amino acid k-mer-based CAZyme classification, motif identification and genome annotation tool using a bipartite network algorithm. Using this tool, we classified 390 CAZyme families into thousands of subfamilies each with distinguishing k-mer peptides. These k-mers represented the characteristic motifs (in the form of a collection of conserved short peptides) of each subfamily, and thus were further used to annotate new genomes for CAZymes. This idea was also generalized to extract characteristic k-mer peptides for all the Swiss-Prot enzymes classified by the EC (enzyme commission) numbers and applied to enzyme EC prediction.

RESULTS

This new tool was implemented as a Python package named eCAMI. Benchmark analysis of eCAMI against the state-of-the-art tools on CAZyme and enzyme EC datasets found that: (i) eCAMI has the best performance in terms of accuracy and memory use for CAZyme and enzyme EC classification and annotation; (ii) the k-mer-based tools (including PPR-Hotpep, CUPP and eCAMI) perform better than homology-based tools and deep-learning tools in enzyme EC prediction. Lastly, we confirmed that the k-mer-based tools have the unique ability to identify the characteristic k-mer peptides in the predicted enzymes.

AVAILABILITY AND IMPLEMENTATION

https://github.com/yinlabniu/eCAMI and https://github.com/zhanglabNKU/eCAMI.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Horizontal sound localisation and speech perception in Bonebridge-implanted single-sided deafness patients

OBJECTIVE

This study aimed to investigate the benefit of Bonebridge devices in patients with single-sided deafness.

METHOD

Five patients with single-sided deafness who were implanted with Bonebridge devices were recruited in a single-centre study. Participants' speech perception and horizontal sound localisation abilities were assessed at 6 and 12 months post-operatively. Speech intelligibility in noisy environments was measured in three different testing conditions (speech and noise presented from the front, speech and noise presented from the front and contralateral (normal ear) side separately, and speech presented from the ipsilateral (implanted Bonebridge) side and noise from the contralateral side). Sound localisation was evaluated in Bonebridge-aided and Bonebridge-unaided conditions at different stimuli levels (65, 70 and 75 dB SPL).

RESULTS

All participants showed a better capacity for speech intelligibility in quiet environments with the Bonebridge device. The speech recognition threshold with the Bonebridge device was significantly decreased at both short- and long-term follow up in the speech presented from the ipsilateral (implanted Bonebridge) side and noise from the contralateral side condition (p < 0.05). Additionally, participants maintained similar levels of sound localisation between the Bonebridge-aided and unaided conditions (p > 0.05). However, the accuracy of localisation showed some improvement at 70 dB SPL and 75 dB SPL post-operatively.

CONCLUSION

The Bonebridge device provides the benefit of improved speech perception performance in patients with single-sided deafness. Sound localisation abilities were neither improved nor worsened with Bonebridge implantation at the follow-up assessments.

Development and Validation of a Novel 8 Immune Gene Prognostic Signature Based on the Immune Expression Profile for Hepatocellular Carcinoma

Background

The immune microenvironment plays a vital role in the development of hepatocellular carcinoma (HCC). This study explored novel immune-related biomarkers to predict the prognosis of patients with HCC.

Methods

RNA-Seq data were downloaded from The Cancer Genome Atlas (TCGA). Univariate Cox regression was used to identify prognosis-related genes; the Lasso method was used to construct the prognosis risk model. Validation was performed on the International Cancer Genome Consortium (ICGC) cohort, and the C-index was calculated to evaluate its overall predictive performance. Western blots were conducted to evaluate the expression of genes.

Results

There were 320 immune-related genes, 40 of which were significantly related to prognosis. Eight immune gene signatures (CKLF, IL12A, CCL20, PRELID1, GLMN, ACVR2A, CD7, and FYN) were established by Lasso Cox regression analysis. This immune signature performed well in different cohorts and can be an independent risk factor for prognosis. In addition, the overall predictive performance of this model was higher than the other models reported previously.

Conclusion

The predictive immune model will enable patients with HCC to be more accurately managed in immunotherapy.

P3DOCK: a protein-RNA docking webserver based on template-based and template-free docking

MOTIVATION

The main function of protein-RNA interaction is to regulate the expression of genes. Therefore, studying protein-RNA interactions is of great significance. The information of three-dimensional (3D) structures reveals that atomic interactions are particularly important. The calculation method for modeling a 3D structure of a complex mainly includes two strategies: free docking and template-based docking. These two methods are complementary in protein-protein docking. Therefore, integrating these two methods may improve the prediction accuracy.

RESULTS

In this article, we compare the difference between the free docking and the template-based algorithm. Then we show the complementarity of these two methods. Based on the analysis of the calculation results, the transition point is confirmed and used to integrate two docking algorithms to develop P3DOCK. P3DOCK holds the advantages of both algorithms. The results of the three docking benchmarks show that P3DOCK is better than those two non-hybrid docking algorithms. The success rate of P3DOCK is also higher (3-20%) than state-of-the-art hybrid and non-hybrid methods. Finally, the hierarchical clustering algorithm is utilized to cluster the P3DOCK's decoys. The clustering algorithm improves the success rate of P3DOCK. For ease of use, we provide a P3DOCK webserver, which can be accessed at www.rnabinding.com/P3DOCK/P3DOCK.html. An integrated protein-RNA docking benchmark can be downloaded from http://rnabinding.com/P3DOCK/benchmark.html.

AVAILABILITY AND IMPLEMENTATION

www.rnabinding.com/P3DOCK/P3DOCK.html.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.