RESULTS: We developed DeSigN, a web-based tool for predicting drug efficacy against cancer cell lines using gene expression patterns. The algorithm correlates phenotype-specific gene signatures derived from differentially expressed genes with pre-defined gene expression profiles associated with drug response data (IC50) from 140 drugs. DeSigN successfully predicted the right drug sensitivity outcome in four published GEO studies. Additionally, it predicted bosutinib, a Src/Abl kinase inhibitor, as a sensitive inhibitor for oral squamous cell carcinoma (OSCC) cell lines. In vitro validation of bosutinib in OSCC cell lines demonstrated that indeed, these cell lines were sensitive to bosutinib with IC50 of 0.8-1.2 μM. As further confirmation, we demonstrated experimentally that bosutinib has anti-proliferative activity in OSCC cell lines, demonstrating that DeSigN was able to robustly predict drug that could be beneficial for tumour control.
CONCLUSIONS: DeSigN is a robust method that is useful for the identification of candidate drugs using an input gene signature obtained from gene expression analysis. This user-friendly platform could be used to identify drugs with unanticipated efficacy against cancer cell lines of interest, and therefore could be used for the repurposing of drugs, thus improving the efficiency of drug development.
AIM OF THE STUDY: This study aimed to use a computational target fishing approach to predict the possible therapeutic effect of Marantodes pumilum and evaluated their effectivity.
MATERIALS AND METHODS: This study involves a computational approach to identify the potential targets by using target fishing. Several databases were used: PubChem database to obtain the chemical structure of interested compounds; Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) server and the SWISSADME web tool to identify and select the compounds having drug-likeness properties; PharmMapper was used to identify top ten target protein of the selected compounds and Online Mendelian Inheritance in Man (OMIM) was used to predict human genetic problems; the gene id of top-10 proteins was obtained from UniProtKB to be analyzed by using GeneMANIA server to check the genes' function and their co-expression; Gene Pathway established by Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) of the selected targets were analyzed by using EnrichR server and confirmed by using DAVID (The Database for Annotation, Visualization and Integrated Discovery) version 6.8 and STRING database. All the interaction data was analyzed by Cytoscape version 3.7.2 software. The protein structure of most putative proteins was obtained from the RCSB protein data bank. Thedocking analysis was conducted using PyRx biological software v0.8 and illustrated by BIOVIA Discovery Studio Visualizer version 20.1.0. As a preliminary evaluation, a cell viability assay using Sulforhodamine B was conducted to evaluate the potential of the predicted therapeutic effect.
RESULTS: It was found that four studied compounds are highly correlated with three proteins: EFGR, CDK2, and ESR1. These proteins are highly associated with cancer pathways, especially breast cancer and prostate cancer. Qualitatively, cell proliferation assay conducted shown that the extract has IC50 of 88.69 μg/ml against MCF-7 and 66.51 μg/ml against MDA-MB-231.
CONCLUSIONS: Natural herbs are one of the most common forms of complementary and alternative medicine, and they play an important role in disease treatment. The results of this study show that in addition to being used traditionally to maintain women's health, the use of Marantodes pumilum indirectly has the potential to protect against the development of cancer cells, especially breast cancer. Therefore, further research is necessary to confirm the potential of this plant to be used in the development of anti-cancer drugs, especially for breast cancer.
RESULTS: All HPs of B. lehensis G1 were grouped according to their predicted functions based on the presence of functional domains in their sequences. From the metal-binding group of HPs of the cluster, an HP termed Bleg1_2507 was discovered to contain a thioredoxin (Trx) domain and highly-conserved metal-binding ligands represented by Cys69, Cys73 and His159, similar to all prokaryotic and eukaryotic Sco proteins. The built 3D structure of Bleg1_2507 showed that it shared the βαβαββ core structure of Trx-like proteins as well as three flanking β-sheets, a 310 -helix at the N-terminus and a hairpin structure unique to Sco proteins. Docking simulations provided an interesting view of Bleg1_2507 in association with its putative cytochrome c oxidase subunit II (COXII) redox partner, Bleg1_2337, where the latter can be seen to hold its partner in an embrace, facilitated by hydrophobic and ionic interactions between the proteins. Although Bleg1_2507 shares relatively low sequence identity (47%) to BsSco, interestingly, the predicted metal-binding residues of Bleg1_2507 i.e. Cys-69, Cys-73 and His-159 were located at flexible active loops similar to other Sco proteins across biological taxa. This highlights structural conservation of Sco despite their various functions in prokaryotes and eukaryotes.
CONCLUSIONS: We propose that HP Bleg1_2507 is a Sco protein which is able to interact with COXII, its redox partner and therefore, may possess metallochaperone and redox functions similar to other documented bacterial Sco proteins. It is hoped that this scientific effort will help to spur the search for other physiologically relevant proteins among the so-called "orphan" proteins of any given organism.
FINDINGS: We optimized the assembly of a Hevea bark transcriptome based on 16 Gb Illumina PE RNA-Seq reads using the Oases assembler across a range of k-mer sizes. We then assessed assembly quality based on transcript N50 length and transcript mapping statistics in relation to (a) known Hevea cDNAs with complete open reading frames, (b) a set of core eukaryotic genes and (c) Hevea genome scaffolds. This was followed by a systematic transcript mapping process where sub-assemblies from a series of incremental amounts of bark transcripts were aligned to transcripts from the entire bark transcriptome assembly. The exercise served to relate read amounts to the degree of transcript mapping level, the latter being an indicator of the coverage of gene transcripts expressed in the sample. As read amounts or datasize increased toward 16 Gb, the number of transcripts mapped to the entire bark assembly approached saturation. A colour matrix was subsequently generated to illustrate sequencing depth requirement in relation to the degree of coverage of total sample transcripts.
CONCLUSIONS: We devised a procedure, the "transcript mapping saturation test", to estimate the amount of RNA-Seq reads needed for deep coverage of transcriptomes. For Hevea de novo assembly, we propose generating between 5-8 Gb reads, whereby around 90% transcript coverage could be achieved with optimized k-mers and transcript N50 length. The principle behind this methodology may also be applied to other non-model plants, or with reads from other second generation sequencing platforms.