Abstract: In order to understand the mechanisms of drug-drug interaction (DDI), the study of pharmacokinetics (PK), pharmacodynamics (PD), and pharmacogenetics (PG) data are significant. In recent years, drug PK parameters, drug interaction parameters, and PG data have been unevenly collected in different databases and published extensively in literature. Also the lack of an appropriate PK ontology and a well-annotated PK corpus, which provide the background knowledge and the criteria of determining DDI, respectively, lead to the difficulty of developing DDI text mining tools for PK data collection from the literature and data integration from multiple databases.To conquer the issues, we constructed a comprehensive pharmacokinetics ontology. It includes all aspects of in vitro pharmacokinetics experiments, in vivo pharmacokinetics studies, as well as drug metabolism and transportation enzymes. Using our pharmacokinetics ontology, a PK corpus was constructed to present four classes of pharmacokinetics abstracts: in vivo pharmacokinetics studies, in vivo pharmacogenetic studies, in vivo drug interaction studies, and in vitro drug interaction studies. A novel hierarchical three-level annotation scheme was proposed and implemented to tag key terms, drug interaction sentences, and drug interaction pairs. The utility of the pharmacokinetics ontology was demonstrated by annotating three pharmacokinetics studies; and the utility of the PK corpus was demonstrated by a drug interaction extraction text mining analysis.The pharmacokinetics ontology annotates both in vitro pharmacokinetics experiments and in vivo pharmacokinetics studies. The PK corpus is a highly valuable resource for the text mining of pharmacokinetics parameters and drug interactions.

Abstract: Alterations in cell cycle regulating proteins are a key characteristic in neoplastic proliferation of lymphoblast cells in patients with Acute Lymphoblastic Leukemia (ALL). The aim of our study was to investigate whether the routinely administered ALL chemotherapeutic agents would be able to bind and inhibit the key deregulated cell cycle proteins such as--Cyclins E1, D1, D3, A1 and Cyclin Dependent Kinases (CDK) 2 and 6. We used Schrodinger Glide docking protocol to dock the chemotherapeutic drugs such as Doxorubicin and Daunorubicin and others which are not very common including Clofarabine, Nelarabine and Flavopiridol, to the crystal structures of these proteins. We observed that the drugs were able to bind and interact with cyclins E1 and A1 and CDKs 2 and 6 while their docking to cyclins D1 and D3 were not successful. This binding proved favorable to interact with the G1/S cell cycle phase proteins that were examined in this study and may lead to the interruption of the growth of leukemic cells. Our observations therefore suggest that these drugs could be explored for use as inhibitors for these cell cycle proteins. Further, we have also highlighted residues which could be important in the designing of pharmacophores against these cell cycle proteins. This is the first report in understanding the mechanism of action of the drugs targeting these cell cycle proteins in leukemia through the visualization of drug-target binding and molecular docking using computational methods.

Abstract: PURPOSE: Gadofosveset is a Gd-based contrast agent used for magnetic resonance imaging (MRI). Gadolinium kinetic distribution models are implemented in T1-weighted dynamic contrast-enhanced perfusion MRI for characterization of lesion sites in the body. Physiology changes in a disease state potentially can influence the pharmacokinetics of drugs and to this respect modify the distribution properties of contrast agents. This work focuses on the in silico modelling of pharmacokinetic properties of gadofosveset in different population groups through the application of physiologically-based pharmacokinetic models (PBPK) embedded in Simcyp(R) population pharmacokinetics platform. METHODS: Physicochemical and pharmacokinetic properties of gadofosveset were introduced into Simcyp(R) simulator platform and a min-PBPK model was applied. In silico clinical trials were generated simulating the administration of the recommended dose for the contrast agent (i.v., 30 mg/kg) in population cohorts of healthy volunteers, obese, renal and liver impairment, and in a generated virtual oncology population. Results were evaluated regarding basic pharmacokinetic parameters of Cmax, AUC and systemic CL and differences were assessed through ANOVA and estimation of ratio of geometric mean between healthy volunteers and the other population groups. RESULTS: Simcyp(R) predicted a mean Cmax = 551.60 mg/l, a mean AUC = 4079.12 mg/L*h and a mean systemic CL = 0.56 L/h for the virtual population of healthy volunteers. Obese population showed a modulation in Cmax and CL, attributed to increased administered dose. In renal and liver impairment cohorts a significant modulation in Cmax, AUC and CL of gadofosveset is predicted. Oncology population exhibited statistical significant differences regarding AUC when compared with healthy volunteers. CONCLUSIONS: This work employed Simcyp(R) population pharmacokinetics platform in order to compute gadofosveset's pharmacokinetic profiles through PBPK models and in silico clinical trials and evaluate possible differences between population groups. The approach showed promising results that could provide new insights regarding administration of contrast agents in special population cohorts. In silico pharmacokinetics could further be used for evaluating of possible toxicity, interpretation of MRI PK image maps and development of novel contrast agents.

Abstract: Bedaquiline (BDQ), an ATP synthase inhibitor, is the first drug to be approved for treatment of multi-drug resistant tuberculosis in decades. In vitro resistance to BDQ was previously shown to be due to target-based mutations. Here we report that non-target based resistance to BDQ, and cross-resistance to clofazimine (CFZ), is due to mutations in Rv0678, a transcriptional repressor of the genes encoding the MmpS5-MmpL5 efflux pump. Efflux-based resistance was identified in paired isolates from patients treated with BDQ, as well as in mice, in which it was confirmed to decrease bactericidal efficacy. The efflux inhibitors verapamil and reserpine decreased the minimum inhibitory concentrations of BDQ and CFZ in vitro, but verapamil failed to increase the bactericidal effect of BDQ in mice and was unable to reverse efflux-based resistance in vivo. Cross-resistance between BDQ and CFZ may have important clinical implications.

Abstract: Recently, huge amounts of data are generated in the domain of biology. Embedded with domain knowledge from different disciplines, the isolated biological resources are implicitly connected. Thus it has shaped a big network of versatile biological knowledge. Faced with such massive, disparate, and interlinked biological data, providing an efficient way to model, integrate, and analyze the big biological network becomes a challenge. In this paper, we present a general OWL (web ontology language) reasoning framework to study the implicit relationships among biological entities. A comprehensive biological ontology across traditional Chinese medicine (TCM) and western medicine (WM) is used to create a conceptual model for the biological network. Then corresponding biological data is integrated into a biological knowledge network as the data model. Based on the conceptual model and data model, a scalable OWL reasoning method is utilized to infer the potential associations between biological entities from the biological network. In our experiment, we focus on the association discovery between TCM and WM. The derived associations are quite useful for biologists to promote the development of novel drugs and TCM modernization. The experimental results show that the system achieves high efficiency, accuracy, scalability, and effectivity.

Abstract: Diabetic retinopathy is the leading cause of blindness worldwide. It is caused by the abnormal growth of the retinal blood vessels. Plasminogen activator inhibitor1 (PAI1) is the key growth factor and the inhibition of PAI1 can reduce the angiogenesis. In this study, currently available inhibitors are taken and tested for the toxicity, binding affinity, and bioactivities of the compounds by in silico approach. Five toxic free inhibitors were identified, among which N-acetyl-D-glucosamine shows the significant binding affinity and two of the molecules are having the better bioactivity properties. The molecular optimization of 2-(acetylamino)-2-deoxy-A-D-glucopyranose and alpha-L-fucose can be used for the treatment of diabetic retinopathy.

Abstract: Prioritization of cancer implicated genes has received growing attention as an effective way to reduce wet lab cost by computational analysis that ranks candidate genes according to the likelihood that experimental verifications will succeed. A multitude of gene prioritization tools have been developed, each integrating different data sources covering gene sequences, differential expressions, function annotations, gene regulations, protein domains, protein interactions, and pathways. This review places existing gene prioritization tools against the backdrop of an integrative Omic hierarchy view toward cancer and focuses on the analysis of their text mining components. We explain the relatively slow progress of text mining in gene prioritization, identify several challenges to current text mining methods, and highlight a few directions where more effective text mining algorithms may improve the overall prioritization task and where prioritizing the pathways may be more desirable than prioritizing only genes.

Abstract: The influence of mitochondrial dysfunction on pathological states involving inflammatory and/or oxidative stress in tissues that do not show frank cellular apoptosis or necrosis has been rather difficult to unravel, and the literature is replete with contradictory information. Although such discrepancies have many potential causes related to the type of injurious agent, the severity and duration of the injury, and the particular cells and tissues and the functions involved, it is the successful induction of cellular adaptive responses that ultimately governs the resolution of mitochondrial dysfunction and survival of the cell. Much recent attention has been devoted to unraveling the signaling pathways that activate mitochondrial biogenesis and other processes involved in mitochondrial quality control (QC) during inflammatory and oxidative stress with an eye towards the development of novel targets for therapeutic mitigation of the resultant tissue damage. This review provides a brief overview of this emerging field with an emphasis on the role of signaling through the endogenous gases (NO, CO and H2S) and a redox-based approach that brings transparency to key factors that contribute to the resolution of mitochondrial dysfunction and the maintenance of cell vitality. We make the case that targeted stimulation of mitochondrial biogenesis could be a potentially valuable approach for the development of new therapies for the treatment of diseases for which mitochondrial damage is a major consideration.

Abstract: Drug addiction is a chronic and complex brain disease, adding much burden on the community. Though numerous efforts have been made to identify the effective treatment, it is necessary to find more novel therapeutics for this complex disease. As network pharmacology has become a promising approach for drug repurposing, we proposed to apply the approach to drug addiction, which might provide new clues for the development of effective addiction treatment drugs. We first extracted 44 addictive drugs from the NIDA and their targets from DrugBank. Then, we constructed two networks: an addictive drug-target network and an expanded addictive drug-target network by adding other drugs that have at least one common target with these addictive drugs. By performing network analyses, we found that those addictive drugs with similar actions tended to cluster together. Additionally, we predicted 94 nonaddictive drugs with potential pharmacological functions to the addictive drugs. By examining the PubMed data, 51 drugs significantly cooccurred with addictive keywords than expected. Thus, the network analyses provide a list of candidate drugs for further investigation of their potential in addiction treatment or risk.

Abstract: Traditional Chinese medicine (TCM) has unique therapeutic effects for complex chronic diseases. However, for the lack of an effective systematic approach, the research progress on the effective substances and pharmacological mechanism of action has been very slow. In this paper, by incorporating network biology, bioinformatics and chemoinformatics methods, an integrated approach was proposed to systematically investigate and explain the pharmacological mechanism of action and effective substances of TCM. This approach includes the following main steps: First, based on the known drug targets, network biology was used to screen out putative drug targets; Second, the molecular docking method was used to calculate whether the molecules from TCM and drug targets related to chronic kidney diseases (CKD) interact or not; Third, according to the result of molecular docking, natural product-target network, main component-target network and compound-target network were constructed; Finally, through analysis of network characteristics and literature mining, potential effective multi-components and their synergistic mechanism were putatively identified and uncovered. Bu-shen-Huo-xue formula (BSHX) which was frequently used for treating CKD, was used as the case to demonstrate reliability of our proposed approach. The results show that BSHX has the therapeutic effect by using multi-channel network regulation, such as regulating the coagulation and fibrinolytic balance, and the expression of inflammatory factors, inhibiting abnormal ECM accumulation. Tanshinone IIA, rhein, curcumin, calycosin and quercetin may be potential effective ingredients of BSHX. This research shows that the integration approach can be an effective means for discovering active substances and revealing their pharmacological mechanisms of TCM.