KSFinder-a knowledge graph model for link prediction of novel phosphorylated substrates of kinases.

Background: Aberrant protein kinase regulation leading to abnormal substrate phosphorylation is associated with several human diseases. Despite the promise of therapies targeting kinases, many human kinases remain understudied. Most existing computational tools predicting phosphorylation cover less than 50% of known human kinases. They utilize local feature selection based on protein sequences, motifs, domains, structures, and/or functions, and do not consider the heterogeneous relationships of the proteins. In this work, we present KSFinder, a tool that predicts kinase-substrate links by capturing the inherent association of proteins in a network comprising 85% of the known human kinases. We also postulate the potential role of two understudied kinases based on their substrate predictions from KSFinder. Methods: KSFinder learns the semantic relationships in a phosphoproteome knowledge graph using a knowledge graph embedding algorithm and represents the nodes in low-dimensional vectors. A multilayer perceptron (MLP) classifier is trained to discern kinase-substrate links using the embedded vectors. KSFinder uses a strategic negative generation approach that eliminates biases in entity representation and combines data from experimentally validated non-interacting protein pairs, proteins from different subcellular locations, and random sampling. We assess KSFinder's generalization capability on four different datasets and compare its performance with other state-of-the-art prediction models. We employ KSFinder to predict substrates of 68 "dark" kinases considered understudied by the Illuminating the Druggable Genome program and use our text-mining tool, RLIMS-P along with manual curation, to search for literature evidence for the predictions. In a case study, we performed functional enrichment analysis for two dark kinases - HIPK3 and CAMKK1 using their predicted substrates. Results: KSFinder shows improved performance over other kinase-substrate prediction models and generalized prediction ability on different datasets. We identified literature evidence for 17 novel predictions involving an understudied kinase. All of these 17 predictions had a probability score ≥0.7 (nine at >0.9, six at 0.8-0.9, and two at 0.7-0.8). The evaluation of 93,593 negative predictions (probability ≤0.3) identified four false negatives. The top enriched biological processes of HIPK3 substrates relate to the regulation of extracellular matrix and epigenetic gene expression, while CAMKK1 substrates include lipid storage regulation and glucose homeostasis. Conclusions: KSFinder outperforms the current kinase-substrate prediction tools with higher kinase coverage. The strategically developed negatives provide a superior generalization ability for KSFinder. We predicted substrates of 432 kinases, 68 of which are understudied, and hypothesized the potential functions of two dark kinases using their predicted substrates.

Identification of key differentially expressed MicroRNAs in cancer patients through pan-cancer analysis.

microRNAs (miRNAs) functioning in gene silencing have been associated with cancer progression. However, common abnormal miRNA expression patterns and their potential roles in cancer have not yet been evaluated. To account for individual differences between patients, we retrieved miRNA sequencing data for 575 patients with both tumor and adjacent non-tumorous tissues from 14 cancer types from The Cancer Genome Atlas (TCGA). We then performed differential expression analysis using DESeq2 and edgeR. Results showed that cancer types can be grouped based on the distribution of miRNAs with different expression patterns between tumor and non-tumor samples. We found 81 significantly differentially expressed miRNAs (SDEmiRNAs) in a single cancer. We also found 21 key SDEmiRNAs (nine over-expressed and 12 under-expressed) associated with at least eight cancers each and enriched in more than 60% of patients per cancer, including four newly identified SDEmiRNAs (hsa-mir-4746, hsa-mir-3648, hsa-mir-3687, and hsa-mir-1269a). The downstream effects of these 21 SDEmiRNAs on cellular function were evaluated through enrichment and pathway analysis of 7186 protein-coding gene targets mined from literature reports of differential expression of miRNAs in cancer. This analysis enables identification of SDEmiRNA functional similarity in cell proliferation control across a wide range of cancers, and assembly of common regulatory networks over cancer-related pathways. These findings were validated by construction of a regulatory network in the PI3K pathway. This study provides evidence for the value of further analysis of SDEmiRNAs as potential biomarkers and therapeutic targets for cancer diagnosis and treatment.

Immunocontraceptives: How far from reality?

Despite high expectations of safer, effective, economical, longer acting contraceptives, to date, there are no licensed contraceptive vaccines available in the market. Nevertheless, a role for vaccines undoubtedly exists as an aid to birth spacing and as a nonsurgical means of generating sterility. The research concerned in the area so far has been successful on the feline population, with room still for exhaustive studies on humans. The future of contraceptive vaccines holds great promise in terms of comfort, price, efficacy, rare complications, and possibly nonselective action on animal populations as well as on humans. This brief review deals with the basic aspects of immunocontraceptives along with the efforts done so far. There is a need for further research in aspects involving the rate of evolution of contraception resistance based on genetics, resistance phenotypes, or cross generation effects. Gonadotropin-releasing hormone and luteinizing-hormone have not been investigated in humans, as both reported impotency in animals; the follicle-stimulating hormone has been shown to cause oligospermia; zona pellucida has also not been studied in humans as it causes irreversible oophoritis, while the sperm has the potential for success in humans based on the data from immunoreproductive studies. Even as the position of the human chorionic gonadotropin vaccine looks hopeful, research on other possible targets continue with an eventual aim of discovering a vaccine that is more immunogenically effective.

Multicompartment micelle-structured peptide nanoparticles: a new biocompatible gene- and drug-delivery tool.

Self-assembled, biodegradable materials that embed fragile, soluble, or insoluble compounds of therapeutic interest have potential use as drug delivery systems. The bead-forming peptide Ac-X3-gT can embed hydrophobic and hydrophilic payloads. Loaded peptide beads were internalized by human acute monocytic leukemia cell line (THP-1) macrophages, THP-1 monocytes, and hepatocellular carcinoma cells (Huh7). Furthermore, paclitaxel and doxorubicin coencapsulated in the peptide beads were delivered to THP-1 monocytes, causing a decrease in cell viability due to the activity of the anticancer drugs. In addition to the bead-forming peptide Ac-X3-gT, the use of a positively charged peptide analogue increased the RNA/DNA embedding efficiency to 99% by charge compensation and micellar complexation. Internalization of the resulting gene delivery systems by Huh7 cells led to specific gene silencing either by embedded small interfering RNA or by plasmid-encoding small hairpin RNA delivered in cells. The new class of purely peptidic material caused no measurable toxicity during in vitro experiments, thereby indicating potential use as a drug delivery system for multidrug delivery and gene therapy.

eFIP: a tool for mining functional impact of phosphorylation from literature.

Technologies and experimental strategies have improved dramatically in the field of genomics and proteomics facilitating analysis of cellular and biochemical processes, as well as of proteins networks. Based on numerous such analyses, there has been a significant increase of publications in life sciences and biomedicine. In this respect, knowledge bases are struggling to cope with the literature volume and they may not be able to capture in detail certain aspects of proteins and genes. One important aspect of proteins is their phosphorylated states and their implication in protein function and protein interacting networks. For this reason, we developed eFIP, a web-based tool, which aids scientists to find quickly abstracts mentioning phosphorylation of a given protein (including site and kinase), coupled with mentions of interactions and functional aspects of the protein. eFIP combines information provided by applications such as eGRAB, RLIMS-P, eGIFT and AIIAGMT, to rank abstracts mentioning phosphorylation, and to display the results in a highlighted and tabular format for a quick inspection. In this chapter, we present a case study of results returned by eFIP for the protein BAD, which is a key regulator of apoptosis that is posttranslationally modified by phosphorylation.

Beyond information retrieval--medical question answering.

Physicians have many questions when caring for patients, and frequently need to seek answers for their questions. Information retrieval systems (e.g., PubMed) typically return a list of documents in response to a user's query. Frequently the number of returned documents is large and makes physicians' information seeking "practical only 'after hours' and not in the clinical settings". Question answering techniques are based on automatically analyzing thousands of electronic documents to generate short-text answers in response to clinical questions that are posed by physicians. The authors address physicians' information needs and described the design, implementation, and evaluation of the medical question answering system (MedQA). Although our long term goal is to enable MedQA to answer all types of medical questions, currently, we implemented MedQA to integrate information retrieval, extraction, and summarization techniques to automatically generate paragraph-level text for definitional questions (i.e., "What is X?"). MedQA can be accessed at http://www.dbmi.columbia.edu/~yuh9001/research/MedQA.html.

Light-dependent transformation of aniline to indole esters by the purple bacterium Rhodobacter sphaeroides OU5.

In an attempt to understand the aromatic hydrocarbon metabolism by purple bacteria that do not grow at their expense, we earlier reported 2-aminobenzoate transformation by a purple non-sulfur bacterium, Rhodobacter sphaeroides OU5 (Sunayana et al., 2005, J Ind Microbiol Biotech 32:41-45), which is extended in the present study with aniline, a major environmental pollutant. Aniline did not support photo (light anaerobic) or chemo (dark aerobic) heterotrophic growth of Rhodobacter sphaeroides OU5 either as a sole source of carbon or nitrogen. However, light-dependent aniline transformation was observed in the culture supernatants and the products were identified as indole derivatives. The transformation was dependent on a tricarboxylate intermediate, fumarate. Five intermediates of the aniline biotransformation pathway were isolated and identified as indole esters having a mass of 443, 441, 279, 189, and 167 with unstoichiometric total indole yields of 0.16 mM: from 5 mM: of aniline consumed. The pathway proposed based on these intermediates suggest a novel xenobiotic detoxification process in bacteria.