Adolescent inhalant abuse leads to other drug use and impaired growth; implications for diagnosis.

PubMed

Crossin, Rose; Cairney, Sheree; Lawrence, Andrew J; Duncan, Jhodie R

2017-02-01

Abuse of inhalants containing the volatile solvent toluene is a significant public health issue, especially for adolescent and Indigenous communities. Adolescent inhalant abuse can lead to chronic health issues and may initiate a trajectory towards further drug use. Identification of at-risk individuals is difficult and diagnostic tools are limited primarily to measurement of serum toluene. Our objective was to identify the effects of adolescent inhalant abuse on subsequent drug use and growth parameters, and to test the predictive power of growth parameters as a diagnostic measure for inhalant abuse. We retrospectively analysed drug use and growth data from 118 Indigenous males; 86 chronically sniffed petrol as adolescents. Petrol sniffing was the earliest drug used (mean 13 years) and increased the likelihood and earlier use of other drugs. Petrol sniffing significantly impaired height and weight and was associated with meeting 'failure to thrive' criteria; growth diagnostically out-performed serum toluene. Adolescent inhalant abuse increases the risk for subsequent and earlier drug use. It also impairs growth such that individuals meet 'failure to thrive' criteria, representing an improved diagnostic model for inhalant abuse. Implications for Public Health: Improved diagnosis of adolescent inhalant abuse may lead to earlier detection and enhanced health outcomes. © 2016 The Authors.

Chemistry challenges in lead optimization: silicon isosteres in drug discovery.

PubMed

Showell, Graham A; Mills, John S

2003-06-15

During the lead optimization phase of drug discovery projects, the factors contributing to subsequent failure might include poor portfolio decision-making and a sub-optimal intellectual property (IP) position. The pharmaceutical industry has an ongoing need for new, safe medicines with a genuine biomedical benefit, a clean IP position and commercial viability. Inherent drug-like properties and chemical tractability are also essential for the smooth development of such agents. The introduction of bioisosteres, to improve the properties of a molecule and obtain new classes of compounds without prior art in the patent literature, is a key strategy used by medicinal chemists during the lead optimization process. Sila-substitution (C/Si exchange) of existing drugs is an approach to search for new drug-like candidates that have beneficial biological properties and a clear IP position. Some of the fundamental differences between carbon and silicon can lead to marked alterations in the physicochemical and biological properties of the silicon-containing analogues and the resulting benefits can be exploited in the drug design process.

Knowledge-Based, Central Nervous System (CNS) Lead Selection and Lead Optimization for CNS Drug Discovery

PubMed Central

2011-01-01

The central nervous system (CNS) is the major area that is affected by aging. Alzheimer’s disease (AD), Parkinson’s disease (PD), brain cancer, and stroke are the CNS diseases that will cost trillions of dollars for their treatment. Achievement of appropriate blood–brain barrier (BBB) penetration is often considered a significant hurdle in the CNS drug discovery process. On the other hand, BBB penetration may be a liability for many of the non-CNS drug targets, and a clear understanding of the physicochemical and structural differences between CNS and non-CNS drugs may assist both research areas. Because of the numerous and challenging issues in CNS drug discovery and the low success rates, pharmaceutical companies are beginning to deprioritize their drug discovery efforts in the CNS arena. Prompted by these challenges and to aid in the design of high-quality, efficacious CNS compounds, we analyzed the physicochemical property and the chemical structural profiles of 317 CNS and 626 non-CNS oral drugs. The conclusions derived provide an ideal property profile for lead selection and the property modification strategy during the lead optimization process. A list of substructural units that may be useful for CNS drug design was also provided here. A classification tree was also developed to differentiate between CNS drugs and non-CNS oral drugs. The combined analysis provided the following guidelines for designing high-quality CNS drugs: (i) topological molecular polar surface area of <76 Å2 (25–60 Å2), (ii) at least one (one or two, including one aliphatic amine) nitrogen, (iii) fewer than seven (two to four) linear chains outside of rings, (iv) fewer than three (zero or one) polar hydrogen atoms, (v) volume of 740–970 Å3, (vi) solvent accessible surface area of 460–580 Å2, and (vii) positive QikProp parameter CNS. The ranges within parentheses may be used during lead optimization. One violation to this proposed profile may be acceptable. The

Neoclassic drug discovery: the case for lead generation using phenotypic and functional approaches.

PubMed

Lee, Jonathan A; Berg, Ellen L

2013-12-01

Innovation and new molecular entity production by the pharmaceutical industry has been below expectations. Surprisingly, more first-in-class small-molecule drugs approved by the U.S. Food and Drug Administration (FDA) between 1999 and 2008 were identified by functional phenotypic lead generation strategies reminiscent of pre-genomics pharmacology than contemporary molecular targeted strategies that encompass the vast majority of lead generation efforts. This observation, in conjunction with the difficulty in validating molecular targets for drug discovery, has diminished the impact of the "genomics revolution" and has led to a growing grassroots movement and now broader trend in pharma to reconsider the use of modern physiology-based or phenotypic drug discovery (PDD) strategies. This "From the Guest Editors" column provides an introduction and overview of the two-part special issues of Journal of Biomolecular Screening on PDD. Terminology and the business case for use of PDD are defined. Key issues such as assay performance, chemical optimization, target identification, and challenges to the organization and implementation of PDD are discussed. Possible solutions for these challenges and a new neoclassic vision for PDD that combines phenotypic and functional approaches with technology innovations resulting from the genomics-driven era of target-based drug discovery (TDD) are also described. Finally, an overview of the manuscripts in this special edition is provided.

Modern drug discovery technologies: opportunities and challenges in lead discovery.

PubMed

Guido, Rafael V C; Oliva, Glaucius; Andricopulo, Adriano D

2011-12-01

The identification of promising hits and the generation of high quality leads are crucial steps in the early stages of drug discovery projects. The definition and assessment of both chemical and biological space have revitalized the screening process model and emphasized the importance of exploring the intrinsic complementary nature of classical and modern methods in drug research. In this context, the widespread use of combinatorial chemistry and sophisticated screening methods for the discovery of lead compounds has created a large demand for small organic molecules that act on specific drug targets. Modern drug discovery involves the employment of a wide variety of technologies and expertise in multidisciplinary research teams. The synergistic effects between experimental and computational approaches on the selection and optimization of bioactive compounds emphasize the importance of the integration of advanced technologies in drug discovery programs. These technologies (VS, HTS, SBDD, LBDD, QSAR, and so on) are complementary in the sense that they have mutual goals, thereby the combination of both empirical and in silico efforts is feasible at many different levels of lead optimization and new chemical entity (NCE) discovery. This paper provides a brief perspective on the evolution and use of key drug design technologies, highlighting opportunities and challenges.

Analysis of National Drug Code Identifiers in Ambulatory E-Prescribing.

PubMed

Dhavle, Ajit A; Ward-Charlerie, Stacy; Rupp, Michael T; Amin, Vishal P; Ruiz, Joshua

2015-11-01

Communication of an accurate and interpretable drug identifier between prescriber and pharmacist is critically important for realizing the potential benefits of electronic prescribing (e-prescribing) while minimizing its risk. The National Drug Code (NDC) is the most commonly used codified drug identifier in ambulatory care e-prescribing, but concerns have been raised regarding its use for this purpose.  To (a) assess the frequency of NDC identifier transmission in ambulatory e-prescribing; (b) characterize the type of NDC identifier transmitted (representative, repackaged, obsolete, private label, and unit dose); and (c) assess the level of agreement between drug descriptions corresponding to NDC identifiers in electronic prescriptions (e-prescriptions) and the free-text drug descriptions that were entered by prescribers.  We analyzed a sample of 49,997 e-prescriptions that were transmitted by ambulatory care prescribers to outlets of a national retail drugstore chain during a single day in April 2014. The First Databank MedKnowledge drug database was used as the primary reference data base to assess the frequency and types of NDC numbers in the e-prescription messages. The FDA's Comprehensive NDC Standard Product Labeling Data Elements File and the National Library of Medicine's RxNorm data file were used as secondary and tertiary references, respectively, to identify NDC numbers that could not be located in the primary reference file. Three experienced reviewers compared the free-text drug description that had been entered by the prescriber with the drug description corresponding to the NDC number from 1 of the 3 reference database files to identify discrepancies. Two licensed pharmacists with residency training and ambulatory care experience served as final adjudicators. A total of 42,602 e-prescriptions contained a value in the NDC field, of which 42,335 (84.71%) were found in 1 of the 3 study reference databases and were thus considered to be valid NDC

Drugs from the Oceans: Marine Natural Products as Leads for Drug Discovery.

PubMed

Altmann, Karl-Heinz

2017-10-25

The marine environment harbors a vast number of species that are the source of a wide array of structurally diverse bioactive secondary metabolites. At this point in time, roughly 27'000 marine natural products are known, of which eight are (were) at the origin of seven marketed drugs, mostly for the treatment of cancer. The majority of these drugs and also of drug candidates currently undergoing clinical evaluation (excluding antibody-drug conjugates) are unmodified natural products, but synthetic chemistry has played a central role in the discovery and/or development of all but one of the approved marine-derived drugs. More than 1000 new marine natural products have been isolated per year over the last decade, but the pool of new and unique structures is far from exhausted. To fully leverage the potential offered by the structural diversity of marine-produced secondary metabolites for drug discovery will require their broad assessment for different bioactivities and the productive interplay between new fermentation technologies, synthetic organic chemistry, and medicinal chemistry, in order to secure compound supply and enable lead optimization.

Refining adverse drug reaction signals by incorporating interaction variables identified using emergent pattern mining.

PubMed

Reps, Jenna M; Aickelin, Uwe; Hubbard, Richard B

2016-02-01

To develop a framework for identifying and incorporating candidate confounding interaction terms into a regularised cox regression analysis to refine adverse drug reaction signals obtained via longitudinal observational data. We considered six drug families that are commonly associated with myocardial infarction in observational healthcare data, but where the causal relationship ground truth is known (adverse drug reaction or not). We applied emergent pattern mining to find itemsets of drugs and medical events that are associated with the development of myocardial infarction. These are the candidate confounding interaction terms. We then implemented a cohort study design using regularised cox regression that incorporated and accounted for the candidate confounding interaction terms. The methodology was able to account for signals generated due to confounding and a cox regression with elastic net regularisation correctly ranking the drug families known to be true adverse drug reactions above those that are not. This was not the case without the inclusion of the candidate confounding interaction terms, where confounding leads to a non-adverse drug reaction being ranked highest. The methodology is efficient, can identify high-order confounding interactions and does not require expert input to specify outcome specific confounders, so it can be applied for any outcome of interest to quickly refine its signals. The proposed method shows excellent potential to overcome some forms of confounding and therefore reduce the false positive rate for signal analysis using longitudinal data. Copyright © 2015 Elsevier Ltd. All rights reserved.

Structure-Guided Lead Optimization of Triazolopyrimidine-Ring Substituents Identifies Potent Plasmodium falciparum Dihydroorotate Dehydrogenase Inhibitors with Clinical Candidate Potential

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coteron, Jose M.; Marco, Maria; Esquivias, Jorge

2012-02-27

Drug therapy is the mainstay of antimalarial therapy, yet current drugs are threatened by the development of resistance. In an effort to identify new potential antimalarials, we have undertaken a lead optimization program around our previously identified triazolopyrimidine-based series of Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH) inhibitors. The X-ray structure of PfDHODH was used to inform the medicinal chemistry program allowing the identification of a potent and selective inhibitor (DSM265) that acts through DHODH inhibition to kill both sensitive and drug resistant strains of the parasite. This compound has similar potency to chloroquine in the humanized SCID mouse P. falciparum model,more » can be synthesized by a simple route, and rodent pharmacokinetic studies demonstrated it has excellent oral bioavailability, a long half-life and low clearance. These studies have identified the first candidate in the triazolopyrimidine series to meet previously established progression criteria for efficacy and ADME properties, justifying further development of this compound toward clinical candidate status.« less

An integrated in vitro and in vivo high throughput screen identifies treatment leads for ependymoma

PubMed Central

Atkinson, Jennifer M.; Shelat, Anang A.; Carcaboso, Angel Montero; Kranenburg, Tanya A.; Arnold, Alexander; Boulos, Nidal; Wright, Karen; Johnson, Robert A.; Poppleton, Helen; Mohankumar, Kumarasamypet M.; Feau, Clementine; Phoenix, Timothy; Gibson, Paul; Zhu, Liqin; Tong, Yiai; Eden, Chris; Ellison, David W.; Priebe, Waldemar; Koul, Dimpy; Yung, W. K. Alfred; Gajjar, Amar; Stewart, Clinton F.; Guy, R. Kip; Gilbertson, Richard J.

2011-01-01

Summary Using a mouse model of ependymoma—a chemoresistant brain tumor—we combined multi-cell high-throughput screening (HTS), kinome-wide binding assays, and in vivo efficacy studies, to identify potential treatments with predicted toxicity against neural stem cells (NSC). We identified kinases within the insulin signaling pathway and centrosome cycle as regulators of ependymoma cell proliferation, and their corresponding inhibitors as potential therapies. FDA approved drugs not currently used to treat ependymoma were also identified that posses selective toxicity against ependymoma cells relative to normal NSCs both in vitro and in vivo e.g., 5-fluoruracil. Our comprehensive approach advances understanding of the biology and treatment of ependymoma including the discovery of several treatment leads for immediate clinical translation. PMID:21907928

Leading change: 1--identifying the issue.

PubMed

Kerridge, Joanna

To enable sustainable change, nurses need to take the lead in managing it. Recent national initiatives have emphasised the importance of frontline staff in service improvement. The ability to influence and manage change has been identified as an essential skill for delivering new models of care. This article is the first in a three-part series designed to help nurses at all levels develop the knowledge and skills they will need to initiate and manage change. This article focuses on identifying what needs to be changed and why.

Transcriptomic profiling and quantitative high-throughput (qHTS) drug screening of CDH1 deficient hereditary diffuse gastric cancer (HDGC) cells identify treatment leads for familial gastric cancer.

PubMed

Chen, Ina; Mathews-Greiner, Lesley; Li, Dandan; Abisoye-Ogunniyan, Abisola; Ray, Satyajit; Bian, Yansong; Shukla, Vivek; Zhang, Xiaohu; Guha, Raj; Thomas, Craig; Gryder, Berkley; Zacharia, Athina; Beane, Joal D; Ravichandran, Sarangan; Ferrer, Marc; Rudloff, Udo

2017-05-01

Patients with hereditary diffuse gastric cancer (HDGC), a cancer predisposition syndrome associated with germline mutations of the CDH1 (E-cadherin) gene, have few effective treatment options. Despite marked differences in natural history, histopathology, and genetic profile to patients afflicted by sporadic gastric cancer, patients with HDGC receive, in large, identical systemic regimens. The lack of a robust preclinical in vitro system suitable for effective drug screening has been one of the obstacles to date which has hampered therapeutic advances in this rare disease. In order to identify therapeutic leads selective for the HDGC subtype of gastric cancer, we compared gene expression profiles and drug phenotype derived from an oncology library of 1912 compounds between gastric cancer cells established from a patient with metastatic HDGC harboring a c.1380delA CDH1 germline variant and sporadic gastric cancer cells. Unsupervised hierarchical cluster analysis shows select gene expression alterations in c.1380delA CDH1 SB.mhdgc-1 cells compared to a panel of sporadic gastric cancer cell lines with enrichment of ERK1-ERK2 (extracellular signal regulated kinase) and IP3 (inositol trisphosphate)/DAG (diacylglycerol) signaling as the top networks in c.1380delA SB.mhdgc-1 cells. Intracellular phosphatidylinositol intermediaries were increased upon direct measure in c.1380delA CDH1 SB.mhdgc-1 cells. Differential high-throughput drug screening of c.1380delA CDH1 SB.mhdgc-1 versus sporadic gastric cancer cells identified several compound classes with enriched activity in c.1380 CDH1 SB.mhdgc-1 cells including mTOR (Mammalian Target Of Rapamycin), MEK (Mitogen-Activated Protein Kinase), c-Src kinase, FAK (Focal Adhesion Kinase), PKC (Protein Kinase C), or TOPO2 (Topoisomerase II) inhibitors. Upon additional drug response testing, dual PI3K (Phosphatidylinositol 3-Kinase)/mTOR and topoisomerase 2A inhibitors displayed up to >100-fold increased activity in hereditary c.1380

A genome-wide RNAi screen identifies novel targets of neratinib resistance leading to identification of potential drug resistant genetic markers.

PubMed

Seyhan, Attila A; Varadarajan, Usha; Choe, Sung; Liu, Wei; Ryan, Terence E

2012-04-01

Neratinib (HKI-272) is a small molecule tyrosine kinase inhibitor of the ErbB receptor family currently in Phase III clinical trials. Despite its efficacy, the mechanism of potential cellular resistance to neratinib and genes involved with it remains unknown. We have used a pool-based lentiviral genome-wide functional RNAi screen combined with a lethal dose of neratinib to discover chemoresistant interactions with neratinib. Our screen has identified a collection of genes whose inhibition by RNAi led to neratinib resistance including genes involved in oncogenesis (e.g. RAB33A, RAB6A and BCL2L14), transcription factors (e.g. FOXP4, TFEC, ZNF), cellular ion transport (e.g. CLIC3, TRAPPC2P1, P2RX2), protein ubiquitination (e.g. UBL5), cell cycle (e.g. CCNF), and genes known to interact with breast cancer-associated genes (e.g. CCNF, FOXP4, TFEC, several ZNF factors, GNA13, IGFBP1, PMEPA1, SOX5, RAB33A, RAB6A, FXR1, DDO, TFEC, OLFM2). The identification of novel mediators of cellular resistance to neratinib could lead to the identification of new or neoadjuvant drug targets. Their use as patient or treatment selection biomarkers could make the application of anti-ErbB therapeutics more clinically effective.

Insights into Integrated Lead Generation and Target Identification in Malaria and Tuberculosis Drug Discovery

PubMed Central

2017-01-01

Conspectus New, safe and effective drugs are urgently needed to treat and control malaria and tuberculosis, which affect millions of people annually. However, financial return on investment in the poor settings where these diseases are mostly prevalent is very minimal to support market-driven drug discovery and development. Moreover, the imminent loss of therapeutic lifespan of existing therapies due to evolution and spread of drug resistance further compounds the urgency to identify novel effective drugs. However, the advent of new public–private partnerships focused on tropical diseases and the recent release of large data sets by pharmaceutical companies on antimalarial and antituberculosis compounds derived from phenotypic whole cell high throughput screening have spurred renewed interest and opened new frontiers in malaria and tuberculosis drug discovery. This Account recaps the existing challenges facing antimalarial and antituberculosis drug discovery, including limitations associated with experimental animal models as well as biological complexities intrinsic to the causative pathogens. We enlist various highlights from a body of work within our research group aimed at identifying and characterizing new chemical leads, and navigating these challenges to contribute toward the global drug discovery and development pipeline in malaria and tuberculosis. We describe a catalogue of in-house efforts toward deriving safe and efficacious preclinical drug development candidates via cell-based medicinal chemistry optimization of phenotypic whole-cell medium and high throughput screening hits sourced from various small molecule chemical libraries. We also provide an appraisal of target-based screening, as invoked in our laboratory for mechanistic evaluation of the hits generated, with particular focus on the enzymes within the de novo pyrimidine biosynthetic and hemoglobin degradation pathways, the latter constituting a heme detoxification process and an associated

Potent Plasmodium falciparum gametocytocidal activity of diaminonaphthoquinones, lead antimalarial chemotypes identified in an antimalarial compound screen.

PubMed

Tanaka, Takeshi Q; Guiguemde, W Armand; Barnett, David S; Maron, Maxim I; Min, Jaeki; Connelly, Michele C; Suryadevara, Praveen Kumar; Guy, R Kiplin; Williamson, Kim C

2015-03-01

Forty percent of the world's population is threatened by malaria, which is caused by Plasmodium parasites and results in an estimated 200 million clinical cases and 650,000 deaths each year. Drug resistance has been reported for all commonly used antimalarials and has prompted screens to identify new drug candidates. However, many of these new candidates have not been evaluated against the parasite stage responsible for transmission, gametocytes. If Plasmodium falciparum gametocytes are not eliminated, patients continue to spread malaria for weeks after asexual parasite clearance. Asymptomatic individuals can also harbor gametocyte burdens sufficient for transmission, and a safe, effective gametocytocidal agent could also be used in community-wide malaria control programs. Here, we identify 15 small molecules with nanomolar activity against late-stage gametocytes. Fourteen are diaminonaphthoquinones (DANQs), and one is a 2-imino-benzo[d]imidazole (IBI). One of the DANQs identified, SJ000030570, is a lead antimalarial candidate. In contrast, 94% of the 650 compounds tested are inactive against late-stage gametocytes. Consistent with the ineffectiveness of most approved antimalarials against gametocytes, of the 19 novel compounds with activity against known anti-asexual-stage targets, only 3 had any strong effect on gametocyte viability. These data demonstrate the distinct biology of the transmission stages and emphasize the importance of screening for gametocytocidal activity. The potent gametocytocidal activity of DANQ and IBI coupled with their efficacy against asexual parasites provides leads for the development of antimalarials with the potential to prevent both the symptoms and the spread of malaria. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Emergence of Chinese drug discovery research: impact of hit and lead identification.

PubMed

Zhou, Caihong; Zhou, Yan; Wang, Jia; Zhu, Yue; Deng, Jiejie; Wang, Ming-Wei

2015-03-01

The identification of hits and the generation of viable leads is an early and yet crucial step in drug discovery. In the West, the main players of drug discovery are pharmaceutical and biotechnology companies, while in China, academic institutions remain central in the field of drug discovery. There has been a tremendous amount of investment from the public as well as private sectors to support infrastructure buildup and expertise consolidation relative to drug discovery and development in the past two decades. A large-scale compound library has been established in China, and a series of high-impact discoveries of lead compounds have been made by integrating information obtained from different technology-based strategies. Natural products are a major source in China's drug discovery efforts. Knowledge has been enhanced via disruptive breakthroughs such as the discovery of Boc5 as a nonpeptidic agonist of glucagon-like peptide 1 receptor (GLP-1R), one of the class B G protein-coupled receptors (GPCRs). Most of the original hit identification and lead generation were carried out by academic institutions, including universities and specialized research institutes. The Chinese pharmaceutical industry is gradually transforming itself from manufacturing low-end generics and active pharmaceutical ingredients to inventing new drugs. © 2014 Society for Laboratory Automation and Screening.

Identifying Drug-Drug Interactions by Data Mining: A Pilot Study of Warfarin-Associated Drug Interactions.

PubMed

Hansen, Peter Wæde; Clemmensen, Line; Sehested, Thomas S G; Fosbøl, Emil Loldrup; Torp-Pedersen, Christian; Køber, Lars; Gislason, Gunnar H; Andersson, Charlotte

2016-11-01

Knowledge about drug-drug interactions commonly arises from preclinical trials, from adverse drug reports, or based on knowledge of mechanisms of action. Our aim was to investigate whether drug-drug interactions were discoverable without prior hypotheses using data mining. We focused on warfarin-drug interactions as the prototype. We analyzed altered prothrombin time (measured as international normalized ratio [INR]) after initiation of a novel prescription in previously INR-stable warfarin-treated patients with nonvalvular atrial fibrillation. Data sets were retrieved from clinical work. Random forest (a machine-learning method) was set up to predict altered INR levels after novel prescriptions. The most important drug groups from the analysis were further investigated using logistic regression in a new data set. Two hundred and twenty drug groups were analyzed in 61 190 novel prescriptions. We rediscovered 2 drug groups having known interactions (β-lactamase-resistant penicillins [dicloxacillin] and carboxamide derivatives) and 3 antithrombotic/anticoagulant agents (platelet aggregation inhibitors excluding heparin, direct thrombin inhibitors [dabigatran etexilate], and heparins) causing decreasing INR. Six drug groups with known interactions were rediscovered causing increasing INR (antiarrhythmics class III [amiodarone], other opioids [tramadol], glucocorticoids, triazole derivatives, and combinations of penicillins, including β-lactamase inhibitors) and two had a known interaction in a closely related drug group (oripavine derivatives [buprenorphine] and natural opium alkaloids). Antipropulsives had an unknown signal of increasing INR. We were able to identify known warfarin-drug interactions without a prior hypothesis using clinical registries. Additionally, we discovered a few potentially novel interactions. This opens up for the use of data mining to discover unknown drug-drug interactions in cardiovascular medicine. © 2016 American Heart Association

In Silico Repositioning-Chemogenomics Strategy Identifies New Drugs with Potential Activity against Multiple Life Stages of Schistosoma mansoni

PubMed Central

Neves, Bruno J.; Braga, Rodolpho C.; Bezerra, José C. B.; Cravo, Pedro V. L.; Andrade, Carolina H.

2015-01-01

Morbidity and mortality caused by schistosomiasis are serious public health problems in developing countries. Because praziquantel is the only drug in therapeutic use, the risk of drug resistance is a concern. In the search for new schistosomicidal drugs, we performed a target-based chemogenomics screen of a dataset of 2,114 proteins to identify drugs that are approved for clinical use in humans that may be active against multiple life stages of Schistosoma mansoni. Each of these proteins was treated as a potential drug target, and its amino acid sequence was used to interrogate three databases: Therapeutic Target Database (TTD), DrugBank and STITCH. Predicted drug-target interactions were refined using a combination of approaches, including pairwise alignment, conservation state of functional regions and chemical space analysis. To validate our strategy, several drugs previously shown to be active against Schistosoma species were correctly predicted, such as clonazepam, auranofin, nifedipine, and artesunate. We were also able to identify 115 drugs that have not yet been experimentally tested against schistosomes and that require further assessment. Some examples are aprindine, gentamicin, clotrimazole, tetrabenazine, griseofulvin, and cinnarizine. In conclusion, we have developed a systematic and focused computer-aided approach to propose approved drugs that may warrant testing and/or serve as lead compounds for the design of new drugs against schistosomes. PMID:25569258

Identifying drugs that cause acute thrombocytopenia: an analysis using 3 distinct methods

PubMed Central

Reese, Jessica A.; Li, Xiaoning; Hauben, Manfred; Aster, Richard H.; Bougie, Daniel W.; Curtis, Brian R.; George, James N.

2010-01-01

Drug-induced immune thrombocytopenia (DITP) is often suspected in patients with acute thrombocytopenia unexplained by other causes, but documenting that a drug is the cause of thrombocytopenia can be challenging. To provide a resource for diagnosis of DITP and for drug safety surveillance, we analyzed 3 distinct methods for identifying drugs that may cause thrombocytopenia. (1) Published case reports of DITP have described 253 drugs suspected of causing thrombocytopenia; using defined clinical criteria, 87 (34%) were identified with evidence that the drug caused thrombocytopenia. (2) Serum samples from patients with suspected DITP were tested for 202 drugs; drug-dependent, platelet-reactive antibodies were identified for 67 drugs (33%). (3) The Food and Drug Administration's Adverse Event Reporting System database was searched for drugs associated with thrombocytopenia by use of data mining algorithms; 1444 drugs had at least 1 report associated with thrombocytopenia, and 573 (40%) drugs demonstrated a statistically distinctive reporting association with thrombocytopenia. Among 1468 drugs suspected of causing thrombocytopenia, 102 were evaluated by all 3 methods, and 23 of these 102 drugs had evidence for an association with thrombocytopenia by all 3 methods. Multiple methods, each with a distinct perspective, can contribute to the identification of drugs that can cause thrombocytopenia. PMID:20530792

2010 drug packaging review: identifying problems to prevent errors.

PubMed

2011-06-01

Prescrire's analyses showed that the quality of drug packaging in 2010 still left much to be desired. Potentially dangerous packaging remains a significant problem: unclear labelling is source of medication errors; dosing devices for some psychotropic drugs create a risk of overdose; child-proof caps are often lacking; and too many patient information leaflets are misleading or difficult to understand. Everything that is needed for safe drug packaging is available; it is now up to regulatory agencies and drug companies to act responsibly. In the meantime, health professionals can help their patients by learning to identify the pitfalls of drug packaging and providing safe information to help prevent medication errors.

Screening approach for identifying candidate drugs and drug-drug interactions related to hip fracture risk in persons with Alzheimer disease.

PubMed

Tolppanen, Anna-Maija; Taipale, Heidi; Koponen, Marjaana; Tanskanen, Antti; Lavikainen, Piia; Paananen, Jussi; Tiihonen, Jari; Hartikainen, Sirpa

2017-08-01

To assess whether a "drugome-wide" screen with case-crossover design is a feasible approach for identifying candidate drugs and drug-drug interactions. All community-dwelling residents of Finland who received a clinically verified Alzheimer disease diagnosis in 2005 to 2011 and experienced incident hip fracture (HF) afterwards (N = 4851). Three scenarios were used to test the sensitivity of this approach (1) hazard period 0 to 30 and control period 31 to 61 days before HF, (2) hazard period 0 to 30 and control period 336 to 366 days before HF, and (3) hazard period 0 to 14 and control period 16 to 30 days before HF. Nine, 44, and 5 drugs were associated with increased HF risk and 8, 23, and 4 with decreased risk in scenarios 1, 2, and 3, respectively. Six drugs were identified with scenario 1 only and 54 and 1 with scenarios 2 and 3, respectively. Only six drugs (metoprolol, simvastatin, trimethoprim, codeine combinations, fentanyl, and paracetamol) were associated with HF in all scenarios, four with 1 and 2 (cefalexin, buprenorphine, olanzapine, and memantine), and one with 1 and 3 (enalapril) or 2 and 3 (ciprofloxacin). The direction of associations was the same in all/both scenarios. The interaction results were equally versatile, with hydroxocobalamin*oxazepam being the only interaction observed in all scenarios. Case-crossover analysis is a potential approach for identifying candidate drugs and drug-drug interactions associated with adverse events as it implicitly controls for fixed confounders. The results are highly dependent on applied hazard and control periods, but the choice of periods can help in targeting the analyses to different phases of drug use. Copyright © 2017 John Wiley & Sons, Ltd.

Chemically triggered drug release from an antibody-drug conjugate leads to potent antitumour activity in mice.

PubMed

Rossin, Raffaella; Versteegen, Ron M; Wu, Jeremy; Khasanov, Alisher; Wessels, Hans J; Steenbergen, Erik J; Ten Hoeve, Wolter; Janssen, Henk M; van Onzen, Arthur H A M; Hudson, Peter J; Robillard, Marc S

2018-05-04

Current antibody-drug conjugates (ADCs) target internalising receptors on cancer cells leading to intracellular drug release. Typically, only a subset of patients with solid tumours has sufficient expression of such a receptor, while there are suitable non-internalising receptors and stroma targets. Here, we demonstrate potent therapy in murine tumour models using a non-internalising ADC that releases its drugs upon a click reaction with a chemical activator, which is administered in a second step. This was enabled by the development of a diabody-based ADC with a high tumour uptake and very low retention in healthy tissues, allowing systemic administration of the activator 2 days later, leading to efficient and selective activation throughout the tumour. In contrast, the analogous ADC comprising the protease-cleavable linker used in the FDA approved ADC Adcetris is not effective in these tumour models. This first-in-class ADC holds promise for a broader applicability of ADCs across patient populations.

UniDrug-target: a computational tool to identify unique drug targets in pathogenic bacteria.

PubMed

Chanumolu, Sree Krishna; Rout, Chittaranjan; Chauhan, Rajinder S

2012-01-01

Targeting conserved proteins of bacteria through antibacterial medications has resulted in both the development of resistant strains and changes to human health by destroying beneficial microbes which eventually become breeding grounds for the evolution of resistances. Despite the availability of more than 800 genomes sequences, 430 pathways, 4743 enzymes, 9257 metabolic reactions and protein (three-dimensional) 3D structures in bacteria, no pathogen-specific computational drug target identification tool has been developed. A web server, UniDrug-Target, which combines bacterial biological information and computational methods to stringently identify pathogen-specific proteins as drug targets, has been designed. Besides predicting pathogen-specific proteins essentiality, chokepoint property, etc., three new algorithms were developed and implemented by using protein sequences, domains, structures, and metabolic reactions for construction of partial metabolic networks (PMNs), determination of conservation in critical residues, and variation analysis of residues forming similar cavities in proteins sequences. First, PMNs are constructed to determine the extent of disturbances in metabolite production by targeting a protein as drug target. Conservation of pathogen-specific protein's critical residues involved in cavity formation and biological function determined at domain-level with low-matching sequences. Last, variation analysis of residues forming similar cavities in proteins sequences from pathogenic versus non-pathogenic bacteria and humans is performed. The server is capable of predicting drug targets for any sequenced pathogenic bacteria having fasta sequences and annotated information. The utility of UniDrug-Target server was demonstrated for Mycobacterium tuberculosis (H37Rv). The UniDrug-Target identified 265 mycobacteria pathogen-specific proteins, including 17 essential proteins which can be potential drug targets. UniDrug-Target is expected to accelerate

A physarum-inspired prize-collecting steiner tree approach to identify subnetworks for drug repositioning.

PubMed

Sun, Yahui; Hameed, Pathima Nusrath; Verspoor, Karin; Halgamuge, Saman

2016-12-05

Drug repositioning can reduce the time, costs and risks of drug development by identifying new therapeutic effects for known drugs. It is challenging to reposition drugs as pharmacological data is large and complex. Subnetwork identification has already been used to simplify the visualization and interpretation of biological data, but it has not been applied to drug repositioning so far. In this paper, we fill this gap by proposing a new Physarum-inspired Prize-Collecting Steiner Tree algorithm to identify subnetworks for drug repositioning. Drug Similarity Networks (DSN) are generated using the chemical, therapeutic, protein, and phenotype features of drugs. In DSNs, vertex prizes and edge costs represent the similarities and dissimilarities between drugs respectively, and terminals represent drugs in the cardiovascular class, as defined in the Anatomical Therapeutic Chemical classification system. A new Physarum-inspired Prize-Collecting Steiner Tree algorithm is proposed in this paper to identify subnetworks. We apply both the proposed algorithm and the widely-used GW algorithm to identify subnetworks in our 18 generated DSNs. In these DSNs, our proposed algorithm identifies subnetworks with an average Rand Index of 81.1%, while the GW algorithm can only identify subnetworks with an average Rand Index of 64.1%. We select 9 subnetworks with high Rand Index to find drug repositioning opportunities. 10 frequently occurring drugs in these subnetworks are identified as candidates to be repositioned for cardiovascular diseases. We find evidence to support previous discoveries that nitroglycerin, theophylline and acarbose may be able to be repositioned for cardiovascular diseases. Moreover, we identify seven previously unknown drug candidates that also may interact with the biological cardiovascular system. These discoveries show our proposed Prize-Collecting Steiner Tree approach as a promising strategy for drug repositioning.

Drug Repurposing Screening Identifies Novel Compounds That Effectively Inhibit Toxoplasma gondii Growth

PubMed Central

Dittmar, Ashley J.; Drozda, Allison A.

2016-01-01

ABSTRACT The urgent need to develop new antimicrobial therapies has spawned the development of repurposing screens in which well-studied drugs and other types of compounds are tested for potential off-label uses. As a proof-of-principle screen to identify compounds effective against Toxoplasma gondii, we screened a collection of 1,120 compounds for the ability to significantly reduce Toxoplasma replication. A total of 94 compounds blocked parasite replication with 50% inhibitory concentrations of <5 µM. A significant number of these compounds are established inhibitors of dopamine or estrogen signaling. Follow-up experiments with the dopamine receptor inhibitor pimozide revealed that the drug impacted both parasite invasion and replication but did so independently of inhibition of dopamine or other neurotransmitter receptor signaling. Tamoxifen, which is an established inhibitor of the estrogen receptor, also reduced parasite invasion and replication. Even though Toxoplasma can activate the estrogen receptor, tamoxifen inhibits parasite growth independently of this transcription factor. Tamoxifen is also a potent inducer of autophagy, and we find that the drug stimulates recruitment of the autophagy marker light chain 3-green fluorescent protein onto the membrane of the vacuolar compartment in which the parasite resides and replicates. In contrast to other antiparasitic drugs, including pimozide, tamoxifen treatment of infected cells leads to a time-dependent elimination of intracellular parasites. Taken together, these data suggest that tamoxifen restricts Toxoplasma growth by inducing xenophagy or autophagic destruction of this obligate intracellular parasite. IMPORTANCE There is an urgent need to develop new therapies to treat microbial infections, and the repurposing of well-characterized compounds is emerging as one approach to achieving this goal. Using the protozoan parasite Toxoplasma gondii, we screened a library of 1,120 compounds and identified several

Lead Phytochemicals for Anticancer Drug Development

PubMed Central

Singh, Sukhdev; Sharma, Bhupender; Kanwar, Shamsher S.; Kumar, Ashok

2016-01-01

Cancer is a serious concern at present. A large number of patients die each year due to cancer illnesses in spite of several interventions available. Development of an effective and side effects lacking anticancer therapy is the trending research direction in healthcare pharmacy. Chemical entities present in plants proved to be very potential in this regard. Bioactive phytochemicals are preferential as they pretend differentially on cancer cells only, without altering normal cells. Carcinogenesis is a complex process and includes multiple signaling events. Phytochemicals are pleiotropic in their function and target these events in multiple manners; hence they are most suitable candidate for anticancer drug development. Efforts are in progress to develop lead candidates from phytochemicals those can block or retard the growth of cancer without any side effect. Several phytochemicals manifest anticancer function in vitro and in vivo. This article deals with these lead phytomolecules with their action mechanisms on nuclear and cellular factors involved in carcinogenesis. Additionally, druggability parameters and clinical development of anticancer phytomolecules have also been discussed. PMID:27877185

Systems pharmacology identifies drug targets for Stargardt disease–associated retinal degeneration

PubMed Central

Chen, Yu; Palczewska, Grazyna; Mustafi, Debarshi; Golczak, Marcin; Dong, Zhiqian; Sawada, Osamu; Maeda, Tadao; Maeda, Akiko; Palczewski, Krzysztof

2013-01-01

A systems pharmacological approach that capitalizes on the characterization of intracellular signaling networks can transform our understanding of human diseases and lead to therapy development. Here, we applied this strategy to identify pharmacological targets for the treatment of Stargardt disease, a severe juvenile form of macular degeneration. Diverse GPCRs have previously been implicated in neuronal cell survival, and crosstalk between GPCR signaling pathways represents an unexplored avenue for pharmacological intervention. We focused on this receptor family for potential therapeutic interventions in macular disease. Complete transcriptomes of mouse and human samples were analyzed to assess the expression of GPCRs in the retina. Focusing on adrenergic (AR) and serotonin (5-HT) receptors, we found that adrenoceptor α 2C (Adra2c) and serotonin receptor 2a (Htr2a) were the most highly expressed. Using a mouse model of Stargardt disease, we found that pharmacological interventions that targeted both GPCR signaling pathways and adenylate cyclases (ACs) improved photoreceptor cell survival, preserved photoreceptor function, and attenuated the accumulation of pathological fluorescent deposits in the retina. These findings demonstrate a strategy for the identification of new drug candidates and FDA-approved drugs for the treatment of monogenic and complex diseases. PMID:24231350

Using Social Media Data to Identify Potential Candidates for Drug Repurposing: A Feasibility Study.

PubMed

Rastegar-Mojarad, Majid; Liu, Hongfang; Nambisan, Priya

2016-06-16

Drug repurposing (defined as discovering new indications for existing drugs) could play a significant role in drug development, especially considering the declining success rates of developing novel drugs. Typically, new indications for existing medications are identified by accident. However, new technologies and a large number of available resources enable the development of systematic approaches to identify and validate drug-repurposing candidates. Patients today report their experiences with medications on social media and reveal side effects as well as beneficial effects of those medications. Our aim was to assess the feasibility of using patient reviews from social media to identify potential candidates for drug repurposing. We retrieved patient reviews of 180 medications from an online forum, WebMD. Using dictionary-based and machine learning approaches, we identified disease names in the reviews. Several publicly available resources were used to exclude comments containing known indications and adverse drug effects. After manually reviewing some of the remaining comments, we implemented a rule-based system to identify beneficial effects. The dictionary-based system and machine learning system identified 2178 and 6171 disease names respectively in 64,616 patient comments. We provided a list of 10 common patterns that patients used to report any beneficial effects or uses of medication. After manually reviewing the comments tagged by our rule-based system, we identified five potential drug repurposing candidates. To our knowledge, this is the first study to consider using social media data to identify drug-repurposing candidates. We found that even a rule-based system, with a limited number of rules, could identify beneficial effect mentions in patient comments. Our preliminary study shows that social media has the potential to be used in drug repurposing.

Hot spot analysis for driving the development of hits into leads in fragment based drug discovery

PubMed Central

Hall, David R.; Ngan, Chi Ho; Zerbe, Brandon S.; Kozakov, Dima; Vajda, Sandor

2011-01-01

Fragment based drug design (FBDD) starts with finding fragment-sized compounds that are highly ligand efficient and can serve as a core moiety for developing high affinity leads. Although the core-bound structure of a protein facilitates the construction of leads, effective design is far from straightforward. We show that protein mapping, a computational method developed to find binding hot spots and implemented as the FTMap server, provides information that complements the fragment screening results and can drive the evolution of core fragments into larger leads with a minimal loss or, in some cases, even a gain in ligand efficiency. The method places small molecular probes, the size of organic solvents, on a dense grid around the protein, and identifies the hot spots as consensus clusters formed by clusters of several probes. The hot spots are ranked based on the number of probe clusters, which predicts the binding propensity of the subsites and hence their importance for drug design. Accordingly, with a single exception the main hot spot identified by FTMap binds the core compound found by fragment screening. The most useful information is provided by the neighboring secondary hot spots, indicating the regions where the core can be extended to increase its affinity. To quantify this information, we calculate the density of probes from mapping, which describes the binding propensity at each point, and show that the change in the correlation between a ligand position and the probe density upon extending or repositioning the core moiety predicts the expected change in ligand efficiency. PMID:22145575

How to Identify Drug Paraphernalia

MedlinePlus

... red eyes, changes in pupil size, or eye movements Items or associations that may indicate interest in illegal drugs or drug use. Clothing, jewelry, tattoos, teen slang with drug culture messages. Websites, music, or publications that glamorize drug use. Where do ...

Identifying and Preventing Health Problems among Young Drug-Misusing Offenders

ERIC Educational Resources Information Center

Bennett, Trevor; Holloway, Katy

2008-01-01

Purpose: The purpose of this paper is to identify the health problems and treatment needs of drug-misusing offenders and to draw out the implications of the findings for health education and prevention. Design/methodology/approach: This analysis is based on data collected as part of the New English and Welsh Arrestee Drug Abuse Monitoring…

Fragment screening for drug leads by weak affinity chromatography (WAC-MS).

PubMed

Ohlson, Sten; Duong-Thi, Minh-Dao

2018-02-23

Fragment-based drug discovery is an important tool for design of small molecule hit-to-lead compounds against various biological targets. Several approved drugs have been derived from an initial fragment screen and many such candidates are in various stages of clinical trials. Finding fragment hits, that are suitable for optimisation by medicinal chemists, is still a challenge as the binding between the small fragment and its target is weak in the range of mM to µM of K d and irrelevant non-specific interactions are abundant in this area of transient interactions. Fortunately, there are methods that can study weak interactions quite efficiently of which NMR, surface plasmon resonance (SPR) and X-ray crystallography are the most prominent. Now, a new technology based on zonal affinity chromatography, weak affinity chromatography (WAC), has been introduced which has remedied many of the problems with other technologies. By combining WAC with mass spectrometry (WAC-MS), it is a powerful tool to identify binders quantitatively in terms of affinity and kinetics either from fragment libraries or from complex mixtures of biological extracts. As WAC-MS can be multiplexed by analysing mixtures of fragments (20-100 fragments) in one sample, this approach yields high throughput, where a whole library of e.g. >2000 fragments can be analysed quantitatively within a day. WAC-MS is easy to perform, where the robustness and quality of HPLC is fully utilized. This review will highlight the rationale behind the application of WAC-MS for fragment screening in drug discovery. Copyright © 2018 Elsevier Inc. All rights reserved.

A Drug Combination Screen Identifies Drugs Active against Amoxicillin-Induced Round Bodies of In Vitro Borrelia burgdorferi Persisters from an FDA Drug Library

PubMed Central

Feng, Jie; Shi, Wanliang; Zhang, Shuo; Sullivan, David; Auwaerter, Paul G.; Zhang, Ying

2016-01-01

Although currently recommended antibiotics for Lyme disease such as doxycycline or amoxicillin cure the majority of the patients, about 10–20% of patients treated for Lyme disease may experience lingering symptoms including fatigue, pain, or joint and muscle aches. Under experimental stress conditions such as starvation or antibiotic exposure, Borrelia burgdorferi can develop round body forms, which are a type of persister bacteria that appear resistant in vitro to customary first-line antibiotics for Lyme disease. To identify more effective drugs with activity against the round body form of B. burgdorferi, we established a round body persister model induced by exposure to amoxicillin (50 μg/ml) and then screened the Food and Drug Administration drug library consisting of 1581 drug compounds and also 22 drug combinations using the SYBR Green I/propidium iodide viability assay. We identified 23 drug candidates that have higher activity against the round bodies of B. burgdorferi than either amoxicillin or doxycycline. Eleven individual drugs scored better than metronidazole and tinidazole which have been previously described to be active against round bodies. In this amoxicillin-induced round body model, some drug candidates such as daptomycin and clofazimine also displayed enhanced activity which was similar to a previous screen against stationary phase B. burgdorferi persisters not exposure to amoxicillin. Additional candidate drugs active against round bodies identified include artemisinin, ciprofloxacin, nifuroxime, fosfomycin, chlortetracycline, sulfacetamide, sulfamethoxypyridazine and sulfathiozole. Two triple drug combinations had the highest activity against amoxicillin-induced round bodies and stationary phase B. burgdorferi persisters: artemisinin/cefoperazone/doxycycline and sulfachlorpyridazine/daptomycin/doxycycline. These findings confirm and extend previous findings that certain drug combinations have superior activity against B. burgdorferi

A Drug Combination Screen Identifies Drugs Active against Amoxicillin-Induced Round Bodies of In Vitro Borrelia burgdorferi Persisters from an FDA Drug Library.

PubMed

Feng, Jie; Shi, Wanliang; Zhang, Shuo; Sullivan, David; Auwaerter, Paul G; Zhang, Ying

2016-01-01

Although currently recommended antibiotics for Lyme disease such as doxycycline or amoxicillin cure the majority of the patients, about 10-20% of patients treated for Lyme disease may experience lingering symptoms including fatigue, pain, or joint and muscle aches. Under experimental stress conditions such as starvation or antibiotic exposure, Borrelia burgdorferi can develop round body forms, which are a type of persister bacteria that appear resistant in vitro to customary first-line antibiotics for Lyme disease. To identify more effective drugs with activity against the round body form of B. burgdorferi, we established a round body persister model induced by exposure to amoxicillin (50 μg/ml) and then screened the Food and Drug Administration drug library consisting of 1581 drug compounds and also 22 drug combinations using the SYBR Green I/propidium iodide viability assay. We identified 23 drug candidates that have higher activity against the round bodies of B. burgdorferi than either amoxicillin or doxycycline. Eleven individual drugs scored better than metronidazole and tinidazole which have been previously described to be active against round bodies. In this amoxicillin-induced round body model, some drug candidates such as daptomycin and clofazimine also displayed enhanced activity which was similar to a previous screen against stationary phase B. burgdorferi persisters not exposure to amoxicillin. Additional candidate drugs active against round bodies identified include artemisinin, ciprofloxacin, nifuroxime, fosfomycin, chlortetracycline, sulfacetamide, sulfamethoxypyridazine and sulfathiozole. Two triple drug combinations had the highest activity against amoxicillin-induced round bodies and stationary phase B. burgdorferi persisters: artemisinin/cefoperazone/doxycycline and sulfachlorpyridazine/daptomycin/doxycycline. These findings confirm and extend previous findings that certain drug combinations have superior activity against B. burgdorferi

Synthesis, characterization and histopathological study of a lead-based Indian traditional drug: naga bhasma.

PubMed

Singh, S K; Gautam, D N S; Kumar, M; Rai, S B

2010-01-01

The aim of the present study is to prepare and characterize Naga bhasma on structural and elemental basis to address the role of the raw materials used during the preparation, compound form of the lead bhasma, nature (crystalline/amorphous) and crystallite/particle size of the drug. The study also covers the toxicological effect of the drug on albino rats. It was found that drug contains lead in nano-crystalline (~60 nm) lead sulfide form (Pb(2+)) associated with the organic contents and different nutrient elements coming from the herbs used during the preparation. Naga bhasma prepared was found to be totally safe in histopathology study on rats at a dose of 6 mg/100 g/day. The different characterization techniques used present a role model for the quality control and standardization of such kinds of herbo-metallic medicines.

Identifying housing that poisons: a critical step in eliminating childhood lead poisoning.

PubMed

Reyes, Nimia L; Wong, Lee-Yang; MacRoy, Patrick M; Curtis, Gerald; Meyer, Pamela A; Evens, Anne; Brown, Mary Jean

2006-01-01

The purpose of our study was to develop a method to identify and prioritize "high-risk" buildings in Chicago that could be targeted for childhood lead poisoning prevention activities. We defined "high-risk" buildings as those where multiple children younger than 6 years with elevated blood lead levels (BLLs) had lived and where lead hazards were previously identified on environmental inspection. By linking 1997-2003 Chicago elevated blood lead surveillance, environmental inspection, and building footprint data, we found that 49,362 children younger than 6 years with elevated BLLs lived at 30,742 buildings. Of those, 67 were "high-risk" buildings and these were associated with 994 children with elevated BLLs. On average, 15 children with elevated BLLs had lived in each building (range: 10-53, median: 13). Almost two thirds (n = 43) of the high-risk buildings had two or more referrals for inspection to the same apartment or housing unit; of those, 40 percent (n = 17) failed to maintain lead-safe status after compliance. Linking blood lead surveillance, environmental inspection, and building footprint databases allowed us to identify individual high-risk buildings. This approach prioritizes lead hazard control efforts and may help health, housing, and environmental agencies in targeting limited resources to increase lead-safe housing for children.

Combinatorial Drug Screening Identifies Ewing Sarcoma-specific Sensitivities.

PubMed

Radic-Sarikas, Branka; Tsafou, Kalliopi P; Emdal, Kristina B; Papamarkou, Theodore; Huber, Kilian V M; Mutz, Cornelia; Toretsky, Jeffrey A; Bennett, Keiryn L; Olsen, Jesper V; Brunak, Søren; Kovar, Heinrich; Superti-Furga, Giulio

2017-01-01

Improvements in survival for Ewing sarcoma pediatric and adolescent patients have been modest over the past 20 years. Combinations of anticancer agents endure as an option to overcome resistance to single treatments caused by compensatory pathways. Moreover, combinations are thought to lessen any associated adverse side effects through reduced dosing, which is particularly important in childhood tumors. Using a parallel phenotypic combinatorial screening approach of cells derived from three pediatric tumor types, we identified Ewing sarcoma-specific interactions of a diverse set of targeted agents including approved drugs. We were able to retrieve highly synergistic drug combinations specific for Ewing sarcoma and identified signaling processes important for Ewing sarcoma cell proliferation determined by EWS-FLI1 We generated a molecular target profile of PKC412, a multikinase inhibitor with strong synergistic propensity in Ewing sarcoma, revealing its targets in critical Ewing sarcoma signaling routes. Using a multilevel experimental approach including quantitative phosphoproteomics, we analyzed the molecular rationale behind the disease-specific synergistic effect of simultaneous application of PKC412 and IGF1R inhibitors. The mechanism of the drug synergy between these inhibitors is different from the sum of the mechanisms of the single agents. The combination effectively inhibited pathway crosstalk and averted feedback loop repression, in EWS-FLI1-dependent manner. Mol Cancer Ther; 16(1); 88-101. ©2016 AACR. ©2016 American Association for Cancer Research.

Synergy testing of FDA-approved drugs identifies potent drug combinations against Trypanosoma cruzi.

PubMed

Planer, Joseph D; Hulverson, Matthew A; Arif, Jennifer A; Ranade, Ranae M; Don, Robert; Buckner, Frederick S

2014-07-01

An estimated 8 million persons, mainly in Latin America, are infected with Trypanosoma cruzi, the etiologic agent of Chagas disease. Existing antiparasitic drugs for Chagas disease have significant toxicities and suboptimal effectiveness, hence new therapeutic strategies need to be devised to address this neglected tropical disease. Due to the high research and development costs of bringing new chemical entities to the clinic, we and others have investigated the strategy of repurposing existing drugs for Chagas disease. Screens of FDA-approved drugs (described in this paper) have revealed a variety of chemical classes that have growth inhibitory activity against mammalian stage Trypanosoma cruzi parasites. Aside from azole antifungal drugs that have low or sub-nanomolar activity, most of the active compounds revealed in these screens have effective concentrations causing 50% inhibition (EC50's) in the low micromolar or high nanomolar range. For example, we have identified an antihistamine (clemastine, EC50 of 0.4 µM), a selective serotonin reuptake inhibitor (fluoxetine, EC50 of 4.4 µM), and an antifolate drug (pyrimethamine, EC50 of 3.8 µM) and others. When tested alone in the murine model of Trypanosoma cruzi infection, most compounds had insufficient efficacy to lower parasitemia thus we investigated using combinations of compounds for additive or synergistic activity. Twenty-four active compounds were screened in vitro in all possible combinations. Follow up isobologram studies showed at least 8 drug pairs to have synergistic activity on T. cruzi growth. The combination of the calcium channel blocker, amlodipine, plus the antifungal drug, posaconazole, was found to be more effective at lowering parasitemia in mice than either drug alone, as was the combination of clemastine and posaconazole. Using combinations of FDA-approved drugs is a promising strategy for developing new treatments for Chagas disease.

Synergy Testing of FDA-Approved Drugs Identifies Potent Drug Combinations against Trypanosoma cruzi

PubMed Central

Ranade, Ranae M.; Don, Robert; Buckner, Frederick S.

2014-01-01

An estimated 8 million persons, mainly in Latin America, are infected with Trypanosoma cruzi, the etiologic agent of Chagas disease. Existing antiparasitic drugs for Chagas disease have significant toxicities and suboptimal effectiveness, hence new therapeutic strategies need to be devised to address this neglected tropical disease. Due to the high research and development costs of bringing new chemical entities to the clinic, we and others have investigated the strategy of repurposing existing drugs for Chagas disease. Screens of FDA-approved drugs (described in this paper) have revealed a variety of chemical classes that have growth inhibitory activity against mammalian stage Trypanosoma cruzi parasites. Aside from azole antifungal drugs that have low or sub-nanomolar activity, most of the active compounds revealed in these screens have effective concentrations causing 50% inhibition (EC50's) in the low micromolar or high nanomolar range. For example, we have identified an antihistamine (clemastine, EC50 of 0.4 µM), a selective serotonin reuptake inhibitor (fluoxetine, EC50 of 4.4 µM), and an antifolate drug (pyrimethamine, EC50 of 3.8 µM) and others. When tested alone in the murine model of Trypanosoma cruzi infection, most compounds had insufficient efficacy to lower parasitemia thus we investigated using combinations of compounds for additive or synergistic activity. Twenty-four active compounds were screened in vitro in all possible combinations. Follow up isobologram studies showed at least 8 drug pairs to have synergistic activity on T. cruzi growth. The combination of the calcium channel blocker, amlodipine, plus the antifungal drug, posaconazole, was found to be more effective at lowering parasitemia in mice than either drug alone, as was the combination of clemastine and posaconazole. Using combinations of FDA-approved drugs is a promising strategy for developing new treatments for Chagas disease. PMID:25033456

Risk of single and combined exposure of birds to non-steroidal anti-inflammatory drugs and lead.

PubMed

Osickova, Jitka; Skochova, Hana; Ondracek, Karel; Kral, Jiri; Damkova, Veronika; Peckova, Lucie; Pohanka, Miroslav; Vitula, Frantisek; Bandouchova, Hana; Pikula, Jiri

2012-01-01

Pharmaceuticals and heavy metals such as diclofenac and lead, respectively, have been identified as environmental contaminants toxic to birds and posing serious threats to declining populations of raptors worldwide. The aim of the present study was to test the hypothesis that a sublethal combination of non-steroidal anti-inflammatory drugs and lead induces more pronounced effects than single exposures in birds. A total of 40 Japanese quails (Coturnix coturnix japonica) at the age of 2 months and average weight of 180g were on a random basis divided into four experimental groups of 10 specimens (i.e., control, diclofenac, lead, and lead+diclofenac exposures). Six lead shots in the total weight of 1.5 grams were inserted into the crop on day 0 of the experiment, while a total of 5 mg/kg of diclofenac administered intramuscularly were divided into treatments on days 0 and 5. Group responses were compared using haematology and biochemistry after 10 days. There was no mortality in control and both single and combined diclofenac and lead exposure groups, nor did the birds show any clinical signs of intoxication. Univariate analyses of blood parameters yielded a decrease in haematocrit in birds exposed to both substances when compared with the control, a lower haemoglobin level of the lead-exposed group, increased activity of aspartate aminotransferase in the NSAIDs-exposed group, increased activity of alkaline phosphatase in birds exposed to a combination of diclofenac and lead, and a higher phosphorus level in the lead-exposed group. The principal component analysis revealed no multivariate pattern of responses of blood parameters and did not allow separation of exposure groups from controls when the variables and samples were projected onto a two dimensional space. Results of the present study can enhance understanding of combination toxicity of veterinary drugs and heavy metals in birds, i.e. a scenario that has become environmentally relevant in recent decades

Cancer in silico drug discovery: a systems biology tool for identifying candidate drugs to target specific molecular tumor subtypes.

PubMed

San Lucas, F Anthony; Fowler, Jerry; Chang, Kyle; Kopetz, Scott; Vilar, Eduardo; Scheet, Paul

2014-12-01

Large-scale cancer datasets such as The Cancer Genome Atlas (TCGA) allow researchers to profile tumors based on a wide range of clinical and molecular characteristics. Subsequently, TCGA-derived gene expression profiles can be analyzed with the Connectivity Map (CMap) to find candidate drugs to target tumors with specific clinical phenotypes or molecular characteristics. This represents a powerful computational approach for candidate drug identification, but due to the complexity of TCGA and technology differences between CMap and TCGA experiments, such analyses are challenging to conduct and reproduce. We present Cancer in silico Drug Discovery (CiDD; scheet.org/software), a computational drug discovery platform that addresses these challenges. CiDD integrates data from TCGA, CMap, and Cancer Cell Line Encyclopedia (CCLE) to perform computational drug discovery experiments, generating hypotheses for the following three general problems: (i) determining whether specific clinical phenotypes or molecular characteristics are associated with unique gene expression signatures; (ii) finding candidate drugs to repress these expression signatures; and (iii) identifying cell lines that resemble the tumors being studied for subsequent in vitro experiments. The primary input to CiDD is a clinical or molecular characteristic. The output is a biologically annotated list of candidate drugs and a list of cell lines for in vitro experimentation. We applied CiDD to identify candidate drugs to treat colorectal cancers harboring mutations in BRAF. CiDD identified EGFR and proteasome inhibitors, while proposing five cell lines for in vitro testing. CiDD facilitates phenotype-driven, systematic drug discovery based on clinical and molecular data from TCGA. ©2014 American Association for Cancer Research.

Recreational drug discovery: natural products as lead structures for the synthesis of smart drugs.

PubMed

Appendino, Giovanni; Minassi, Alberto; Taglialatela-Scafati, Orazio

2014-07-01

Covering: up to December 2013. Over the past decade, there has been a growing transition in recreational drugs from natural materials (marijuana, hashish, opium), natural products (morphine, cocaine), or their simple derivatives (heroin), to synthetic agents more potent than their natural prototypes, which are sometimes less harmful in the short term, or that combine properties from different classes of recreational prototypes. These agents have been named smart drugs, and have become popular both for personal consumption and for collective intoxication at rave parties. The reasons for this transition are varied, but are mainly regulatory and commercial. New analogues of known illegal intoxicants are invisible to most forensic detection techniques, while the alleged natural status and the lack of avert acute toxicity make them appealing to a wide range of users. On the other hand, the advent of the internet has made possible the quick dispersal of information among users and the on-line purchase of these agents and/or the precursors for their synthesis. Unlike their natural products chemotypes (ephedrine, mescaline, cathinone, psilocybin, THC), most new drugs of abuse are largely unfamiliar to the organic chemistry community as well as to health care providers. To raise awareness of the growing plague of smart drugs we have surveyed, in a medicinal chemistry fashion, their development from natural products leads, their current methods of production, and the role that clandestine home laboratories and underground chemists have played in the surge of popularity of these drugs.

Drug-drug Interactions of Statins Potentially Leading to Muscle-Related Side Effects in Hospitalized Patients.

PubMed

Bucsa, Camelia; Farcas, Andreea; Leucuta, D; Mogosan, Cristina; Bojita, M; Dumitrascu, D L

2015-01-01

The associations of drugs that may interact with the statins resulting in elevated serum concentration of the statins are an important risk factor for statin induced muscle disorders. We aimed to determine the prevalence of these associations in all hospitalized patients that had been prescribed statins before/during hospitalization and to find out how often they are associated with muscle-related side effects. This prospective, non-interventional study performed in two internal medicine departments included patients with statin therapy before/during hospitalization. Data on each patient demographic characteristics, co-morbidities and treatment was collected from medical charts and interviews. We evaluated patients' therapy for the targeted associations using Thomson Micromedex Drug Interactions checker and we ranked the identified drug-drug interactions (DDIs) accordingly. Each patient with statin treatment before admission was additionally interviewed in order to identify muscular symptoms. In 109 patients on statin treatment we found 35 potential (p) DDIs of statins in 30 (27.5%) patients, most of which were in the therapy before admission (27 pDDIs). The pDDIs were moderate (20 pDDIs) and major (15 pDDIs). Of the total number of pDDIs, 24 were targeting the muscular system. The drugs most frequently involved in the statins' pDDIs were amiodarone and fenofibrate. Two of the patients with pDDIs reported muscle pain, both having additional risk factors for statin induced muscular effects. The prevalence of statins' pDDIs was high in our study, mostly in the therapy before admission, with only a small number of pDDIs resulting in clinical outcome.

Selected approaches for rational drug design and high throughput screening to identify anti-cancer molecules.

PubMed

Hedvat, Michael; Emdad, Luni; Das, Swadesh K; Kim, Keetae; Dasgupta, Santanu; Thomas, Shibu; Hu, Bin; Zhu, Shan; Dash, Rupesh; Quinn, Bridget A; Oyesanya, Regina A; Kegelman, Timothy P; Sokhi, Upneet K; Sarkar, Siddik; Erdogan, Eda; Menezes, Mitchell E; Bhoopathi, Praveen; Wang, Xiang-Yang; Pomper, Martin G; Wei, Jun; Wu, Bainan; Stebbins, John L; Diaz, Paul W; Reed, John C; Pellecchia, Maurizio; Sarkar, Devanand; Fisher, Paul B

2012-11-01

Structure-based modeling combined with rational drug design, and high throughput screening approaches offer significant potential for identifying and developing lead compounds with therapeutic potential. The present review focuses on these two approaches using explicit examples based on specific derivatives of Gossypol generated through rational design and applications of a cancer-specificpromoter derived from Progression Elevated Gene-3. The Gossypol derivative Sabutoclax (BI-97C1) displays potent anti-tumor activity against a diverse spectrum of human tumors. The model of the docked structure of Gossypol bound to Bcl-XL provided a virtual structure-activity-relationship where appropriate modifications were predicted on a rational basis. These structure-based studies led to the isolation of Sabutoclax, an optically pure isomer of Apogossypol displaying superior efficacy and reduced toxicity. These studies illustrate the power of combining structure-based modeling with rational design to predict appropriate derivatives of lead compounds to be empirically tested and evaluated for bioactivity. Another approach to cancer drug discovery utilizes a cancer-specific promoter as readouts of the transformed state. The promoter region of Progression Elevated Gene-3 is such a promoter with cancer-specific activity. The specificity of this promoter has been exploited as a means of constructing cancer terminator viruses that selectively kill cancer cells and as a systemic imaging modality that specifically visualizes in vivo cancer growth with no background from normal tissues. Screening of small molecule inhibitors that suppress the Progression Elevated Gene-3-promoter may provide relevant lead compounds for cancer therapy that can be combined with further structure-based approaches leading to the development of novel compounds for cancer therapy.

A genome-wide RNAi screen identifies potential drug targets in a C. elegans model of α1-antitrypsin deficiency.

PubMed

O'Reilly, Linda P; Long, Olivia S; Cobanoglu, Murat C; Benson, Joshua A; Luke, Cliff J; Miedel, Mark T; Hale, Pamela; Perlmutter, David H; Bahar, Ivet; Silverman, Gary A; Pak, Stephen C

2014-10-01

α1-Antitrypsin deficiency (ATD) is a common genetic disorder that can lead to end-stage liver and lung disease. Although liver transplantation remains the only therapy currently available, manipulation of the proteostasis network (PN) by small molecule therapeutics offers great promise. To accelerate the drug-discovery process for this disease, we first developed a semi-automated high-throughput/content-genome-wide RNAi screen to identify PN modifiers affecting the accumulation of the α1-antitrypsin Z mutant (ATZ) in a Caenorhabditis elegans model of ATD. We identified 104 PN modifiers, and these genes were used in a computational strategy to identify human ortholog-ligand pairs. Based on rigorous selection criteria, we identified four FDA-approved drugs directed against four different PN targets that decreased the accumulation of ATZ in C. elegans. We also tested one of the compounds in a mammalian cell line with similar results. This methodology also proved useful in confirming drug targets in vivo, and predicting the success of combination therapy. We propose that small animal models of genetic disorders combined with genome-wide RNAi screening and computational methods can be used to rapidly, economically and strategically prime the preclinical discovery pipeline for rare and neglected diseases with limited therapeutic options. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Drug efficiency: a new concept to guide lead optimization programs towards the selection of better clinical candidates.

PubMed

Braggio, Simone; Montanari, Dino; Rossi, Tino; Ratti, Emiliangelo

2010-07-01

As a result of their wide acceptance and conceptual simplicity, drug-like concepts are having a major influence on the drug discovery process, particularly in the selection of the 'optimal' absorption, distribution, metabolism, excretion and toxicity and physicochemical parameters space. While they have an undisputable value when assessing the potential of lead series or in evaluating inherent risk of a portfolio of drug candidates, they result much less useful in weighing up compounds for the selection of the best potential clinical candidate. We introduce the concept of drug efficiency as a new tool both to guide the drug discovery program teams during the lead optimization phase and to better assess the developability potential of a drug candidate.

A genome-wide RNAi screen identifies novel targets of neratinib sensitivity leading to neratinib and paclitaxel combination drug treatments.

PubMed

Seyhan, Attila A; Varadarajan, Usha; Choe, Sung; Liu, Yan; McGraw, John; Woods, Matthew; Murray, Stuart; Eckert, Amy; Liu, Wei; Ryan, Terence E

2011-06-01

ErbB2 is frequently activated in tumors, and influences a wide array of cellular functions, including proliferation, apoptosis, cell motility and adhesion. HKI-272 (neratinib) is a small molecule pan-kinase inhibitor of the ErbB family of receptor tyrosine kinases, and shows strong antiproliferative activity in ErbB2-overexpressing breast cancer cells. We undertook a genome-wide pooled lentiviral RNAi screen to identify synthetic lethal or enhancer (synthetic modulator screen) genes that interact with neratinib in a human breast cancer cell line (SKBR-3). These genes upon knockdown would modulate cell viability in the presence of subeffective concentrations of neratinib. We discovered a diverse set of genes whose depletion selectively impaired or enhanced the viability of SKBR-3 cells in the presence of neratinib. We observed diverse pathways including EGFR, hypoxia, cAMP, and protein ubiquitination that, when co-treated with RNAi and neratinib, resulted in arrest of cell proliferation. Examining the changes of these genes and their protein products also led to a rationale for clinically relevant drug combination treatments. Treatment of cells with either paclitaxel or cytarabine in combination with neratinib resulted in a strong antiproliferative effect. The identification of novel mediators of cellular response to neratinib and the development of potential drug combination treatments have expanded our understanding of neratinib's mode-of-action for the development of more effective therapeutic regimens. Notably, our findings support a paclitaxel and neratinib phase III clinical trial in breast cancer patients.

The in silico drug discovery toolbox: applications in lead discovery and optimization.

PubMed

Bruno, Agostino; Costantino, Gabriele; Sartori, Luca; Radi, Marco

2017-11-06

Discovery and development of a new drug is a long lasting and expensive journey that takes around 15 years from starting idea to approval and marketing of new medication. Despite the R&D expenditures have been constantly increasing in the last few years, number of new drugs introduced into market has been steadily declining. This is mainly due to preclinical and clinical safety issues, which still represent about 40% of drug discontinuation. From this point of view, it is clear that if we want to increase drug-discovery success rate and reduce costs associated with development of a new drug, a comprehensive evaluation/prediction of potential safety issues should be conducted as soon as possible during early drug discovery phase. In the present review, we will analyse the early steps of drug-discovery pipeline, describing the sequence of steps from disease selection to lead optimization and focusing on the most common in silico tools used to assess attrition risks and build a mitigation plan. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Identifying types of drug intoxication : laboratory evaluation of a subject-examination procedure

DOT National Transportation Integrated Search

1985-05-01

The Los Angeles Police Department (LAPD) has developed a rating procedures for use in detecting drug-impaired drivers. The purpose of the rating procedures is to determine whether the driver is impaired and to identify the responsible drug class (e.g...

SQ109, a New Drug Lead for Chagas Disease

PubMed Central

Veiga-Santos, Phercyles; Li, Kai; Lameira, Lilianne; de Carvalho, Tecia Maria Ulisses; Huang, Guozhong; Galizzi, Melina; Shang, Na; Li, Qian; Gonzalez-Pacanowska, Dolores; Hernandez-Rodriguez, Vanessa; Benaim, Gustavo; Guo, Rey-Ting; Urbina, Julio A.; Docampo, Roberto; de Souza, Wanderley

2015-01-01

-resistant tuberculosis, may also have potential as a drug lead against Chagas disease. PMID:25583723

Strategy for Identifying Repurposed Drugs for the Treatment of Cerebral Cavernous Malformation

PubMed Central

Gibson, Christopher C.; Zhu, Weiquan; Davis, Chadwick T.; Bowman-Kirigin, Jay A.; Chan, Aubrey C.; Ling, Jing; Walker, Ashley E.; Goitre, Luca; Monache, Simona Delle; Retta, Saverio Francesco; Shiu, Yan-Ting E.; Grossmann, Allie H.; Thomas, Kirk R.; Donato, Anthony J.; Lesniewski, Lisa A.; Whitehead, Kevin J.; Li, Dean Y.

2014-01-01

Background Cerebral cavernous malformation (CCM) is a hemorrhagic stroke disease affecting up to 0.5% of North Americans with no approved non-surgical treatment. A subset of patients have a hereditary form of the disease due primarily to loss-of-function mutations in KRIT1, CCM2, or PDCD10. We sought to identify known drugs that could be repurposed to treat CCM. Methods and Results We developed an unbiased screening platform based on both cellular and animal models of loss-of-function of CCM2. Our discovery strategy consisted of four steps: an automated immunofluorescence and machine-learning-based primary screen of structural phenotypes in human endothelial cells deficient in CCM2; a secondary screen of functional changes in endothelial stability in these same cells; a rapid in vivo tertiary screen of dermal microvascular leak in mice lacking endothelial Ccm2; and finally a quaternary screen of CCM lesion burden in these same mice. We screened 2,100 known drugs and bioactive compounds, and identified two candidates for further study, cholecalciferol (Vitamin D3) and tempol (a scavenger of superoxide). Each drug decreased lesion burden in a mouse model of CCM vascular disease by approximately 50%. Conclusions By identifying known drugs as potential therapeutics for CCM, we have decreased the time, cost, and risk of bringing treatments to patients. Each drug also prompts additional exploration of biomarkers of CCM disease. We further suggest that the structure-function screening platform presented here may be adapted and scaled to facilitate drug discovery for diverse loss-of-function genetic vascular disease. PMID:25486933

Expansion of chemical space for collaborative lead generation and drug discovery: the European Lead Factory Perspective.

PubMed

Karawajczyk, Anna; Giordanetto, Fabrizio; Benningshof, Jorg; Hamza, Daniel; Kalliokoski, Tuomo; Pouwer, Kees; Morgentin, Remy; Nelson, Adam; Müller, Gerhard; Piechot, Alexander; Tzalis, Dimitrios

2015-11-01

High-throughput screening (HTS) represents a major cornerstone of drug discovery. The availability of an innovative, relevant and high-quality compound collection to be screened often dictates the final fate of a drug discovery campaign. Given that the chemical space to be sampled in research programs is practically infinite and sparsely populated, significant efforts and resources need to be invested in the generation and maintenance of a competitive compound collection. The European Lead Factory (ELF) project is addressing this challenge by leveraging the diverse experience and know-how of academic groups and small and medium enterprises (SMEs) engaged in synthetic and/or medicinal chemistry. Here, we describe the novelty, diversity, structural complexity, physicochemical characteristics and overall attractiveness of this first batch of ELF compounds for HTS purposes. Copyright © 2015 Elsevier Ltd. All rights reserved.

Drug-drug interactions between anti-retroviral therapies and drugs of abuse in HIV systems.

PubMed

Kumar, Santosh; Rao, P S S; Earla, Ravindra; Kumar, Anil

2015-03-01

Substance abuse is a common problem among HIV-infected individuals. Importantly, addictions as well as moderate use of alcohol, smoking, or other illicit drugs have been identified as major reasons for non-adherence to antiretroviral therapy (ART) among HIV patients. The literature also suggests a decrease in the response to ART among HIV patients who use these substances, leading to failure to achieve optimal virological response and increased disease progression. This review discusses the challenges with adherence to ART as well as observed drug interactions and known toxicities with major drugs of abuse, such as alcohol, smoking, methamphetamine, cocaine, marijuana, and opioids. The lack of adherence and drug interactions potentially lead to decreased efficacy of ART drugs and increased ART, and drugs of abuse-mediated toxicity. As CYP is the common pathway in metabolizing both ART and drugs of abuse, we discuss the possible involvement of CYP pathways in such drug interactions. We acknowledge that further studies focusing on common metabolic pathways involving CYP and advance research in this area would help to potentially develop novel/alternate interventions and drug dose/regimen adjustments to improve medication outcomes in HIV patients who consume drugs of abuse.

Identifying genomic and developmental causes of adverse drug reactions in children

PubMed Central

Becker, Mara L; Leeder, J Steven

2011-01-01

Adverse drug reactions are a concern for all clinicians who utilize medications to treat adults and children; however, the frequency of adult and pediatric adverse drug reactions is likely to be under-reported. In this age of genomics and personalized medicine, identifying genetic variation that results in differences in drug biotransformation and response has contributed to significant advances in the utilization of several commonly used medications in adults. In order to better understand the variability of drug response in children however, we must not only consider differences in genotype, but also variation in gene expression during growth and development, namely ontogeny. In this article, recommendations for systematically approaching pharmacogenomic studies in children are discussed, and several examples of studies that investigate the genomic and developmental contribution to adverse drug reactions in children are reviewed. PMID:21121777

Identifying clinically relevant drug resistance genes in drug-induced resistant cancer cell lines and post-chemotherapy tissues.

PubMed

Tong, Mengsha; Zheng, Weicheng; Lu, Xingrong; Ao, Lu; Li, Xiangyu; Guan, Qingzhou; Cai, Hao; Li, Mengyao; Yan, Haidan; Guo, You; Chi, Pan; Guo, Zheng

2015-12-01

Until recently, few molecular signatures of drug resistance identified in drug-induced resistant cancer cell models can be translated into clinical practice. Here, we defined differentially expressed genes (DEGs) between pre-chemotherapy colorectal cancer (CRC) tissue samples of non-responders and responders for 5-fluorouracil and oxaliplatin-based therapy as clinically relevant drug resistance genes (CRG5-FU/L-OHP). Taking CRG5-FU/L-OHP as reference, we evaluated the clinical relevance of several types of genes derived from HCT116 CRC cells with resistance to 5-fluorouracil and oxaliplatin, respectively. The results revealed that DEGs between parental and resistant cells, when both were treated with the corresponding drug for a certain time, were significantly consistent with the CRG5-FU/L-OHP as well as the DEGs between the post-chemotherapy CRC specimens of responders and non-responders. This study suggests a novel strategy to extract clinically relevant drug resistance genes from both drug-induced resistant cell models and post-chemotherapy cancer tissue specimens.

Identifying critical transitions and their leading biomolecular networks in complex diseases.

PubMed

Liu, Rui; Li, Meiyi; Liu, Zhi-Ping; Wu, Jiarui; Chen, Luonan; Aihara, Kazuyuki

2012-01-01

Identifying a critical transition and its leading biomolecular network during the initiation and progression of a complex disease is a challenging task, but holds the key to early diagnosis and further elucidation of the essential mechanisms of disease deterioration at the network level. In this study, we developed a novel computational method for identifying early-warning signals of the critical transition and its leading network during a disease progression, based on high-throughput data using a small number of samples. The leading network makes the first move from the normal state toward the disease state during a transition, and thus is causally related with disease-driving genes or networks. Specifically, we first define a state-transition-based local network entropy (SNE), and prove that SNE can serve as a general early-warning indicator of any imminent transitions, regardless of specific differences among systems. The effectiveness of this method was validated by functional analysis and experimental data.

Identifying anti-cancer drug response related genes using an integrative analysis of transcriptomic and genomic variations with cell line-based drug perturbations.

PubMed

Sun, Yi; Zhang, Wei; Chen, Yunqin; Ma, Qin; Wei, Jia; Liu, Qi

2016-02-23

Clinical responses to anti-cancer therapies often only benefit a defined subset of patients. Predicting the best treatment strategy hinges on our ability to effectively translate genomic data into actionable information on drug responses. To achieve this goal, we compiled a comprehensive collection of baseline cancer genome data and drug response information derived from a large panel of cancer cell lines. This data set was applied to identify the signature genes relevant to drug sensitivity and their resistance by integrating CNVs and the gene expression of cell lines with in vitro drug responses. We presented an efficient in-silico pipeline for integrating heterogeneous cell line data sources with the simultaneous modeling of drug response values across all the drugs and cell lines. Potential signature genes correlated with drug response (sensitive or resistant) in different cancer types were identified. Using signature genes, our collaborative filtering-based drug response prediction model outperformed the 44 algorithms submitted to the DREAM competition on breast cancer cells. The functions of the identified drug response related signature genes were carefully analyzed at the pathway level and the synthetic lethality level. Furthermore, we validated these signature genes by applying them to the classification of the different subtypes of the TCGA tumor samples, and further uncovered their in vivo implications using clinical patient data. Our work may have promise in translating genomic data into customized marker genes relevant to the response of specific drugs for a specific cancer type of individual patients.

Levels and source apportionment of children's lead exposure: could urinary lead be used to identify the levels and sources of children's lead pollution?

PubMed

Cao, Suzhen; Duan, Xiaoli; Zhao, Xiuge; Wang, Beibei; Ma, Jin; Fan, Delong; Sun, Chengye; He, Bin; Wei, Fusheng; Jiang, Guibin

2015-04-01

As a highly toxic heavy metal, the pollution and exposure risks of lead are of widespread concern for human health. However, the collection of blood samples for use as an indicator of lead pollution is not always feasible in most cohort or longitudinal studies, especially those involving children health. To evaluate the potential use of urinary lead as an indicator of exposure levels and source apportionment, accompanying with environmental media samples, lead concentrations and isotopic measurements (expressed as (207)Pb/(206)Pb, (208)Pb/(206)Pb and (204)Pb/(206)Pb) were investigated and compared between blood and urine from children living in the vicinities of a typical coking plant and lead-acid battery factory. The results showed urinary lead might not be a preferable proxy for estimating blood lead levels. Fortunately, urinary lead isotopic measurements could be used as an alternative for identifying the sources of children's lead exposure, which coincided well with the blood lead isotope ratio analysis. Copyright © 2015 Elsevier Ltd. All rights reserved.

Walking on thin ice! Identifying methamphetamine "drug mules" on digital plain radiography.

PubMed

Abdul Rashid, S N; Mohamad Saini, S B; Abdul Hamid, S; Muhammad, S J; Mahmud, R; Thali, M J; Flach, P M

2014-04-01

The purpose of this study was to retrospectively evaluate the sensitivity, specificity and accuracy of identifying methamphetamine (MA) internal payloads in "drug mules" by plain abdominal digital radiography (DR). The study consisted of 35 individuals suspected of internal MA drug containers. A total of 59 supine digital radiographs were collected. An overall calculation regarding the diagnostic accuracy for all "drug mules" and a specific evaluation concerning the radiological appearance of drug packs as well as the rate of clearance and complications in correlation with the reader's experience were performed. The gold standard was the presence of secured drug packs in the faeces. There were 16 true-positive "drug mules" identified. DR of all drug carriers for Group 1 (forensic imaging experienced readers, n = 2) exhibited a sensitivity of 100%, a mean specificity of 76.3%, positive predictive value (PPV) of 78.5%, negative predictive value (NPV) of 100% and a mean accuracy 87.2%. Group 2 (inexperienced readers, n = 3) showed a lower sensitivity (93.7%), a mean specificity of 86%, a PPV of 86.5%, an NPV of 94.1% and a mean accuracy of 89.5%. The interrater agreement within Group 1 was 0.72 and within Group 2 averaged to 0.79, indicating a fair to very good agreement. DR is a valuable screening tool in cases of MA body packers with huge internal payloads being associated with a high diagnostic insecurity. Diagnostic insecurity on plain films may be overcome by low-dose CT as a cross-sectional imaging modality and addressed by improved radiological education in reporting drug carriers on imaging. Diagnostic signs (double-condom and halo signs) on digital plain radiography are specific in MA "drug mules", although DR is associated with high diagnostic insecurity and underreports the total internal payload.

Identifying clinically relevant drug resistance genes in drug-induced resistant cancer cell lines and post- chemotherapy tissues

PubMed Central

Tong, Mengsha; Zheng, Weicheng; Lu, Xingrong; Ao, Lu; Li, Xiangyu; Guan, Qingzhou; Cai, Hao; Li, Mengyao; Yan, Haidan; Guo, You; Chi, Pan; Guo, Zheng

2015-01-01

Until recently, few molecular signatures of drug resistance identified in drug-induced resistant cancer cell models can be translated into clinical practice. Here, we defined differentially expressed genes (DEGs) between pre-chemotherapy colorectal cancer (CRC) tissue samples of non-responders and responders for 5-fluorouracil and oxaliplatin-based therapy as clinically relevant drug resistance genes (CRG5-FU/L-OHP). Taking CRG5-FU/L-OHP as reference, we evaluated the clinical relevance of several types of genes derived from HCT116 CRC cells with resistance to 5-fluorouracil and oxaliplatin, respectively. The results revealed that DEGs between parental and resistant cells, when both were treated with the corresponding drug for a certain time, were significantly consistent with the CRG5-FU/L-OHP as well as the DEGs between the post-chemotherapy CRC specimens of responders and non-responders. This study suggests a novel strategy to extract clinically relevant drug resistance genes from both drug-induced resistant cell models and post-chemotherapy cancer tissue specimens. PMID:26515599

Membrane Interactions of Phytochemicals as Their Molecular Mechanism Applicable to the Discovery of Drug Leads from Plants.

PubMed

Tsuchiya, Hironori

2015-10-16

In addition to interacting with functional proteins such as receptors, ion channels, and enzymes, a variety of drugs mechanistically act on membrane lipids to change the physicochemical properties of biomembranes as reported for anesthetic, adrenergic, cholinergic, non-steroidal anti-inflammatory, analgesic, antitumor, antiplatelet, antimicrobial, and antioxidant drugs. As well as these membrane-acting drugs, bioactive plant components, phytochemicals, with amphiphilic or hydrophobic structures, are presumed to interact with biological membranes and biomimetic membranes prepared with phospholipids and cholesterol, resulting in the modification of membrane fluidity, microviscosity, order, elasticity, and permeability with the potencies being consistent with their pharmacological effects. A novel mechanistic point of view of phytochemicals would lead to a better understanding of their bioactivities, an insight into their medicinal benefits, and a strategic implication for discovering drug leads from plants. This article reviews the membrane interactions of different classes of phytochemicals by highlighting their induced changes in membrane property. The phytochemicals to be reviewed include membrane-interactive flavonoids, terpenoids, stilbenoids, capsaicinoids, phloroglucinols, naphthodianthrones, organosulfur compounds, alkaloids, anthraquinonoids, ginsenosides, pentacyclic triterpene acids, and curcuminoids. The membrane interaction's applicability to the discovery of phytochemical drug leads is also discussed while referring to previous screening and isolating studies.

Screening North American plant extracts in vitro against Trypanosoma brucei for discovery of new antitrypanosomal drug leads.

PubMed

Jain, Surendra; Jacob, Melissa; Walker, Larry; Tekwani, Babu

2016-05-18

Human African Trypanosomiasis (HAT) is a protozoan parasitic disease caused by Trypanosoma brucei. The disease is endemic in regions of sub-Saharan Africa, covering 36 countries and more than 60 million people at the risk. Only few drugs are available for the treatment of HAT. Current drugs suffer from severe toxicities and require intramuscular or intravenous administrations. The situation is further aggravated due to the emergence of drug resistance. There is an urgent need of new drugs that are effective orally against both stages of HAT. Natural products offer an unmatched source for bioactive molecules with new chemotypes. The extracts prepared from 522 plants collected from various parts of the North America were screened in vitro against blood stage trypamastigote forms of T. brucei. Active extracts were further screened at concentrations ranging from 10 to 0.4 μg/mL. Active extracts were also investigated for toxicity in Differentiated THP1 cells at 10 μg/mL concentration. The results were computed for dose-response analysis and determination of IC50/IC90 values. A significant number (150) of extracts showed >90 % inhibition of growth of trypomastigote blood forms of T. brucei in primary screening at 20 μg/mL concentration. The active extracts were further investigated for dose-response inhibition of T. brucei growth. The antitrypansomal activity of 125 plant extracts was confirmed with IC50 < 10 μg/mL. None of these active extracts showed toxicity against differentiated THP1 cells. Eight plants extracts namely, Alnus rubra, Hoita macrostachya, Sabal minor, Syzygium aqueum, Hamamelis virginiana, Coccoloba pubescens, Rhus integrifolia and Nuphar luteum were identified as highly potent antitrypanosomal extracts with IC50 values <1 μg/mL. Limited phytochemical and pharmacological reports are available for the lead plant extracts with potent antitrypanosomal activity. Follow up evaluation of these plant extracts is likely to yield new

Mortality among patients due to adverse drug reactions that lead to hospitalization: a meta-analysis.

PubMed

Patel, Tejas K; Patel, Parvati B

2018-06-01

The aim of this study was to estimate the prevalence of mortality among patients due to adverse drug reactions that lead to hospitalisation (fatal ADR Ad ), to explore the heterogeneity in its estimation through subgroup analysis of study characteristics, and to identify system-organ classes involved and causative drugs for fatal ADR Ad . We identified prospective ADR Ad -related studies via screening of the PubMed and Google Scholar databases with appropriate key terms. We estimated the prevalence of fatal ADR Ad using a double arcsine method and explored heterogeneity using the following study characteristics: age groups, wards, study region, ADR definitions, ADR identification methods, study duration and sample size. We examined patterns of fatal ADR Ad and causative drugs. Among 312 full-text articles assessed, 49 studies satisfied the selection criteria and were included in the analysis. The mean prevalence of fatal ADR Ad was 0.20% (95% CI: 0.13-0.27%; I 2  = 93%). The age groups and study wards were the important heterogeneity modifiers. The mean fatal ADR Ad prevalence varied from 0.01% in paediatric patients to 0.44% in the elderly. Subgroup analysis showed a higher prevalence of fatal ADR Ad in intensive care units, emergency departments, multispecialty wards and whole hospitals. Computer-based monitoring systems in combination with other methods detected higher mortality. Intracranial haemorrhage, renal failure and gastrointestinal bleeding accounted for more than 50% of fatal ADR Ad cases. Warfarin, aspirin, renin-angiotensin system (RAS) inhibitors and digoxin accounted for 60% of fatal ADR Ad . ADR Ad is an important cause of mortality. Strategies targeting the safer use of warfarin, aspirin, RAS inhibitors and digoxin could reduce the large number of fatal ADR Ad cases.

Drug-Target Interactions: Prediction Methods and Applications.

PubMed

Anusuya, Shanmugam; Kesherwani, Manish; Priya, K Vishnu; Vimala, Antonydhason; Shanmugam, Gnanendra; Velmurugan, Devadasan; Gromiha, M Michael

2018-01-01

Identifying the interactions between drugs and target proteins is a key step in drug discovery. This not only aids to understand the disease mechanism, but also helps to identify unexpected therapeutic activity or adverse side effects of drugs. Hence, drug-target interaction prediction becomes an essential tool in the field of drug repurposing. The availability of heterogeneous biological data on known drug-target interactions enabled many researchers to develop various computational methods to decipher unknown drug-target interactions. This review provides an overview on these computational methods for predicting drug-target interactions along with available webservers and databases for drug-target interactions. Further, the applicability of drug-target interactions in various diseases for identifying lead compounds has been outlined. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

The future of drug discovery: enabling technologies for enhancing lead characterization and profiling therapeutic potential.

PubMed

Janero, David R

2014-08-01

Technology often serves as a handmaiden and catalyst of invention. The discovery of safe, effective medications depends critically upon experimental approaches capable of providing high-impact information on the biological effects of drug candidates early in the discovery pipeline. This information can enable reliable lead identification, pharmacological compound differentiation and successful translation of research output into clinically useful therapeutics. The shallow preclinical profiling of candidate compounds promulgates a minimalistic understanding of their biological effects and undermines the level of value creation necessary for finding quality leads worth moving forward within the development pipeline with efficiency and prognostic reliability sufficient to help remediate the current pharma-industry productivity drought. Three specific technologies discussed herein, in addition to experimental areas intimately associated with contemporary drug discovery, appear to hold particular promise for strengthening the preclinical valuation of drug candidates by deepening lead characterization. These are: i) hydrogen-deuterium exchange mass spectrometry for characterizing structural and ligand-interaction dynamics of disease-relevant proteins; ii) activity-based chemoproteomics for profiling the functional diversity of mammalian proteomes; and iii) nuclease-mediated precision gene editing for developing more translatable cellular and in vivo models of human diseases. When applied in an informed manner congruent with the clinical understanding of disease processes, technologies such as these that span levels of biological organization can serve as valuable enablers of drug discovery and potentially contribute to reducing the current, unacceptably high rates of compound clinical failure.

Illicit Drug Use in a Community-Based Sample of Heterosexually Identified Emerging Adults

ERIC Educational Resources Information Center

Halkitis, Perry N.; Manasse, Ashley N.; McCready, Karen C.

2010-01-01

In this study we assess lifetime and recent drug use patterns among 261 heterosexually identified 18- to 25-year-olds through brief street intercept surveys conducted in New York City. Marijuana, hallucinogens, powder cocaine, and ecstasy were the most frequently reported drugs for both lifetime and recent use. Findings further suggest significant…

Hit and lead criteria in drug discovery for infectious diseases of the developing world.

PubMed

Katsuno, Kei; Burrows, Jeremy N; Duncan, Ken; Hooft van Huijsduijnen, Rob; Kaneko, Takushi; Kita, Kiyoshi; Mowbray, Charles E; Schmatz, Dennis; Warner, Peter; Slingsby, B T

2015-11-01

Reducing the burden of infectious diseases that affect people in the developing world requires sustained collaborative drug discovery efforts. The quality of the chemical starting points for such projects is a key factor in improving the likelihood of clinical success, and so it is important to set clear go/no-go criteria for the progression of hit and lead compounds. With this in mind, the Japanese Global Health Innovative Technology (GHIT) Fund convened with experts from the Medicines for Malaria Venture, the Drugs for Neglected Diseases initiative and the TB Alliance, together with representatives from the Bill &Melinda Gates Foundation, to set disease-specific criteria for hits and leads for malaria, tuberculosis, visceral leishmaniasis and Chagas disease. Here, we present the agreed criteria and discuss the underlying rationale.

Walking on thin ice! Identifying methamphetamine “drug mules” on digital plain radiography

PubMed Central

Abdul Rashid, S N; Mohamad Saini, S B; Abdul Hamid, S; Muhammad, S J; Mahmud, R; Thali, M J

2014-01-01

Objective: The purpose of this study was to retrospectively evaluate the sensitivity, specificity and accuracy of identifying methamphetamine (MA) internal payloads in “drug mules” by plain abdominal digital radiography (DR). Methods: The study consisted of 35 individuals suspected of internal MA drug containers. A total of 59 supine digital radiographs were collected. An overall calculation regarding the diagnostic accuracy for all “drug mules” and a specific evaluation concerning the radiological appearance of drug packs as well as the rate of clearance and complications in correlation with the reader's experience were performed. The gold standard was the presence of secured drug packs in the faeces. Results: There were 16 true-positive “drug mules” identified. DR of all drug carriers for Group 1 (forensic imaging experienced readers, n = 2) exhibited a sensitivity of 100%, a mean specificity of 76.3%, positive predictive value (PPV) of 78.5%, negative predictive value (NPV) of 100% and a mean accuracy 87.2%. Group 2 (inexperienced readers, n = 3) showed a lower sensitivity (93.7%), a mean specificity of 86%, a PPV of 86.5%, an NPV of 94.1% and a mean accuracy of 89.5%. The interrater agreement within Group 1 was 0.72 and within Group 2 averaged to 0.79, indicating a fair to very good agreement. Conclusion: DR is a valuable screening tool in cases of MA body packers with huge internal payloads being associated with a high diagnostic insecurity. Diagnostic insecurity on plain films may be overcome by low-dose CT as a cross-sectional imaging modality and addressed by improved radiological education in reporting drug carriers on imaging. Advances in knowledge: Diagnostic signs (double-condom and halo signs) on digital plain radiography are specific in MA “drug mules”, although DR is associated with high diagnostic insecurity and underreports the total internal payload. PMID:24472728

The use of lead isotope analysis to identify potential sources of lead toxicosis in a juvenile bald eagle (Haliaeetus leucocephalus) with ventricular foreign bodies

USGS Publications Warehouse

Franzen-Klein, Dana; McRuer, David; Slabe, Vincent; Katzner, Todd

2018-01-01

A male juvenile bald eagle (Haliaeetus leucocephalus) was admitted to the Wildlife Center of Virginia with a left humeral fracture a large quantity of anthropogenic debris in the ventriculus, a blood lead level of 0.616 ppm, and clinical signs consistent with chronic lead toxicosis. Because of the poor prognosis for recovery and release, the eagle was euthanatized. Lead isotope analysis was performed to identify potential anthropogenic sources of lead in this bird. The lead isotope ratios in the eagle's femur (0.8773), liver (0.8761), and kidneys (0.8686) were most closely related to lead paint (0.8925), leaded gasoline (0.8450), and zinc smelting (0.8240). The lead isotope ratios were dissimilar to lead ammunition (0.8179) and the anthropogenic debris in the ventriculus. This case report documents foreign body ingestion in a free-ranging bald eagle and demonstrates the clinical utility of lead isotope analysis to potentially identify or exclude anthropogenic sources of lead poisoning in wildlife patients.

Advances in fragment-based drug discovery platforms.

PubMed

Orita, Masaya; Warizaya, Masaichi; Amano, Yasushi; Ohno, Kazuki; Niimi, Tatsuya

2009-11-01

Fragment-based drug discovery (FBDD) has been established as a powerful alternative and complement to traditional high-throughput screening techniques for identifying drug leads. At present, this technique is widely used among academic groups as well as small biotech and large pharmaceutical companies. In recent years, > 10 new compounds developed with FBDD have entered clinical development, and more and more attention in the drug discovery field is being focused on this technique. Under the FBDD approach, a fragment library of relatively small compounds (molecular mass = 100 - 300 Da) is screened by various methods and the identified fragment hits which normally weakly bind to the target are used as starting points to generate more potent drug leads. Because FBDD is still a relatively new drug discovery technology, further developments and optimizations in screening platforms and fragment exploitation can be expected. This review summarizes recent advances in FBDD platforms and discusses the factors important for the successful application of this technique. Under the FBDD approach, both identifying the starting fragment hit to be developed and generating the drug lead from that starting fragment hit are important. Integration of various techniques, such as computational technology, X-ray crystallography, NMR, surface plasmon resonance, isothermal titration calorimetry, mass spectrometry and high-concentration screening, must be applied in a situation-appropriate manner.

Growing PAINS in academic drug discovery.

PubMed

Whitty, Adrian

2011-05-01

In a recent article it was argued that compounds published as drug leads by academic laboratories commonly contain functionality that identifies them as nonspecific 'pan-assay interference compounds' (PAINS). The article raises broad questions about why best practices for hit and lead qualification that are well known in industry are not more widely employed in academia, as well as about the role of journals in publishing manuscripts that report drug leads of little potential value. Barriers to adoption of best practices for some academic drug-discovery researchers include knowledge gaps and infrastructure deficiencies, but they also arise from fundamental differences in how academic research is structured and how success is measured. Academic drug discovery should not seek to become identical to commercial pharmaceutical research, but we can do a better job of assessing and communicating the true potential of the drug leads we publish, thereby reducing the wastage of resources on nonviable compounds.

DrugECs: An Ensemble System with Feature Subspaces for Accurate Drug-Target Interaction Prediction

PubMed Central

Jiang, Jinjian; Wang, Nian; Zhang, Jun

2017-01-01

Background Drug-target interaction is key in drug discovery, especially in the design of new lead compound. However, the work to find a new lead compound for a specific target is complicated and hard, and it always leads to many mistakes. Therefore computational techniques are commonly adopted in drug design, which can save time and costs to a significant extent. Results To address the issue, a new prediction system is proposed in this work to identify drug-target interaction. First, drug-target pairs are encoded with a fragment technique and the software “PaDEL-Descriptor.” The fragment technique is for encoding target proteins, which divides each protein sequence into several fragments in order and encodes each fragment with several physiochemical properties of amino acids. The software “PaDEL-Descriptor” creates encoding vectors for drug molecules. Second, the dataset of drug-target pairs is resampled and several overlapped subsets are obtained, which are then input into kNN (k-Nearest Neighbor) classifier to build an ensemble system. Conclusion Experimental results on the drug-target dataset showed that our method performs better and runs faster than the state-of-the-art predictors. PMID:28744468

A probabilistic approach to identify putative drug targets in biochemical networks.

PubMed

Murabito, Ettore; Smallbone, Kieran; Swinton, Jonathan; Westerhoff, Hans V; Steuer, Ralf

2011-06-06

Network-based drug design holds great promise in clinical research as a way to overcome the limitations of traditional approaches in the development of drugs with high efficacy and low toxicity. This novel strategy aims to study how a biochemical network as a whole, rather than its individual components, responds to specific perturbations in different physiological conditions. Proteins exerting little control over normal cells and larger control over altered cells may be considered as good candidates for drug targets. The application of network-based drug design would greatly benefit from using an explicit computational model describing the dynamics of the system under investigation. However, creating a fully characterized kinetic model is not an easy task, even for relatively small networks, as it is still significantly hampered by the lack of data about kinetic mechanisms and parameters values. Here, we propose a Monte Carlo approach to identify the differences between flux control profiles of a metabolic network in different physiological states, when information about the kinetics of the system is partially or totally missing. Based on experimentally accessible information on metabolic phenotypes, we develop a novel method to determine probabilistic differences in the flux control coefficients between the two observable phenotypes. Knowledge of how differences in flux control are distributed among the different enzymatic steps is exploited to identify points of fragility in one of the phenotypes. Using a prototypical cancerous phenotype as an example, we demonstrate how our approach can assist researchers in developing compounds with high efficacy and low toxicity. © 2010 The Royal Society

Identifying Drug-Target Interactions with Decision Templates.

PubMed

Yan, Xiao-Ying; Zhang, Shao-Wu

2018-01-01

During the development process of new drugs, identification of the drug-target interactions wins primary concerns. However, the chemical or biological experiments bear the limitation in coverage as well as the huge cost of both time and money. Based on drug similarity and target similarity, chemogenomic methods can be able to predict potential drug-target interactions (DTIs) on a large scale and have no luxurious need about target structures or ligand entries. In order to reflect the cases that the drugs having variant structures interact with common targets and the targets having dissimilar sequences interact with same drugs. In addition, though several other similarity metrics have been developed to predict DTIs, the combination of multiple similarity metrics (especially heterogeneous similarities) is too naïve to sufficiently explore the multiple similarities. In this paper, based on Gene Ontology and pathway annotation, we introduce two novel target similarity metrics to address above issues. More importantly, we propose a more effective strategy via decision template to integrate multiple classifiers designed with multiple similarity metrics. In the scenarios that predict existing targets for new drugs and predict approved drugs for new protein targets, the results on the DTI benchmark datasets show that our target similarity metrics are able to enhance the predictive accuracies in two scenarios. And the elaborate fusion strategy of multiple classifiers has better predictive power than the naïve combination of multiple similarity metrics. Compared with other two state-of-the-art approaches on the four popular benchmark datasets of binary drug-target interactions, our method achieves the best results in terms of AUC and AUPR for predicting available targets for new drugs (S2), and predicting approved drugs for new protein targets (S3).These results demonstrate that our method can effectively predict the drug-target interactions. The software package can

iEzy-Drug: A Web Server for Identifying the Interaction between Enzymes and Drugs in Cellular Networking

PubMed Central

Min, Jian-Liang; Chou, Kuo-Chen

2013-01-01

With the features of extremely high selectivity and efficiency in catalyzing almost all the chemical reactions in cells, enzymes play vitally important roles for the life of an organism and hence have become frequent targets for drug design. An essential step in developing drugs by targeting enzymes is to identify drug-enzyme interactions in cells. It is both time-consuming and costly to do this purely by means of experimental techniques alone. Although some computational methods were developed in this regard based on the knowledge of the three-dimensional structure of enzyme, unfortunately their usage is quite limited because three-dimensional structures of many enzymes are still unknown. Here, we reported a sequence-based predictor, called “iEzy-Drug,” in which each drug compound was formulated by a molecular fingerprint with 258 feature components, each enzyme by the Chou's pseudo amino acid composition generated via incorporating sequential evolution information and physicochemical features derived from its sequence, and the prediction engine was operated by the fuzzy K-nearest neighbor algorithm. The overall success rate achieved by iEzy-Drug via rigorous cross-validations was about 91%. Moreover, to maximize the convenience for the majority of experimental scientists, a user-friendly web server was established, by which users can easily obtain their desired results. PMID:24371828

Identifying genetic loci affecting antidepressant drug response in depression using drug–gene interaction models

PubMed Central

Noordam, Raymond; Avery, Christy L; Visser, Loes E; Stricker, Bruno H

2016-01-01

Antidepressants are often only moderately successful in decreasing the severity of depressive symptoms. In part, antidepressant treatment response in patients with depression is genetically determined. However, although a large number of studies have been conducted aiming to identify genetic variants associated with antidepressant drug response in depression, only a few variants have been repeatedly identified. Within the present review, we will discuss the methodological challenges and limitations of the studies that have been conducted on this topic to date (e.g., ‘treated-only design’, statistical power) and we will discuss how specifically drug–gene interaction models can be used to be better able to identify genetic variants associated with antidepressant drug response in depression. PMID:27248517

Substituted 2-Phenyl-Imidazopyridines: A New Class of Drug Leads for Human African Trypanosomiasis

PubMed Central

Tatipaka, Hari Babu; Gillespie, J. Robert; Chatterjee, Arnab K.; Norcross, Neil R.; Hulverson, Matthew A.; Ranade, Ranae M.; Nagendar, Pendem; Creason, Sharon A.; McQueen, Joshua; Duster, Nicole A.; Nagle, Advait; Supek, Frantisek; Molteni, Valentina; Wenzler, Tanja; Brun, Reto; Glynne, Richard; Buckner, Frederick S.; Gelb, Michael H.

2014-01-01

A phenotypic screen of a compound library for antiparasitic activity on Trypanosoma brucei, the causative agent of human African trypanosomiasis, led to the identification of substituted 2-(3-aminophenyl) oxazolopyridines as a starting point for hit-to-lead medicinal chemistry. A total of 110 analogues were prepared, which led to the identification of 64, a substituted 2-(3-aminophenyl) imidazopyridine. This compound showed antiparasitic activity in vitro with an EC50 of 2 nM and displayed reasonable drug-like properties when tested in a number of in vitro assays. The compound was orally bioavailable and displayed good plasma and brain exposure in mice. Compound 64 cured mice infected with Trypanosoma brucei when dosed orally down to 2.5 mg/kg. Given its potent anti-parasitic properties and its ease of synthesis, compound 64 represents a new lead for the development of drugs to treat human African trypanosomiasis. PMID:24354316

Dual-acting of Hybrid Compounds - A New Dawn in the Discovery of Multi-target Drugs: Lead Generation Approaches.

PubMed

Abdolmaleki, Azizeh; Ghasemi, Jahan B

2017-01-01

Finding high quality beginning compounds is a critical job at the start of the lead generation stage for multi-target drug discovery (MTDD). Designing hybrid compounds as selective multitarget chemical entity is a challenge, opportunity, and new idea to better act against specific multiple targets. One hybrid molecule is formed by two (or more) pharmacophore group's participation. So, these new compounds often exhibit two or more activities going about as multi-target drugs (mtdrugs) and may have superior safety or efficacy. Application of integrating a range of information and sophisticated new in silico, bioinformatics, structural biology, pharmacogenomics methods may be useful to discover/design, and synthesis of the new hybrid molecules. In this regard, many rational and screening approaches have followed by medicinal chemists for the lead generation in MTDD. Here, we review some popular lead generation approaches that have been used for designing multiple ligands (DMLs). This paper focuses on dual- acting chemical entities that incorporate a part of two drugs or bioactive compounds to compose hybrid molecules. Also, it presents some of key concepts and limitations/strengths of lead generation methods by comparing combination framework method with screening approaches. Besides, a number of examples to represent applications of hybrid molecules in the drug discovery are included. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

History as a tool in identifying "new" old drugs.

PubMed

Riddle, John M

2002-01-01

To trace the history of a natural product and its use, it is necessary to identify to correct plant among around a half-million species. One must also know how and when harvest the plant and the morphology of location and extraction. Within the same species plant chemistry varies, depending upon climatic and soil conditions, stage of maturity and even diurnal factors. To all of these variations must be added the diagnostic ability of physicians and native healers (to distinguish between Hippocratically-trained Western physicians and whose knowledge is less formally taught). Seldom was a disease identified as we Know it today, but the constellations of symptoms described, when studied carefully within the framework historical setting of the culture, can be related to modern medicine. It is essential to study the historical contemporary usage data in the language in which those accounts were writTen. Translators are often philologists who are not sensitive to medical nuances. Modern readers of translated historical documents often are unaware of the precision the authors delivered in describing medical afflictions and their treatments. Natural product drugs are truly products of human knowledge. Because so many modern pharmaceuticals are manufactured synthetically we forget that once either the compound or its affinity had a home in a natural product. Over 2,500 years ago man first used a drug obtained from white willow bark, which was aspirin or acetylsalicylic acid. Today's scientists continue to be bewildered by just what aspirin's mechanisms of action are, discovering new modes of action, and how they relate to medical diagnostics. Whatever the science of aspirin, an intelligent person today takes it just as our ancestors did fo millennia. Throughout time, explanations continue to vary just as purpose of administration do as well. Nevertheless, aspirin is perceived as being beneficial. Historical in-use data can also be a factor in judging a drug's safety, since

Combining Computational Methods for Hit to Lead Optimization in Mycobacterium tuberculosis Drug Discovery

PubMed Central

Ekins, Sean; Freundlich, Joel S.; Hobrath, Judith V.; White, E. Lucile; Reynolds, Robert C

2013-01-01

Purpose Tuberculosis treatments need to be shorter and overcome drug resistance. Our previous large scale phenotypic high-throughput screening against Mycobacterium tuberculosis (Mtb) has identified 737 active compounds and thousands that are inactive. We have used this data for building computational models as an approach to minimize the number of compounds tested. Methods A cheminformatics clustering approach followed by Bayesian machine learning models (based on publicly available Mtb screening data) was used to illustrate that application of these models for screening set selections can enrich the hit rate. Results In order to explore chemical diversity around active cluster scaffolds of the dose-response hits obtained from our previous Mtb screens a set of 1924 commercially available molecules have been selected and evaluated for antitubercular activity and cytotoxicity using Vero, THP-1 and HepG2 cell lines with 4.3%, 4.2% and 2.7% hit rates, respectively. We demonstrate that models incorporating antitubercular and cytotoxicity data in Vero cells can significantly enrich the selection of non-toxic actives compared to random selection. Across all cell lines, the Molecular Libraries Small Molecule Repository (MLSMR) and cytotoxicity model identified ~10% of the hits in the top 1% screened (>10 fold enrichment). We also showed that seven out of nine Mtb active compounds from different academic published studies and eight out of eleven Mtb active compounds from a pharmaceutical screen (GSK) would have been identified by these Bayesian models. Conclusion Combining clustering and Bayesian models represents a useful strategy for compound prioritization and hit-to lead optimization of antitubercular agents. PMID:24132686

ICD-10 codes used to identify adverse drug events in administrative data: a systematic review.

PubMed

Hohl, Corinne M; Karpov, Andrei; Reddekopp, Lisa; Doyle-Waters, Mimi; Stausberg, Jürgen

2014-01-01

Adverse drug events, the unintended and harmful effects of medications, are important outcome measures in health services research. Yet no universally accepted set of International Classification of Diseases (ICD) revision 10 codes or coding algorithms exists to ensure their consistent identification in administrative data. Our objective was to synthesize a comprehensive set of ICD-10 codes used to identify adverse drug events. We developed a systematic search strategy and applied it to five electronic reference databases. We searched relevant medical journals, conference proceedings, electronic grey literature and bibliographies of relevant studies, and contacted content experts for unpublished studies. One author reviewed the titles and abstracts for inclusion and exclusion criteria. Two authors reviewed eligible full-text articles and abstracted data in duplicate. Data were synthesized in a qualitative manner. Of 4241 titles identified, 41 were included. We found a total of 827 ICD-10 codes that have been used in the medical literature to identify adverse drug events. The median number of codes used to search for adverse drug events was 190 (IQR 156-289) with a large degree of variability between studies in the numbers and types of codes used. Authors commonly used external injury (Y40.0-59.9) and disease manifestation codes. Only two papers reported on the sensitivity of their code set. Substantial variability exists in the methods used to identify adverse drug events in administrative data. Our work may serve as a point of reference for future research and consensus building in this area.

ICD-10 codes used to identify adverse drug events in administrative data: a systematic review

PubMed Central

Hohl, Corinne M; Karpov, Andrei; Reddekopp, Lisa; Stausberg, Jürgen

2014-01-01

Background Adverse drug events, the unintended and harmful effects of medications, are important outcome measures in health services research. Yet no universally accepted set of International Classification of Diseases (ICD) revision 10 codes or coding algorithms exists to ensure their consistent identification in administrative data. Our objective was to synthesize a comprehensive set of ICD-10 codes used to identify adverse drug events. Methods We developed a systematic search strategy and applied it to five electronic reference databases. We searched relevant medical journals, conference proceedings, electronic grey literature and bibliographies of relevant studies, and contacted content experts for unpublished studies. One author reviewed the titles and abstracts for inclusion and exclusion criteria. Two authors reviewed eligible full-text articles and abstracted data in duplicate. Data were synthesized in a qualitative manner. Results Of 4241 titles identified, 41 were included. We found a total of 827 ICD-10 codes that have been used in the medical literature to identify adverse drug events. The median number of codes used to search for adverse drug events was 190 (IQR 156–289) with a large degree of variability between studies in the numbers and types of codes used. Authors commonly used external injury (Y40.0–59.9) and disease manifestation codes. Only two papers reported on the sensitivity of their code set. Conclusions Substantial variability exists in the methods used to identify adverse drug events in administrative data. Our work may serve as a point of reference for future research and consensus building in this area. PMID:24222671

Analyzing the Chinese landscape in anti-diabetic drug research: leading knowledge production institutions and thematic communities.

PubMed

Deng, Junling; Sitou, Kaweng; Zhang, Yongping; Yan, Ru; Hu, Yuanjia

2016-01-01

The discovery of anti-diabetic drugs is an active Chinese medicine research area. This study aims to map out anti-diabetic drug research in China using a network-based systemic approach based on co-authorship of academic publications. We focused on identifying leading knowledge production institutions, analyzing interactions among them, detecting communities with high internal associations, and exploring future research directions. Target articles published in 2009-2013 under the topic "diabetes" and subject category "pharmacology & pharmacy," with "China," "Taiwan," "Hong Kong," or "Macao" (or "Macau") in the authors' address field were retrieved from the science citation index expanded database and their bibliographic information (e.g., article title, authors, keywords, and authors' affiliation addresses) analyzed. A social network approach was used to construct an institutional collaboration network based on co-publications. Gephi software was used to visualize the network and relationships among institutes were analyzed using centrality measurements. Thematic analysis based on article keywords and R sc value was applied to reveal the research hotspots and directions of network communities. The top 50 institutions were identified; these included Shanghai Jiao Tong University, National Taiwan University, Peking University, and China Pharmaceutical University. Institutes from Taiwan tended to cooperate with institutes outside Taiwan, but those from mainland China showed low interest in external collaboration. Fourteen thematic communities were detected with the Louvain algorithm and further labeled by their high-frequency and characteristic keywords, such as Chinese medicines, diabetic complications, oxidative stress, pharmacokinetics, and insulin resistance. The keyword Chinese medicines comprised a range of Chinese medicine-related topics, including berberine, flavonoids, Astragalus polysaccharide, emodin, and ginsenoside. These keywords suggest potential fields

Drug repurposing identifies a synergistic combination therapy with imatinib mesylate for gastrointestinal stromal tumor.

PubMed

Pessetto, Ziyan Y; Ma, Yan; Hirst, Jeff J; von Mehren, Margaret; Weir, Scott J; Godwin, Andrew K

2014-10-01

Gastrointestinal stromal tumor (GIST) is a rare and therefore often neglected disease. Introduction of the kinase inhibitor imatinib mesylate radically improved the clinical response of patients with GIST; however, its effects are often short-lived, with GISTs demonstrating a median time-to-progression of approximately two years. Although many investigational drugs, approved first for other cancers, have been subsequently evaluated for the management of GIST, few have greatly affected the overall survival of patients with advanced disease. We employed a novel, focused, drug-repurposing effort for GIST, including imatinib mesylate-resistant GIST, evaluating a large library of FDA-approved drugs regardless of current indication. As a result of the drug-repurposing screen, we identified eight FDA-approved drugs, including fludarabine phosphate (F-AMP), that showed synergy with and/or overcame resistance to imatinib mesylate. F-AMP induces DNA damage, Annexin V, and caspase-3/7 activities as the cytotoxic effects on GIST cells, including imatinib mesylate-resistant GIST cells. F-AMP and imatinib mesylate combination treatment showed greater inhibition of GIST cell proliferation when compared with imatinib mesylate and F-AMP alone. Successful in vivo experiments confirmed the combination of imatinib mesylate with F-AMP enhanced the antitumor effects compared with imatinib mesylate alone. Our results identified F-AMP as a promising, repurposed drug therapy for the treatment of GISTs, with potential to be administered in combination with imatinib mesylate or for treatment of imatinib mesylate-refractory tumors. ©2014 American Association for Cancer Research.

Identifying high risk medications causing potential drug-drug interactions in outpatients: A prescription database study based on an online surveillance system.

PubMed

Toivo, T M; Mikkola, J A V; Laine, K; Airaksinen, M

2016-01-01

Drug-drug interactions (DDIs) are a significant cause for adverse drug events (ADEs). DDIs are often predictable and preventable, but their prevention and management require systematic service development. Most DDI studies focus on interaction rates in hospitalized patients. Less is known of DDIs in outpatients, particularly how community pharmacists could contribute to DDI management by applying their surveillance systems for identifying high-risk medications. The study was related to the implementation of the first online DDI surveillance system in Finnish community pharmacies. The goal was to demonstrate how community pharmacies can utilize their prospective surveillance system 1) for identifying high risk medications causing potential DDIs in outpatients, 2) for collaborative service development with local physicians, and 3) for academic risk management research purposes. All DDI alerts given by the online surveillance system were collected during a one-month period in 16 out of 17 University Pharmacy outlets in Finland, covering approximately 10% of the national outpatient prescription volume. The surveillance system was based on the FASS database, which categorizes DDIs into four classes (A-D) according to their clinical significance. Potential drug-drug DDIs were analyzed for 276,891 dispensed community pharmacy prescriptions. Potential DDIs were associated with 10.8%, or 31,110 of these prescriptions. Clinically significant interaction alerts categorized as FASS classes D (most severe, should be avoided) and C (clinically significant but controllable) were associated with 0.5% and 7.0% of the prescriptions, respectively. Methotrexate and warfarin had the highest risk of causing potentially serious (class D) interactions. These interaction alerts were most frequently between methotrexate and NSAIDs and warfarin and NSAIDs. In general, NSAIDs were the most commonly interacting drugs in this study. This study demonstrates that community pharmacies can actively

Identifying the Gaps in Practice for Combating Lead in Drinking Water in Hong Kong

PubMed Central

Lee, Wai Ling; Jia, Jie; Bao, Yani

2016-01-01

Excessive lead has been found in drinking water in Hong Kong in tests carried out in 2015. Investigations have identified that the problem in public rental housing estates was caused by the problematic solders used in the plumbing, and recommendations on enhancing the quality control system and strengthening the relevant water quality standards have been proposed. The cause for the same problem happening in other premises where soldering has not been adopted for water pipe connections is left unidentified. Considering the unidentified cause and the recommendations made, this study aims to identify the gaps in practice followed in Hong Kong for safeguarding the water quality of new installations. A holistic review of governing ordinances and regulations, products and materials used and the testing and commissioning requirements adopted in Hong Kong and elsewhere in the world were conducted. Based on international practices and parametric analysis, it was found that there are gaps in practices followed in Hong Kong, which are directly and indirectly leading to the lead-in-water crisis. Recommendations for improvement in the quality control system, and the water quality standards including the allowable lead content and leaching limit for products and materials and the testing and commissioning requirements on plumbing installations have been made. The review and the identified gaps would become useful reference for countries in strengthening their relevant water quality standards. PMID:27706062

Identifying the Gaps in Practice for Combating Lead in Drinking Water in Hong Kong.

PubMed

Lee, Wai Ling; Jia, Jie; Bao, Yani

2016-09-30

Excessive lead has been found in drinking water in Hong Kong in tests carried out in 2015. Investigations have identified that the problem in public rental housing estates was caused by the problematic solders used in the plumbing, and recommendations on enhancing the quality control system and strengthening the relevant water quality standards have been proposed. The cause for the same problem happening in other premises where soldering has not been adopted for water pipe connections is left unidentified. Considering the unidentified cause and the recommendations made, this study aims to identify the gaps in practice followed in Hong Kong for safeguarding the water quality of new installations. A holistic review of governing ordinances and regulations, products and materials used and the testing and commissioning requirements adopted in Hong Kong and elsewhere in the world were conducted. Based on international practices and parametric analysis, it was found that there are gaps in practices followed in Hong Kong, which are directly and indirectly leading to the lead-in-water crisis. Recommendations for improvement in the quality control system, and the water quality standards including the allowable lead content and leaching limit for products and materials and the testing and commissioning requirements on plumbing installations have been made. The review and the identified gaps would become useful reference for countries in strengthening their relevant water quality standards.

Early phase drugs and biologicals clinical trials on worldwide leading causes of death: a descriptive analysis.

PubMed

Dal-Ré, Rafael

2011-06-01

To describe the global effort targeting the major causes of mortality in terms of "open" early phase clinical trials with drugs and biologicals. Sixteen of the 20 leading causes of death were chosen; 9 of these were also amongst the top 10 causes of death in low-income countries. Studies were identified from the ClinicalTrials.gov database and included phase 1 and/or 2 "interventional" "open" trials, i.e. those recruiting or about to start recruitment. Trials were considered in terms of sponsorship [industry, universities and other organisations (UNO), and US federal agencies (NIH included)], genders and age groups included, and whether they were conducted with drugs and/or biologicals. The search was performed in March 2010. A total of 2,298 (824 phase 1; 1,474 phase 2) trials were retrieved. Of these, 67% were on trachea, bronchus, and lung cancers (25%); diabetes mellitus (15%); colon and rectum cancers (14%); and HIV/AIDS (12%). In contrast, only 4% were trials on diarrhoeal disease, nephrosis and nephritis, liver cirrhosis, and prematurity and low birth weight. UNO were the first source of funding. Fifty-two percent of phase 1 non-cancer trials were on healthy volunteers. Twenty-nine percent of all trials were co-funded. There were 4.6 times as many drug trials as those with biologicals. Only 7% were conducted with a combination of drugs and biologicals, the majority (78%) on cancers. Discrimination in terms of gender or age group was not observed. Four of the 16 diseases considered represented 2/3 of early phase trials. Cancers were a top priority for all sponsors. Increasing attention should be given to conditions with current and projected global high mortality rates that had few "open" early phase trials.

Using Click Chemistry to Identify Potential Drug Targets in Plasmodium

DTIC Science & Technology

2015-04-01

step of the Plasmodium mammalian cycle . Inhibiting this step can block malaria at an early step. However, few anti-malarials target liver infection...points in the life cycle of malaria parasites. PLoS Biol 12: e1001806. 2. Falae A, Combe A, Amaladoss A, Carvalho T, Menard R, et al. (2010) Role of...AWARD NUMBER: W81XWH-13-1-0429 TITLE: Using "Click Chemistry" to Identify Potential Drug Targets in Plasmodium PRINCIPAL INVESTIGATOR: Dr. Purnima

A Role for Fragment-Based Drug Design in Developing Novel Lead Compounds for Central Nervous System Targets.

PubMed

Wasko, Michael J; Pellegrene, Kendy A; Madura, Jeffry D; Surratt, Christopher K

2015-01-01

Hundreds of millions of U.S. dollars are invested in the research and development of a single drug. Lead compound development is an area ripe for new design strategies. Therapeutic lead candidates have been traditionally found using high-throughput in vitro pharmacological screening, a costly method for assaying thousands of compounds. This approach has recently been augmented by virtual screening (VS), which employs computer models of the target protein to narrow the search for possible leads. A variant of VS is fragment-based drug design (FBDD), an emerging in silico lead discovery method that introduces low-molecular weight fragments, rather than intact compounds, into the binding pocket of the receptor model. These fragments serve as starting points for "growing" the lead candidate. Current efforts in virtual FBDD within central nervous system (CNS) targets are reviewed, as is a recent rule-based optimization strategy in which new molecules are generated within a 3D receptor-binding pocket using the fragment as a scaffold. This process not only places special emphasis on creating synthesizable molecules but also exposes computational questions worth addressing. Fragment-based methods provide a viable, relatively low-cost alternative for therapeutic lead discovery and optimization that can be applied to CNS targets to augment current design strategies.

A Role for Fragment-Based Drug Design in Developing Novel Lead Compounds for Central Nervous System Targets

PubMed Central

Wasko, Michael J.; Pellegrene, Kendy A.; Madura, Jeffry D.; Surratt, Christopher K.

2015-01-01

Hundreds of millions of U.S. dollars are invested in the research and development of a single drug. Lead compound development is an area ripe for new design strategies. Therapeutic lead candidates have been traditionally found using high-throughput in vitro pharmacological screening, a costly method for assaying thousands of compounds. This approach has recently been augmented by virtual screening (VS), which employs computer models of the target protein to narrow the search for possible leads. A variant of VS is fragment-based drug design (FBDD), an emerging in silico lead discovery method that introduces low-molecular weight fragments, rather than intact compounds, into the binding pocket of the receptor model. These fragments serve as starting points for “growing” the lead candidate. Current efforts in virtual FBDD within central nervous system (CNS) targets are reviewed, as is a recent rule-based optimization strategy in which new molecules are generated within a 3D receptor-binding pocket using the fragment as a scaffold. This process not only places special emphasis on creating synthesizable molecules but also exposes computational questions worth addressing. Fragment-based methods provide a viable, relatively low-cost alternative for therapeutic lead discovery and optimization that can be applied to CNS targets to augment current design strategies. PMID:26441817

Application of the Pareto principle to identify and address drug-therapy safety issues.

PubMed

Müller, Fabian; Dormann, Harald; Pfistermeister, Barbara; Sonst, Anja; Patapovas, Andrius; Vogler, Renate; Hartmann, Nina; Plank-Kiegele, Bettina; Kirchner, Melanie; Bürkle, Thomas; Maas, Renke

2014-06-01

Adverse drug events (ADE) and medication errors (ME) are common causes of morbidity in patients presenting at emergency departments (ED). Recognition of ADE as being drug related and prevention of ME are key to enhancing pharmacotherapy safety in ED. We assessed the applicability of the Pareto principle (~80 % of effects result from 20 % of causes) to address locally relevant problems of drug therapy. In 752 cases consecutively admitted to the nontraumatic ED of a major regional hospital, ADE, ME, contributing drugs, preventability, and detection rates of ADE by ED staff were investigated. Symptoms, errors, and drugs were sorted by frequency in order to apply the Pareto principle. In total, 242 ADE were observed, and 148 (61.2 %) were assessed as preventable. ADE contributed to 110 inpatient hospitalizations. The ten most frequent symptoms were causally involved in 88 (80.0 %) inpatient hospitalizations. Only 45 (18.6 %) ADE were recognized as drug-related problems until discharge from the ED. A limited set of 33 drugs accounted for 184 (76.0 %) ADE; ME contributed to 57 ADE. Frequency-based listing of ADE, ME, and drugs involved allowed identification of the most relevant problems and development of easily to implement safety measures, such as wall and pocket charts. The Pareto principle provides a method for identifying the locally most relevant ADE, ME, and involved drugs. This permits subsequent development of interventions to increase patient safety in the ED admission process that best suit local needs.

HCS-Neurons: identifying phenotypic changes in multi-neuron images upon drug treatments of high-content screening.

PubMed

Charoenkwan, Phasit; Hwang, Eric; Cutler, Robert W; Lee, Hua-Chin; Ko, Li-Wei; Huang, Hui-Ling; Ho, Shinn-Ying

2013-01-01

High-content screening (HCS) has become a powerful tool for drug discovery. However, the discovery of drugs targeting neurons is still hampered by the inability to accurately identify and quantify the phenotypic changes of multiple neurons in a single image (named multi-neuron image) of a high-content screen. Therefore, it is desirable to develop an automated image analysis method for analyzing multi-neuron images. We propose an automated analysis method with novel descriptors of neuromorphology features for analyzing HCS-based multi-neuron images, called HCS-neurons. To observe multiple phenotypic changes of neurons, we propose two kinds of descriptors which are neuron feature descriptor (NFD) of 13 neuromorphology features, e.g., neurite length, and generic feature descriptors (GFDs), e.g., Haralick texture. HCS-neurons can 1) automatically extract all quantitative phenotype features in both NFD and GFDs, 2) identify statistically significant phenotypic changes upon drug treatments using ANOVA and regression analysis, and 3) generate an accurate classifier to group neurons treated by different drug concentrations using support vector machine and an intelligent feature selection method. To evaluate HCS-neurons, we treated P19 neurons with nocodazole (a microtubule depolymerizing drug which has been shown to impair neurite development) at six concentrations ranging from 0 to 1000 ng/mL. The experimental results show that all the 13 features of NFD have statistically significant difference with respect to changes in various levels of nocodazole drug concentrations (NDC) and the phenotypic changes of neurites were consistent to the known effect of nocodazole in promoting neurite retraction. Three identified features, total neurite length, average neurite length, and average neurite area were able to achieve an independent test accuracy of 90.28% for the six-dosage classification problem. This NFD module and neuron image datasets are provided as a freely downloadable

Aptamers as tools for target prioritization and lead identification.

PubMed

Burgstaller, Petra; Girod, Anne; Blind, Michael

2002-12-15

The increasing number of potential drug target candidates has driven the development of novel technologies designed to identify functionally important targets and enhance the subsequent lead discovery process. Highly specific synthetic nucleic acid ligands--also known as aptamers--offer a new exciting route in the drug discovery process by linking target validation directly with HTS. Recently, aptamers have proven to be valuable tools for modulating the function of endogenous cellular proteins in their natural environment. A set of technologies has been developed to use these sophisticated ligands for the validation of potential drug targets in disease models. Moreover, aptamers that are specific antagonists of protein function can act as substitute interaction partners in HTS assays to facilitate the identification of small-molecule lead compounds.

Drug-Induced Acute Myocardial Infarction: Identifying ‘Prime Suspects’ from Electronic Healthcare Records-Based Surveillance System

PubMed Central

Coloma, Preciosa M.; Schuemie, Martijn J.; Trifirò, Gianluca; Furlong, Laura; van Mulligen, Erik; Bauer-Mehren, Anna; Avillach, Paul; Kors, Jan; Sanz, Ferran; Mestres, Jordi; Oliveira, José Luis; Boyer, Scott; Helgee, Ernst Ahlberg; Molokhia, Mariam; Matthews, Justin; Prieto-Merino, David; Gini, Rosa; Herings, Ron; Mazzaglia, Giampiero; Picelli, Gino; Scotti, Lorenza; Pedersen, Lars; van der Lei, Johan; Sturkenboom, Miriam

2013-01-01

Background Drug-related adverse events remain an important cause of morbidity and mortality and impose huge burden on healthcare costs. Routinely collected electronic healthcare data give a good snapshot of how drugs are being used in ‘real-world’ settings. Objective To describe a strategy that identifies potentially drug-induced acute myocardial infarction (AMI) from a large international healthcare data network. Methods Post-marketing safety surveillance was conducted in seven population-based healthcare databases in three countries (Denmark, Italy, and the Netherlands) using anonymised demographic, clinical, and prescription/dispensing data representing 21,171,291 individuals with 154,474,063 person-years of follow-up in the period 1996–2010. Primary care physicians’ medical records and administrative claims containing reimbursements for filled prescriptions, laboratory tests, and hospitalisations were evaluated using a three-tier triage system of detection, filtering, and substantiation that generated a list of drugs potentially associated with AMI. Outcome of interest was statistically significant increased risk of AMI during drug exposure that has not been previously described in current literature and is biologically plausible. Results Overall, 163 drugs were identified to be associated with increased risk of AMI during preliminary screening. Of these, 124 drugs were eliminated after adjustment for possible bias and confounding. With subsequent application of criteria for novelty and biological plausibility, association with AMI remained for nine drugs (‘prime suspects’): azithromycin; erythromycin; roxithromycin; metoclopramide; cisapride; domperidone; betamethasone; fluconazole; and megestrol acetate. Limitations Although global health status, co-morbidities, and time-invariant factors were adjusted for, residual confounding cannot be ruled out. Conclusion A strategy to identify potentially drug-induced AMI from electronic healthcare data has

Identifying potential impact of lead contamination using a geographic information system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bocco, G.; Sanchez, R.

1997-01-01

The main objective of this research was to identify the potential hazards associated with lead contamination from fixed sources in the city of Tijuana. An exploratory model is presented that describes the potential polluting sources as well as the exposed universe. The results of the analysis provide a clear picture of the geographic distribution of hazards areas for potential lead pollution in Tijuana. The findings are indicative of the dramatic consequences of rapid industrialization and urbanization in a city where there have not been significant planning efforts to mitigate the negative effects of this growth. The approach followed helps tomore » narrow the universe of potential pollution sources, which can help to direct attention, research priorities, and resources to the most critical areas. 16 refs.« less

Identifying Demand Responses to Illegal Drug Supply Interdictions.

PubMed

Cunningham, Scott; Finlay, Keith

2016-10-01

Successful supply-side interdictions into illegal drug markets are predicated on the responsiveness of drug prices to enforcement and the price elasticity of demand for addictive drugs. We present causal estimates that targeted interventions aimed at methamphetamine input markets ('precursor control') can temporarily increase retail street prices, but methamphetamine consumption is weakly responsive to higher drug prices. After the supply interventions, purity-adjusted prices increased then quickly returned to pre-treatment levels within 6-12 months, demonstrating the short-term effects of precursor control. The price elasticity of methamphetamine demand is -0.13 to -0.21 for self-admitted drug treatment admissions and between -0.24 and -0.28 for hospital inpatient admissions. We find some evidence of a positive cross-price effect for cocaine, but we do not find robust evidence that increases in methamphetamine prices increased heroin, alcohol, or marijuana drug use. This study can inform policy discussions regarding other synthesized drugs, including illicit use of pharmaceuticals. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Drug–drug interactions between anti-retroviral therapies and drugs of abuse in HIV systems

PubMed Central

Rao, PSS; Earla, Ravindra; Kumar, Anil

2015-01-01

Introduction Substance abuse is a common problem among HIV-infected individuals. Importantly, addictions as well as moderate use of alcohol, smoking, or other illicit drugs have been identified as major reasons for non-adherence to antiretroviral therapy (ART) among HIV patients. The literature also suggests a decrease in the response to ART among HIV patients who use these substances, leading to failure to achieve optimal virological response and increased disease progression. Areas covered This review discusses the challenges with adherence to ART as well as observed drug interactions and known toxicities with major drugs of abuse, such as alcohol, smoking, methamphetamine, cocaine, marijuana, and opioids. The lack of adherence and drug interactions potentially lead to decreased efficacy of ART drugs and increased ART, and drugs of abuse-mediated toxicity. As CYP is the common pathway in metabolizing both ART and drugs of abuse, we discuss the possible involvement of CYP pathways in such drug interactions. Expert opinion We acknowledge that further studies focusing on common metabolic pathways involving CYP and advance research in this area would help to potentially develop novel/alternate interventions and drug dose/regimen adjustments to improve medication outcomes in HIV patients who consume drugs of abuse. PMID:25539046

New HSP27 inhibitors efficiently suppress drug resistance development in cancer cells.

PubMed

Heinrich, Jörg C; Donakonda, Sainitin; Haupt, V Joachim; Lennig, Petra; Zhang, Yixin; Schroeder, Michael

2016-10-18

Drug resistance is an important open problem in cancer treatment. In recent years, the heat shock protein HSP27 (HSPB1) was identified as a key player driving resistance development. HSP27 is overexpressed in many cancer types and influences cellular processes such as apoptosis, DNA repair, recombination, and formation of metastases. As a result cancer cells are able to suppress apoptosis and develop resistance to cytostatic drugs. To identify HSP27 inhibitors we follow a novel computational drug repositioning approach. We exploit a similarity between a predicted HSP27 binding site to a viral thymidine kinase to generate lead inhibitors for HSP27. Six of these leads were verified experimentally. They bind HSP27 and down-regulate its chaperone activity. Most importantly, all six compounds inhibit development of drug resistance in cellular assays. One of the leads - chlorpromazine - is an antipsychotic, which has a positive effect on survival time in human breast cancer. In summary, we make two important contributions: First, we put forward six novel leads, which inhibit HSP27 and tackle drug resistance. Second, we demonstrate the power of computational drug repositioning.

New HSP27 inhibitors efficiently suppress drug resistance development in cancer cells

PubMed Central

Lennig, Petra; Zhang, Yixin; Schroeder, Michael

2016-01-01

Drug resistance is an important open problem in cancer treatment. In recent years, the heat shock protein HSP27 (HSPB1) was identified as a key player driving resistance development. HSP27 is overexpressed in many cancer types and influences cellular processes such as apoptosis, DNA repair, recombination, and formation of metastases. As a result cancer cells are able to suppress apoptosis and develop resistance to cytostatic drugs. To identify HSP27 inhibitors we follow a novel computational drug repositioning approach. We exploit a similarity between a predicted HSP27 binding site to a viral thymidine kinase to generate lead inhibitors for HSP27. Six of these leads were verified experimentally. They bind HSP27 and down-regulate its chaperone activity. Most importantly, all six compounds inhibit development of drug resistance in cellular assays. One of the leads – chlorpromazine – is an antipsychotic, which has a positive effect on survival time in human breast cancer. In summary, we make two important contributions: First, we put forward six novel leads, which inhibit HSP27 and tackle drug resistance. Second, we demonstrate the power of computational drug repositioning. PMID:27626687

Prescription drug coverage and effects on drug expenditures among elderly Medicare beneficiaries.

PubMed

Huh, Soonim; Rice, Thomas; Ettner, Susan L

2008-06-01

To identify determinants of drug coverage among elderly Medicare beneficiaries and to investigate the impact of drug coverage on drug expenditures with and without taking selection bias into account. The primary data were from the 2000 Medicare Current Beneficiary Survey (MCBS) Cost and Use file, linked to other data sources at the county or state-level that provided instrumental variables. Community-dwelling elderly Medicare beneficiaries who completed the survey were included in the study (N=7,525). A probit regression to predict the probability of having drug coverage and the effects of drug coverage on drug expenditures was estimated by a two-part model, assuming no correlation across equations. In addition, the discrete factor model estimated choice of drug coverage and expenditures for prescription drugs simultaneously to control for self-selection into drug coverage, allowing for correlation of error terms across equations. Findings indicated that unobservable characteristics leading elderly Medicare beneficiaries to purchase drug coverage also lead them to have higher drug expenditures on conditional use (i.e., adverse selection), while the same unobservable factors do not influence their decisions whether to use any drugs. After controlling for potential selection bias, the probability of any drug use among persons with drug coverage use was 4.5 percent higher than among those without, and drug coverage led to an increase in drug expenditures of $308 among those who used prescription drugs. Given significant adverse selection into drug coverage before the implementation of the Medicare Prescription Drug Improvement and Modernization Act, it is essential that selection effects be monitored as beneficiaries choose whether or not to enroll in this voluntary program.

A high throughput screening for TLR3-IRF3 signaling pathway modulators identifies several antipsychotic drugs as TLR inhibitors1

PubMed Central

Zhu, Jianzhong; Smith, Kevin; Hsieh, Paishiun N.; Mburu, Yvonne K.; Chattopadhyay, Saurabh; Sen, Ganes C.; Sarkar, Saumendra N.

2010-01-01

Toll-like Receptor 3 (TLR3) is one of the major innate immune sensors of double stranded RNA (dsRNA). The signal transduction pathway activated by TLR3, upon binding to dsRNA, leads to the activation of two major transcription factors: NF-κB and IRF3. In an effort to identify specific chemical modulators of TLR3-IRF3 signal transduction pathway we developed a cell-based read out system. Using the interferon stimulated gene 56 (ISG56) promoter driven firefly luciferase gene stably integrated in a TLR3 expressing HEK293 cell line, we were able to generate a cell line where treatment with dsRNA resulted in a dose dependent induction of luciferase activity. A screen of two pharmacologically active compound libraries using this system, identified a number of TLR3-IRF3 signaling pathway modulators. Among them we focused on a subset of inhibitors and characterized their mode of action. Several antipsychotic drugs, such as Sertraline, Trifluoperazine and Fluphenazine were found to be direct inhibitors of the innate immune signaling pathway. These inhibitors also showed the ability to inhibit ISG56 induction mediated by TLR4 and TLR7/8 pathways. Interestingly, they did not show significant effect on TLR3, TLR7 and TLR8 mediated NF-κB activation. Detailed analysis of the signaling pathway indicated that these drugs may be exerting their inhibitory effects on IRF3 via PI3K signaling pathway. The data presented here provides mechanistic explanation of possible anti-inflammatory roles of some antipsychotic drugs. PMID:20382888

3D-QSAR pharmacophore-based virtual screening, molecular docking and molecular dynamics simulation toward identifying lead compounds for NS2B-NS3 protease inhibitors.

PubMed

Luo, Pei H; Zhang, Xuan R; Huang, Lan; Yuan, Lun; Zhou, Xang Z; Gao, X; Li, Ling S

2017-10-01

NS2B-NS3 protease has been identified to serve as lead drug design target due to its significant role in West Nile viral (WNV) and dengue virus (DENV) reproduction and replication. There are currently no approved chemotherapeutic drugs and effective vaccines to inhibit DENV and WNV infections. In this work, 3D-QSAR pharmacophore model has been developed to discover potential inhibitory candidates. Validation through Fischer's model and decoy test indicate that the developed 3D pharmacophore model is highly predictive for DENV inhibitors, which was then employed to screen ZINC chemical library to obtain reasonable hits. Following ADMET filtering, 15 hits were subjected to further filter through molecular docking and CoMFA modeling. Finally, top three hits were identified as lead compounds or potential inhibitory candidates with IC 50 values of ∼0.4637 µM and fitness of ∼57.73. It is implied from CoMFA modeling that substituents at the side site of benzotriazole such as a p-nitro group (e.g. biphenyl head) and a carbonyl (e.g. carboxylate function) at the side site of furan or amino group may improve bioactivity of ZINC85645245, respectively. Molecular dynamics simulations (MDS) were performed to discover new interactions and reinforce the binding modes from docking for the hits also. The QSAR and MDS results obtained from this work should be useful in determining structural requirements for inhibitor development as well as in designing more potential inhibitors for NS2B-NS3 protease.

Identifying Risk Factors for Drug Use in an Iranian Treatment Sample: A Prediction Approach Using Decision Trees.

PubMed

Amirabadizadeh, Alireza; Nezami, Hossein; Vaughn, Michael G; Nakhaee, Samaneh; Mehrpour, Omid

2018-05-12

Substance abuse exacts considerable social and health care burdens throughout the world. The aim of this study was to create a prediction model to better identify risk factors for drug use. A prospective cross-sectional study was conducted in South Khorasan Province, Iran. Of the total of 678 eligible subjects, 70% (n: 474) were randomly selected to provide a training set for constructing decision tree and multiple logistic regression (MLR) models. The remaining 30% (n: 204) were employed in a holdout sample to test the performance of the decision tree and MLR models. Predictive performance of different models was analyzed by the receiver operating characteristic (ROC) curve using the testing set. Independent variables were selected from demographic characteristics and history of drug use. For the decision tree model, the sensitivity and specificity for identifying people at risk for drug abuse were 66% and 75%, respectively, while the MLR model was somewhat less effective at 60% and 73%. Key independent variables in the analyses included first substance experience, age at first drug use, age, place of residence, history of cigarette use, and occupational and marital status. While study findings are exploratory and lack generalizability they do suggest that the decision tree model holds promise as an effective classification approach for identifying risk factors for drug use. Convergent with prior research in Western contexts is that age of drug use initiation was a critical factor predicting a substance use disorder.

Drug synergy screen and network modeling in dedifferentiated liposarcoma identifies CDK4 and IGF1R as synergistic drug targets.

PubMed

Miller, Martin L; Molinelli, Evan J; Nair, Jayasree S; Sheikh, Tahir; Samy, Rita; Jing, Xiaohong; He, Qin; Korkut, Anil; Crago, Aimee M; Singer, Samuel; Schwartz, Gary K; Sander, Chris

2013-09-24

Dedifferentiated liposarcoma (DDLS) is a rare but aggressive cancer with high recurrence and low response rates to targeted therapies. Increasing treatment efficacy may require combinations of targeted agents that counteract the effects of multiple abnormalities. To identify a possible multicomponent therapy, we performed a combinatorial drug screen in a DDLS-derived cell line and identified cyclin-dependent kinase 4 (CDK4) and insulin-like growth factor 1 receptor (IGF1R) as synergistic drug targets. We measured the phosphorylation of multiple proteins and cell viability in response to systematic drug combinations and derived computational models of the signaling network. These models predict that the observed synergy in reducing cell viability with CDK4 and IGF1R inhibitors depends on the activity of the AKT pathway. Experiments confirmed that combined inhibition of CDK4 and IGF1R cooperatively suppresses the activation of proteins within the AKT pathway. Consistent with these findings, synergistic reductions in cell viability were also found when combining CDK4 inhibition with inhibition of either AKT or epidermal growth factor receptor (EGFR), another receptor similar to IGF1R that activates AKT. Thus, network models derived from context-specific proteomic measurements of systematically perturbed cancer cells may reveal cancer-specific signaling mechanisms and aid in the design of effective combination therapies.

Virtual screening methods as tools for drug lead discovery from large chemical libraries.

PubMed

Ma, X H; Zhu, F; Liu, X; Shi, Z; Zhang, J X; Yang, S Y; Wei, Y Q; Chen, Y Z

2012-01-01

Virtual screening methods have been developed and explored as useful tools for searching drug lead compounds from chemical libraries, including large libraries that have become publically available. In this review, we discussed the new developments in exploring virtual screening methods for enhanced performance in searching large chemical libraries, their applications in screening libraries of ~ 1 million or more compounds in the last five years, the difficulties in their applications, and the strategies for further improving these methods.

Role of scanning electron microscopy in identifying drugs used in medical practice.

PubMed

Fazil Marickar, Y M; Sylaja, N; Koshy, Peter

2009-10-01

Several plant preparations are administered for treatment of stone disease without scientific basis. This paper presents the results of in vitro and animal experimental studies using scanning electron microscopy (SEM) in the identification of the therapeutic properties of trial drugs in medicine. In the first set of the study, urinary crystals namely calcium oxalate monohydrate and calcium oxalate dehydrate were grown in six sets of Hane's tubes in silica gel medium. Trial drugs namely scoparia dulcis Lynn, musa sapiens and dolicos biflorus were incorporated in the gel medium to identify the dopant effect of the trial drugs on the size and extent of crystal column growth. The changes in morphology of crystals were studied using SEM. In the second set, six male Wistar rats each were calculogenised by administering sodium oxalate and ethylene glycol and diabetised using streptozotocin. The SEM changes of calculogenisation were studied. The rats were administered trial drugs before calculogenisation or after. The kidneys of the rats studied under the scanning electron microscope showed changes in tissue morphology and crystal deposition produced by calculogenisation and alterations produced by addition of trial drugs. The trial drugs produced changes in the pattern of crystal growth and in the crystal morphology of both calcium oxalate monohydrate and calcium oxalate dihydrate grown in vitro. Elemental distribution analysis showed that the crystal purity was not altered by the trial drugs. Scoparia dulcis Lynn was found to be the most effective anticalculogenic agent. Musa sapiens and dolicos biflorus were found to have no significant effect in inhibiting crystal growth. The kidneys of rats on calculogenisation showed different grades of crystals in the glomerulus and interstitial tissues, extrusion of the crystals into the tubular lumen, collodisation and tissue inflammatory cell infiltration. Scoparia dulcis Lynn exhibited maximum protector effect against the

Identifying injection drug use and estimating population size of people who inject drugs using healthcare administrative datasets.

PubMed

Janjua, Naveed Zafar; Islam, Nazrul; Kuo, Margot; Yu, Amanda; Wong, Stanley; Butt, Zahid A; Gilbert, Mark; Buxton, Jane; Chapinal, Nuria; Samji, Hasina; Chong, Mei; Alvarez, Maria; Wong, Jason; Tyndall, Mark W; Krajden, Mel

2018-05-01

Large linked healthcare administrative datasets could be used to monitor programs providing prevention and treatment services to people who inject drugs (PWID). However, diagnostic codes in administrative datasets do not differentiate non-injection from injection drug use (IDU). We validated algorithms based on diagnostic codes and prescription records representing IDU in administrative datasets against interview-based IDU data. The British Columbia Hepatitis Testers Cohort (BC-HTC) includes ∼1.7 million individuals tested for HCV/HIV or reported HBV/HCV/HIV/tuberculosis cases in BC from 1990 to 2015, linked to administrative datasets including physician visit, hospitalization and prescription drug records. IDU, assessed through interviews as part of enhanced surveillance at the time of HIV or HCV/HBV diagnosis from a subset of cases included in the BC-HTC (n = 6559), was used as the gold standard. ICD-9/ICD-10 codes for IDU and injecting-related infections (IRI) were grouped with records of opioid substitution therapy (OST) into multiple IDU algorithms in administrative datasets. We assessed the performance of IDU algorithms through calculation of sensitivity, specificity, positive predictive, and negative predictive values. Sensitivity was highest (90-94%), and specificity was lowest (42-73%) for algorithms based either on IDU or IRI and drug misuse codes. Algorithms requiring both drug misuse and IRI had lower sensitivity (57-60%) and higher specificity (90-92%). An optimal sensitivity and specificity combination was found with two medical visits or a single hospitalization for injectable drugs with (83%/82%) and without OST (78%/83%), respectively. Based on algorithms that included two medical visits, a single hospitalization or OST records, there were 41,358 (1.2% of 11-65 years individuals in BC) recent PWID in BC based on health encounters during 3- year period (2013-2015). Algorithms for identifying PWID using diagnostic codes in linked administrative

Molecular design of anticancer drug leads based on three-dimensional quantitative structure-activity relationship.

PubMed

Huang, Xiao Yan; Shan, Zhi Jie; Zhai, Hong Lin; Li, Li Na; Zhang, Xiao Yun

2011-08-22

Heat shock protein 90 (Hsp90) takes part in the developments of several cancers. Novobiocin, a typically C-terminal inhibitor for Hsp90, will probably used as an important anticancer drug in the future. In this work, we explored the valuable information and designed new novobiocin derivatives based on a three-dimensional quantitative structure-activity relationship (3D QSAR). The comparative molecular field analysis and comparative molecular similarity indices analysis models with high predictive capability were established, and their reliabilities are supported by the statistical parameters. Based on the several important influence factors obtained from these models, six new novobiocin derivatives with higher inhibitory activities were designed and confirmed by the molecular simulation with our models, which provide the potential anticancer drug leads for further research.

How Monte Carlo heuristics aid to identify the physical processes of drug release kinetics.

PubMed

Lecca, Paola

2018-01-01

We implement a Monte Carlo heuristic algorithm to model drug release from a solid dosage form. We show that with Monte Carlo simulations it is possible to identify and explain the causes of the unsatisfactory predictive power of current drug release models. It is well known that the power-law, the exponential models, as well as those derived from or inspired by them accurately reproduce only the first 60% of the release curve of a drug from a dosage form. In this study, by using Monte Carlo simulation approaches, we show that these models fit quite accurately almost the entire release profile when the release kinetics is not governed by the coexistence of different physico-chemical mechanisms. We show that the accuracy of the traditional models are comparable with those of Monte Carlo heuristics when these heuristics approximate and oversimply the phenomenology of drug release. This observation suggests to develop and use novel Monte Carlo simulation heuristics able to describe the complexity of the release kinetics, and consequently to generate data more similar to those observed in real experiments. Implementing Monte Carlo simulation heuristics of the drug release phenomenology may be much straightforward and efficient than hypothesizing and implementing from scratch complex mathematical models of the physical processes involved in drug release. Identifying and understanding through simulation heuristics what processes of this phenomenology reproduce the observed data and then formalize them in mathematics may allow avoiding time-consuming, trial-error based regression procedures. Three bullet points, highlighting the customization of the procedure. •An efficient heuristics based on Monte Carlo methods for simulating drug release from solid dosage form encodes is presented. It specifies the model of the physical process in a simple but accurate way in the formula of the Monte Carlo Micro Step (MCS) time interval.•Given the experimentally observed curve of

Complementary Approaches to Existing Target Based Drug Discovery for Identifying Novel Drug Targets.

PubMed

Vasaikar, Suhas; Bhatia, Pooja; Bhatia, Partap G; Chu Yaiw, Koon

2016-11-21

In the past decade, it was observed that the relationship between the emerging New Molecular Entities and the quantum of R&D investment has not been favorable. There might be numerous reasons but few studies stress the introduction of target based drug discovery approach as one of the factors. Although a number of drugs have been developed with an emphasis on a single protein target, yet identification of valid target is complex. The approach focuses on an in vitro single target, which overlooks the complexity of cell and makes process of validation drug targets uncertain. Thus, it is imperative to search for alternatives rather than looking at success stories of target-based drug discovery. It would be beneficial if the drugs were developed to target multiple components. New approaches like reverse engineering and translational research need to take into account both system and target-based approach. This review evaluates the strengths and limitations of known drug discovery approaches and proposes alternative approaches for increasing efficiency against treatment.

A proteomic approach to identifying new drug targets (potentiating topoisomerase II poisons).

PubMed

Jenkins, J R

2008-10-01

Topoisomerase II poisons are an established part of best clinical practice for the treatment of a number of solid tumours and haematological malignancies. However, toxicity and resistance to chemotherapeutic drugs often complicate the treatment. Furthermore, topoisomerase II poisons can also induce sister chromatid exchange, chromosomal recombination and chromosome aberrations and are associated with a significant risk of secondary leukaemia. It would therefore be of great clinical benefit if the efficacy of topoisomerase II inhibitors could be enhanced without the increased toxic side effects. It is proposed that clinical agents targeting topoisomerase II can be enhanced by inhibiting proteins that modulate topoisomerase II. The aim is to identify proteins, that by the nature of their interaction with topoisomerase II, represent putative drug targets.

Azolium analogues as CDK4 inhibitors: Pharmacophore modeling, 3D QSAR study and new lead drug discovery

NASA Astrophysics Data System (ADS)

Rondla, Rohini; Padma Rao, Lavanya Souda; Ramatenki, Vishwanath; Vadija, Rajender; Mukkera, Thirupathi; Potlapally, Sarita Rajender; Vuruputuri, Uma

2017-04-01

The cyclin-dependent kinase 4 (CDK4) enzyme is a key regulator in cell cycle G1 phase progression. It is often overexpressed in variety of cancer cells, which makes it an attractive therapeutic target for cancer treatment. A number of chemical scaffolds have been reported as CDK4 inhibitors in the literature, and in particular azolium scaffolds as potential inhibitors. Here, a ligand based pharmacophore modeling and an atom based 3D-QSAR analyses for a series of azolium based CDK4 inhibitors are presented. A five point pharmacophore hypothesis, i.e. APRRR with one H-bond acceptor (A), one positive cationic feature (P) and three ring aromatic sites (R) is developed, which yielded an atom based 3D-QSAR model that shows an excellent correlation coefficient value- R2 = 0.93, fisher ratio- F = 207, along with good predictive ability- Q2 = 0.79, and Pearson R value = 0.89. The visual inspection of the 3D-QSAR model, with the most active and the least active ligands, demonstrates the favorable and unfavorable structural regions for the activity towards CDK4. The roles of positively charged nitrogen, the steric effect, ligand flexibility, and the substituents on the activity are in good agreement with the previously reported experimental results. The generated 3D QSAR model is further applied as query for a 3D database screening, which identifies 23 lead drug candidates with good predicted activities and diverse scaffolds. The ADME analysis reveals that, the pharmacokinetic parameters of all the identified new leads are within the acceptable range.

Novel Small Molecule Inhibitors of Choline Kinase Identified by Fragment-Based Drug Discovery.

PubMed

Zech, Stephan G; Kohlmann, Anna; Zhou, Tianjun; Li, Feng; Squillace, Rachel M; Parillon, Lois E; Greenfield, Matthew T; Miller, David P; Qi, Jiwei; Thomas, R Mathew; Wang, Yihan; Xu, Yongjin; Miret, Juan J; Shakespeare, William C; Zhu, Xiaotian; Dalgarno, David C

2016-01-28

Choline kinase α (ChoKα) is an enzyme involved in the synthesis of phospholipids and thereby plays key roles in regulation of cell proliferation, oncogenic transformation, and human carcinogenesis. Since several inhibitors of ChoKα display antiproliferative activity in both cellular and animal models, this novel oncogene has recently gained interest as a promising small molecule target for cancer therapy. Here we summarize our efforts to further validate ChoKα as an oncogenic target and explore the activity of novel small molecule inhibitors of ChoKα. Starting from weakly binding fragments, we describe a structure based lead discovery approach, which resulted in novel highly potent inhibitors of ChoKα. In cancer cell lines, our lead compounds exhibit a dose-dependent decrease of phosphocholine, inhibition of cell growth, and induction of apoptosis at low micromolar concentrations. The druglike lead series presented here is optimizable for improvements in cellular potency, drug target residence time, and pharmacokinetic parameters. These inhibitors may be utilized not only to further validate ChoKα as antioncogenic target but also as novel chemical matter that may lead to antitumor agents that specifically interfere with cancer cell metabolism.

Systems level mapping of metabolic complexity in Mycobacterium tuberculosis to identify high-value drug targets.

PubMed

Vashisht, Rohit; Bhat, Ashwini G; Kushwaha, Shreeram; Bhardwaj, Anshu; Brahmachari, Samir K

2014-10-11

The effectiveness of current therapeutic regimens for Mycobacterium tuberculosis (Mtb) is diminished by the need for prolonged therapy and the rise of drug resistant/tolerant strains. This global health threat, despite decades of basic research and a wealth of legacy knowledge, is due to a lack of systems level understanding that can innovate the process of fast acting and high efficacy drug discovery. The enhanced functional annotations of the Mtb genome, which were previously obtained through a crowd sourcing approach was used to reconstruct the metabolic network of Mtb in a bottom up manner. We represent this information by developing a novel Systems Biology Spindle Map of Metabolism (SBSM) and comprehend its static and dynamic structure using various computational approaches based on simulation and design. The reconstructed metabolism of Mtb encompasses 961 metabolites, involved in 1152 reactions catalyzed by 890 protein coding genes, organized into 50 pathways. By accounting for static and dynamic analysis of SBSM in Mtb we identified various critical proteins required for the growth and survival of bacteria. Further, we assessed the potential of these proteins as putative drug targets that are fast acting and less toxic. Further, we formulate a novel concept of metabolic persister genes (MPGs) and compared our predictions with published in vitro and in vivo experimental evidence. Through such analyses, we report for the first time that de novo biosynthesis of NAD may give rise to bacterial persistence in Mtb under conditions of metabolic stress induced by conventional anti-tuberculosis therapy. We propose such MPG's as potential combination of drug targets for existing antibiotics that can improve their efficacy and efficiency for drug tolerant bacteria. The systems level framework formulated by us to identify potential non-toxic drug targets and strategies to circumvent the issue of bacterial persistence can substantially aid in the process of TB drug

A Challenge for Diagnosing Acute Liver Injury with Concomitant/Sequential Exposure to Multiple Drugs: Can Causality Assessment Scales Be Utilized to Identify the Offending Drug?

PubMed Central

Lim, Roxanne; Conner, Kim; Karnsakul, Wikrom

2014-01-01

Drug-induced hepatotoxicity most commonly manifests as an acute hepatitis syndrome and remains the leading cause of drug-induced death/mortality and the primary reason for withdrawal of drugs from the pharmaceutical market. We report a case of acute liver injury in a 12-year-old Hispanic boy, who received a series of five antibiotics (amoxicillin, ceftriaxone, vancomycin, ampicillin/sulbactam, and clindamycin) for cervical lymphadenitis/retropharyngeal cellulitis. Histopathology of the liver biopsy specimen revealed acute cholestatic hepatitis. All known causes of acute liver injury were appropriately excluded and (only) drug-induced liver injury was left as a cause of his cholestasis. Liver-specific causality assessment scales such as Council for the International Organization of Medical Sciences/Roussel Uclaf Causality Assessment Method scoring system (CIOMS/RUCAM), Maria and Victorino scale, and Digestive Disease Week-Japan were applied to seek the most likely offending drug. Although clindamycin is the most likely cause by clinical diagnosis, none of causality assessment scales aid in the diagnosis. PMID:25506455

Identifying Patients With Problematic Drug Use in the Emergency Department: Results of a Multisite Study

PubMed Central

Konstantopoulos, Wendy L. Macias; Dreifuss, Jessica A.; McDermott, Katherine A.; Parry, Blair Alden; Howell, Melissa L.; Mandler, Raul N.; Fitzmaurice, Garrett M.; Bogenschutz, Michael P.; Weiss, Roger D.

2014-01-01

Study objective Drug-related emergency department (ED) visits have steadily increased, with substance users relying heavily on the ED for medical care. The present study aims to identify clinical correlates of problematic drug use that would facilitate identification of ED patients in need of substance use treatment. Methods Using previously validated tests, 15,224 adult ED patients across 6 academic institutions were prescreened for drug use as part of a large randomized prospective trial. Data for 3,240 participants who reported drug use in the past 30 days were included. Self-reported variables related to demographics, substance use, and ED visit were examined to determine their correlative value for problematic drug use. Results Of the 3,240 patients, 2,084 (64.3%) met criteria for problematic drug use (Drug Abuse Screening Test score ≥3). Age greater than or equal to 30 years, tobacco smoking, daily or binge alcohol drinking, daily drug use, primary noncannabis drug use, resource-intense ED triage level, and perceived drug-relatedness of ED visit were highly correlated with problematic drug use. Among primary cannabis users, correlates of problematic drug use were age younger than 30 years, tobacco smoking, binge drinking, daily drug use, and perceived relatedness of the ED visit to drug use. Conclusion Clinical correlates of drug use problems may assist the identification of ED patients who would benefit from comprehensive screening, intervention, and referral to treatment. A clinical decision rule is proposed. The correlation between problematic drug use and resource-intense ED triage levels suggests that ED-based efforts to reduce the unmet need for substance use treatment may help decrease overall health care costs. PMID:24999283

Causality Analysis: Identifying the Leading Element in a Coupled Dynamical System

PubMed Central

BozorgMagham, Amir E.; Motesharrei, Safa; Penny, Stephen G.; Kalnay, Eugenia

2015-01-01

Physical systems with time-varying internal couplings are abundant in nature. While the full governing equations of these systems are typically unknown due to insufficient understanding of their internal mechanisms, there is often interest in determining the leading element. Here, the leading element is defined as the sub-system with the largest coupling coefficient averaged over a selected time span. Previously, the Convergent Cross Mapping (CCM) method has been employed to determine causality and dominant component in weakly coupled systems with constant coupling coefficients. In this study, CCM is applied to a pair of coupled Lorenz systems with time-varying coupling coefficients, exhibiting switching between dominant sub-systems in different periods. Four sets of numerical experiments are carried out. The first three cases consist of different coupling coefficient schemes: I) Periodic–constant, II) Normal, and III) Mixed Normal/Non-normal. In case IV, numerical experiment of cases II and III are repeated with imposed temporal uncertainties as well as additive normal noise. Our results show that, through detecting directional interactions, CCM identifies the leading sub-system in all cases except when the average coupling coefficients are approximately equal, i.e., when the dominant sub-system is not well defined. PMID:26125157

Drug sensitivity profiling identifies potential therapies for lymphoproliferative disorders with overactive JAK/STAT3 signaling

PubMed Central

Kuusanmäki, Heikki; Dufva, Olli; Parri, Elina; van Adrichem, Arjan J.; Rajala, Hanna; Majumder, Muntasir M.; Yadav, Bhagwan; Parsons, Alun; Chan, Wing C.; Wennerberg, Krister; Mustjoki, Satu; Heckman, Caroline A.

2017-01-01

Constitutive JAK/STAT3 signaling contributes to disease progression in many lymphoproliferative disorders. Recent genetic analyses have revealed gain-of-function STAT3 mutations in lymphoid cancers leading to hyperactivation of STAT3, which may represent a potential therapeutic target. Using a functional reporter assay, we screened 306 compounds with selective activity against various target molecules to identify drugs capable of inhibiting the cellular activity of STAT3. Top hits were further validated with additional models including STAT3-mutated natural killer (NK)-cell leukemia/lymphoma cell lines and primary large granular lymphocytic (LGL) leukemia cells to assess their ability to inhibit STAT3 phosphorylation and STAT3 dependent cell viability. We identified JAK, mTOR, Hsp90 and CDK inhibitors as potent inhibitors of both WT and mutant STAT3 activity. The Hsp90 inhibitor luminespib was highly effective at reducing the viability of mutant STAT3 NK cell lines and LGL leukemia patient samples. Luminespib decreased the phosphorylation of mutant STAT3 at Y705, whereas JAK1/JAK2 inhibitor ruxolitinib had reduced efficacy on mutant STAT3 phosphorylation. Additionally, combinations involving Hsp90, JAK and mTOR inhibitors were more effective at reducing cell viability than single agents. Our findings show alternative approaches to inhibit STAT3 activity and suggest Hsp90 as a therapeutic target in lymphoproliferative disorders with constitutively active STAT3. PMID:29228628

A screen to identify drug resistant variants to target-directed anti-cancer agents

PubMed Central

Azam, Mohammad; Raz, Tal; Nardi, Valentina; Opitz, Sarah L.

2003-01-01

The discovery of oncogenes and signal transduction pathways important for mitogenesis has triggered the development of target-specific small molecule anti-cancer compounds. As exemplified by imatinib (Gleevec), a specific inhibitor of the Chronic Myeloid Leukemia (CML)-associated Bcr-Abl kinase, these agents promise impressive activity in clinical trials, with low levels of clinical toxicity. However, such therapy is susceptible to the emergence of drug resistance due to amino acid substitutions in the target protein. Defining the spectrum of such mutations is important for patient monitoring and the design of next-generation inhibitors. Using imatinib and BCR/ABL as a paradigm for a drug-target pair, we recently reported a retroviral vector-based screening strategy to identify the spectrum of resistance-conferring mutations. Here we provide a detailed methodology for the screen, which can be generally applied to any drug-target pair. PMID:14615817

New drug candidates for liposomal delivery identified by computer modeling of liposomes' remote loading and leakage.

PubMed

Cern, Ahuva; Marcus, David; Tropsha, Alexander; Barenholz, Yechezkel; Goldblum, Amiram

2017-04-28

Remote drug loading into nano-liposomes is in most cases the best method for achieving high concentrations of active pharmaceutical ingredients (API) per nano-liposome that enable therapeutically viable API-loaded nano-liposomes, referred to as nano-drugs. This approach also enables controlled drug release. Recently, we constructed computational models to identify APIs that can achieve the desired high concentrations in nano-liposomes by remote loading. While those previous models included a broad spectrum of experimental conditions and dealt only with loading, here we reduced the scope to the molecular characteristics alone. We model and predict API suitability for nano-liposomal delivery by fixing the main experimental conditions: liposome lipid composition and size to be similar to those of Doxil® liposomes. On that basis, we add a prediction of drug leakage from the nano-liposomes during storage. The latter is critical for having pharmaceutically viable nano-drugs. The "load and leak" models were used to screen two large molecular databases in search of candidate APIs for delivery by nano-liposomes. The distribution of positive instances in both loading and leakage models was similar in the two databases screened. The screening process identified 667 molecules that were positives by both loading and leakage models (i.e., both high-loading and stable). Among them, 318 molecules received a high score in both properties and of these, 67 are FDA-approved drugs. This group of molecules, having diverse pharmacological activities, may be the basis for future liposomal drug development. Copyright © 2017 Elsevier B.V. All rights reserved.

A Text Searching Tool to Identify Patients with Idiosyncratic Drug-Induced Liver Injury.

PubMed

Heidemann, Lauren; Law, James; Fontana, Robert J

2017-03-01

Idiosyncratic drug-induced liver injury (DILI) is an uncommon but important cause of liver disease that is challenging to diagnose and identify in the electronic medical record (EMR). To develop an accurate, reliable, and efficient method of identifying patients with bonafide DILI in an EMR system. In total, 527,000 outpatient and ER encounters in an EPIC-based EMR were searched for potential DILI cases attributed to eight drugs. A searching algorithm that extracted 200 characters of text around 14 liver injury terms in the EMR were extracted and collated. Physician investigators reviewed the data outputs and used standardized causality assessment methods to adjudicate the potential DILI cases. A total of 101 DILI cases were identified from the 2564 potential DILI cases that included 62 probable DILI cases, 25 possible DILI cases, nine historical DILI cases, and five allergy-only cases. Elimination of the term "liver disease" from the search strategy improved the search recall from 4 to 19 %, while inclusion of the four highest yield liver injury terms further improved the positive predictive value to 64 % but reduced the overall case detection rate by 47 %. RUCAM scores of the 57 probable DILI cases were generally high and concordant with expert opinion causality assessment scores. A novel text searching tool was developed that identified a large number of DILI cases from a widely used EMR system. A computerized extraction of dictated text followed by the manual review of text snippets can rapidly identify bona fide cases of idiosyncratic DILI.

Drug Synergy Screen and Network Modeling in Dedifferentiated Liposarcoma Identifies CDK4 and IGF1R as Synergistic Drug Targets

PubMed Central

Miller, Martin L.; Molinelli, Evan J.; Nair, Jayasree S.; Sheikh, Tahir; Samy, Rita; Jing, Xiaohong; He, Qin; Korkut, Anil; Crago, Aimee M.; Singer, Samuel; Schwartz, Gary K.; Sander, Chris

2014-01-01

Dedifferentiated liposarcoma (DDLS) is a rare but aggressive cancer with high recurrence and low response rates to targeted therapies. Increasing treatment efficacy may require combinations of targeted agents that counteract the effects of multiple abnormalities. To identify a possible multicomponent therapy, we performed a combinatorial drug screen in a DDLS-derived cell line and identified cyclin-dependent kinase 4 (CDK4) and insulin-like growth factor 1 receptor (IGF1R) as synergistic drug targets. We measured the phosphorylation of multiple proteins and cell viability in response to systematic drug combinations and derived computational models of the signaling network. These models predict that the observed synergy in reducing cell viability with CDK4 and IGF1R inhibitors depend on activity of the AKT pathway. Experiments confirmed that combined inhibition of CDK4 and IGF1R cooperatively suppresses the activation of proteins within the AKT pathway. Consistent with these findings, synergistic reductions in cell viability were also found when combining CDK4 inhibition with inhibition of either AKT or epidermal growth factor receptor (EGFR), another receptor similar to IGF1R that activates AKT. Thus, network models derived from context-specific proteomic measurements of systematically perturbed cancer cells may reveal cancer-specific signaling mechanisms and aid in the design of effective combination therapies. PMID:24065146

Identifying mechanism-of-action targets for drugs and probes

PubMed Central

Gregori-Puigjané, Elisabet; Setola, Vincent; Hert, Jérôme; Crews, Brenda A.; Irwin, John J.; Lounkine, Eugen; Marnett, Lawrence; Roth, Bryan L.; Shoichet, Brian K.

2012-01-01

Notwithstanding their key roles in therapy and as biological probes, 7% of approved drugs are purported to have no known primary target, and up to 18% lack a well-defined mechanism of action. Using a chemoinformatics approach, we sought to “de-orphanize” drugs that lack primary targets. Surprisingly, targets could be easily predicted for many: Whereas these targets were not known to us nor to the common databases, most could be confirmed by literature search, leaving only 13 Food and Drug Administration—approved drugs with unknown targets; the number of drugs without molecular targets likely is far fewer than reported. The number of worldwide drugs without reasonable molecular targets similarly dropped, from 352 (25%) to 44 (4%). Nevertheless, there remained at least seven drugs for which reasonable mechanism-of-action targets were unknown but could be predicted, including the antitussives clemastine, cloperastine, and nepinalone; the antiemetic benzquinamide; the muscle relaxant cyclobenzaprine; the analgesic nefopam; and the immunomodulator lobenzarit. For each, predicted targets were confirmed experimentally, with affinities within their physiological concentration ranges. Turning this question on its head, we next asked which drugs were specific enough to act as chemical probes. Over 100 drugs met the standard criteria for probes, and 40 did so by more stringent criteria. A chemical information approach to drug-target association can guide therapeutic development and reveal applications to probe biology, a focus of much current interest. PMID:22711801

A drug repositioning approach identifies tricyclic antidepressants as inhibitors of small cell lung cancer and other neuroendocrine tumors

PubMed Central

Jahchan, Nadine S; Dudley, Joel T; Mazur, Pawel K; Flores, Natasha; Yang, Dian; Palmerton, Alec; Zmoos, Anne-Flore; Vaka, Dedeepya; Tran, Kim QT; Zhou, Margaret; Krasinska, Karolina; Riess, Jonathan W; Neal, Joel W; Khatri, Purvesh; Park, Kwon S; Butte, Atul J; Sage, Julien

2013-01-01

Small cell lung cancer (SCLC) is an aggressive neuroendocrine subtype of lung cancer with high mortality. We used a systematic drug-repositioning bioinformatics approach querying a large compendium of gene expression profiles to identify candidate FDA-approved drugs to treat SCLC. We found that tricyclic antidepressants and related molecules potently induce apoptosis in both chemonaïve and chemoresistant SCLC cells in culture, in mouse and human SCLC tumors transplanted into immunocompromised mice, and in endogenous tumors from a mouse model for human SCLC. The candidate drugs activate stress pathways and induce cell death in SCLC cells, at least in part by disrupting autocrine survival signals involving neurotransmitters and their G protein-coupled receptors. The candidate drugs inhibit the growth of other neuroendocrine tumors, including pancreatic neuroendocrine tumors and Merkel cell carcinoma. These experiments identify novel targeted strategies that can be rapidly evaluated in patients with neuroendocrine tumors through the repurposing of approved drugs. PMID:24078773

Target-similarity search using Plasmodium falciparum proteome identifies approved drugs with anti-malarial activity and their possible targets

PubMed Central

Akala, Hoseah M.; Macharia, Rosaline W.; Juma, Dennis W.; Cheruiyot, Agnes C.; Andagalu, Ben; Brown, Mathew L.; El-Shemy, Hany A.; Nyanjom, Steven G.

2017-01-01

Malaria causes about half a million deaths annually, with Plasmodium falciparum being responsible for 90% of all the cases. Recent reports on artemisinin resistance in Southeast Asia warrant urgent discovery of novel drugs for the treatment of malaria. However, most bioactive compounds fail to progress to treatments due to safety concerns. Drug repositioning offers an alternative strategy where drugs that have already been approved as safe for other diseases could be used to treat malaria. This study screened approved drugs for antimalarial activity using an in silico chemogenomics approach prior to in vitro verification. All the P. falciparum proteins sequences available in NCBI RefSeq were mined and used to perform a similarity search against DrugBank, TTD and STITCH databases to identify similar putative drug targets. Druggability indices of the potential P. falciparum drug targets were obtained from TDR targets database. Functional amino acid residues of the drug targets were determined using ConSurf server which was used to fine tune the similarity search. This study predicted 133 approved drugs that could target 34 P. falciparum proteins. A literature search done at PubMed and Google Scholar showed 105 out of the 133 drugs to have been previously tested against malaria, with most showing activity. For further validation, drug susceptibility assays using SYBR Green I method were done on a representative group of 10 predicted drugs, eight of which did show activity against P. falciparum 3D7 clone. Seven had IC50 values ranging from 1 μM to 50 μM. This study also suggests drug-target association and hence possible mechanisms of action of drugs that did show antiplasmodial activity. The study results validate the use of proteome-wide target similarity approach in identifying approved drugs with activity against P. falciparum and could be adapted for other pathogens. PMID:29088219

Experiences in fragment-based drug discovery.

PubMed

Murray, Christopher W; Verdonk, Marcel L; Rees, David C

2012-05-01

Fragment-based drug discovery (FBDD) has become established in both industry and academia as an alternative approach to high-throughput screening for the generation of chemical leads for drug targets. In FBDD, specialised detection methods are used to identify small chemical compounds (fragments) that bind to the drug target, and structural biology is usually employed to establish their binding mode and to facilitate their optimisation. In this article, we present three recent and successful case histories in FBDD. We then re-examine the key concepts and challenges of FBDD with particular emphasis on recent literature and our own experience from a substantial number of FBDD applications. Our opinion is that careful application of FBDD is living up to its promise of delivering high quality leads with good physical properties and that in future many drug molecules will be derived from fragment-based approaches. Copyright © 2012 Elsevier Ltd. All rights reserved.

Ontology-based literature mining and class effect analysis of adverse drug reactions associated with neuropathy-inducing drugs.

PubMed

Hur, Junguk; Özgür, Arzucan; He, Yongqun

2018-06-07

drugs and their associated ADRs. Furthermore, our analysis of drug class effects identified 3 benzimidazole drugs sharing 43 ADRs, leading to new hypothesis generation and possible mechanism understanding of drug-induced peripheral neuropathy.

Novel Approaches to Pulmonary Arterial Hypertension Drug Discovery

PubMed Central

Sung, Yon K.; Yuan, Ke; de Jesus Perez, Vinicio A.

2016-01-01

Introduction Pulmonary arterial hypertension (PAH) is a rare disorder associated with abnormally elevated pulmonary pressures that, if untreated, leads to right heart failure and premature death. The goal of drug development for PAH is to develop effective therapies that halt, or ideally, reverse the obliterative vasculopathy that results in vessel loss and obstruction of blood flow to the lungs. Areas Covered This review summarizes the current approach to candidate discovery in PAH and discusses the currently available drug discovery methods that should be implemented to prioritize targets and obtain a comprehensive pharmacological profile of promising compounds with well-defined mechanisms. Expert opinion To improve the successful identification of leading drug candidates, it is necessary that traditional pre-clinical studies are combined with drug screening strategies that maximize the characterization of biological activity and identify relevant off-target effects that could hinder the clinical efficacy of the compound when tested in human subjects. A successful drug discovery strategy in PAH will require collaboration of clinician scientists with medicinal chemists and pharmacologists who can identify compounds with an adequate safety profile and biological activity against relevant disease mechanisms. PMID:26901465

Food and drug interaction: consequences for the nutrition/health status.

PubMed

Genser, Dieter

2008-01-01

Food-drug interactions are defined as alterations of pharmacokinetics or pharmacodynamics of a drug or nutritional element or a compromise in nutritional status as a result of the addition of a drug. Elderly patients are particularly at risk because more than 30% of all the prescription drugs are taken by this population. Failure to identify and properly manage drug-nutrient interactions can lead to serious consequences. For instance, drug-nutrient interactions can result in reduced absorption of certain oral antibiotics and may lead to suboptimal antibiotic concentrations at the site of infection. This predisposes the patient to treatment failure. Induction or inhibition of enzymes in the gut by nutrients may lead to a significant change in oral bioavailability of drugs or vice versa. For example, grapefruit juice is a selective intestinal CYP3A4 inhibitor. The overall exposure of some drugs can be increased by more than fivefold when taken with grapefruit juice and increase the risk of adverse effects. The use of certain drugs may affect GI tract function and may lead to a loss of bodily electrolytes and fluid. Limiting drug prescriptions to essential medications for as short a period as possible and periodic re-evaluations of the treatment chosen are essential to minimize adverse drug-nutrient interactions. Copyright 2008 S. Karger AG, Basel.

Systems Biology-Based Investigation of Cellular Antiviral Drug Targets Identified by Gene-Trap Insertional Mutagenesis.

PubMed

Cheng, Feixiong; Murray, James L; Zhao, Junfei; Sheng, Jinsong; Zhao, Zhongming; Rubin, Donald H

2016-09-01

Viruses require host cellular factors for successful replication. A comprehensive systems-level investigation of the virus-host interactome is critical for understanding the roles of host factors with the end goal of discovering new druggable antiviral targets. Gene-trap insertional mutagenesis is a high-throughput forward genetics approach to randomly disrupt (trap) host genes and discover host genes that are essential for viral replication, but not for host cell survival. In this study, we used libraries of randomly mutagenized cells to discover cellular genes that are essential for the replication of 10 distinct cytotoxic mammalian viruses, 1 gram-negative bacterium, and 5 toxins. We herein reported 712 candidate cellular genes, characterizing distinct topological network and evolutionary signatures, and occupying central hubs in the human interactome. Cell cycle phase-specific network analysis showed that host cell cycle programs played critical roles during viral replication (e.g. MYC and TAF4 regulating G0/1 phase). Moreover, the viral perturbation of host cellular networks reflected disease etiology in that host genes (e.g. CTCF, RHOA, and CDKN1B) identified were frequently essential and significantly associated with Mendelian and orphan diseases, or somatic mutations in cancer. Computational drug repositioning framework via incorporating drug-gene signatures from the Connectivity Map into the virus-host interactome identified 110 putative druggable antiviral targets and prioritized several existing drugs (e.g. ajmaline) that may be potential for antiviral indication (e.g. anti-Ebola). In summary, this work provides a powerful methodology with a tight integration of gene-trap insertional mutagenesis testing and systems biology to identify new antiviral targets and drugs for the development of broadly acting and targeted clinical antiviral therapeutics.

Predicting Pharmacodynamic Drug-Drug Interactions through Signaling Propagation Interference on Protein-Protein Interaction Networks.

PubMed

Park, Kyunghyun; Kim, Docyong; Ha, Suhyun; Lee, Doheon

2015-01-01

As pharmacodynamic drug-drug interactions (PD DDIs) could lead to severe adverse effects in patients, it is important to identify potential PD DDIs in drug development. The signaling starting from drug targets is propagated through protein-protein interaction (PPI) networks. PD DDIs could occur by close interference on the same targets or within the same pathways as well as distant interference through cross-talking pathways. However, most of the previous approaches have considered only close interference by measuring distances between drug targets or comparing target neighbors. We have applied a random walk with restart algorithm to simulate signaling propagation from drug targets in order to capture the possibility of their distant interference. Cross validation with DrugBank and Kyoto Encyclopedia of Genes and Genomes DRUG shows that the proposed method outperforms the previous methods significantly. We also provide a web service with which PD DDIs for drug pairs can be analyzed at http://biosoft.kaist.ac.kr/targetrw.

An RNAi-mediated screen identifies novel targets for next-generation antiepileptic drugs based on increased expression of the homeostatic regulator pumilio.

PubMed

Lin, Wei-Hsiang; He, Miaomiao; Fan, Yuen Ngan; Baines, Richard A

2018-05-02

Despite availability of a diverse range of anti-epileptic drugs (AEDs), only about two-thirds of epilepsy patients respond well to drug treatment. Thus, novel targets are required to catalyse the design of next-generation AEDs. Manipulation of neuron firing-rate homoeostasis, through enhancing Pumilio (Pum) activity, has been shown to be potently anticonvulsant in Drosophila. In this study, we performed a genome-wide RNAi screen in S2R + cells, using a luciferase-based dPum activity reporter and identified 1166 genes involved in dPum regulation. Of these genes, we focused on 699 genes that, on knock-down, potentiate dPum activity/expression. Of this subgroup, 101 genes are activity-dependent based on comparison with genes previously identified as activity-dependent by RNA-sequencing. Functional cluster analysis shows these genes are enriched in pathways involved in DNA damage, regulation of cell cycle and proteasomal protein catabolism. To test for anticonvulsant activity, we utilised an RNA-interference approach in vivo. RNAi-mediated knockdown showed that 57/101 genes (61%) are sufficient to significantly reduce seizure duration in the characterized seizure mutant, para bss . We further show that chemical inhibitors of protein products of some of the genes targeted are similarly anticonvulsant. Finally, to establish whether the anticonvulsant activity of identified compounds results from increased dpum transcription, we performed a luciferase-based assay to monitor dpum promoter activity. Third instar larvae exposed to sodium fluoride, gemcitabine, metformin, bestatin, WP1066 or valproic acid all showed increased dpum promoter activity. Thus, this study validates Pum as a favourable target for AED design and, moreover, identifies a number of lead compounds capable of increasing the expression of this homeostatic regulator.

Three-Dimensional Cell Culture-Based Screening Identifies the Anthelmintic Drug Nitazoxanide as a Candidate for Treatment of Colorectal Cancer.

PubMed

Senkowski, Wojciech; Zhang, Xiaonan; Olofsson, Maria Hägg; Isacson, Ruben; Höglund, Urban; Gustafsson, Mats; Nygren, Peter; Linder, Stig; Larsson, Rolf; Fryknäs, Mårten

2015-06-01

Because dormant cancer cells in hypoxic and nutrient-deprived regions of solid tumors provide a major obstacle to treatment, compounds targeting those cells might have clinical benefits. Here, we describe a high-throughput drug screening approach, using glucose-deprived multicellular tumor spheroids (MCTS) with inner hypoxia, to identify compounds that specifically target this cell population. We used a concept of drug repositioning-using known molecules for new indications. This is a promising strategy to identify molecules for rapid clinical advancement. By screening 1,600 compounds with documented clinical history, we aimed to identify candidates with unforeseen potential for repositioning as anticancer drugs. Our screen identified five molecules with pronounced MCTS-selective activity: nitazoxanide, niclosamide, closantel, pyrvinium pamoate, and salinomycin. Herein, we show that all five compounds inhibit mitochondrial respiration. This suggests that cancer cells in low glucose concentrations depend on oxidative phosphorylation rather than solely glycolysis. Importantly, continuous exposure to the compounds was required to achieve effective treatment. Nitazoxanide, an FDA-approved antiprotozoal drug with excellent pharmacokinetic and safety profile, is the only molecule among the screening hits that reaches high plasma concentrations persisting for up to a few hours after single oral dose. Nitazoxanide activated the AMPK pathway and downregulated c-Myc, mTOR, and Wnt signaling at clinically achievable concentrations. Nitazoxanide combined with the cytotoxic drug irinotecan showed anticancer activity in vivo. We here report that the FDA-approved anthelmintic drug nitazoxanide could be a potential candidate for advancement into cancer clinical trials. ©2015 American Association for Cancer Research.

Binding Free Energy Calculations for Lead Optimization: Assessment of Their Accuracy in an Industrial Drug Design Context.

PubMed

Homeyer, Nadine; Stoll, Friederike; Hillisch, Alexander; Gohlke, Holger

2014-08-12

Correctly ranking compounds according to their computed relative binding affinities will be of great value for decision making in the lead optimization phase of industrial drug discovery. However, the performance of existing computationally demanding binding free energy calculation methods in this context is largely unknown. We analyzed the performance of the molecular mechanics continuum solvent, the linear interaction energy (LIE), and the thermodynamic integration (TI) approach for three sets of compounds from industrial lead optimization projects. The data sets pose challenges typical for this early stage of drug discovery. None of the methods was sufficiently predictive when applied out of the box without considering these challenges. Detailed investigations of failures revealed critical points that are essential for good binding free energy predictions. When data set-specific features were considered accordingly, predictions valuable for lead optimization could be obtained for all approaches but LIE. Our findings lead to clear recommendations for when to use which of the above approaches. Our findings also stress the important role of expert knowledge in this process, not least for estimating the accuracy of prediction results by TI, using indicators such as the size and chemical structure of exchanged groups and the statistical error in the predictions. Such knowledge will be invaluable when it comes to the question which of the TI results can be trusted for decision making.

How Cannabis Causes Paranoia: Using the Intravenous Administration of ∆9-Tetrahydrocannabinol (THC) to Identify Key Cognitive Mechanisms Leading to Paranoia

PubMed Central

Freeman, Daniel; Dunn, Graham; Murray, Robin M.; Evans, Nicole; Lister, Rachel; Antley, Angus; Slater, Mel; Godlewska, Beata; Cornish, Robert; Williams, Jonathan; Di Simplicio, Martina; Igoumenou, Artemis; Brenneisen, Rudolf; Tunbridge, Elizabeth M.; Harrison, Paul J.; Harmer, Catherine J.; Cowen, Philip; Morrison, Paul D.

2015-01-01

Paranoia is receiving increasing attention in its own right, since it is a central experience of psychotic disorders and a marker of the health of a society. Paranoia is associated with use of the most commonly taken illicit drug, cannabis. The objective was to determine whether the principal psychoactive ingredient of cannabis—∆9-tetrahydrocannabinol (THC)—causes paranoia and to use the drug as a probe to identify key cognitive mechanisms underlying paranoia. A randomized, placebo-controlled, between-groups test of the effects of intravenous THC was conducted. A total of 121 individuals with paranoid ideation were randomized to receive placebo, THC, or THC preceded by a cognitive awareness condition. Paranoia was assessed extensively via a real social situation, an immersive virtual reality experiment, and standard self-report and interviewer measures. Putative causal factors were assessed. Principal components analysis was used to create a composite paranoia score and composite causal variables to be tested in a mediation analysis. THC significantly increased paranoia, negative affect (anxiety, worry, depression, negative thoughts about the self), and a range of anomalous experiences, and reduced working memory capacity. The increase in negative affect and in anomalous experiences fully accounted for the increase in paranoia. Working memory changes did not lead to paranoia. Making participants aware of the effects of THC had little impact. In this largest study of intravenous THC, it was definitively demonstrated that the drug triggers paranoid thoughts in vulnerable individuals. The most likely mechanism of action causing paranoia was the generation of negative affect and anomalous experiences. PMID:25031222

Drug and Alcohol Exposed Children: Implications for Special Education for Students Identified as Behaviorally Disordered.

ERIC Educational Resources Information Center

Bauer, Anne M.

1991-01-01

This article reviews the literature on children prenatally exposed to drugs and alcohol, the potential impact on the educational and social services systems, and implications for programing for children identified as behaviorally disordered. (Author/JDD)

Fragment-based drug discovery and molecular docking in drug design.

PubMed

Wang, Tao; Wu, Mian-Bin; Chen, Zheng-Jie; Chen, Hua; Lin, Jian-Ping; Yang, Li-Rong

2015-01-01

Fragment-based drug discovery (FBDD) has caused a revolution in the process of drug discovery and design, with many FBDD leads being developed into clinical trials or approved in the past few years. Compared with traditional high-throughput screening, it displays obvious advantages such as efficiently covering chemical space, achieving higher hit rates, and so forth. In this review, we focus on the most recent developments of FBDD for improving drug discovery, illustrating the process and the importance of FBDD. In particular, the computational strategies applied in the process of FBDD and molecular-docking programs are highlighted elaborately. In most cases, docking is used for predicting the ligand-receptor interaction modes and hit identification by structurebased virtual screening. The successful cases of typical significance and the hits identified most recently are discussed.

Spirocyclic ureas: orally bioavailable 11 beta-HSD1 inhibitors identified by computer-aided drug design.

PubMed

Tice, Colin M; Zhao, Wei; Xu, Zhenrong; Cacatian, Salvacion T; Simpson, Robert D; Ye, Yuan-Jie; Singh, Suresh B; McKeever, Brian M; Lindblom, Peter; Guo, Joan; Krosky, Paula M; Kruk, Barbara A; Berbaum, Jennifer; Harrison, Richard K; Johnson, Judith J; Bukhtiyarov, Yuri; Panemangalore, Reshma; Scott, Boyd B; Zhao, Yi; Bruno, Joseph G; Zhuang, Linghang; McGeehan, Gerard M; He, Wei; Claremon, David A

2010-02-01

Structure-guided drug design led to the identification of a class of spirocyclic ureas which potently inhibit human 11beta-HSD1 in vitro. Lead compound 10j was shown to be orally bioavailable in three species, distributed into adipose tissue in the mouse, and its (R) isomer 10j2 was efficacious in a primate pharmacodynamic model. Copyright (c) 2009 Elsevier Ltd. All rights reserved.

Oncology drug discovery: planning a turnaround.

PubMed

Toniatti, Carlo; Jones, Philip; Graham, Hilary; Pagliara, Bruno; Draetta, Giulio

2014-04-01

We have made remarkable progress in our understanding of the pathophysiology of cancer. This improved understanding has resulted in increasingly effective targeted therapies that are better tolerated than conventional cytotoxic agents and even curative in some patients. Unfortunately, the success rate of drug approval has been limited, and therapeutic improvements have been marginal, with too few exceptions. In this article, we review the current approach to oncology drug discovery and development, identify areas in need of improvement, and propose strategies to improve patient outcomes. We also suggest future directions that may improve the quality of preclinical and early clinical drug evaluation, which could lead to higher approval rates of anticancer drugs.

An investigation into drug-related problems identifiable by commercial medication review software.

PubMed

Curtain, Colin; Bindoff, Ivan; Westbury, Juanita; Peterson, Gregory

2013-01-01

Accredited pharmacists conduct home medicines reviews (HMRs) to detect and resolve potential drug-related problems (DRPs). A commercial expert system, Medscope Review Mentor (MRM), has been developed to assist pharmacists in the detection and resolution of potential DRPs. This study compares types of DRPs identified with the commercial system which uses multiple classification ripple down rules (MCRDR) with the findings of pharmacists. HMR data from 570 reviews collected from accredited pharmacists was entered into MRM and the DRPs were identified. A list of themes describing the main concept of each DRP identified by MRM was developed to allow comparison with pharmacists. Theme types, frequencies, similarity and dissimilarity were explored. The expert system was capable of detecting a wide range of potential DRPs: 2854 themes; compared to pharmacists: 1680 themes. The system identified the same problems as pharmacists in many patient cases. Ninety of 119 types of themes identifiable by pharmacists were also identifiable by software. MRM could identify the same problems in the same patients as pharmacists for 389 problems, resulting in a low overlap of similarity with an averaged Jaccard Index of 0.09. MRM found significantly more potential DRPs than pharmacists. MRM identified a wide scope of DRPs approaching the range of DRPs that were identified by pharmacists. Differences may be associated with system consistency and perhaps human oversight or human selective prioritisation. DRPs identified by the system were still considered relevant even though the system identified a larger number of problems.

Inhibitors of ubiquitin E3 ligase as potential new antimalarial drug leads.

PubMed

Jain, Jagrati; Jain, Surendra K; Walker, Larry A; Tekwani, Babu L

2017-06-02

inhibitors shall provide better understanding regarding the importance of E3 ligase functions in the malaria parasite as a potential new antimalarial drug target and a new class of antimalarial drug leads.

Pharmacokinetic de-risking tools for selection of monoclonal antibody lead candidates

PubMed Central

Dostalek, Miroslav; Prueksaritanont, Thomayant; Kelley, Robert F.

2017-01-01

ABSTRACT Pharmacokinetic studies play an important role in all stages of drug discovery and development. Recent advancements in the tools for discovery and optimization of therapeutic proteins have created an abundance of candidates that may fulfill target product profile criteria. Implementing a set of in silico, small scale in vitro and in vivo tools can help to identify a clinical lead molecule with promising properties at the early stages of drug discovery, thus reducing the labor and cost in advancing multiple candidates toward clinical development. In this review, we describe tools that should be considered during drug discovery, and discuss approaches that could be included in the pharmacokinetic screening part of the lead candidate generation process to de-risk unexpected pharmacokinetic behaviors of Fc-based therapeutic proteins, with an emphasis on monoclonal antibodies. PMID:28463063

Back to the Future: Lessons Learned in Modern Target-based and Whole-Cell Lead Optimization of Antimalarials

PubMed Central

Chatterjee, Arnab K; Yeung, Bryan KS

2012-01-01

Antimalarial drug discovery has historically benefited from the whole-cell (phenotypic) screening approach to identify lead molecules in the search for new drugs. However over the past two decades there has been a shift in the pharmaceutical industry to move away from whole-cell screening to target-based approaches. As part of a Wellcome Trust and Medicines for Malaria Venture (MMV) funded consortium to discover new blood-stage antimalarials, we used both approaches to identify new antimalarial chemotypes, two of which have progressed beyond the lead optimization phase and display excellent in vivo efficacy in mice. These two advanced series were identified through a cell-based optimization devoid of target information and in this review we summarize the advantages of this approach versus a target-based optimization. Although the each lead optimization required slightly different medicinal chemistry strategies, we observed some common issues across the different the scaffolds which could be applied to other cell based lead optimization programs. PMID:22242845

Identifying and Quantifying Heterogeneity in High Content Analysis: Application of Heterogeneity Indices to Drug Discovery

PubMed Central

Gough, Albert H.; Chen, Ning; Shun, Tong Ying; Lezon, Timothy R.; Boltz, Robert C.; Reese, Celeste E.; Wagner, Jacob; Vernetti, Lawrence A.; Grandis, Jennifer R.; Lee, Adrian V.; Stern, Andrew M.; Schurdak, Mark E.; Taylor, D. Lansing

2014-01-01

One of the greatest challenges in biomedical research, drug discovery and diagnostics is understanding how seemingly identical cells can respond differently to perturbagens including drugs for disease treatment. Although heterogeneity has become an accepted characteristic of a population of cells, in drug discovery it is not routinely evaluated or reported. The standard practice for cell-based, high content assays has been to assume a normal distribution and to report a well-to-well average value with a standard deviation. To address this important issue we sought to define a method that could be readily implemented to identify, quantify and characterize heterogeneity in cellular and small organism assays to guide decisions during drug discovery and experimental cell/tissue profiling. Our study revealed that heterogeneity can be effectively identified and quantified with three indices that indicate diversity, non-normality and percent outliers. The indices were evaluated using the induction and inhibition of STAT3 activation in five cell lines where the systems response including sample preparation and instrument performance were well characterized and controlled. These heterogeneity indices provide a standardized method that can easily be integrated into small and large scale screening or profiling projects to guide interpretation of the biology, as well as the development of therapeutics and diagnostics. Understanding the heterogeneity in the response to perturbagens will become a critical factor in designing strategies for the development of therapeutics including targeted polypharmacology. PMID:25036749

Identifying and quantifying heterogeneity in high content analysis: application of heterogeneity indices to drug discovery.

PubMed

Gough, Albert H; Chen, Ning; Shun, Tong Ying; Lezon, Timothy R; Boltz, Robert C; Reese, Celeste E; Wagner, Jacob; Vernetti, Lawrence A; Grandis, Jennifer R; Lee, Adrian V; Stern, Andrew M; Schurdak, Mark E; Taylor, D Lansing

2014-01-01

One of the greatest challenges in biomedical research, drug discovery and diagnostics is understanding how seemingly identical cells can respond differently to perturbagens including drugs for disease treatment. Although heterogeneity has become an accepted characteristic of a population of cells, in drug discovery it is not routinely evaluated or reported. The standard practice for cell-based, high content assays has been to assume a normal distribution and to report a well-to-well average value with a standard deviation. To address this important issue we sought to define a method that could be readily implemented to identify, quantify and characterize heterogeneity in cellular and small organism assays to guide decisions during drug discovery and experimental cell/tissue profiling. Our study revealed that heterogeneity can be effectively identified and quantified with three indices that indicate diversity, non-normality and percent outliers. The indices were evaluated using the induction and inhibition of STAT3 activation in five cell lines where the systems response including sample preparation and instrument performance were well characterized and controlled. These heterogeneity indices provide a standardized method that can easily be integrated into small and large scale screening or profiling projects to guide interpretation of the biology, as well as the development of therapeutics and diagnostics. Understanding the heterogeneity in the response to perturbagens will become a critical factor in designing strategies for the development of therapeutics including targeted polypharmacology.

Analytical surveillance of emerging drugs of abuse and drug formulations

PubMed Central

Thomas, Brian F.; Pollard, Gerald T.; Grabenauer, Megan

2012-01-01

Uncontrolled recreational drugs are proliferating in number and variety. Effects of long-term use are unknown, and regulation is problematic, as efforts to control one chemical often lead to several other structural analogs. Advanced analytical instrumentation and methods are continuing to be developed to identify drugs, chemical constituents of products, and drug substances and metabolites in biological fluids. Several mass spectrometry based approaches appear promising, particularly those that involve high resolution chromatographic and mass spectrometric methods that allow unbiased data acquisition and sophisticated data interrogation. Several of these techniques are shown to facilitate both targeted and broad spectrum analysis, which is often of particular benefit when dealing with misleadingly labeled products or assessing a biological matrix for illicit drugs and metabolites. The development and application of novel analytical approaches such as these will help to assess the nature and degree of exposure and risk and, where necessary, inform forensics and facilitate implementation of specific regulation and control measures. PMID:23154240

Can we identify response markers to antihypertensive drugs? First results from the IDEAL Trial.

PubMed

Gueyffier, F; Subtil, F; Bejan-Angoulvant, T; Zerbib, Y; Baguet, J P; Boivin, J M; Mercier, A; Leftheriotis, G; Gagnol, J P; Fauvel, J P; Giraud, C; Bricca, G; Maucort-Boulch, D; Erpeldinger, S

2015-01-01

Current antihypertensive strategies do not take into account that individual characteristics may influence the magnitude of blood pressure (BP) reduction. Guidelines promote trial-and-error approaches with many different drugs. We conducted the Identification of the Determinants of the Efficacy of Arterial blood pressure Lowering drugs (IDEAL) Trial to identify factors associated with BP responses to perindopril and indapamide. IDEAL was a cross-over, double-blind, placebo-controlled trial, involving four 4-week periods: indapamide, perindopril and two placebo. Eligible patients were untreated, hypertensive and aged 25-70 years. The main outcome was systolic BP (SBP) response to drugs. The 112 participants with good compliance had a mean age of 52. One in every three participants was a woman. In middle-aged women, the SBP reduction from drugs was -11.5 mm Hg (indapamide) and -8.3 mm Hg (perindopril). In men, the response was significantly smaller: -4.8 mm Hg (indapamide) and -4.3 (perindopril) (P for sex differences 0.001 and 0.015, respectively). SBP response to perindopril decreased by 2 mm Hg every 10 years of age in both sexes (P=0.01). The response to indapamide increased by 3 mm Hg every 10 years of age gradient in women (P=0.02). Age and sex were important determinants of BP response for antihypertensive drugs in the IDEAL population. This should be taken into account when choosing drugs a priori.

Drug Discovery Using Chemical Systems Biology: Repositioning the Safe Medicine Comtan to Treat Multi-Drug and Extensively Drug Resistant Tuberculosis

PubMed Central

Tonge, Peter J.; Xie, Lei; Bourne, Philip E.

2009-01-01

The rise of multi-drug resistant (MDR) and extensively drug resistant (XDR) tuberculosis around the world, including in industrialized nations, poses a great threat to human health and defines a need to develop new, effective and inexpensive anti-tubercular agents. Previously we developed a chemical systems biology approach to identify off-targets of major pharmaceuticals on a proteome-wide scale. In this paper we further demonstrate the value of this approach through the discovery that existing commercially available drugs, prescribed for the treatment of Parkinson's disease, have the potential to treat MDR and XDR tuberculosis. These drugs, entacapone and tolcapone, are predicted to bind to the enzyme InhA and directly inhibit substrate binding. The prediction is validated by in vitro and InhA kinetic assays using tablets of Comtan, whose active component is entacapone. The minimal inhibition concentration (MIC99) of entacapone for Mycobacterium tuberculosis (M.tuberculosis) is approximately 260.0 µM, well below the toxicity concentration determined by an in vitro cytotoxicity model using a human neuroblastoma cell line. Moreover, kinetic assays indicate that Comtan inhibits InhA activity by 47.0% at an entacapone concentration of approximately 80 µM. Thus the active component in Comtan represents a promising lead compound for developing a new class of anti-tubercular therapeutics with excellent safety profiles. More generally, the protocol described in this paper can be included in a drug discovery pipeline in an effort to discover novel drug leads with desired safety profiles, and therefore accelerate the development of new drugs. PMID:19578428

Genetical Toxicogenomics in Drosophila Identifies Master Modulatory Loci that are Regulated by Developmental Exposure to Lead

PubMed Central

Ruden, Douglas M.; Chen, Lang; Possidente, Debra; Possidente, Bernard; Rasouli, Parsa; Wang, Luan; Lu, Xiangyi; Garfinkel, Mark D.; Hirsch, Helmut V. B.; Page, Grier P.

2009-01-01

The genetics of gene expression in recombinant inbred lines (RILs) can be mapped as expression quantitative trait loci (eQTLs). So-called “genetical genomics” studies have identified locally-acting eQTLs (cis-eQTLs) for genes that show differences in steady state RNA levels. These studies have also identified distantly-acting master-modulatory trans-eQTLs that regulate tens or hundreds of transcripts (hotspots or transbands). We expand on these studies by performing genetical genomics experiments in two environments in order to identify trans-eQTL that might be regulated by developmental exposure to the neurotoxin lead. Flies from each of 75 RIL were raised from eggs to adults on either control food (made with 250 µM sodium acetate), or lead-treated food (made with 250 µM lead acetate, PbAc). RNA expression analyses of whole adult male flies (5–10 days old) were performed with Affymetrix DrosII whole genome arrays (18,952 probesets). Among the 1,389 genes with cis-eQTL, there were 405 genes unique to control flies and 544 genes unique to lead-treated ones (440 genes had the same cis-eQTLs in both samples). There are 2,396 genes with trans-eQTL which mapped to 12 major transbands with greater than 95 genes. Permutation analyses of the strain labels but not the expression data suggests that the total number of eQTL and the number of transbands are more important criteria for validation than the size of the transband. Two transbands, one located on the 2nd chromosome and one on the 3rd chromosome, co-regulate 33 lead-induced genes, many of which are involved in neurodevelopmental processes. For these 33 genes, rather than allelic variation at one locus exerting differential effects in two environments, we found that variation at two different loci are required for optimal effects on lead-induced expression. PMID:19737576

In Silico Identification of Proteins Associated with Drug-induced Liver Injury Based on the Prediction of Drug-target Interactions.

PubMed

Ivanov, Sergey; Semin, Maxim; Lagunin, Alexey; Filimonov, Dmitry; Poroikov, Vladimir

2017-07-01

Drug-induced liver injury (DILI) is the leading cause of acute liver failure as well as one of the major reasons for drug withdrawal from clinical trials and the market. Elucidation of molecular interactions associated with DILI may help to detect potentially hazardous pharmacological agents at the early stages of drug development. The purpose of our study is to investigate which interactions with specific human protein targets may cause DILI. Prediction of interactions with 1534 human proteins was performed for the dataset with information about 699 drugs, which were divided into three categories of DILI: severe (178 drugs), moderate (310 drugs) and without DILI (211 drugs). Based on the comparison of drug-target interactions predicted for different drugs' categories and interpretation of those results using clustering, Gene Ontology, pathway and gene expression analysis, we identified 61 protein targets associated with DILI. Most of the revealed proteins were linked with hepatocytes' death caused by disruption of vital cellular processes, as well as the emergence of inflammation in the liver. It was found that interaction of a drug with the identified targets is the essential molecular mechanism of the severe DILI for the most of the considered pharmaceuticals. Thus, pharmaceutical agents interacting with many of the identified targets may be considered as candidates for filtering out at the early stages of drug research. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Safety Lead Optimization and Candidate Identification: Integrating New Technologies into Decision-Making.

PubMed

Dambach, Donna M; Misner, Dinah; Brock, Mathew; Fullerton, Aaron; Proctor, William; Maher, Jonathan; Lee, Dong; Ford, Kevin; Diaz, Dolores

2016-04-18

Discovery toxicology focuses on the identification of the most promising drug candidates through the development and implementation of lead optimization strategies and hypothesis-driven investigation of issues that enable rational and informed decision-making. The major goals are to [a] identify and progress the drug candidate with the best overall drug safety profile for a therapeutic area, [b] remove the most toxic drugs from the portfolio prior to entry into humans to reduce clinical attrition due to toxicity, and [c] establish a well-characterized hazard and translational risk profile to enable clinical trial designs. This is accomplished through a framework that balances the multiple considerations to identify a drug candidate with the overall best drug characteristics and provides a cogent understanding of mechanisms of toxicity. The framework components include establishing a target candidate profile for each program that defines the qualities of a successful candidate based on the intended therapeutic area, including the risk tolerance for liabilities; evaluating potential liabilities that may result from engaging the therapeutic target (pharmacology-mediated or on-target) and that are chemical structure-mediated (off-target); and characterizing identified liabilities. Lead optimization and investigation relies upon the integrated use of a variety of technologies and models (in silico, in vitro, and in vivo) that have achieved a sufficient level of qualification or validation to provide confidence in their use. We describe the strategic applications of various nonclinical models (established and new) for a holistic and integrated risk assessment that is used for rational decision-making. While this review focuses on strategies for small molecules, the overall concepts, approaches, and technologies are generally applicable to biotherapeutics.

How cannabis causes paranoia: using the intravenous administration of ∆9-tetrahydrocannabinol (THC) to identify key cognitive mechanisms leading to paranoia.

PubMed

Freeman, Daniel; Dunn, Graham; Murray, Robin M; Evans, Nicole; Lister, Rachel; Antley, Angus; Slater, Mel; Godlewska, Beata; Cornish, Robert; Williams, Jonathan; Di Simplicio, Martina; Igoumenou, Artemis; Brenneisen, Rudolf; Tunbridge, Elizabeth M; Harrison, Paul J; Harmer, Catherine J; Cowen, Philip; Morrison, Paul D

2015-03-01

Paranoia is receiving increasing attention in its own right, since it is a central experience of psychotic disorders and a marker of the health of a society. Paranoia is associated with use of the most commonly taken illicit drug, cannabis. The objective was to determine whether the principal psychoactive ingredient of cannabis-∆(9)-tetrahydrocannabinol (THC)-causes paranoia and to use the drug as a probe to identify key cognitive mechanisms underlying paranoia. A randomized, placebo-controlled, between-groups test of the effects of intravenous THC was conducted. A total of 121 individuals with paranoid ideation were randomized to receive placebo, THC, or THC preceded by a cognitive awareness condition. Paranoia was assessed extensively via a real social situation, an immersive virtual reality experiment, and standard self-report and interviewer measures. Putative causal factors were assessed. Principal components analysis was used to create a composite paranoia score and composite causal variables to be tested in a mediation analysis. THC significantly increased paranoia, negative affect (anxiety, worry, depression, negative thoughts about the self), and a range of anomalous experiences, and reduced working memory capacity. The increase in negative affect and in anomalous experiences fully accounted for the increase in paranoia. Working memory changes did not lead to paranoia. Making participants aware of the effects of THC had little impact. In this largest study of intravenous THC, it was definitively demonstrated that the drug triggers paranoid thoughts in vulnerable individuals. The most likely mechanism of action causing paranoia was the generation of negative affect and anomalous experiences. © The Author 2014. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.

Lead - nutritional considerations

MedlinePlus

... and brains are growing rapidly. Many federal agencies study and monitor lead exposure. The Food and Drug Administration (FDA) monitors lead in food, beverages, food containers, and tableware. The Environmental Protection Agency ( ...

Leading the Game, Losing the Competition: Identifying Leaders and Followers in a Repeated Game

PubMed Central

Seip, Knut Lehre; Grøn, Øyvind

2016-01-01

We explore a new method for identifying leaders and followers, LF, in repeated games by analyzing an experimental, repeated (50 rounds) game where Row player shifts the payoff between small and large values–a type of “investor” and Column player determines who gets the payoff–a type of “manager”. We found that i) the Investor (Row) most often is a leading player and the manager (Column) a follower. The longer the Investor leads the game, the higher is both player’s payoff. Surprisingly however, it is always the Manager that achieves the largest payoff. ii) The game has an efficient cooperative strategy where the players alternate in receiving a high payoff, but the players never identify, or accept, that strategy. iii) Under the assumption that the information used by the players is closely associated with the leader- follower sequence, and that information is available before the player’s decisions are made, the players switched LF- strategy primarily as a function of information on the Investor’s investment and moves and secondly as a function of the Manager’s payoff. PMID:26968032

Exploration of the Anti-Inflammatory Drug Space Through Network Pharmacology: Applications for Drug Repurposing

PubMed Central

de Anda-Jáuregui, Guillermo; Guo, Kai; McGregor, Brett A.; Hur, Junguk

2018-01-01

The quintessential biological response to disease is inflammation. It is a driver and an important element in a wide range of pathological states. Pharmacological management of inflammation is therefore central in the clinical setting. Anti-inflammatory drugs modulate specific molecules involved in the inflammatory response; these drugs are traditionally classified as steroidal and non-steroidal drugs. However, the effects of these drugs are rarely limited to their canonical targets, affecting other molecules and altering biological functions with system-wide effects that can lead to the emergence of secondary therapeutic applications or adverse drug reactions (ADRs). In this study, relationships among anti-inflammatory drugs, functional pathways, and ADRs were explored through network models. We integrated structural drug information, experimental anti-inflammatory drug perturbation gene expression profiles obtained from the Connectivity Map and Library of Integrated Network-Based Cellular Signatures, functional pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome databases, as well as adverse reaction information from the U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). The network models comprise nodes representing anti-inflammatory drugs, functional pathways, and adverse effects. We identified structural and gene perturbation similarities linking anti-inflammatory drugs. Functional pathways were connected to drugs by implementing Gene Set Enrichment Analysis (GSEA). Drugs and adverse effects were connected based on the proportional reporting ratio (PRR) of an adverse effect in response to a given drug. Through these network models, relationships among anti-inflammatory drugs, their functional effects at the pathway level, and their adverse effects were explored. These networks comprise 70 different anti-inflammatory drugs, 462 functional pathways, and 1,175 ADRs. Network-based properties, such as degree

Exploration of the Anti-Inflammatory Drug Space Through Network Pharmacology: Applications for Drug Repurposing.

PubMed

de Anda-Jáuregui, Guillermo; Guo, Kai; McGregor, Brett A; Hur, Junguk

2018-01-01

The quintessential biological response to disease is inflammation. It is a driver and an important element in a wide range of pathological states. Pharmacological management of inflammation is therefore central in the clinical setting. Anti-inflammatory drugs modulate specific molecules involved in the inflammatory response; these drugs are traditionally classified as steroidal and non-steroidal drugs. However, the effects of these drugs are rarely limited to their canonical targets, affecting other molecules and altering biological functions with system-wide effects that can lead to the emergence of secondary therapeutic applications or adverse drug reactions (ADRs). In this study, relationships among anti-inflammatory drugs, functional pathways, and ADRs were explored through network models. We integrated structural drug information, experimental anti-inflammatory drug perturbation gene expression profiles obtained from the Connectivity Map and Library of Integrated Network-Based Cellular Signatures, functional pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome databases, as well as adverse reaction information from the U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). The network models comprise nodes representing anti-inflammatory drugs, functional pathways, and adverse effects. We identified structural and gene perturbation similarities linking anti-inflammatory drugs. Functional pathways were connected to drugs by implementing Gene Set Enrichment Analysis (GSEA). Drugs and adverse effects were connected based on the proportional reporting ratio (PRR) of an adverse effect in response to a given drug. Through these network models, relationships among anti-inflammatory drugs, their functional effects at the pathway level, and their adverse effects were explored. These networks comprise 70 different anti-inflammatory drugs, 462 functional pathways, and 1,175 ADRs. Network-based properties, such as degree

Identifying adverse drug event information in clinical notes with distributional semantic representations of context.

PubMed

Henriksson, Aron; Kvist, Maria; Dalianis, Hercules; Duneld, Martin

2015-10-01

For the purpose of post-marketing drug safety surveillance, which has traditionally relied on the voluntary reporting of individual cases of adverse drug events (ADEs), other sources of information are now being explored, including electronic health records (EHRs), which give us access to enormous amounts of longitudinal observations of the treatment of patients and their drug use. Adverse drug events, which can be encoded in EHRs with certain diagnosis codes, are, however, heavily underreported. It is therefore important to develop capabilities to process, by means of computational methods, the more unstructured EHR data in the form of clinical notes, where clinicians may describe and reason around suspected ADEs. In this study, we report on the creation of an annotated corpus of Swedish health records for the purpose of learning to identify information pertaining to ADEs present in clinical notes. To this end, three key tasks are tackled: recognizing relevant named entities (disorders, symptoms, drugs), labeling attributes of the recognized entities (negation, speculation, temporality), and relationships between them (indication, adverse drug event). For each of the three tasks, leveraging models of distributional semantics - i.e., unsupervised methods that exploit co-occurrence information to model, typically in vector space, the meaning of words - and, in particular, combinations of such models, is shown to improve the predictive performance. The ability to make use of such unsupervised methods is critical when faced with large amounts of sparse and high-dimensional data, especially in domains where annotated resources are scarce. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Introduction to fragment-based drug discovery.

PubMed

Erlanson, Daniel A

2012-01-01

Fragment-based drug discovery (FBDD) has emerged in the past decade as a powerful tool for discovering drug leads. The approach first identifies starting points: very small molecules (fragments) that are about half the size of typical drugs. These fragments are then expanded or linked together to generate drug leads. Although the origins of the technique date back some 30 years, it was only in the mid-1990s that experimental techniques became sufficiently sensitive and rapid for the concept to be become practical. Since that time, the field has exploded: FBDD has played a role in discovery of at least 18 drugs that have entered the clinic, and practitioners of FBDD can be found throughout the world in both academia and industry. Literally dozens of reviews have been published on various aspects of FBDD or on the field as a whole, as have three books (Jahnke and Erlanson, Fragment-based approaches in drug discovery, 2006; Zartler and Shapiro, Fragment-based drug discovery: a practical approach, 2008; Kuo, Fragment based drug design: tools, practical approaches, and examples, 2011). However, this chapter will assume that the reader is approaching the field with little prior knowledge. It will introduce some of the key concepts, set the stage for the chapters to follow, and demonstrate how X-ray crystallography plays a central role in fragment identification and advancement.

Global approach to reducing lead exposure and poisoning.

PubMed

Meyer, Pamela A; Brown, Mary Jean; Falk, Henry

2008-01-01

Lead poisoning is an important environmental disease that can have life-long adverse health effects. Most susceptible are children, and most commonly exposed are those who are poor and live in developing countries. Studies of children's blood-lead levels (BLLs) are showing cognitive impairment at increasingly lower BLLs. Lead is dangerous at all levels in children. The sources of lead exposure vary among and within countries depending on past and current uses. Sources of lead may be from historic contamination, recycling old lead products, or from manufacturing new products. In all countries that have banned leaded gasoline, average population BLLs have declined rapidly. In many developing countries where leaded gasoline is no longer used, many children and workers are exposed to fugitive emissions and mining wastes. Unexpected lead threats, such as improper disposal of electronics and children's toys contaminated with lead, continue to emerge. The only medical treatment available is chelation, which can save lives of persons with very high BLLs. However, chelating drugs are not always available in developing countries and have limited value in reducing the sequelae of chronic low dose lead exposure. Therefore, the best approach is to prevent exposure to lead. Because a key strategy for preventing lead poisoning is to identify and control or eliminate lead sources, this article highlights several major sources of lead poisoning worldwide. In addition, we recommend three primary prevention strategies for lead poisoning: identify sources, eliminate or control sources, and monitor environmental exposures and hazards.

Patient-derived models of acquired resistance can identify effective drug combinations for cancer.

PubMed

Crystal, Adam S; Shaw, Alice T; Sequist, Lecia V; Friboulet, Luc; Niederst, Matthew J; Lockerman, Elizabeth L; Frias, Rosa L; Gainor, Justin F; Amzallag, Arnaud; Greninger, Patricia; Lee, Dana; Kalsy, Anuj; Gomez-Caraballo, Maria; Elamine, Leila; Howe, Emily; Hur, Wooyoung; Lifshits, Eugene; Robinson, Hayley E; Katayama, Ryohei; Faber, Anthony C; Awad, Mark M; Ramaswamy, Sridhar; Mino-Kenudson, Mari; Iafrate, A John; Benes, Cyril H; Engelman, Jeffrey A

2014-12-19

Targeted cancer therapies have produced substantial clinical responses, but most tumors develop resistance to these drugs. Here, we describe a pharmacogenomic platform that facilitates rapid discovery of drug combinations that can overcome resistance. We established cell culture models derived from biopsy samples of lung cancer patients whose disease had progressed while on treatment with epidermal growth factor receptor (EGFR) or anaplastic lymphoma kinase (ALK) tyrosine kinase inhibitors and then subjected these cells to genetic analyses and a pharmacological screen. Multiple effective drug combinations were identified. For example, the combination of ALK and MAPK kinase (MEK) inhibitors was active in an ALK-positive resistant tumor that had developed a MAP2K1 activating mutation, and the combination of EGFR and fibroblast growth factor receptor (FGFR) inhibitors was active in an EGFR mutant resistant cancer with a mutation in FGFR3. Combined ALK and SRC (pp60c-src) inhibition was effective in several ALK-driven patient-derived models, a result not predicted by genetic analysis alone. With further refinements, this strategy could help direct therapeutic choices for individual patients. Copyright © 2014, American Association for the Advancement of Science.

Identifying the translational gap in the evaluation of drug-induced QTc interval prolongation

PubMed Central

Chain, Anne SY; Dubois, Vincent FS; Danhof, Meindert; Sturkenboom, Miriam CJM; Della Pasqua, Oscar

2013-01-01

Aims Given the similarities in QTc response between dogs and humans, dogs are used in pre-clinical cardiovascular safety studies. The objective of our investigation was to characterize the PKPD relationships and identify translational gaps across species following the administration of three compounds known to cause QTc interval prolongation, namely cisapride, d, l-sotalol and moxifloxacin. Methods Pharmacokinetic and pharmacodynamic data from experiments in conscious dogs and clinical trials were included in this analysis. First, pharmacokinetic modelling and deconvolution methods were applied to derive drug concentrations at the time of each QT measurement. A Bayesian PKPD model was then used to describe QT prolongation, allowing discrimination of drug-specific effects from other physiological factors known to alter QT interval duration. A threshold of ≥10 ms was used to explore the probability of prolongation after drug administration. Results A linear relationship was found to best describe the pro-arrhythmic effects of cisapride, d,l-sotalol and moxifloxacin both in dogs and in humans. The drug-specific parameter (slope) in dogs was statistically significantly different from humans. Despite such differences, our results show that the probability of QTc prolongation ≥10 ms in dogs nears 100% for all three compounds at the therapeutic exposure range in humans. Conclusions Our findings indicate that the slope of PKPD relationship in conscious dogs may be used as the basis for the prediction of drug-induced QTc prolongation in humans. Furthermore, the risk of QTc prolongation can be expressed in terms of the probability associated with an increase ≥10 ms, allowing direct inferences about the clinical relevance of the pro-arrhythmic potential of a molecule. PMID:23351036

Quantifying the Evolutionary Conservation of Genes Encoding Multidrug Efflux Pumps in the ESKAPE Pathogens To Identify Antimicrobial Drug Targets.

PubMed

Brooks, Lauren E; Ul-Hasan, Sabah; Chan, Benjamin K; Sistrom, Mark J

2018-01-01

Increasing rates of antibiotic-resistant bacterial infection are one of the most pressing contemporary global health concerns. The ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) have been identified as the leading global cause of multidrug-resistant bacterial infections, and overexpression of multidrug efflux (MEX) transport systems has been identified as one of the most critical mechanisms facilitating the evolution of multidrug resistance in ESKAPE pathogens. Despite efforts to develop efflux pump inhibitors to combat antibiotic resistance, the need persists to identify additional targets for future investigations. We evaluated evolutionary pressures on 110 MEX-encoding genes from all annotated ESKAPE organism genomes. We identify several MEX genes under stabilizing selection-representing targets which can facilitate broad-spectrum treatments with evolutionary constraints limiting the potential emergence of escape mutants. We also examine MEX systems being evaluated as drug targets, demonstrating that divergent selection may underlie some of the problems encountered in the development of effective treatments-specifically in relation to the NorA system in S. aureus. This study provides a comprehensive evolutionary context to efflux in the ESKAPE pathogens, which will provide critical context to the evaluation of efflux systems as antibiotic targets. IMPORTANCE Increasing rates of antibiotic-resistant bacterial infection are one of the most pressing contemporary global health concerns. The ESKAPE pathogen group represents the leading cause of these infections, and upregulation of efflux pump expression is a significant mechanism of resistance in these pathogens. This has resulted in substantial interest in the development of efflux pump inhibitors to combat antibiotic-resistant infections; however, no widespread treatments have been developed to date

Quantifying the Evolutionary Conservation of Genes Encoding Multidrug Efflux Pumps in the ESKAPE Pathogens To Identify Antimicrobial Drug Targets

PubMed Central

Ul-Hasan, Sabah; Chan, Benjamin K.; Sistrom, Mark J.

2018-01-01

ABSTRACT Increasing rates of antibiotic-resistant bacterial infection are one of the most pressing contemporary global health concerns. The ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) have been identified as the leading global cause of multidrug-resistant bacterial infections, and overexpression of multidrug efflux (MEX) transport systems has been identified as one of the most critical mechanisms facilitating the evolution of multidrug resistance in ESKAPE pathogens. Despite efforts to develop efflux pump inhibitors to combat antibiotic resistance, the need persists to identify additional targets for future investigations. We evaluated evolutionary pressures on 110 MEX-encoding genes from all annotated ESKAPE organism genomes. We identify several MEX genes under stabilizing selection—representing targets which can facilitate broad-spectrum treatments with evolutionary constraints limiting the potential emergence of escape mutants. We also examine MEX systems being evaluated as drug targets, demonstrating that divergent selection may underlie some of the problems encountered in the development of effective treatments—specifically in relation to the NorA system in S. aureus. This study provides a comprehensive evolutionary context to efflux in the ESKAPE pathogens, which will provide critical context to the evaluation of efflux systems as antibiotic targets. IMPORTANCE Increasing rates of antibiotic-resistant bacterial infection are one of the most pressing contemporary global health concerns. The ESKAPE pathogen group represents the leading cause of these infections, and upregulation of efflux pump expression is a significant mechanism of resistance in these pathogens. This has resulted in substantial interest in the development of efflux pump inhibitors to combat antibiotic-resistant infections; however, no widespread treatments have been

76 FR 44593 - Identifying the Center for Drug Evaluation and Research's Science and Research Needs...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-07-26

... . Submit written comments to the Division of Dockets Management (HFA-305), Food and Drug Administration... from CDER's offices were asked to identify: (1) Scientific challenges currently addressed on a case-by-case basis that might benefit from the development of a systematized approach; (2) recurrent science...

Can surveillance systems identify and avert adverse drug events? A prospective evaluation of a commercial application.

PubMed

Jha, Ashish K; Laguette, Julia; Seger, Andrew; Bates, David W

2008-01-01

Computerized monitors can effectively detect and potentially prevent adverse drug events (ADEs). Most monitors have been developed in large academic hospitals and are not readily usable in other settings. We assessed the ability of a commercial program to identify and prevent ADEs in a community hospital. and Measurement We prospectively evaluated the commercial application in a community-based hospital. We examined the frequency and types of alerts produced, how often they were associated with ADEs and potential ADEs, and the potential financial impact of monitoring for ADEs. Among 2,407 patients screened, the application generated 516 high priority alerts. We were able to review 266 alerts at the time they were generated and among these, 30 (11.3%) were considered substantially important to warrant contacting the physician caring for the patient. These 30 alerts were associated with 4 ADEs and 11 potential ADEs. In all 15 cases, the responsible physician was unaware of the event, leading to a change in clinical care in 14 cases. Overall, 23% of high priority alerts were associated with an ADE (95% confidence interval [CI] 12% to 34%) and another 15% were associated with a potential ADE (95% CI 6% to 24%). Active surveillance used approximately 1.5 hours of pharmacist time daily. A commercially available, computer-based ADE detection tool was effective at identifying ADEs. When used as part of an active surveillance program, it can have an impact on preventing or ameliorating ADEs.

QSAR Modeling and Prediction of Drug-Drug Interactions.

PubMed

Zakharov, Alexey V; Varlamova, Ekaterina V; Lagunin, Alexey A; Dmitriev, Alexander V; Muratov, Eugene N; Fourches, Denis; Kuz'min, Victor E; Poroikov, Vladimir V; Tropsha, Alexander; Nicklaus, Marc C

2016-02-01

Severe adverse drug reactions (ADRs) are the fourth leading cause of fatality in the U.S. with more than 100,000 deaths per year. As up to 30% of all ADRs are believed to be caused by drug-drug interactions (DDIs), typically mediated by cytochrome P450s, possibilities to predict DDIs from existing knowledge are important. We collected data from public sources on 1485, 2628, 4371, and 27,966 possible DDIs mediated by four cytochrome P450 isoforms 1A2, 2C9, 2D6, and 3A4 for 55, 73, 94, and 237 drugs, respectively. For each of these data sets, we developed and validated QSAR models for the prediction of DDIs. As a unique feature of our approach, the interacting drug pairs were represented as binary chemical mixtures in a 1:1 ratio. We used two types of chemical descriptors: quantitative neighborhoods of atoms (QNA) and simplex descriptors. Radial basis functions with self-consistent regression (RBF-SCR) and random forest (RF) were utilized to build QSAR models predicting the likelihood of DDIs for any pair of drug molecules. Our models showed balanced accuracy of 72-79% for the external test sets with a coverage of 81.36-100% when a conservative threshold for the model's applicability domain was applied. We generated virtually all possible binary combinations of marketed drugs and employed our models to identify drug pairs predicted to be instances of DDI. More than 4500 of these predicted DDIs that were not found in our training sets were confirmed by data from the DrugBank database.

Potential drug-drug interactions between anti-cancer agents and community pharmacy dispensed drugs.

PubMed

Voll, Marsha L; Yap, Kim D; Terpstra, Wim E; Crul, Mirjam

2010-10-01

To identify the prevalence of potential drug-drug interactions between hospital pharmacy dispensed anti-cancer agents and community pharmacy dispensed drugs. A retrospective cohort study was conducted on the haematology/oncology department of the internal medicine ward in a large teaching hospital in Amsterdam, the Netherlands. Prescription data from the last 100 patients treated with anti-cancer agents were obtained from Paracelsus, the chemotherapy prescribing system in the hospital. The community pharmacy dispensed drugs of these patients were obtained by using OZIS, a system that allows regionally linked pharmacies to call up active medication on any patient. Both medication lists were manually screened for potential drug-drug interactions by using several information sources on interactions, e.g. Pubmed, the Flockhart P450 table, Micromedex and Dutch reference books. Prevalence of potential drug-drug interactions between anti-cancer agents provided by the hospital pharmacy and drugs dispensed by the community pharmacy. Ninety-one patients were included in the study. A total of 31 potential drug-drug interactions were found in 16 patients, of which 15 interactions were clinically relevant and would have required an intervention. Of these interactions 1 had a level of severity ≥ D, meaning the potential drug-drug interaction could lead to long lasting or permanent damage, or even death. The majority of the interactions requiring an intervention (67%) had a considerable level of evidence (≥ 2) and were based on well-documented case reports or controlled interaction studies. Most of the potential drug-drug interactions involved the antiretroviral drugs (40%), proton pump inhibitors (20%) and antibiotics (20%). The anti-cancer drug most involved in the drug-drug interactions is methotrexate (33%). This study reveals a high prevalence of potential drug-drug interactions between anti-cancer agents provided by the hospital pharmacy and drugs dispensed by the

21 CFR 870.3620 - Pacemaker lead adaptor.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Pacemaker lead adaptor. 870.3620 Section 870.3620 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES CARDIOVASCULAR DEVICES Cardiovascular Prosthetic Devices § 870.3620 Pacemaker lead adaptor...

Rational drug design paradigms: the odyssey for designing better drugs.

PubMed

Kellici, Tahsin; Ntountaniotis, Dimitrios; Vrontaki, Eleni; Liapakis, George; Moutevelis-Minakakis, Panagiota; Kokotos, George; Hadjikakou, Sotiris; Tzakos, Andreas G; Afantitis, Antreas; Melagraki, Georgia; Bryant, Sharon; Langer, Thierry; Di Marzo, Vincenzo; Mavromoustakos, Thomas

2015-01-01

Due to the time and effort requirements for the development of a new drug, and the high attrition rates associated with this developmental process, there is an intense effort by academic and industrial researchers to find novel ways for more effective drug development schemes. The first step in the discovery process of a new drug is the identification of the lead compound. The modern research tendency is to avoid the synthesis of new molecules based on chemical intuition, which is time and cost consuming, and instead to apply in silico rational drug design. This approach reduces the consumables and human personnel involved in the initial steps of the drug design. In this review real examples from our research activity aiming to discover new leads will be given for various dire warnings diseases. There is no recipe to follow for discovering new leads. The strategy to be followed depends on the knowledge of the studied system and the experience of the researchers. The described examples constitute successful and unsuccessful efforts and reflect the reality which medicinal chemists have to face in drug design and development. The drug stability is also discussed in both organic molecules and metallotherapeutics. This is an important issue in drug discovery as drug metabolism in the body can lead to various toxic and undesired molecules.

Predicting essential genes for identifying potential drug targets in Aspergillus fumigatus.

PubMed

Lu, Yao; Deng, Jingyuan; Rhodes, Judith C; Lu, Hui; Lu, Long Jason

2014-06-01

Aspergillus fumigatus (Af) is a ubiquitous and opportunistic pathogen capable of causing acute, invasive pulmonary disease in susceptible hosts. Despite current therapeutic options, mortality associated with invasive Af infections remains unacceptably high, increasing 357% since 1980. Therefore, there is an urgent need for the development of novel therapeutic strategies, including more efficacious drugs acting on new targets. Thus, as noted in a recent review, "the identification of essential genes in fungi represents a crucial step in the development of new antifungal drugs". Expanding the target space by rapidly identifying new essential genes has thus been described as "the most important task of genomics-based target validation". In previous research, we were the first to show that essential gene annotation can be reliably transferred between distantly related four Prokaryotic species. In this study, we extend our machine learning approach to the much more complex Eukaryotic fungal species. A compendium of essential genes is predicted in Af by transferring known essential gene annotations from another filamentous fungus Neurospora crassa. This approach predicts essential genes by integrating diverse types of intrinsic and context-dependent genomic features encoded in microbial genomes. The predicted essential datasets contained 1674 genes. We validated our results by comparing our predictions with known essential genes in Af, comparing our predictions with those predicted by homology mapping, and conducting conditional expressed alleles. We applied several layers of filters and selected a set of potential drug targets from the predicted essential genes. Finally, we have conducted wet lab knockout experiments to verify our predictions, which further validates the accuracy and wide applicability of the machine learning approach. The approach presented here significantly extended our ability to predict essential genes beyond orthologs and made it possible to

Short communication: cheminformatics analysis to identify predictors of antiviral drug penetration into the female genital tract.

PubMed

Thompson, Corbin G; Sedykh, Alexander; Nicol, Melanie R; Muratov, Eugene; Fourches, Denis; Tropsha, Alexander; Kashuba, Angela D M

2014-11-01

The exposure of oral antiretroviral (ARV) drugs in the female genital tract (FGT) is variable and almost unpredictable. Identifying an efficient method to find compounds with high tissue penetration would streamline the development of regimens for both HIV preexposure prophylaxis and viral reservoir targeting. Here we describe the cheminformatics investigation of diverse drugs with known FGT penetration using cluster analysis and quantitative structure-activity relationships (QSAR) modeling. A literature search over the 1950-2012 period identified 58 compounds (including 21 ARVs and representing 13 drug classes) associated with their actual concentration data for cervical or vaginal tissue, or cervicovaginal fluid. Cluster analysis revealed significant trends in the penetrative ability for certain chemotypes. QSAR models to predict genital tract concentrations normalized to blood plasma concentrations were developed with two machine learning techniques utilizing drugs' molecular descriptors and pharmacokinetic parameters as inputs. The QSAR model with the highest predictive accuracy had R(2)test=0.47. High volume of distribution, high MRP1 substrate probability, and low MRP4 substrate probability were associated with FGT concentrations ≥1.5-fold plasma concentrations. However, due to the limited FGT data available, prediction performances of all models were low. Despite this limitation, we were able to support our findings by correctly predicting the penetration class of rilpivirine and dolutegravir. With more data to enrich the models, we believe these methods could potentially enhance the current approach of clinical testing.

Drug-Associated Acute Kidney Injury Identified in the United States Food and Drug Administration Adverse Event Reporting System Database.

PubMed

Welch, Hanna K; Kellum, John A; Kane-Gill, Sandra L

2018-06-08

Acute kidney injury (AKI) is a common condition associated with both short-term and long-term consequences including dialysis, chronic kidney disease, and mortality. Although the United States Food and Drug Administration Adverse Event Reporting System (FAERS) database is a powerful tool to examine drug-associated events, to our knowledge, no study has analyzed this database to identify the most common drugs reported with AKI. The objective of this study was to analyze AKI reports and associated medications in the FAERS database. Retrospective pharmacovigilance disproportionality analysis. FAERS database. We queried the FAERS database for reports of AKI from 2004 quarter 1 through 2015 quarter 3. Extracted drugs were assessed using published references and categorized as known, possible, or new potential nephrotoxins. The reporting odds ratio (ROR), a measure of reporting disproportionality, was calculated for the 20 most frequently reported drugs in each category. We retrieved 7,241,385 adverse event reports, of which 193,996 (2.7%) included a report of AKI. Of the AKI reports, 16.5% were known nephrotoxins, 18.6% were possible nephrotoxins, and 64.8% were new potential nephrotoxins. Among the most commonly reported drugs, those with the highest AKI ROR were aprotinin (7,614 reports; ROR 115.70, 95% confidence interval [CI] 110.63-121.01), sodium phosphate (1,687 reports; ROR 55.81, 95% CI 51.78-60.17), furosemide (1,743 reports; ROR 12.61, 95% CI 11.94-13.32), vancomycin (1,270 reports, ROR 12.19, 95% CI 11.45-12.99), and metformin (4,701 reports; ROR 10.65, 95% CI 10.31-11.00). The combined RORs for the 20 most frequently reported drugs with each nephrotoxin classification were 3.71 (95% CI 3.66-3.76) for known nephrotoxins, 2.09 (95% CI 2.06-2.12) for possible nephrotoxins, and 1.55 (95% CI 1.53-1.57) for new potential nephrotoxins. AKI was a common reason for adverse event reporting in the FAERS. Most AKI reports were generated for medications not recognized

The Tuberculosis Drug Discovery and Development Pipeline and Emerging Drug Targets

PubMed Central

Mdluli, Khisimuzi; Kaneko, Takushi; Upton, Anna

2015-01-01

The recent accelerated approval for use in extensively drug-resistant and multidrug-resistant-tuberculosis (MDR-TB) of two first-in-class TB drugs, bedaquiline and delamanid, has reinvigorated the TB drug discovery and development field. However, although several promising clinical development programs are ongoing to evaluate new TB drugs and regimens, the number of novel series represented is few. The global early-development pipeline is also woefully thin. To have a chance of achieving the goal of better, shorter, safer TB drug regimens with utility against drug-sensitive and drug-resistant disease, a robust and diverse global TB drug discovery pipeline is key, including innovative approaches that make use of recently acquired knowledge on the biology of TB. Fortunately, drug discovery for TB has resurged in recent years, generating compounds with varying potential for progression into developable leads. In parallel, advances have been made in understanding TB pathogenesis. It is now possible to apply the lessons learned from recent TB hit generation efforts and newly validated TB drug targets to generate the next wave of TB drug leads. Use of currently underexploited sources of chemical matter and lead-optimization strategies may also improve the efficiency of future TB drug discovery. Novel TB drug regimens with shorter treatment durations must target all subpopulations of Mycobacterium tuberculosis existing in an infection, including those responsible for the protracted TB treatment duration. This review summarizes the current TB drug development pipeline and proposes strategies for generating improved hits and leads in the discovery phase that could help achieve this goal. PMID:25635061

Clustering drug-drug interaction networks with energy model layouts: community analysis and drug repurposing.

PubMed

Udrescu, Lucreţia; Sbârcea, Laura; Topîrceanu, Alexandru; Iovanovici, Alexandru; Kurunczi, Ludovic; Bogdan, Paul; Udrescu, Mihai

2016-09-07

Analyzing drug-drug interactions may unravel previously unknown drug action patterns, leading to the development of new drug discovery tools. We present a new approach to analyzing drug-drug interaction networks, based on clustering and topological community detection techniques that are specific to complex network science. Our methodology uncovers functional drug categories along with the intricate relationships between them. Using modularity-based and energy-model layout community detection algorithms, we link the network clusters to 9 relevant pharmacological properties. Out of the 1141 drugs from the DrugBank 4.1 database, our extensive literature survey and cross-checking with other databases such as Drugs.com, RxList, and DrugBank 4.3 confirm the predicted properties for 85% of the drugs. As such, we argue that network analysis offers a high-level grasp on a wide area of pharmacological aspects, indicating possible unaccounted interactions and missing pharmacological properties that can lead to drug repositioning for the 15% drugs which seem to be inconsistent with the predicted property. Also, by using network centralities, we can rank drugs according to their interaction potential for both simple and complex multi-pathology therapies. Moreover, our clustering approach can be extended for applications such as analyzing drug-target interactions or phenotyping patients in personalized medicine applications.

Clustering drug-drug interaction networks with energy model layouts: community analysis and drug repurposing

PubMed Central

Udrescu, Lucreţia; Sbârcea, Laura; Topîrceanu, Alexandru; Iovanovici, Alexandru; Kurunczi, Ludovic; Bogdan, Paul; Udrescu, Mihai

2016-01-01

Analyzing drug-drug interactions may unravel previously unknown drug action patterns, leading to the development of new drug discovery tools. We present a new approach to analyzing drug-drug interaction networks, based on clustering and topological community detection techniques that are specific to complex network science. Our methodology uncovers functional drug categories along with the intricate relationships between them. Using modularity-based and energy-model layout community detection algorithms, we link the network clusters to 9 relevant pharmacological properties. Out of the 1141 drugs from the DrugBank 4.1 database, our extensive literature survey and cross-checking with other databases such as Drugs.com, RxList, and DrugBank 4.3 confirm the predicted properties for 85% of the drugs. As such, we argue that network analysis offers a high-level grasp on a wide area of pharmacological aspects, indicating possible unaccounted interactions and missing pharmacological properties that can lead to drug repositioning for the 15% drugs which seem to be inconsistent with the predicted property. Also, by using network centralities, we can rank drugs according to their interaction potential for both simple and complex multi-pathology therapies. Moreover, our clustering approach can be extended for applications such as analyzing drug-target interactions or phenotyping patients in personalized medicine applications. PMID:27599720

Translational research in brain metastasis is identifying molecular pathways that may lead to the development of new therapeutic strategies

PubMed Central

Gril, Brunilde; Evans, Lynda; Palmieri, Diane; Steeg, Patricia S.

2010-01-01

Central nervous system (CNS) or brain metastasis is an emerging area of interest in organ-specific metastasis research. Lung and breast cancers are the most common types of primary tumors to develop brain metastases. This disease complication contributes significantly to the morbidity and mortality of both of these common cancers; as such, brain metastasis is designated an unmet medical need by the US Food and Drug Administration. Recently, an increase in incidence of CNS disease has been noted in the literature for breast cancer, while it has been an ongoing major complication from lung cancer. Progress in treating brain metastases has been hampered by a lack of model systems, a lack of human tissue samples, and the exclusion of brain metastatic patients from many clinical trials. While each of those is significant, the major impediment to effectively treating brain metastatic disease is the blood–brain barrier (BBB). This barrier excludes most chemotherapeutics from the brain and creates a sanctuary site for metastatic tumors. Recent findings on the biology of this disease and translational leads identified by molecular studies are discussed in this article. PMID:20303257

Translational research in brain metastasis is identifying molecular pathways that may lead to the development of new therapeutic strategies.

PubMed

Gril, Brunilde; Evans, Lynda; Palmieri, Diane; Steeg, Patricia S

2010-05-01

Central nervous system (CNS) or brain metastasis is an emerging area of interest in organ-specific metastasis research. Lung and breast cancers are the most common types of primary tumors to develop brain metastases. This disease complication contributes significantly to the morbidity and mortality of both of these common cancers; as such, brain metastasis is designated an unmet medical need by the US Food and Drug Administration (FDA). Recently, an increase in incidence of CNS disease has been noted in the literature for breast cancer, while it has been an ongoing major complication from lung cancer. Progress in treating brain metastases has been hampered by a lack of model systems, a lack of human tissue samples, and the exclusion of brain metastatic patients from many clinical trials. While each of those is significant, the major impediment to effectively treating brain metastatic disease is the blood-brain barrier (BBB). This barrier excludes most chemotherapeutics from the brain and creates a sanctuary site for metastatic tumors. Recent findings on the biology of this disease and translational leads identified by molecular studies are discussed in this article. Published by Elsevier Ltd.

Identification of cysteine protease inhibitors as new drug leads against Naegleria fowleri.

PubMed

Zyserman, Ingrid; Mondal, Deboprosad; Sarabia, Francisco; McKerrow, James H; Roush, William R; Debnath, Anjan

2018-05-01

Primary amebic meningoencephalitis (PAM) is a rapidly fatal infection caused by the free-living ameba Naegleria fowleri. PAM occurs principally in healthy children of less than 13 years old with a history of recent exposure to warm fresh water. While as yet not a reportable disease, the Centers for Disease Control and Prevention (CDC) documents a total of 143 cases in the United States. Only four patients have survived. Infection results from water containing N. fowleri entering the nose, followed by migration of the amebae to the brain. Within the brain, N. fowleri infection results in extensive necrosis, leading to death in 3-7 days. Mortality among patients with PAM is greater than 95%. The drugs of choice in treating PAM are the antifungal amphotericin B, and the antileishmanial, miltefosine. However neither drug is FDA-approved for this indication and the use of amphotericin B is associated with severe adverse effects. Moreover, very few patients treated with amphotericin B have survived PAM. Therefore, development of new, safe and effective drugs is a critical unmet need to avert future deaths of children. The molecular mechanisms underlying the pathogenesis of PAM are poorly understood but it is known that cysteine proteases of N. fowleri play a role in the progression of PAM. We therefore assessed the in vitro activity of the synthetic vinyl sulfone cysteine protease inhibitor, K11777, and 33 analogs with valine, phenylalanine or pyridylalanine at P2 position, against cysteine protease activity in the lysate of N. fowleri. Inhibitors with phenylalanine or pyridylalanine at P2 position were particularly effective in inhibiting the cysteine protease activity of N. fowleri cell lysate with IC 50 ranging between 3 nM and 6.6 μM. Three of the 34 inhibitors also showed inhibitory activity against N. fowleri in a cell viability assay and were 1.6- to 2.5-fold more potent than the standard of care drug miltefosine. Our study provides the first evidence

Drug Abuse

MedlinePlus

... drugs, including opioids Drug abuse also plays a role in many major social problems, such as drugged driving, violence, stress, and child abuse. Drug abuse can lead to homelessness, crime, and missed work or problems with keeping a job. It harms ...

Evaluation of commercial multi-drug oral fluid devices to identify 39 new amphetamine-designer drugs.

PubMed

Nieddu, Maria; Burrai, Lucia; Trignano, Claudia; Boatto, Gianpiero

2014-03-01

Recently, the diffusion on the black market of new psychoactive substances not controlled and often sold as 'legal highs', is exponentially increasing in Europe. Generally, the first analysis for these drugs involves an immunoassay screening in urine or plasma. Actually, there is growing interest in the use of oral fluid (OF) as alternative specimen over conventional biological fluids for drug testing, because of the significant advantages, as a non-invasive collection under direct observation without undue embarrassment or invasion of privacy, and a good correlation with plasma analytical data. Few assays have been developed for detection of new psychoactive compounds in biological samples, so it is important to investigate how they may or may not react in pre-existing commercial immunoassays. In this paper, two different multi-drugs oral fluid screen devices (OFDs) (Screen® Multi-Drug OFD and GIMA One Step Multi-Line Screen Test OFD) were evaluated to determine the cross-reactivity of thirty-nine new amphetamine designer drugs, including twelve substances officially recognized as illicit by italian legislation. Cross-reactivity towards most drugs analyzed was <1 in assays targeting amphetamine (AMP) or methamphetamine (MET). Only two (p-methoxyamphetamine and p-methoxymethamphetamine) of all tested amphetamines gave a positive result. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

QTL Mapping and CRISPR/Cas9 Editing to Identify a Drug Resistance Gene in Toxoplasma gondii.

PubMed

Shen, Bang; Powell, Robin H; Behnke, Michael S

2017-06-22

Scientific knowledge is intrinsically linked to available technologies and methods. This article will present two methods that allowed for the identification and verification of a drug resistance gene in the Apicomplexan parasite Toxoplasma gondii, the method of Quantitative Trait Locus (QTL) mapping using a Whole Genome Sequence (WGS) -based genetic map and the method of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 -based gene editing. The approach of QTL mapping allows one to test if there is a correlation between a genomic region(s) and a phenotype. Two datasets are required to run a QTL scan, a genetic map based on the progeny of a recombinant cross and a quantifiable phenotype assessed in each of the progeny of that cross. These datasets are then formatted to be compatible with R/qtl software that generates a QTL scan to identify significant loci correlated with the phenotype. Although this can greatly narrow the search window of possible candidates, QTLs span regions containing a number of genes from which the causal gene needs to be identified. Having WGS of the progeny was critical to identify the causal drug resistance mutation at the gene level. Once identified, the candidate mutation can be verified by genetic manipulation of drug sensitive parasites. The most facile and efficient method to genetically modify T. gondii is the CRISPR/Cas9 system. This system comprised of just 2 components both encoded on a single plasmid, a single guide RNA (gRNA) containing a 20 bp sequence complementary to the genomic target and the Cas9 endonuclease that generates a double-strand DNA break (DSB) at the target, repair of which allows for insertion or deletion of sequences around the break site. This article provides detailed protocols to use CRISPR/Cas9 based genome editing tools to verify the gene responsible for sinefungin resistance and to construct transgenic parasites.

Comprehensive Genomic Profiling Identifies Frequent Drug-Sensitive EGFR Exon 19 Deletions in NSCLC not Identified by Prior Molecular Testing.

PubMed

Schrock, Alexa B; Frampton, Garrett M; Herndon, Dana; Greenbowe, Joel R; Wang, Kai; Lipson, Doron; Yelensky, Roman; Chalmers, Zachary R; Chmielecki, Juliann; Elvin, Julia A; Wollner, Mira; Dvir, Addie; -Gutman, Lior Soussan; Bordoni, Rodolfo; Peled, Nir; Braiteh, Fadi; Raez, Luis; Erlich, Rachel; Ou, Sai-Hong Ignatius; Mohamed, Mohamed; Ross, Jeffrey S; Stephens, Philip J; Ali, Siraj M; Miller, Vincent A

2016-07-01

Reliable detection of drug-sensitive activating EGFR mutations is critical in the care of advanced non-small cell lung cancer (NSCLC), but such testing is commonly performed using a wide variety of platforms, many of which lack rigorous analytic validation. A large pool of NSCLC cases was assayed with well-validated, hybrid capture-based comprehensive genomic profiling (CGP) at the request of the individual treating physicians in the course of clinical care for the purpose of making therapy decisions. From these, 400 cases harboring EGFR exon 19 deletions (Δex19) were identified, and available clinical history was reviewed. Pathology reports were available for 250 consecutive cases with classical EGFR Δex19 (amino acids 743-754) and were reviewed to assess previous non-hybrid capture-based EGFR testing. Twelve of 71 (17%) cases with EGFR testing results available were negative by previous testing, including 8 of 46 (17%) cases for which the same biopsy was analyzed. Independently, five of six (83%) cases harboring C-helical EGFR Δex19 were previously negative. In a subset of these patients with available clinical outcome information, robust benefit from treatment with EGFR inhibitors was observed. CGP identifies drug-sensitive EGFR Δex19 in NSCLC cases that have undergone prior EGFR testing and returned negative results. Given the proven benefit in progression-free survival conferred by EGFR tyrosine kinase inhibitors in patients with these alterations, CGP should be considered in the initial presentation of advanced NSCLC and when previous testing for EGFR mutations or other driver alterations is negative. Clin Cancer Res; 22(13); 3281-5. ©2016 AACR. ©2016 American Association for Cancer Research.

Validating the Modified Drug Adherence Work-Up (M-DRAW) Tool to Identify and Address Barriers to Medication Adherence.

PubMed

Lee, Sun; Bae, Yuna H; Worley, Marcia; Law, Anandi

2017-09-08

Barriers to medication adherence stem from multiple factors. An effective and convenient tool is needed to identify these barriers so that clinicians can provide a tailored, patient-centered consultation with patients. The Modified Drug Adherence Work-up Tool (M-DRAW) was developed as a 13-item checklist questionnaire to identify barriers to medication adherence. The response scale was a 4-point Likert scale of frequency of occurrence (1 = never to 4 = often). The checklist was accompanied by a GUIDE that provided corresponding motivational interview-based intervention strategies for each identified barrier. The current pilot study examined the psychometric properties of the M-DRAW checklist (reliability, responsiveness and discriminant validity) in patients taking one or more prescription medication(s) for chronic conditions. A cross-sectional sample of 26 patients was recruited between December 2015 and March 2016 at an academic medical center pharmacy in Southern California. A priming question that assessed self-reported adherence was used to separate participants into the control group of 17 "adherers" (65.4%), and into the intervention group of nine "unintentional and intentional non-adherers" (34.6%). Comparable baseline characteristics were observed between the two groups. The M-DRAW checklist showed acceptable reliability (13 item; alpha = 0.74) for identifying factors and barriers leading to medication non-adherence. Discriminant validity of the tool and the priming question was established by the four-fold number of barriers to adherence identified within the self-selected intervention group compared to the control group (4.4 versus 1.2 barriers, p < 0.05). The current study did not investigate construct validity due to small sample size and challenges on follow-up with patients. Future testing of the tool will include construct validation.

A staged screening of registered drugs highlights remyelinating drug candidates for clinical trials

NASA Astrophysics Data System (ADS)

Eleuteri, C.; Olla, S.; Veroni, C.; Umeton, R.; Mechelli, R.; Romano, S.; Buscarinu, Mc.; Ferrari, F.; Calò, G.; Ristori, G.; Salvetti, M.; Agresti, C.

2017-04-01

There is no treatment for the myelin loss in multiple sclerosis, ultimately resulting in the axonal degeneration that leads to the progressive phase of the disease. We established a multi-tiered platform for the sequential screening of drugs that could be repurposed as remyelinating agents. We screened a library of 2,000 compounds (mainly Food and Drug Administration (FDA)-approved compounds and natural products) for cellular metabolic activity on mouse oligodendrocyte precursors (OPC), identifying 42 molecules with significant stimulating effects. We then characterized the effects of these compounds on OPC proliferation and differentiation in mouse glial cultures, and on myelination and remyelination in organotypic cultures. Three molecules, edaravone, 5-methyl-7-methoxyisoflavone and lovastatin, gave positive results in all screening tiers. We validated the results by retesting independent stocks of the compounds, analyzing their purity, and performing dose-response curves. To identify the chemical features that may be modified to enhance the compounds’ activity, we tested chemical analogs and identified, for edaravone, the functional groups that may be essential for its activity. Among the selected remyelinating candidates, edaravone appears to be of strong interest, also considering that this drug has been approved as a neuroprotective agent for acute ischemic stroke and amyotrophic lateral sclerosis in Japan.

A staged screening of registered drugs highlights remyelinating drug candidates for clinical trials

PubMed Central

Eleuteri, C.; Olla, S.; Veroni, C.; Umeton, R.; Mechelli, R.; Romano, S.; Buscarinu, MC.; Ferrari, F.; Calò, G.; Ristori, G.; Salvetti, M.; Agresti, C.

2017-01-01

There is no treatment for the myelin loss in multiple sclerosis, ultimately resulting in the axonal degeneration that leads to the progressive phase of the disease. We established a multi-tiered platform for the sequential screening of drugs that could be repurposed as remyelinating agents. We screened a library of 2,000 compounds (mainly Food and Drug Administration (FDA)-approved compounds and natural products) for cellular metabolic activity on mouse oligodendrocyte precursors (OPC), identifying 42 molecules with significant stimulating effects. We then characterized the effects of these compounds on OPC proliferation and differentiation in mouse glial cultures, and on myelination and remyelination in organotypic cultures. Three molecules, edaravone, 5-methyl-7-methoxyisoflavone and lovastatin, gave positive results in all screening tiers. We validated the results by retesting independent stocks of the compounds, analyzing their purity, and performing dose-response curves. To identify the chemical features that may be modified to enhance the compounds’ activity, we tested chemical analogs and identified, for edaravone, the functional groups that may be essential for its activity. Among the selected remyelinating candidates, edaravone appears to be of strong interest, also considering that this drug has been approved as a neuroprotective agent for acute ischemic stroke and amyotrophic lateral sclerosis in Japan. PMID:28387380

Novel Phenotypic Outcomes Identified for a Public Collection of Approved Drugs from a Publicly Accessible Panel of Assays

PubMed Central

Oliver, Sarah; Willard, Francis S.; Heidler, Steven; Peery, Robert B.; Oler, Jennifer; Chu, Shaoyou; Southall, Noel; Dexheimer, Thomas S.; Smallwood, Jeffrey; Huang, Ruili; Guha, Rajarshi; Jadhav, Ajit; Cox, Karen; Austin, Christopher P.; Simeonov, Anton; Sittampalam, G. Sitta; Husain, Saba; Franklin, Natalie; Wild, David J.; Yang, Jeremy J.; Sutherland, Jeffrey J.; Thomas, Craig J.

2015-01-01

Phenotypic assays have a proven track record for generating leads that become first-in-class therapies. Whole cell assays that inform on a phenotype or mechanism also possess great potential in drug repositioning studies by illuminating new activities for the existing pharmacopeia. The National Center for Advancing Translational Sciences (NCATS) pharmaceutical collection (NPC) is the largest reported collection of approved small molecule therapeutics that is available for screening in a high-throughput setting. Via a wide-ranging collaborative effort, this library was analyzed in the Open Innovation Drug Discovery (OIDD) phenotypic assay modules publicly offered by Lilly. The results of these tests are publically available online at www.ncats.nih.gov/expertise/preclinical/pd2 and via the PubChem Database (https://pubchem.ncbi.nlm.nih.gov/) (AID 1117321). Phenotypic outcomes for numerous drugs were confirmed, including sulfonylureas as insulin secretagogues and the anti-angiogenesis actions of multikinase inhibitors sorafenib, axitinib and pazopanib. Several novel outcomes were also noted including the Wnt potentiating activities of rotenone and the antifolate class of drugs, and the anti-angiogenic activity of cetaben. PMID:26177200

Novel Phenotypic Outcomes Identified for a Public Collection of Approved Drugs from a Publicly Accessible Panel of Assays.

PubMed

Lee, Jonathan A; Shinn, Paul; Jaken, Susan; Oliver, Sarah; Willard, Francis S; Heidler, Steven; Peery, Robert B; Oler, Jennifer; Chu, Shaoyou; Southall, Noel; Dexheimer, Thomas S; Smallwood, Jeffrey; Huang, Ruili; Guha, Rajarshi; Jadhav, Ajit; Cox, Karen; Austin, Christopher P; Simeonov, Anton; Sittampalam, G Sitta; Husain, Saba; Franklin, Natalie; Wild, David J; Yang, Jeremy J; Sutherland, Jeffrey J; Thomas, Craig J

2015-01-01

Phenotypic assays have a proven track record for generating leads that become first-in-class therapies. Whole cell assays that inform on a phenotype or mechanism also possess great potential in drug repositioning studies by illuminating new activities for the existing pharmacopeia. The National Center for Advancing Translational Sciences (NCATS) pharmaceutical collection (NPC) is the largest reported collection of approved small molecule therapeutics that is available for screening in a high-throughput setting. Via a wide-ranging collaborative effort, this library was analyzed in the Open Innovation Drug Discovery (OIDD) phenotypic assay modules publicly offered by Lilly. The results of these tests are publically available online at www.ncats.nih.gov/expertise/preclinical/pd2 and via the PubChem Database (https://pubchem.ncbi.nlm.nih.gov/) (AID 1117321). Phenotypic outcomes for numerous drugs were confirmed, including sulfonylureas as insulin secretagogues and the anti-angiogenesis actions of multikinase inhibitors sorafenib, axitinib and pazopanib. Several novel outcomes were also noted including the Wnt potentiating activities of rotenone and the antifolate class of drugs, and the anti-angiogenic activity of cetaben.

Using RNA-seq and targeted nucleases to identify mechanisms of drug resistance in acute myeloid leukemia.

PubMed

Rathe, Susan K; Moriarity, Branden S; Stoltenberg, Christopher B; Kurata, Morito; Aumann, Natalie K; Rahrmann, Eric P; Bailey, Natashay J; Melrose, Ellen G; Beckmann, Dominic A; Liska, Chase R; Largaespada, David A

2014-08-13

The evolution from microarrays to transcriptome deep-sequencing (RNA-seq) and from RNA interference to gene knockouts using Clustered Regularly Interspaced Short Palindromic Repeats (CRISPRs) and Transcription Activator-Like Effector Nucleases (TALENs) has provided a new experimental partnership for identifying and quantifying the effects of gene changes on drug resistance. Here we describe the results from deep-sequencing of RNA derived from two cytarabine (Ara-C) resistance acute myeloid leukemia (AML) cell lines, and present CRISPR and TALEN based methods for accomplishing complete gene knockout (KO) in AML cells. We found protein modifying loss-of-function mutations in Dck in both Ara-C resistant cell lines. CRISPR and TALEN-based KO of Dck dramatically increased the IC₅₀ of Ara-C and introduction of a DCK overexpression vector into Dck KO clones resulted in a significant increase in Ara-C sensitivity. This effort demonstrates the power of using transcriptome analysis and CRISPR/TALEN-based KOs to identify and verify genes associated with drug resistance.

Systematic Analysis of Cell Cycle Effects of Common Drugs Leads to the Discovery of a Suppressive Interaction between Gemfibrozil and Fluoxetine

PubMed Central

Hoose, Scott A.; Duran, Camille; Malik, Indranil; Eslamfam, Shabnam; Shasserre, Samantha C.; Downing, S. Sabina; Hoover, Evelyn M.; Dowd, Katherine E.; Smith, Roger; Polymenis, Michael

2012-01-01

Screening chemical libraries to identify compounds that affect overall cell proliferation is common. However, in most cases, it is not known whether the compounds tested alter the timing of particular cell cycle transitions. Here, we evaluated an FDA-approved drug library to identify pharmaceuticals that alter cell cycle progression in yeast, using DNA content measurements by flow cytometry. This approach revealed strong cell cycle effects of several commonly used pharmaceuticals. We show that the antilipemic gemfibrozil delays initiation of DNA replication, while cells treated with the antidepressant fluoxetine severely delay progression through mitosis. Based on their effects on cell cycle progression, we also examined cell proliferation in the presence of both compounds. We discovered a strong suppressive interaction between gemfibrozil and fluoxetine. Combinations of interest among diverse pharmaceuticals are difficult to identify, due to the daunting number of possible combinations that must be evaluated. The novel interaction between gemfibrozil and fluoxetine suggests that identifying and combining drugs that show cell cycle effects might streamline identification of drug combinations with a pronounced impact on cell proliferation. PMID:22567160

Systematic analysis of cell cycle effects of common drugs leads to the discovery of a suppressive interaction between gemfibrozil and fluoxetine.

PubMed

Hoose, Scott A; Duran, Camille; Malik, Indranil; Eslamfam, Shabnam; Shasserre, Samantha C; Downing, S Sabina; Hoover, Evelyn M; Dowd, Katherine E; Smith, Roger; Polymenis, Michael

2012-01-01

Screening chemical libraries to identify compounds that affect overall cell proliferation is common. However, in most cases, it is not known whether the compounds tested alter the timing of particular cell cycle transitions. Here, we evaluated an FDA-approved drug library to identify pharmaceuticals that alter cell cycle progression in yeast, using DNA content measurements by flow cytometry. This approach revealed strong cell cycle effects of several commonly used pharmaceuticals. We show that the antilipemic gemfibrozil delays initiation of DNA replication, while cells treated with the antidepressant fluoxetine severely delay progression through mitosis. Based on their effects on cell cycle progression, we also examined cell proliferation in the presence of both compounds. We discovered a strong suppressive interaction between gemfibrozil and fluoxetine. Combinations of interest among diverse pharmaceuticals are difficult to identify, due to the daunting number of possible combinations that must be evaluated. The novel interaction between gemfibrozil and fluoxetine suggests that identifying and combining drugs that show cell cycle effects might streamline identification of drug combinations with a pronounced impact on cell proliferation.

Drug-nutrient interactions.

PubMed

Chan, Lingtak-Neander

2013-07-01

Drug-nutrient interactions are defined as physical, chemical, physiologic, or pathophysiologic relationships between a drug and a nutrient. The causes of most clinically significant drug-nutrient interactions are usually multifactorial. Failure to identify and properly manage drug-nutrient interactions can lead to very serious consequences and have a negative impact on patient outcomes. Nevertheless, with thorough review and assessment of the patient's history and treatment regimens and a carefully executed management strategy, adverse events associated with drug-nutrient interactions can be prevented. Based on the physiologic sequence of events after a drug or a nutrient has entered the body and the mechanism of interactions, drug-nutrient interactions can be categorized into 4 main types. Each type of interaction can be managed using similar strategies. The existing data that guide the clinical management of most drug-nutrient interactions are mostly anecdotal experience, uncontrolled observations, and opinions, whereas the science in understanding the mechanism of drug-nutrient interactions remains limited. The challenge for researchers and clinicians is to increase both basic and higher level clinical research in this field to bridge the gap between the science and practice. The research should aim to establish a better understanding of the function, regulation, and substrate specificity of the nutrient-related enzymes and transport proteins present in the gastrointestinal tract, as well as assess how the incidence and management of drug-nutrient interactions can be affected by sex, ethnicity, environmental factors, and genetic polymorphisms. This knowledge can help us develop a true personalized medicine approach in the prevention and management of drug-nutrient interactions.

Lead optimization in the nondrug-like space.

PubMed

Zhao, Hongyu

2011-02-01

Drug-like space might be more densely populated with orally available compounds than the remaining chemical space, but lead optimization can still occur outside this space. Oral drug space is more dynamic than the relatively static drug-like space. As new targets emerge and optimization tools advance the oral drug space might expand. Lead optimization protocols are becoming more complex with greater optimization needs to be satisfied, which consequently could change the role of drug-likeness in the process. Whereas drug-like space should usually be explored preferentially, it can be easier to find oral drugs for certain targets in the nondrug-like space. Copyright © 2010 Elsevier Ltd. All rights reserved.

A dictionary to identify small molecules and drugs in free text.

PubMed

Hettne, Kristina M; Stierum, Rob H; Schuemie, Martijn J; Hendriksen, Peter J M; Schijvenaars, Bob J A; Mulligen, Erik M van; Kleinjans, Jos; Kors, Jan A

2009-11-15

From the scientific community, a lot of effort has been spent on the correct identification of gene and protein names in text, while less effort has been spent on the correct identification of chemical names. Dictionary-based term identification has the power to recognize the diverse representation of chemical information in the literature and map the chemicals to their database identifiers. We developed a dictionary for the identification of small molecules and drugs in text, combining information from UMLS, MeSH, ChEBI, DrugBank, KEGG, HMDB and ChemIDplus. Rule-based term filtering, manual check of highly frequent terms and disambiguation rules were applied. We tested the combined dictionary and the dictionaries derived from the individual resources on an annotated corpus, and conclude the following: (i) each of the different processing steps increase precision with a minor loss of recall; (ii) the overall performance of the combined dictionary is acceptable (precision 0.67, recall 0.40 (0.80 for trivial names); (iii) the combined dictionary performed better than the dictionary in the chemical recognizer OSCAR3; (iv) the performance of a dictionary based on ChemIDplus alone is comparable to the performance of the combined dictionary. The combined dictionary is freely available as an XML file in Simple Knowledge Organization System format on the web site http://www.biosemantics.org/chemlist.

21 CFR 25.44 - Lead and cooperating agencies.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 1 2010-04-01 2010-04-01 false Lead and cooperating agencies. 25.44 Section 25.44 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL ENVIRONMENTAL IMPACT CONSIDERATIONS Preparation of Environmental Documents § 25.44 Lead and cooperating agencies...

[Caenorhabditis elegans: a powerful tool for drug discovery].

PubMed

Jia, Xi-Hua; Cao, Cheng

2009-07-01

A simple model organism Caenorhabditis elegans has contributed substantially to the fundamental researches in biology. In an era of functional genomics, nematode worm has been developed into a multi-purpose tool that can be exploited to identify disease-causing or disease-associated genes, validate potential drug targets. This, coupled with its genetic amenability, low cost experimental manipulation and compatibility with high throughput screening in an intact physiological condition, makes the model organism into an effective toolbox for drug discovery. This review shows the unique features of C. elegans, how it can play a valuable role in our understanding of the molecular mechanism of human diseases and finding drug leads in drug development process.

Learning lessons from drugs that have recently entered the market.

PubMed

Teague, Simon J

2011-05-01

Which projects in the drug discovery field are most likely to be successful? In this article, I provide guidelines for answering this question by examining recent drug market entrants in detail, in particular their route of administration, trial design, novelty, therapeutic target and toxicities. I identify targets, trials and organizations as the key issues that are currently leading to the poor productivity in the pharmaceutical industry. Here, I outline some solutions and reasons for optimism, and suggest that the key determinants for success in drug discovery can be defined by studying recently launched drugs. Copyright © 2011 Elsevier Ltd. All rights reserved.

The European Lead Factory: A Blueprint for Public-Private Partnerships in Early Drug Discovery.

PubMed

Karawajczyk, Anna; Orrling, Kristina M; de Vlieger, Jon S B; Rijnders, Ton; Tzalis, Dimitrios

2016-01-01

The European Lead Factory (ELF) is a public-private partnership (PPP) that provides researchers in Europe with a unique platform for translation of innovative biology and chemistry into high-quality starting points for drug discovery. It combines an exceptional collection of small molecules, high-throughput screening (HTS) infrastructure, and hit follow-up capabilities to advance research projects from both private companies and publicly funded researchers. By active interactions with the wider European life science community, ELF connects and unites bright ideas, talent, and experience from several disciplines. As a result, ELF is a unique, collaborative lead generation engine that has so far resulted in >4,500 hit compounds with a defined biological activity from 83 successfully completed HTS and hit evaluation campaigns. The PPP has also produced more than 120,000 novel innovative library compounds that complement the 327,000 compounds contributed by the participating pharmaceutical companies. Intrinsic to its setup, ELF enables breakthroughs in areas with unmet medical and societal needs, where no individual entity would be able to create a comparable impact in such a short time.

The European Lead Factory: A Blueprint for Public–Private Partnerships in Early Drug Discovery

PubMed Central

Karawajczyk, Anna; Orrling, Kristina M.; de Vlieger, Jon S. B.; Rijnders, Ton; Tzalis, Dimitrios

2017-01-01

The European Lead Factory (ELF) is a public–private partnership (PPP) that provides researchers in Europe with a unique platform for translation of innovative biology and chemistry into high-quality starting points for drug discovery. It combines an exceptional collection of small molecules, high-throughput screening (HTS) infrastructure, and hit follow-up capabilities to advance research projects from both private companies and publicly funded researchers. By active interactions with the wider European life science community, ELF connects and unites bright ideas, talent, and experience from several disciplines. As a result, ELF is a unique, collaborative lead generation engine that has so far resulted in >4,500 hit compounds with a defined biological activity from 83 successfully completed HTS and hit evaluation campaigns. The PPP has also produced more than 120,000 novel innovative library compounds that complement the 327,000 compounds contributed by the participating pharmaceutical companies. Intrinsic to its setup, ELF enables breakthroughs in areas with unmet medical and societal needs, where no individual entity would be able to create a comparable impact in such a short time. PMID:28154815

Machine-Learning Techniques Applied to Antibacterial Drug Discovery

PubMed Central

Durrant, Jacob D.; Amaro, Rommie E.

2014-01-01

The emergence of drug-resistant bacteria threatens to catapult humanity back to the pre-antibiotic era. Even now, multi-drug-resistant bacterial infections annually result in millions of hospital days, billions in healthcare costs, and, most importantly, tens of thousands of lives lost. As many pharmaceutical companies have abandoned antibiotic development in search of more lucrative therapeutics, academic researchers are uniquely positioned to fill the resulting vacuum. Traditional high-throughput screens and lead-optimization efforts are expensive and labor intensive. Computer-aided drug discovery techniques, which are cheaper and faster, can accelerate the identification of novel antibiotics in an academic setting, leading to improved hit rates and faster transitions to pre-clinical and clinical testing. The current review describes two machine-learning techniques, neural networks and decision trees, that have been used to identify experimentally validated antibiotics. We conclude by describing the future directions of this exciting field. PMID:25521642

Discovery of novel drugs for promising targets.

PubMed

Martell, Robert E; Brooks, David G; Wang, Yan; Wilcoxen, Keith

2013-09-01

Once a promising drug target is identified, the steps to actually discover and optimize a drug are diverse and challenging. The goal of this study was to provide a road map to navigate drug discovery. Review general steps for drug discovery and provide illustrating references. A number of approaches are available to enhance and accelerate target identification and validation. Consideration of a variety of potential mechanisms of action of potential drugs can guide discovery efforts. The hit to lead stage may involve techniques such as high-throughput screening, fragment-based screening, and structure-based design, with informatics playing an ever-increasing role. Biologically relevant screening models are discussed, including cell lines, 3-dimensional culture, and in vivo screening. The process of enabling human studies for an investigational drug is also discussed. Drug discovery is a complex process that has significantly evolved in recent years. © 2013 Elsevier HS Journals, Inc. All rights reserved.

[Fragment-based drug discovery: concept and aim].

PubMed

Tanaka, Daisuke

2010-03-01

Fragment-Based Drug Discovery (FBDD) has been recognized as a newly emerging lead discovery methodology that involves biophysical fragment screening and chemistry-driven fragment-to-lead stages. Although fragments, defined as structurally simple and small compounds (typically <300 Da), have not been employed in conventional high-throughput screening (HTS), the recent significant progress in the biophysical screening methods enables fragment screening at a practical level. The intention of FBDD primarily turns our attention to weakly but specifically binding fragments (hit fragments) as the starting point of medicinal chemistry. Hit fragments are then promoted to more potent lead compounds through linking or merging with another hit fragment and/or attaching functional groups. Another positive aspect of FBDD is ligand efficiency. Ligand efficiency is a useful guide in screening hit selection and hit-to-lead phases to achieve lead-likeness. Owing to these features, a number of successful applications of FBDD to "undruggable targets" (where HTS and other lead identification methods failed to identify useful lead compounds) have been reported. As a result, FBDD is now expected to complement more conventional methodologies. This review, as an introduction of the following articles, will summarize the fundamental concepts of FBDD and will discuss its advantages over other conventional drug discovery approaches.

“High On My Own Supply”: Correlates of Drug Dealing among Heterosexually-identified Methamphetamine Users

PubMed Central

Semple, Shirley J.; Strathdee, Steffanie A.; Volkmann, Tyson; Zians, Jim; Patterson, Thomas L.

2011-01-01

Although rates of methamphetamine use continue to increase throughout the United States, little is known about the individuals who sell methamphetamine at the street level. This exploratory study examined the prevalence and correlates of drug-dealing behavior in a sample of 404 heterosexually-identified methamphetamine users who were participants in a sexual risk reduction intervention in San Diego, CA. Twenty-nine percent of participants (N = 116) reported “dealing” methamphetamine in the past two months. In a multivariate logistic regression, methamphetamine dealing was associated with being male (OR = 1.99; 95% CI 1.16 – 3.39), younger age (OR = 1.87 per year; 95% CI 1.10 – 3.17), more frequent use of methamphetamine (OR = 2.69; 95% CI 1.59 – 4.57), injecting methamphetamine (OR = 3.10; 95% CI 1.79 – 5.37), and higher hostility scores (OR = 1.07 per unit increase; 95% CI 1.01 – 1.13). These characteristics, particularly intensity of drug use and hostility, may be associated with greater resistance to drug treatment and lower success in treatment programs. PMID:21999496

An update on the use of C. elegans for preclinical drug discovery: screening and identifying anti-infective drugs.

PubMed

Kim, Wooseong; Hendricks, Gabriel Lambert; Lee, Kiho; Mylonakis, Eleftherios

2017-06-01

The emergence of antibiotic-resistant and -tolerant bacteria is a major threat to human health. Although efforts for drug discovery are ongoing, conventional bacteria-centered screening strategies have thus far failed to yield new classes of effective antibiotics. Therefore, new paradigms for discovering novel antibiotics are of critical importance. Caenorhabditis elegans, a model organism used for in vivo, offers a promising solution for identification of anti-infective compounds. Areas covered: This review examines the advantages of C. elegans-based high-throughput screening over conventional, bacteria-centered in vitro screens. It discusses major anti-infective compounds identified from large-scale C. elegans-based screens and presents the first clinically-approved drugs, then known bioactive compounds, and finally novel small molecules. Expert opinion: There are clear advantages of using a C. elegans-infection based screening method. A C. elegans-based screen produces an enriched pool of non-toxic, efficacious, potential anti-infectives, covering: conventional antimicrobial agents, immunomodulators, and anti-virulence agents. Although C. elegans-based screens do not denote the mode of action of hit compounds, this can be elucidated in secondary studies by comparing the results to target-based screens, or conducting subsequent target-based screens, including the genetic knock-down of host or bacterial genes.

QTL Mapping and CRISPR/Cas9 Editing to Identify a Drug Resistance Gene in Toxoplasma gondii

PubMed Central

Shen, Bang; Powell, Robin H.; Behnke, Michael S.

2017-01-01

Scientific knowledge is intrinsically linked to available technologies and methods. This article will present two methods that allowed for the identification and verification of a drug resistance gene in the Apicomplexan parasite Toxoplasma gondii, the method of Quantitative Trait Locus (QTL) mapping using a Whole Genome Sequence (WGS) -based genetic map and the method of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 -based gene editing. The approach of QTL mapping allows one to test if there is a correlation between a genomic region(s) and a phenotype. Two datasets are required to run a QTL scan, a genetic map based on the progeny of a recombinant cross and a quantifiable phenotype assessed in each of the progeny of that cross. These datasets are then formatted to be compatible with R/qtl software that generates a QTL scan to identify significant loci correlated with the phenotype. Although this can greatly narrow the search window of possible candidates, QTLs span regions containing a number of genes from which the causal gene needs to be identified. Having WGS of the progeny was critical to identify the causal drug resistance mutation at the gene level. Once identified, the candidate mutation can be verified by genetic manipulation of drug sensitive parasites. The most facile and efficient method to genetically modify T. gondii is the CRISPR/Cas9 system. This system comprised of just 2 components both encoded on a single plasmid, a single guide RNA (gRNA) containing a 20 bp sequence complementary to the genomic target and the Cas9 endonuclease that generates a double-strand DNA break (DSB) at the target, repair of which allows for insertion or deletion of sequences around the break site. This article provides detailed protocols to use CRISPR/Cas9 based genome editing tools to verify the gene responsible for sinefungin resistance and to construct transgenic parasites. PMID:28671645

Strategies to design clinical studies to identify predictive biomarkers in cancer research.

PubMed

Perez-Gracia, Jose Luis; Sanmamed, Miguel F; Bosch, Ana; Patiño-Garcia, Ana; Schalper, Kurt A; Segura, Victor; Bellmunt, Joaquim; Tabernero, Josep; Sweeney, Christopher J; Choueiri, Toni K; Martín, Miguel; Fusco, Juan Pablo; Rodriguez-Ruiz, Maria Esperanza; Calvo, Alfonso; Prior, Celia; Paz-Ares, Luis; Pio, Ruben; Gonzalez-Billalabeitia, Enrique; Gonzalez Hernandez, Alvaro; Páez, David; Piulats, Jose María; Gurpide, Alfonso; Andueza, Mapi; de Velasco, Guillermo; Pazo, Roberto; Grande, Enrique; Nicolas, Pilar; Abad-Santos, Francisco; Garcia-Donas, Jesus; Castellano, Daniel; Pajares, María J; Suarez, Cristina; Colomer, Ramon; Montuenga, Luis M; Melero, Ignacio

2017-02-01

The discovery of reliable biomarkers to predict efficacy and toxicity of anticancer drugs remains one of the key challenges in cancer research. Despite its relevance, no efficient study designs to identify promising candidate biomarkers have been established. This has led to the proliferation of a myriad of exploratory studies using dissimilar strategies, most of which fail to identify any promising targets and are seldom validated. The lack of a proper methodology also determines that many anti-cancer drugs are developed below their potential, due to failure to identify predictive biomarkers. While some drugs will be systematically administered to many patients who will not benefit from them, leading to unnecessary toxicities and costs, others will never reach registration due to our inability to identify the specific patient population in which they are active. Despite these drawbacks, a limited number of outstanding predictive biomarkers have been successfully identified and validated, and have changed the standard practice of oncology. In this manuscript, a multidisciplinary panel reviews how those key biomarkers were identified and, based on those experiences, proposes a methodological framework-the DESIGN guidelines-to standardize the clinical design of biomarker identification studies and to develop future research in this pivotal field. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Identifying and solving lead issues from water systems with materials/device replacement in drinking water system configurations

EPA Science Inventory

Identifying and assessing lead contamination and exposure potentialin single-family residences is difficult enough, but doing the samekind of assessment and remediation in buildings, schools, and daycare centers is even more challenging. It is of particular importancebecause of t...

Integrating virtual screening and biochemical experimental approach to identify potential anti-cancer agents from drug databank.

PubMed

Deka, Suman Jyoti; Roy, Ashalata; Manna, Debasis; Trivedi, Vishal

2018-06-01

Chemical libraries constitute a reservoir of pharmacophoric molecules to identify potent anti-cancer agents. Virtual screening of heterocyclic compound library in conjugation with the agonist-competition assay, toxicity-carcinogenicity analysis, and string-based structural searches enabled us to identify several drugs as potential anti-cancer agents targeting protein kinase C (PKC) as a target. Molecular modeling study indicates that Cinnarizine fits well within the PKC C2 domain and exhibits extensive interaction with the protein residues. Molecular dynamics simulation of PKC-Cinnarizine complex at different temperatures (300, 325, 350, 375, and 400[Formula: see text]K) confirms that Cinnarizine fits nicely into the C2 domain and forms a stable complex. The drug Cinnarizine was found to bind PKC with a dissociation constant Kd of [Formula: see text]M. The breast cancer cells stimulated with Cinnarizine causes translocation of PKC-[Formula: see text] to the plasma membrane as revealed by immunoblotting and immunofluorescence studies. Cinnarizine also dose dependently reduced the viability of MDAMB-231 and MCF-7 breast cancer cells with an IC[Formula: see text] of [Formula: see text] and [Formula: see text]g/mL, respectively. It is due to the disturbance of cell cycle of breast cancer cells with reduction of S-phase and accumulation of cells in G1-phase. It disturbs mitochondrial membrane potentials to release cytochrome C into the cytosol and activates caspase-3 to induce apoptosis in cancer cells. The cell death was due to induction of apoptosis involving mitochondrial pathway. Hence, the current study has assigned an additional role to Cinnarizine as an activator of PKC and potentials of the approach to identify new molecules for anti-cancer therapy. Thus, in silico screening along with biochemical experimentation is a robust approach to assign additional roles to the drugs present in the databank for anti-cancer therapy.

Identifying and Solving Lead Issues from Water Systems with Materials/Device Replacement in Schools and other Buildings

EPA Science Inventory

Identifying and assessing lead contamination and exposure potential in single-family residences is difficult enough, but doing the same kind of assessment and remediation in buildings, schools, and day care centers is even more challenging. It is of particular importance because ...

Identifying Liver Cancer and Its Relations with Diseases, Drugs, and Genes: A Literature-Based Approach

PubMed Central

Song, Min

2016-01-01

In biomedicine, scientific literature is a valuable source for knowledge discovery. Mining knowledge from textual data has become an ever important task as the volume of scientific literature is growing unprecedentedly. In this paper, we propose a framework for examining a certain disease based on existing information provided by scientific literature. Disease-related entities that include diseases, drugs, and genes are systematically extracted and analyzed using a three-level network-based approach. A paper-entity network and an entity co-occurrence network (macro-level) are explored and used to construct six entity specific networks (meso-level). Important diseases, drugs, and genes as well as salient entity relations (micro-level) are identified from these networks. Results obtained from the literature-based literature mining can serve to assist clinical applications. PMID:27195695

[Pathogenic Mechanism and Diagnostic Testing for Drug Allergies].

PubMed

Uno, Katsuji

2018-01-01

　Three stages of the pathogenic mechanism of drug allergies can be considered: antigen formation, immune reaction and inflammation/disorder reaction. Drugs are thought to form 4 types of antigens: drug only, polymers, drug-carrier conjugates, and metabolite-carrier complexes. Antigens are recognized by B cell receptors and T cell receptors. Helper T cells (Th) are differentiated into four subsets, namely, Th1, Th2, Th17 and regulatory T cells (Treg). Th1 produces interleukin (IL)-2 and interferon (IFN)-γ, and activates macrophages and cytotoxic T cells (Tc). Macrophages induce type IV allergies, and Tc lead to serious type IV allergies. On the other hand, Th2 produces IL-4, IL-5, and IL-6, etc., and activates B cells. B cells produce IgE antibodies, and the IgE antibody affects mast cells and induces type I allergies. Activated eosinophil leads to the chronic state of type I allergy. Diagnostic testing for allergenic drugs is necessary for patients with drug allergies. Because in vivo diagnostic tests for allergenic drugs are associated with a risk and burden to the patient, in vitro allergy tests are recommended to identify allergenic drugs. In allergy tests performed in vitro, cytological tests are more effective than serological tests, and the leukocyte migration test (LMT) presently has the highest efficacy. An LMT-chamber is better than LMT-agarose in terms of usability and sensitivity, and it can detect about 80% of allergenic drugs.

Pharmacokinetics of Drugs in Cachectic Patients: A Systematic Review

PubMed Central

Trobec, Katja; Kerec Kos, Mojca; von Haehling, Stephan; Springer, Jochen; Anker, Stefan D.; Lainscak, Mitja

2013-01-01

Cachexia is a weight-loss process caused by an underlying chronic disease such as cancer, chronic heart failure, chronic obstructive pulmonary disease, or rheumatoid arthritis. It leads to changes in body structure and function that may influence the pharmacokinetics of drugs. Changes in gut function and decreased subcutaneous tissue may influence the absorption of orally and transdermally applied drugs. Altered body composition and plasma protein concentration may affect drug distribution. Changes in the expression and function of metabolic enzymes could influence the metabolism of drugs, and their renal excretion could be affected by possible reduction in kidney function. Because no general guidelines exist for drug dose adjustments in cachectic patients, we conducted a systematic search to identify articles that investigated the pharmacokinetics of drugs in cachectic patients. PMID:24282510

Identifying Some Factors That Might Predispose Drug Abuse among Learners in a South African Township School

ERIC Educational Resources Information Center

Grobler, R.; Khatite, M.

2012-01-01

This study inquires into some of the factors that might predispose the use and abuse of drugs among secondary school learners in a township school. The objective of this research is to identify these factors and to offer a few suggestions on how the abuse may be prevented. A quantitative research strategy is used and a document analysis technique…

Lead.

PubMed

Bellinger, David C

2004-04-01

Children differ from adults in the relative importance of lead sources and pathways, lead metabolism, and the toxicities expressed. The central nervous system effects of lead on children seem not to be reversible. Periods of enhanced vulnerability within childhood have not consistently been identified. The period of greatest vulnerability might be endpoint specific, perhaps accounting for the failure to identify a coherent "behavioral signature" for lead toxicity. The bases for the substantial individual variability in vulnerability to lead are uncertain, although they might include genetic polymorphisms and contextual factors. The current Centers for Disease Control and Prevention screening guideline of 10 micro g/dL is a risk management tool and should not be interpreted as a threshold for toxicity. No threshold has been identified, and some data are consistent with effects well below 10. Historically, most studies have concentrated on neurocognitive effects of lead, but higher exposures have recently been associated with morbidities such as antisocial behavior and delinquency. Studies of lead toxicity in experimental animal models are critical to the interpretation of nonexperimental human studies, particularly in addressing the likelihood that associations observed in the latter studies can be attributed to residual confounding. Animal models are also helpful in investigating the behavioral and neurobiological mechanisms of the functional deficits observed in lead-exposed humans. Studies of adults who have been exposed to lead are of limited use in understanding childhood lead toxicity because developmental and acquired lead exposure differ in terms of the maturity of the organs affected, the presumed mechanisms of toxicity, and the forms in which toxicities are expressed.

What is wrong with orphan drug policies?

PubMed

Côté, André; Keating, Bernard

2012-12-01

The effects of orphan drug policies raise serious concerns among payer organizations and lead to often-tragic disappointment for patients who are denied much anticipated drug reimbursements. We evaluate the effects of orphan drug policies on the basis of this concern for real accessibility to drugs. We highlight two unforeseen effects of orphan drug policies: 1) they provide unique business opportunities for manufacturers and 2) drugs approved through these policies are often inaccessible because of their high price. We identify six causes of this emergence of effects. The first four are the direct result of incentives included in orphan drug policies. The fifth cause is the "off-label" use of orphan drugs. These emergent effects have several implications: 1) they raise doubts about the equity of access to drugs, 2) they highlight the limitations of the cohort paradigm in medicine, and c) they force third-party payers to make drugs accessible even when the prices of drugs are believed to be disproportionate to the clinical effects obtained. Copyright © 2012 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Pyrimethamine as a Potent and Selective Inhibitor of Acute Myeloid Leukemia Identified by High-throughput Drug Screening.

PubMed

Sharma, Amit; Jyotsana, Nidhi; Lai, Courteney K; Chaturvedi, Anuhar; Gabdoulline, Razif; Görlich, Kerstin; Murphy, Cecilia; Blanchard, Jan E; Ganser, Arnold; Brown, Eric; Hassell, John A; Humphries, R Keith; Morgan, Michael; Heuser, Michael

2016-01-01

Hematopoietic stem and progenitor cell differentiation are blocked in acute myeloid leukemia (AML) resulting in cytopenias and a high risk of death. Most patients with AML become resistant to treatment due to lack of effective cytotoxic and differentiation promoting compounds. High MN1 expression confers poor prognosis to AML patients and induces resistance to cytarabine and alltrans-retinoic acid (ATRA) induced differentiation. Using a high-throughput drug screening, we identified the dihydrofolate reductase (DHFR) antagonist pyrimethamine to be a potent inducer of apoptosis and differentiation in several murine and human leukemia cell lines. Oral pyrimethamine treatment was effective in two xenograft mouse models and specifically targeted leukemic cells in human AML cell lines and primary patient cells, while CD34+ cells from healthy donors were unaffected. The antileukemic effects of PMT could be partially rescued by excess folic acid, suggesting an oncogenic function of folate metabolism in AML. Thus, our study identifies pyrimethamine as a candidate drug that should be further evaluated in AML treatment.

Effects of Drugs

MedlinePlus

... Used Drugs in the Past Drug Use Prevention Phone Numbers and Websites Search ... who aren't yet born. Drug use can hurt the body and the brain, sometimes forever. Drug use can also lead to addiction, a long-lasting brain disease in which people ...

Use of a single alcohol screening question to identify other drug use.

PubMed

Smith, Peter C; Cheng, Debbie M; Allensworth-Davies, Donald; Winter, Michael R; Saitz, Richard

2014-06-01

People who consume unhealthy amounts of alcohol are more likely to use illicit drugs. We tested the ability of a screening test for unhealthy alcohol use to simultaneously detect drug use. Adult English speaking patients (n=286) were enrolled from a primary care waiting room. They were asked the screening question for unhealthy alcohol use "How many times in the past year have you had X or more drinks in a day?", where X is 5 for men and 4 for women, and a response of one or more is considered positive. A standard diagnostic interview was used to determine current (past year) drug use or a drug use disorder (abuse or dependence). Oral fluid testing was also used to detect recent use of common drugs of abuse. The single screening question for unhealthy alcohol use was 67.6% sensitive (95% confidence interval [CI], 50.2-82.0%) and 64.7% specific (95% CI, 58.4-70.6%) for the detection of a drug use disorder. It was similarly insensitive for drug use detected by oral fluid testing and/or self-report. Although a patient with a drug use disorder has twice the odds of screening positive for unhealthy alcohol use compared to one without a drug use disorder, suggesting patients who screen positive for alcohol should be asked about drug use, a single screening question for unhealthy alcohol use was not sensitive or specific for the detection of other drug use or drug use disorders in a sample of primary care patients. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Drug Intervention Response Predictions with PARADIGM (DIRPP) identifies drug resistant cancer cell lines and pathway mechanisms of resistance.

PubMed

Brubaker, Douglas; Difeo, Analisa; Chen, Yanwen; Pearl, Taylor; Zhai, Kaide; Bebek, Gurkan; Chance, Mark; Barnholtz-Sloan, Jill

2014-01-01

The revolution in sequencing techniques in the past decade has provided an extensive picture of the molecular mechanisms behind complex diseases such as cancer. The Cancer Cell Line Encyclopedia (CCLE) and The Cancer Genome Project (CGP) have provided an unprecedented opportunity to examine copy number, gene expression, and mutational information for over 1000 cell lines of multiple tumor types alongside IC50 values for over 150 different drugs and drug related compounds. We present a novel pipeline called DIRPP, Drug Intervention Response Predictions with PARADIGM7, which predicts a cell line's response to a drug intervention from molecular data. PARADIGM (Pathway Recognition Algorithm using Data Integration on Genomic Models) is a probabilistic graphical model used to infer patient specific genetic activity by integrating copy number and gene expression data into a factor graph model of a cellular network. We evaluated the performance of DIRPP on endometrial, ovarian, and breast cancer related cell lines from the CCLE and CGP for nine drugs. The pipeline is sensitive enough to predict the response of a cell line with accuracy and precision across datasets as high as 80 and 88% respectively. We then classify drugs by the specific pathway mechanisms governing drug response. This classification allows us to compare drugs by cellular response mechanisms rather than simply by their specific gene targets. This pipeline represents a novel approach for predicting clinical drug response and generating novel candidates for drug repurposing and repositioning.

Inflammatory mediators leading to protein misfolding and uncompetitive/fast off-rate drug therapy for neurodegenerative disorders.

PubMed

Lipton, Stuart A; Gu, Zezong; Nakamura, Tomohiro

2007-01-01

contributes to the pathogenesis of PD. One way to ameliorate excessive NO production and hence abnormal S-nitrosylations would be to inhibit NMDA receptors. In fact, blockade of excessive NMDA receptor activity can in large measure protect neurons from this type of injury and death. However, inhibition of the NMDA receptor by high-affinity antagonists also blocks the receptor's normal function in synaptic transmission and leads to unacceptable side effects. For this reason, many NMDA receptor antagonists have disappointingly failed in advanced clinical trials. Our group was the first to demonstrate that gentle blockade of NMDA receptors by memantine, via a mechanism of uncompetitive open-channel block with a rapid "off-rate," can prevent this type of damage in a clinically efficacious manner without substantial side effects. For these Uncompetitive/Fast Off-rate therapeutics, we use the term "UFO drugs" because like Unidentified Flying Objects, they leave very quickly as soon as their job is finished. As a result, memantine blocks excessive NMDA receptor activity without disrupting normal activity. Memantine does this by preferentially entering the receptor-associated ion channel when it is excessively open, and, most importantly, when its off-rate from the channel is relatively fast so that it does not accumulate to interfere with normal synaptic transmission. Hence, memantine is clinically well tolerated, has been used in Europe for PD for many years, and recently passed multiple phase III trials for dementia, leading to its approval by the FDA and European Union for moderate-to-severe AD. Clinical studies of memantine for additional neurological disorders, including other dementias, neuropathic pain, and glaucoma, are underway. We have also developed a series of second-generation drugs that display greater neuroprotective properties than memantine. These second-generation drugs take advantage of the fact that the NMDA receptor has other modulatory sites, including critical

Antiviral lead compounds from marine sponges.

PubMed

Sagar, Sunil; Kaur, Mandeep; Minneman, Kenneth P

2010-10-11

Marine sponges are currently one of the richest sources of pharmacologically active compounds found in the marine environment. These bioactive molecules are often secondary metabolites, whose main function is to enable and/or modulate cellular communication and defense. They are usually produced by functional enzyme clusters in sponges and/or their associated symbiotic microorganisms. Natural product lead compounds from sponges have often been found to be promising pharmaceutical agents. Several of them have successfully been approved as antiviral agents for clinical use or have been advanced to the late stages of clinical trials. Most of these drugs are used for the treatment of human immunodeficiency virus (HIV) and herpes simplex virus (HSV). The most important antiviral lead of marine origin reported thus far is nucleoside Ara-A (vidarabine) isolated from sponge Tethya crypta. It inhibits viral DNA polymerase and DNA synthesis of herpes, vaccinica and varicella zoster viruses. However due to the discovery of new types of viruses and emergence of drug resistant strains, it is necessary to develop new antiviral lead compounds continuously. Several sponge derived antiviral lead compounds which are hoped to be developed as future drugs are discussed in this review. Supply problems are usually the major bottleneck to the development of these compounds as drugs during clinical trials. However advances in the field of metagenomics and high throughput microbial cultivation has raised the possibility that these techniques could lead to the cost-effective large scale production of such compounds. Perspectives on biotechnological methods with respect to marine drug development are also discussed.

Silica-based mesoporous nanoparticles for controlled drug delivery

PubMed Central

Kwon, Sooyeon; Singh, Rajendra K; Perez, Roman A; Abou Neel, Ensanya A

2013-01-01

Drug molecules with lack of specificity and solubility lead patients to take high doses of the drug to achieve sufficient therapeutic effects. This is a leading cause of adverse drug reactions, particularly for drugs with narrow therapeutic window or cytotoxic chemotherapeutics. To address these problems, there are various functional biocompatible drug carriers available in the market, which can deliver therapeutic agents to the target site in a controlled manner. Among the carriers developed thus far, mesoporous materials emerged as a promising candidate that can deliver a variety of drug molecules in a controllable and sustainable manner. In particular, mesoporous silica nanoparticles are widely used as a delivery reagent because silica possesses favourable chemical properties, thermal stability and biocompatibility. Currently, sol-gel-derived mesoporous silica nanoparticles in soft conditions are of main interest due to simplicity in production and modification and the capacity to maintain function of bioactive agents. The unique mesoporous structure of silica facilitates effective loading of drugs and their subsequent controlled release. The properties of mesopores, including pore size and porosity as well as the surface properties, can be altered depending on additives used to fabricate mesoporous silica nanoparticles. Active surface enables functionalisation to modify surface properties and link therapeutic molecules. The tuneable mesopore structure and modifiable surface of mesoporous silica nanoparticle allow incorporation of various classes of drug molecules and controlled delivery to the target sites. This review aims to present the state of knowledge of currently available drug delivery system and identify properties of an ideal drug carrier for specific application, focusing on mesoporous silica nanoparticles. PMID:24020012

Analysis of Safety-Related Regulatory Actions for New Drugs in Japan by Nature of Identified Risks.

PubMed

Fujikawa, Makoto; Ono, Shunsuke

2017-01-01

implementing locally optimized pharmacovigilance activities. Caution may be needed not only for drugs with novel MOAs, but also for drugs for which local dose-finding studies have been skipped, expedited review status has been given, timing of launch is close to those in the USA and the EU, and spontaneous reports rather than company-lead surveillance suggest possible safety risks.

[Lead compound optimization strategy(5) – reducing the hERG cardiac toxicity in drug development].

PubMed

Zhou, Sheng-bin; Wang, Jiang; Liu, Hong

2016-10-01

The potassium channel encoded by the human ether-a-go-go related gene(hERG) plays a very important role in the physiological and pathological processes in human. hERG potassium channel determines the outward currents which facilitate the repolarization of the myocardial cells. Some drugs were withdrawn from the market for the serious side effect of long QT interval and arrhythmia due to blockade of hERG channel. The strategies for lead compound optimization are to reduce inhibitory activity of hERG potassium channel and decrease cardiac toxicity. These methods include reduction of lipophilicity and basicity of amines, introduction of hydroxyl and acidic groups, and restricting conformation.

Bayesian Models Leveraging Bioactivity and Cytotoxicity Information for Drug Discovery

PubMed Central

Ekins, Sean; Reynolds, Robert C.; Kim, Hiyun; Koo, Mi-Sun; Ekonomidis, Marilyn; Talaue, Meliza; Paget, Steve D.; Woolhiser, Lisa K.; Lenaerts, Anne J.; Bunin, Barry A.; Connell, Nancy; Freundlich, Joel S.

2013-01-01

SUMMARY Identification of unique leads represents a significant challenge in drug discovery. This hurdle is magnified in neglected diseases such as tuberculosis. We have leveraged public high-throughput screening (HTS) data, to experimentally validate virtual screening approach employing Bayesian models built with bioactivity information (single-event model) as well as bioactivity and cytotoxicity information (dual-event model). We virtually screen a commercial library and experimentally confirm actives with hit rates exceeding typical HTS results by 1-2 orders of magnitude. The first dual-event Bayesian model identified compounds with antitubercular whole-cell activity and low mammalian cell cytotoxicity from a published set of antimalarials. The most potent hit exhibits the in vitro activity and in vitro/in vivo safety profile of a drug lead. These Bayesian models offer significant economies in time and cost to drug discovery. PMID:23521795

The rise of fragment-based drug discovery.

PubMed

Murray, Christopher W; Rees, David C

2009-06-01

The search for new drugs is plagued by high attrition rates at all stages in research and development. Chemists have an opportunity to tackle this problem because attrition can be traced back, in part, to the quality of the chemical leads. Fragment-based drug discovery (FBDD) is a new approach, increasingly used in the pharmaceutical industry, for reducing attrition and providing leads for previously intractable biological targets. FBDD identifies low-molecular-weight ligands (∼150 Da) that bind to biologically important macromolecules. The three-dimensional experimental binding mode of these fragments is determined using X-ray crystallography or NMR spectroscopy, and is used to facilitate their optimization into potent molecules with drug-like properties. Compared with high-throughput-screening, the fragment approach requires fewer compounds to be screened, and, despite the lower initial potency of the screening hits, offers more efficient and fruitful optimization campaigns. Here, we review the rise of FBDD, including its application to discovering clinical candidates against targets for which other chemistry approaches have struggled.

An integrated structure- and system-based framework to identify new targets of metabolites and known drugs

PubMed Central

Naveed, Hammad; Hameed, Umar S.; Harrus, Deborah; Bourguet, William; Arold, Stefan T.; Gao, Xin

2015-01-01

Motivation: The inherent promiscuity of small molecules towards protein targets impedes our understanding of healthy versus diseased metabolism. This promiscuity also poses a challenge for the pharmaceutical industry as identifying all protein targets is important to assess (side) effects and repositioning opportunities for a drug. Results: Here, we present a novel integrated structure- and system-based approach of drug-target prediction (iDTP) to enable the large-scale discovery of new targets for small molecules, such as pharmaceutical drugs, co-factors and metabolites (collectively called ‘drugs’). For a given drug, our method uses sequence order–independent structure alignment, hierarchical clustering and probabilistic sequence similarity to construct a probabilistic pocket ensemble (PPE) that captures promiscuous structural features of different binding sites on known targets. A drug’s PPE is combined with an approximation of its delivery profile to reduce false positives. In our cross-validation study, we use iDTP to predict the known targets of 11 drugs, with 63% sensitivity and 81% specificity. We then predicted novel targets for these drugs—two that are of high pharmacological interest, the peroxisome proliferator-activated receptor gamma and the oncogene B-cell lymphoma 2, were successfully validated through in vitro binding experiments. Our method is broadly applicable for the prediction of protein-small molecule interactions with several novel applications to biological research and drug development. Availability and implementation: The program, datasets and results are freely available to academic users at http://sfb.kaust.edu.sa/Pages/Software.aspx. Contact: xin.gao@kaust.edu.sa and stefan.arold@kaust.edu.sa Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26286808

Lead Poison Detection

NASA Technical Reports Server (NTRS)

1976-01-01

With NASA contracts, Whittaker Corporations Space Science division has developed an electro-optical instrument to mass screen for lead poisoning. Device is portable and detects protoporphyrin in whole blood. Free corpuscular porphyrins occur as an early effect of lead ingestion. Also detects lead in urine used to confirm blood tests. Test is inexpensive and can be applied by relatively unskilled personnel. Similar Whittaker fluorometry device called "drug screen" can measure morphine and quinine in urine much faster and cheaper than other methods.

Potential drug interactions in patients given antiretroviral therapy

PubMed Central

dos Santos, Wendel Mombaque; Secoli, Silvia Regina; Padoin, Stela Maris de Mello

2016-01-01

ABSTRACT Objective: to investigate potential drug-drug interactions (PDDI) in patients with HIV infection on antiretroviral therapy. Methods: a cross-sectional study was conducted on 161 adults with HIV infection. Clinical, socio demographic, and antiretroviral treatment data were collected. To analyze the potential drug interactions, we used the software Micromedex(r). Statistical analysis was performed by binary logistic regression, with a p-value of ≤0.05 considered statistically significant. Results: of the participants, 52.2% were exposed to potential drug-drug interactions. In total, there were 218 potential drug-drug interactions, of which 79.8% occurred between drugs used for antiretroviral therapy. There was an association between the use of five or more medications and potential drug-drug interactions (p = 0.000) and between the time period of antiretroviral therapy being over six years and potential drug-drug interactions (p < 0.00). The clinical impact was prevalent sedation and cardiotoxicity. Conclusions: the PDDI identified in this study of moderate and higher severity are events that not only affect the therapeutic response leading to toxicity in the central nervous and cardiovascular systems, but also can interfere in tests used for detection of HIV resistance to antiretroviral drugs. PMID:27878224

Solid-Phase Biological Assays for Drug Discovery

NASA Astrophysics Data System (ADS)

Forsberg, Erica M.; Sicard, Clémence; Brennan, John D.

2014-06-01

In the past 30 years, there has been a significant growth in the use of solid-phase assays in the area of drug discovery, with a range of new assays being used for both soluble and membrane-bound targets. In this review, we provide some basic background to typical drug targets and immobilization protocols used in solid-phase biological assays (SPBAs) for drug discovery, with emphasis on particularly labile biomolecular targets such as kinases and membrane-bound receptors, and highlight some of the more recent approaches for producing protein microarrays, bioaffinity columns, and other devices that are central to small molecule screening by SPBA. We then discuss key applications of such assays to identify drug leads, with an emphasis on the screening of mixtures. We conclude by highlighting specific advantages and potential disadvantages of SPBAs, particularly as they relate to particular assay formats.

A Drug-Centric View of Drug Development: How Drugs Spread from Disease to Disease

PubMed Central

Rodriguez-Esteban, Raul

2016-01-01

Drugs are often seen as ancillary to the purpose of fighting diseases. Here an alternative view is proposed in which they occupy a spearheading role. In this view, drugs are technologies with an inherent therapeutic potential. Once created, they can spread from disease to disease independently of the drug creator’s original intentions. Through the analysis of extensive literature and clinical trial records, it can be observed that successful drugs follow a life cycle in which they are studied at an increasing rate, and for the treatment of an increasing number of diseases, leading to clinical advancement. Such initial growth, following a power law on average, has a degree of momentum, but eventually decelerates, leading to stagnation and decay. A network model can describe the propagation of drugs from disease to disease in which diseases communicate with each other by receiving and sending drugs. Within this model, some diseases appear more prone to influence other diseases than be influenced, and vice versa. Diseases can also be organized into a drug-centric disease taxonomy based on the drugs that each adopts. This taxonomy reflects not only biological similarities across diseases, but also the level of differentiation of existing therapies. In sum, this study shows that drugs can become contagious technologies playing a driving role in the fight against disease. By better understanding such dynamics, pharmaceutical developers may be able to manage drug projects more effectively. PMID:27124390

A Drug-Centric View of Drug Development: How Drugs Spread from Disease to Disease.

PubMed

Rodriguez-Esteban, Raul

2016-04-01

Drugs are often seen as ancillary to the purpose of fighting diseases. Here an alternative view is proposed in which they occupy a spearheading role. In this view, drugs are technologies with an inherent therapeutic potential. Once created, they can spread from disease to disease independently of the drug creator's original intentions. Through the analysis of extensive literature and clinical trial records, it can be observed that successful drugs follow a life cycle in which they are studied at an increasing rate, and for the treatment of an increasing number of diseases, leading to clinical advancement. Such initial growth, following a power law on average, has a degree of momentum, but eventually decelerates, leading to stagnation and decay. A network model can describe the propagation of drugs from disease to disease in which diseases communicate with each other by receiving and sending drugs. Within this model, some diseases appear more prone to influence other diseases than be influenced, and vice versa. Diseases can also be organized into a drug-centric disease taxonomy based on the drugs that each adopts. This taxonomy reflects not only biological similarities across diseases, but also the level of differentiation of existing therapies. In sum, this study shows that drugs can become contagious technologies playing a driving role in the fight against disease. By better understanding such dynamics, pharmaceutical developers may be able to manage drug projects more effectively.

Chemogenomics profiling of drug targets of peptidoglycan biosynthesis pathway in Leptospira interrogans by virtual screening approaches.

PubMed

Bhattacharjee, Biplab; Simon, Rose Mary; Gangadharaiah, Chaithra; Karunakar, Prashantha

2013-06-28

Leptospirosis is a worldwide zoonosis of global concern caused by Leptospira interrogans. The availability of ligand libraries has facilitated the search for novel drug targets using chemogenomics approaches, compared with the traditional method of drug discovery, which is time consuming and yields few leads with little intracellular information for guiding target selection. Recent subtractive genomics studies have revealed the putative drug targets in peptidoglycan biosynthesis pathways in Leptospira interrogans. Aligand library for the murD ligase enzyme in the peptidoglycan pathway has also been identified. Our approach in this research involves screening of the pre-existing ligand library of murD with related protein family members in the putative drug target assembly in the peptidoglycan biosynthesis pathway. A chemogenomics approach has been implemented here, which involves screening of known ligands of a protein family having analogous domain architecture for identification of leads for existing druggable protein family members. By means of this approach, one murC and one murF inhibitor were identified, providing a platform for developing an antileptospirosis drug targeting the peptidoglycan biosynthesis pathway. Given that the peptidoglycan biosynthesis pathway is exclusive to bacteria, the in silico identified mur ligase inhibitors are expected to be broad-spectrum Gram-negative inhibitors if synthesized and tested in in vitro and in vivo assays.

Sources for Leads: Natural Products and Libraries.

PubMed

van Herwerden, Eric F; Süssmuth, Roderich D

2016-01-01

Natural products have traditionally been a major source of leads in the drug discovery process. However, the development of high-throughput screening led to an increased interest in synthetic methods that enabled the rapid construction of large libraries of molecules. This resulted in the termination or downscaling of many natural product research programs, but the chemical libraries did not necessarily produce a larger amount of drug leads. On one hand, this chapter explores the current state of natural product research within the drug discovery process. On the other hand it evaluates the efforts made to increase the amount of leads generated from chemical libraries and considers what role natural products could play here.

Designer drugs: the evolving science of drug discovery.

PubMed

Wanke, L A; DuBose, R F

1998-07-01

Drug discovery and design are fundamental to drug development. Until recently, most drugs were discovered through random screening or developed through molecular modification. New technologies are revolutionizing this phase of drug development. Rational drug design, using powerful computers and computational chemistry and employing X-ray crystallography, nuclear magnetic resonance spectroscopy, and three-dimensional quantitative structure activity relationship analysis, is creating highly specific, biologically active molecules by virtual reality modeling. Sophisticated screening technologies are eliminating all but the most active lead compounds. These new technologies promise more efficacious, safe, and cost-effective medications, while minimizing drug development time and maximizing profits.

Gore offers to help drug companies pursue research.

PubMed

1996-03-08

A meeting convened between Vice President Al Gore and executives of leading pharmaceutical companies to determine means of accelerating efforts to develop vaccines, therapeutics, and microbicides for people with HIV. Gore explained that the administration will work with pharmaceutical companies to determine the long-term effectiveness of drugs approved by the Food and Drug Administration (FDA), work with international groups to increase investment in vaccine development, help develop new microbicides for women with HIV, and identify promising areas of AIDS research. According to advocates, the Clinton Administration has made great strides in improving and accelerating the FDA's drug approval process. The next goal of the pharmaceutical research agenda should be to include consumer advocates in the decision-making process.

Gene expression-based chemical genomics identifies potential therapeutic drugs in hepatocellular carcinoma.

PubMed

Chen, Ming-Huang; Yang, Wu-Lung R; Lin, Kuan-Ting; Liu, Chia-Hung; Liu, Yu-Wen; Huang, Kai-Wen; Chang, Peter Mu-Hsin; Lai, Jin-Mei; Hsu, Chun-Nan; Chao, Kun-Mao; Kao, Cheng-Yan; Huang, Chi-Ying F

2011-01-01

Hepatocellular carcinoma (HCC) is an aggressive tumor with a poor prognosis. Currently, only sorafenib is approved by the FDA for advanced HCC treatment; therefore, there is an urgent need to discover candidate therapeutic drugs for HCC. We hypothesized that if a drug signature could reverse, at least in part, the gene expression signature of HCC, it might have the potential to inhibit HCC-related pathways and thereby treat HCC. To test this hypothesis, we first built an integrative platform, the "Encyclopedia of Hepatocellular Carcinoma genes Online 2", dubbed EHCO2, to systematically collect, organize and compare the publicly available data from HCC studies. The resulting collection includes a total of 4,020 genes. To systematically query the Connectivity Map (CMap), which includes 6,100 drug-mediated expression profiles, we further designed various gene signature selection and enrichment methods, including a randomization technique, majority vote, and clique analysis. Subsequently, 28 out of 50 prioritized drugs, including tanespimycin, trichostatin A, thioguanosine, and several anti-psychotic drugs with anti-tumor activities, were validated via MTT cell viability assays and clonogenic assays in HCC cell lines. To accelerate their future clinical use, possibly through drug-repurposing, we selected two well-established drugs to test in mice, chlorpromazine and trifluoperazine. Both drugs inhibited orthotopic liver tumor growth. In conclusion, we successfully discovered and validated existing drugs for potential HCC therapeutic use with the pipeline of Connectivity Map analysis and lab verification, thereby suggesting the usefulness of this procedure to accelerate drug repurposing for HCC treatment.

Using Metabolomics to Investigate Biomarkers of Drug Addiction.

PubMed

Ghanbari, Reza; Sumner, Susan

2018-02-01

Drug addiction has been associated with an increased risk for cancer, psychological complications, heart, liver, and lung disease, as well as infection. While genes have been identified that can mark individuals at risk for substance abuse, the initiation step of addiction is attributed to persistent metabolic disruptions occurring following the first instance of narcotic drug use. Advances in analytical technologies can enable the detection of thousands of signals in body fluids and excreta that can be used to define biochemical profiles of addiction. Today, these approaches hold promise for determining how exposure to drugs, in the absence or presence of other environmentally relevant factors, can impact human metabolism. We posit that these can lead to candidate biomarkers of drug dependence, treatment, withdrawal, or relapse. Copyright © 2017. Published by Elsevier Ltd.

Halogen-Enriched Fragment Libraries as Leads for Drug Rescue of Mutant p53

PubMed Central

2012-01-01

The destabilizing p53 cancer mutation Y220C creates a druggable surface crevice. We developed a strategy exploiting halogen bonding for lead discovery to stabilize the mutant with small molecules. We designed halogen-enriched fragment libraries (HEFLibs) as starting points to complement classical approaches. From screening of HEFLibs and subsequent structure-guided design, we developed substituted 2-(aminomethyl)-4-ethynyl-6-iodophenols as p53-Y220C stabilizers. Crystal structures of their complexes highlight two key features: (i) a central scaffold with a robust binding mode anchored by halogen bonding of an iodine with a main-chain carbonyl and (ii) an acetylene linker, enabling the targeting of an additional subsite in the crevice. The best binders showed induction of apoptosis in a human cancer cell line with homozygous Y220C mutation. Our structural and biophysical data suggest a more widespread applicability of HEFLibs in drug discovery. PMID:22439615

21 CFR 189.240 - Lead solders.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 3 2014-04-01 2014-04-01 false Lead solders. 189.240 Section 189.240 Food and...-Contact Surfaces § 189.240 Lead solders. (a) Lead solders are alloys of metals that include lead and are used in the construction of metal food cans. (b) Food packaged in any container that makes use of lead...

GPCR homomers and heteromers: a better choice as targets for drug development than GPCR monomers?

PubMed

Casadó, Vicent; Cortés, Antoni; Mallol, Josefa; Pérez-Capote, Kamil; Ferré, Sergi; Lluis, Carmen; Franco, Rafael; Canela, Enric I

2009-11-01

G protein-coupled receptors (GPCR) are targeted by many therapeutic drugs marketed to fight against a variety of diseases. Selection of novel lead compounds are based on pharmacological parameters obtained assuming that GPCR are monomers. However, many GPCR are expressed as dimers/oligomers. Therefore, drug development may consider GPCR as homo- and hetero-oligomers. A two-state dimer receptor model is now available to understand GPCR operation and to interpret data obtained from drugs interacting with dimers, and even from mixtures of monomers and dimers. Heteromers are distinct entities and therefore a given drug is expected to have different affinities and different efficacies depending on the heteromer. All these concepts would lead to broaden the therapeutic potential of drugs targeting GPCRs, including receptor heteromer-selective drugs with a lower incidence of side effects, or to identify novel pharmacological profiles using cell models expressing receptor heteromers.

"Drug" Discovery with the Help of Organic Chemistry.

PubMed

Itoh, Yukihiro; Suzuki, Takayoshi

2017-01-01

The first step in "drug" discovery is to find compounds binding to a potential drug target. In modern medicinal chemistry, the screening of a chemical library, structure-based drug design, and ligand-based drug design, or a combination of these methods, are generally used for identifying the desired compounds. However, they do not necessarily lead to success and there is no infallible method for drug discovery. Therefore, it is important to explore medicinal chemistry based on not only the conventional methods but also new ideas. So far, we have found various compounds as drug candidates. In these studies, some strategies based on organic chemistry have allowed us to find drug candidates, through 1) construction of a focused library using organic reactions and 2) rational design of enzyme inhibitors based on chemical reactions catalyzed by the target enzyme. Medicinal chemistry based on organic chemical reactions could be expected to supplement the conventional methods. In this review, we present drug discovery with the help of organic chemistry showing examples of our explorative studies on histone deacetylase inhibitors and lysine-specific demethylase 1 inhibitors.

Identifying and Solving Lead Issues from Water Systems with Materials/Device Replacement in Schools and other Buildings - slides

EPA Science Inventory

Identifying and assessing lead contamination and exposure potential in single-family residences is difficult enough, but doing the same kind of assessment and remediation in buildings, schools, and day care centers is even more challenging. It is of particular importance because ...

EMUDRA: Ensemble of Multiple Drug Repositioning Approaches to Improve Prediction Accuracy.

PubMed

Zhou, Xianxiao; Wang, Minghui; Katsyv, Igor; Irie, Hanna; Zhang, Bin

2018-04-24

Availability of large-scale genomic, epigenetic and proteomic data in complex diseases makes it possible to objectively and comprehensively identify therapeutic targets that can lead to new therapies. The Connectivity Map has been widely used to explore novel indications of existing drugs. However, the prediction accuracy of the existing methods, such as Kolmogorov-Smirnov statistic remains low. Here we present a novel high-performance drug repositioning approach that improves over the state-of-the-art methods. We first designed an expression weighted cosine method (EWCos) to minimize the influence of the uninformative expression changes and then developed an ensemble approach termed EMUDRA (Ensemble of Multiple Drug Repositioning Approaches) to integrate EWCos and three existing state-of-the-art methods. EMUDRA significantly outperformed individual drug repositioning methods when applied to simulated and independent evaluation datasets. We predicted using EMUDRA and experimentally validated an antibiotic rifabutin as an inhibitor of cell growth in triple negative breast cancer. EMUDRA can identify drugs that more effectively target disease gene signatures and will thus be a useful tool for identifying novel therapies for complex diseases and predicting new indications for existing drugs. The EMUDRA R package is available at doi:10.7303/syn11510888. bin.zhang@mssm.edu or zhangb@hotmail.com. Supplementary data are available at Bioinformatics online.

A Practical Bayesian Design to Identify the Maximum Tolerated Dose Contour for Drug Combination Trials

PubMed Central

Zhang, Liangcai; Yuan, Ying

2016-01-01

Drug combination therapy has become the mainstream approach to cancer treatment. One fundamental feature that makes combination trials different from single-agent trials is the existence of the maximum tolerated dose (MTD) contour, i.e., multiple MTDs. As a result, unlike single-agent phase I trials, which aim to find a single MTD, it is often of interest to find the MTD contour for combination trials. We propose a new dose-finding design, the waterfall design, to find the MTD contour for drug combination trials. Taking the divide-and-conquer strategy, the waterfall design divides the task of finding the MTD contour into a sequence of one-dimensional dose-finding processes, known as subtrials. The subtrials are conducted sequentially in a certain order, such that the results of each subtrial will be used to inform the design of subsequent subtrials. Such information borrowing allows the waterfall design to explore the two-dimensional dose space efficiently using a limited sample size, and decreases the chance of overdosing and underdosing patients. To accommodate the consideration that doses on the MTD contour may have very different efficacy or synergistic effects due to drug-drug interaction, we further extend our approach to a phase I/II design with the goal of finding the MTD with the highest efficacy. Simulation studies show that the waterfall design is safer and has higher probability of identifying the true MTD contour than some existing designs. The R package “BOIN” to implement the waterfall design is freely available from CRAN. PMID:27580928

Epigenetic Drug Repositioning for Alzheimer's Disease Based on Epigenetic Targets in Human Interactome.

PubMed

Chatterjee, Paulami; Roy, Debjani; Rathi, Nitin

2018-01-01

Epigenetics has emerged as an important field in drug discovery. Alzheimer's disease (AD), the leading neurodegenerative disorder throughout the world, is shown to have an epigenetic basis. Currently, there are very few effective epigenetic drugs available for AD. In this work, for the first time we have proposed 14 AD repositioning epigenetic drugs and identified their targets from extensive human interactome. Interacting partners of the AD epigenetic proteins were identified from the extensive human interactome to construct Epigenetic Protein-Protein Interaction Network (EP-PPIN). Epigenetic Drug-Target Network (EP-DTN) was constructed with the drugs associated with the proteins of EP-PPIN. Regulation of non-coding RNAs associated with the target proteins of these drugs was also studied. AD related target proteins, epigenetic targets, enriched pathways, and functional categories of the proposed repositioning drugs were also studied. The proposed 14 AD epigenetic repositioning drugs have overlapping targets and miRs with known AD epigenetic targets and miRs. Furthermore, several shared functional categories and enriched pathways were obtained for these drugs with FDA approved epigenetic drugs and known AD drugs. The findings of our work might provide insight into future AD epigenetic-therapeutics.

GEAR: A database of Genomic Elements Associated with drug Resistance.

PubMed

Wang, Yin-Ying; Chen, Wei-Hua; Xiao, Pei-Pei; Xie, Wen-Bin; Luo, Qibin; Bork, Peer; Zhao, Xing-Ming

2017-03-15

Drug resistance is becoming a serious problem that leads to the failure of standard treatments, which is generally developed because of genetic mutations of certain molecules. Here, we present GEAR (A database of Genomic Elements Associated with drug Resistance) that aims to provide comprehensive information about genomic elements (including genes, single-nucleotide polymorphisms and microRNAs) that are responsible for drug resistance. Right now, GEAR contains 1631 associations between 201 human drugs and 758 genes, 106 associations between 29 human drugs and 66 miRNAs, and 44 associations between 17 human drugs and 22 SNPs. These relationships are firstly extracted from primary literature with text mining and then manually curated. The drug resistome deposited in GEAR provides insights into the genetic factors underlying drug resistance. In addition, new indications and potential drug combinations can be identified based on the resistome. The GEAR database can be freely accessed through http://gear.comp-sysbio.org.

GEAR: A database of Genomic Elements Associated with drug Resistance

PubMed Central

Wang, Yin-Ying; Chen, Wei-Hua; Xiao, Pei-Pei; Xie, Wen-Bin; Luo, Qibin; Bork, Peer; Zhao, Xing-Ming

2017-01-01

Drug resistance is becoming a serious problem that leads to the failure of standard treatments, which is generally developed because of genetic mutations of certain molecules. Here, we present GEAR (A database of Genomic Elements Associated with drug Resistance) that aims to provide comprehensive information about genomic elements (including genes, single-nucleotide polymorphisms and microRNAs) that are responsible for drug resistance. Right now, GEAR contains 1631 associations between 201 human drugs and 758 genes, 106 associations between 29 human drugs and 66 miRNAs, and 44 associations between 17 human drugs and 22 SNPs. These relationships are firstly extracted from primary literature with text mining and then manually curated. The drug resistome deposited in GEAR provides insights into the genetic factors underlying drug resistance. In addition, new indications and potential drug combinations can be identified based on the resistome. The GEAR database can be freely accessed through http://gear.comp-sysbio.org. PMID:28294141

Herb-drug, food-drug, nutrient-drug, and drug-drug interactions: mechanisms involved and their medical implications.

PubMed

Sørensen, Janina Maria

2002-06-01

Adverse drug reactions (ADRs) and iatrogenic diseases have been identified as significant factors responsible for patient morbidity and mortality. Significant studies on drug metabolism in humans have been published during the last few years, offering a deeper comprehension of the mechanisms underlying adverse drug reactions and interactions. More understanding of these mechanisms, and of recent advances in laboratory technology, can help to evaluate potential drug interactions when drugs are prescribed concurrently. Increasing knowledge of interindividual variation in drug breakdown capacity and recent findings concerning the influence of environment, diet, nutrients, and herbal products can be used to reduce ADRs and iatrogenic diseases. Reviewed data suggest that drug treatment should be increasingly custom tailored to suit the individual patient and that appropriately co-prescribed diet and herbal remedies, could increase drug efficacy and lessen drug toxicity. This review focuses mainly on recently published research material. The cytochrome p450 enzymes, their role in metabolism, and their mechanisms of action are reviewed, and their role in drug-drug interactions are discussed. Drug-food and drug-herb interactions have garnered attention. Interdisciplinary communication among medical herbalists, medical doctors, and dietetic experts needs to be improved and encouraged. Internet resources for obtaining current information regarding drug-drug, drug-herb, and drug-nutrient interactions are provided.

Contextualization of drug-mediator relations using evidence networks.

PubMed

Tran, Hai Joey; Speyer, Gil; Kiefer, Jeff; Kim, Seungchan

2017-05-31

Genomic analysis of drug response can provide unique insights into therapies that can be used to match the "right drug to the right patient." However, the process of discovering such therapeutic insights using genomic data is not straightforward and represents an area of active investigation. EDDY (Evaluation of Differential DependencY), a statistical test to detect differential statistical dependencies, is one method that leverages genomic data to identify differential genetic dependencies. EDDY has been used in conjunction with the Cancer Therapeutics Response Portal (CTRP), a dataset with drug-response measurements for more than 400 small molecules, and RNAseq data of cell lines in the Cancer Cell Line Encyclopedia (CCLE) to find potential drug-mediator pairs. Mediators were identified as genes that showed significant change in genetic statistical dependencies within annotated pathways between drug sensitive and drug non-sensitive cell lines, and the results are presented as a public web-portal (EDDY-CTRP). However, the interpretability of drug-mediator pairs currently hinders further exploration of these potentially valuable results. In this study, we address this challenge by constructing evidence networks built with protein and drug interactions from the STITCH and STRING interaction databases. STITCH and STRING are sister databases that catalog known and predicted drug-protein interactions and protein-protein interactions, respectively. Using these two databases, we have developed a method to construct evidence networks to "explain" the relation between a drug and a mediator.  RESULTS: We applied this approach to drug-mediator relations discovered in EDDY-CTRP analysis and identified evidence networks for ~70% of drug-mediator pairs where most mediators were not known direct targets for the drug. Constructed evidence networks enable researchers to contextualize the drug-mediator pair with current research and knowledge. Using evidence networks, we were

Bacterial inactivation of the anticancer drug doxorubicin.

PubMed

Westman, Erin L; Canova, Marc J; Radhi, Inas J; Koteva, Kalinka; Kireeva, Inga; Waglechner, Nicholas; Wright, Gerard D

2012-10-26

Microbes are exposed to compounds produced by members of their ecological niche, including molecules with antibiotic or antineoplastic activities. As a result, even bacteria that do not produce such compounds can harbor the genetic machinery to inactivate or degrade these molecules. Here, we investigated environmental actinomycetes for their ability to inactivate doxorubicin, an aminoglycosylated anthracycline anticancer drug. One strain, Streptomyces WAC04685, inactivates doxorubicin via a deglycosylation mechanism. Activity-based purification of the enzymes responsible for drug inactivation identified the NADH dehydrogenase component of respiratory electron transport complex I, which was confirmed by gene inactivation studies. A mechanism where reduction of the quinone ring of the anthracycline by NADH dehydrogenase leads to deglycosylation is proposed. This work adds anticancer drug inactivation to the enzymatic inactivation portfolio of actinomycetes and offers possibilities for novel applications in drug detoxification. Copyright © 2012 Elsevier Ltd. All rights reserved.

New Antimicrobial Approaches: Reuse of Old Drugs.

PubMed

Savoia, Dianella

2016-01-01

The global situation of antibiotic resistance and the reduction of investments in antibiotics research by the pharmaceutical industry suggest the need for specific cost-effective approaches in order to identify drugs for the therapy of many microbial infections. Among the viable alternative anti-infective compounds, drug repurposing, i.e. to find new uses for previously approved medicines, revealed some encouraging in vitro and in vivo results. In this article the reader has a panoramic view of the updated references on the strategies encountered during the repositioning process. New findings are reported about the anti-microbial efficacy of antipsychotic, cardiovascular, anti-inflammatory and anti-neoplastic drugs. This approach may enhance the portfolio of pharmaceutical companies reducing the need for pharmacokinetic and toxicity studies; the development of new uses of old drugs for different infectious diseases, leading to better health for patients, also in poor, tropical countries, appears to be having better results.

Systemic analysis of genome-wide expression profiles identified potential therapeutic targets of demethylation drugs for glioblastoma.

PubMed

Ning, Tongbo; Cui, Hao; Sun, Feng; Zou, Jidian

2017-09-05

Glioblastoma represents one of the most aggressive malignant brain tumors with high morbidity and motility. Demethylation drugs have been developed for its treatment with little efficacy has been observed. The purpose of this study was to screen therapeutic targets of demethylation drugs or bioactive molecules for glioblastoma through systemic bioinformatics analysis. We firstly downloaded genome-wide expression profiles from the Gene Expression Omnibus (GEO) and conducted the primary analysis through R software, mainly including preprocessing of raw microarray data, transformation between probe ID and gene symbol and identification of differential expression genes (DEGs). Secondly, functional enrichment analysis was conducted via the Database for Annotation, Visualization and Integrated Discovery (DAVID) to explore biological processes involved in the development of glioblastoma. Thirdly, we constructed protein-protein interaction (PPI) network of interested genes and conducted cross analysis for multi datasets to obtain potential therapeutic targets for glioblastoma. Finally, we further confirmed the therapeutic targets through real-time RT-PCR. As a result, biological processes that related to cancer development, amino metabolism, immune response and etc. were found to be significantly enriched in genes that differential expression in glioblastoma and regulated by 5'aza-dC. Besides, network and cross analysis identified ACAT2, UFC1 and CYB5R1 as novel therapeutic targets of demethylation drugs which also confirmed by real time RT-PCR. In conclusions, our study identified several biological processes and genes that involved in the development of glioblastoma and regulated by 5'aza-dC, which would be helpful for the treatment of glioblastoma. Copyright © 2017 Elsevier B.V. All rights reserved.

[Do pediatricians identify adverse drug reactions even when they do not report them?

PubMed

Morales-Ríos, Olga; Jasso-Gutiérrez, Luis; Garduño-Espinosa, Juan; Olivar-López, Víctor; Muñoz-Hernández, Onofre

Spontaneous notification depends on the ability of pediatricians to identify adverse drug reactions (ADRs) along with their habit of reporting these incidents. During the years 2008 and 2009, the frequency of reports of ADRs to the Electronic Program of Pharmacovigilance (SISFAR) in the Hospital Infantil of Mexico Federico Gomez (HIMFG) was low (0.44% and 0.20%, respectively). Because of the above, the ability of pediatricians from the Emergency Department (ED) to identify ADRs using the clinical chart review was evaluated in 2010 in this study. A descriptive, observational, cross-sectional retrospective study was conducted in the ED from March 1 to August 31. ADRs were classified and quantified as "ADRs identified by pediatricians" when there was evidence in the clinical chart that pediatricians associated a clinical sign, symptom and laboratory value with an ADR. The numbers of notifications reported in SISFAR were quantified. Descriptive analysis was done using SPSS v.18. Considering patients who were admitted to the ED, the frequency of ADRs was 21.8%. The frequency of ADRs identified by physicians in clinical charts was 86%. The pharmacist detected 14% of ADRs. The frequency of ADRs reported by physicians was 6.1%. Although identification of ADRs in the clinical charts by pediatricians was high, it is possible that some ADRs were undetected. Because underreporting was very high, it is necessary to take actions to improve the reporting process. Copyright © 2015. Publicado por Masson Doyma México S.A.

A Prospective Method to Guide Small Molecule Drug Design

ERIC Educational Resources Information Center

Johnson, Alan T.

2015-01-01

At present, small molecule drug design follows a retrospective path when considering what analogs are to be made around a current hit or lead molecule with the focus often on identifying a compound with higher intrinsic potency. What this approach overlooks is the simultaneous need to also improve the physicochemical (PC) and pharmacokinetic (PK)…

Preventing, Identifying, and Treating Prescription Drug Misuse Among Active-Duty Service Members

PubMed Central

Pacula, Rosalie Liccardo; Hunter, Sarah B.; Ober, Allison J.; Osilla, Karen Chan; Vardavas, Raffaele; Blanchard, Janice C.; DeVries, David; Drabo, Emmanuel F.; Leuschner, Kristin J.; Stewart, Warren; Walters, Jennifer

2017-01-01

Abstract Prescription drug misuse (PDM) is of critical concern for the military because of its potential impact on military readiness, the health and well-being of military personnel, and associated health care costs. The purpose of this study is to summarize insights gleaned from a series of activities that the RAND Corporation undertook for the Deputy Assistant Secretary of Defense for Readiness to address this important health and military readiness issue. The authors completed a review of U.S. Department of Defense policies and a comprehensive literature review of clinical guidelines and the empirical literature on the prevention and treatment of PDM and conducted individual face-to-face interviews with 66 health and behavioral health care providers at nine medical treatment facilities across three regions within the contiguous United States to identify best practices in the prevention, identification, and treatment of PDM and the extent to which those practices are known and followed. The study also presents the framework of an analytic tool that, once informed by data available to the military but not available to the authors, can assist the military in predicting future trends in PDM based on current demographics of active-duty service members and rates of injury and prescribing of prescription drugs. The findings from this work led the authors to formulate a set of key insights that they believe might improve the rapid identification and treatment of service members dealing with PDM, thereby improving future force readiness. PMID:29057158

Systematic drug safety evaluation based on public genomic expression (Connectivity Map) data: Myocardial and infectious adverse reactions as application cases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Kejian, E-mail: kejian.wang.bio@gmail.com; Weng, Zuquan; Sun, Liya

Adverse drug reaction (ADR) is of great importance to both regulatory agencies and the pharmaceutical industry. Various techniques, such as quantitative structure–activity relationship (QSAR) and animal toxicology, are widely used to identify potential risks during the preclinical stage of drug development. Despite these efforts, drugs with safety liabilities can still pass through safety checkpoints and enter the market. This situation raises the concern that conventional chemical structure analysis and phenotypic screening are not sufficient to avoid all clinical adverse events. Genomic expression data following in vitro drug treatments characterize drug actions and thus have become widely used in drug repositioning. Inmore » the present study, we explored prediction of ADRs based on the drug-induced gene-expression profiles from cultured human cells in the Connectivity Map (CMap) database. The results showed that drugs inducing comparable ADRs generally lead to similar CMap expression profiles. Based on such ADR-gene expression association, we established prediction models for various ADRs, including severe myocardial and infectious events. Drugs with FDA boxed warnings of safety liability were effectively identified. We therefore suggest that drug-induced gene expression change, in combination with effective computational methods, may provide a new dimension of information to facilitate systematic drug safety evaluation. - Highlights: • Drugs causing common toxicity lead to similar in vitro gene expression changes. • We built a model to predict drug toxicity with drug-specific expression profiles. • Drugs with FDA black box warnings were effectively identified by our model. • In vitro assay can detect severe toxicity in the early stage of drug development.« less

Lead generation and examples opinion regarding how to follow up hits.

PubMed

Orita, Masaya; Ohno, Kazuki; Warizaya, Masaichi; Amano, Yasushi; Niimi, Tatsuya

2011-01-01

In fragment-based drug discovery (FBDD), not only identifying the starting fragment hit to be developed but also generating a drug lead from that starting fragment hit is important. Converting fragment hits to leads is generally similar to a high-throughput screening (HTS) hits-to-leads approach in that properties associated with activity for a target protein, such as selectivity against other targets and absorption, distribution, metabolism, excretion, and toxicity (ADME/Tox), and physicochemical properties should be taken into account. However, enhancing the potency of the fragment hit is a key requirement in FBDD, unlike HTS, because initial fragment hits are generally weak. This enhancement is presently achieved by adding additional chemical groups which bind to additional parts of the target protein or by joining or combining two or more hit fragments; however, strategies for effecting greater improvements in effective activity are needed. X-ray analysis is a key technology attractive for converting fragments to drug leads. This method makes it clear whether a fragment hit can act as an anchor and provides insight regarding introduction of functional groups to improve fragment activity. Data on follow-up chemical synthesis of fragment hits has allowed for the differentiation of four different strategies: fragment optimization, fragment linking, fragment self-assembly, and fragment evolution. Here, we discuss our opinion regarding how to follow up on fragment hits, with a focus on the importance of fragment hits as an anchor moiety to so-called hot spots in the target protein using crystallographic data. Copyright © 2011 Elsevier Inc. All rights reserved.

Identifying kinase dependency in cancer cells by integrating high-throughput drug screening and kinase inhibition data.

PubMed

Ryall, Karen A; Shin, Jimin; Yoo, Minjae; Hinz, Trista K; Kim, Jihye; Kang, Jaewoo; Heasley, Lynn E; Tan, Aik Choon

2015-12-01

Targeted kinase inhibitors have dramatically improved cancer treatment, but kinase dependency for an individual patient or cancer cell can be challenging to predict. Kinase dependency does not always correspond with gene expression and mutation status. High-throughput drug screens are powerful tools for determining kinase dependency, but drug polypharmacology can make results difficult to interpret. We developed Kinase Addiction Ranker (KAR), an algorithm that integrates high-throughput drug screening data, comprehensive kinase inhibition data and gene expression profiles to identify kinase dependency in cancer cells. We applied KAR to predict kinase dependency of 21 lung cancer cell lines and 151 leukemia patient samples using published datasets. We experimentally validated KAR predictions of FGFR and MTOR dependence in lung cancer cell line H1581, showing synergistic reduction in proliferation after combining ponatinib and AZD8055. KAR can be downloaded as a Python function or a MATLAB script along with example inputs and outputs at: http://tanlab.ucdenver.edu/KAR/. aikchoon.tan@ucdenver.edu. Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Affordable orphan drugs: a role for not-for-profit organizations.

PubMed

Davies, Elin H; Fulton, Emma; Brook, Daniel; Hughes, Dyfrig A

2017-07-01

The success of the Regulation on Orphan Medicinal Products in the European Union is evidenced by the 127 orphan drugs that have had market authorization since 2000. However, the incentives aimed at stimulating research and development have had the unintended consequence of increasing drug cost, resulting in many orphan drugs not being cost-effective. Orphan drugs command an increasing share of the pharmaceutical market and account for a disproportionate amount of healthcare expenditure. Orphan drug ownership by socially motivated, not-for-profit organizations may facilitate access to more affordable orphan drugs, for the benefit of patients and healthcare systems alike. This study aims to describe opportunities for such organizations to become orphan drug Market Authorization Holders. We reviewed data on the ownership of EMA designated and approved orphan drugs, identified funding opportunities and business models for not-for-profit organizations, and summarised relevant legal and policy documents concerning intellectual property rights and drug regulation. Using repurposed drugs as a paradigm, this narrative review navigates the regulatory hurdles, describes the legal context and identifies funding opportunities, in a bid to facilitate and encourage not-for-profit organizations to lead on the development of affordable orphan drugs. Although the regulatory steps required to obtain an MA for an orphan drug are numerous and challenging, they are not insurmountable and can be achieved by not-for-profit organizations that are socially motivated to reduce the costs of orphan drugs to the payers of healthcare. Opportunities for orphan drug development resulting in affordable products lie mainly with repurposed drugs. © 2017 The British Pharmacological Society.

21 CFR 189.240 - Lead solders.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 3 2013-04-01 2013-04-01 false Lead solders. 189.240 Section 189.240 Food and... Addition to Human Food Through Food-Contact Surfaces § 189.240 Lead solders. (a) Lead solders are alloys of metals that include lead and are used in the construction of metal food cans. (b) Food packaged in any...

21 CFR 189.240 - Lead solders.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 3 2011-04-01 2011-04-01 false Lead solders. 189.240 Section 189.240 Food and... Addition to Human Food Through Food-Contact Surfaces § 189.240 Lead solders. (a) Lead solders are alloys of metals that include lead and are used in the construction of metal food cans. (b) Food packaged in any...

21 CFR 189.240 - Lead solders.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 3 2012-04-01 2012-04-01 false Lead solders. 189.240 Section 189.240 Food and... Addition to Human Food Through Food-Contact Surfaces § 189.240 Lead solders. (a) Lead solders are alloys of metals that include lead and are used in the construction of metal food cans. (b) Food packaged in any...

21 CFR 189.240 - Lead solders.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 3 2010-04-01 2009-04-01 true Lead solders. 189.240 Section 189.240 Food and... Addition to Human Food Through Food-Contact Surfaces § 189.240 Lead solders. (a) Lead solders are alloys of metals that include lead and are used in the construction of metal food cans. (b) Food packaged in any...

A Chemoinformatics Approach to the Discovery of Lead-Like Molecules from Marine and Microbial Sources En Route to Antitumor and Antibiotic Drugs

PubMed Central

Pereira, Florbela; Latino, Diogo A. R. S.; Gaudêncio, Susana P.

2014-01-01

The comprehensive information of small molecules and their biological activities in the PubChem database allows chemoinformatic researchers to access and make use of large-scale biological activity data to improve the precision of drug profiling. A Quantitative Structure–Activity Relationship approach, for classification, was used for the prediction of active/inactive compounds relatively to overall biological activity, antitumor and antibiotic activities using a data set of 1804 compounds from PubChem. Using the best classification models for antibiotic and antitumor activities a data set of marine and microbial natural products from the AntiMarin database were screened—57 and 16 new lead compounds for antibiotic and antitumor drug design were proposed, respectively. All compounds proposed by our approach are classified as non-antibiotic and non-antitumor compounds in the AntiMarin database. Recently several of the lead-like compounds proposed by us were reported as being active in the literature. PMID:24473174

Di-hadron correlations with identified leading hadrons in 200 GeV Au + Au and d + Au collisions at STAR

NASA Astrophysics Data System (ADS)

Adamczyk, L.; Adkins, J. K.; Agakishiev, G.; Aggarwal, M. M.; Ahammed, Z.; Alekseev, I.; Aparin, A.; Arkhipkin, D.; Aschenauer, E. C.; Averichev, G. S.; Bai, X.; Bairathi, V.; Banerjee, A.; Bellwied, R.; Bhasin, A.; Bhati, A. K.; Bhattarai, P.; Bielcik, J.; Bielcikova, J.; Bland, L. C.; Bordyuzhin, I. G.; Bouchet, J.; Brandenburg, D.; Brandin, A. V.; Bunzarov, I.; Butterworth, J.; Caines, H.; Calderón de la Barca Sánchez, M.; Campbell, J. M.; Cebra, D.; Cervantes, M. C.; Chakaberia, I.; Chaloupka, P.; Chang, Z.; Chattopadhyay, S.; Chen, X.; Chen, J. H.; Cheng, J.; Cherney, M.; Christie, W.; Contin, G.; Crawford, H. J.; Das, S.; De Silva, L. C.; Debbe, R. R.; Dedovich, T. G.; Deng, J.; Derevschikov, A. A.; di Ruzza, B.; Didenko, L.; Dilks, C.; Dong, X.; Drachenberg, J. L.; Draper, J. E.; Du, C. M.; Dunkelberger, L. E.; Dunlop, J. C.; Efimov, L. G.; Engelage, J.; Eppley, G.; Esha, R.; Evdokimov, O.; Eyser, O.; Fatemi, R.; Fazio, S.; Federic, P.; Fedorisin, J.; Feng, Z.; Filip, P.; Fisyak, Y.; Flores, C. E.; Fulek, L.; Gagliardi, C. A.; Garand, D.; Geurts, F.; Gibson, A.; Girard, M.; Greiner, L.; Grosnick, D.; Gunarathne, D. S.; Guo, Y.; Gupta, S.; Gupta, A.; Guryn, W.; Hamad, A.; Hamed, A.; Haque, R.; Harris, J. W.; He, L.; Heppelmann, S.; Heppelmann, S.; Hirsch, A.; Hoffmann, G. W.; Hofman, D. J.; Horvat, S.; Huang, T.; Huang, B.; Huang, H. Z.; Huang, X.; Huck, P.; Humanic, T. J.; Igo, G.; Jacobs, W. W.; Jang, H.; Jia, J.; Jiang, K.; Judd, E. G.; Kabana, S.; Kalinkin, D.; Kang, K.; Kauder, K.; Ke, H. W.; Keane, D.; Kechechyan, A.; Khan, Z. H.; Kikoła, D. P.; Kisiel, A.; Kochenda, L.; Koetke, D. D.; Kosarzewski, L. K.; Kraishan, A. F.; Kravtsov, P.; Krueger, K.; Kumar, L.; Lamont, M. A. C.; Landgraf, J. M.; Landry, K. D.; Lauret, J.; Lebedev, A.; Lednicky, R.; Lee, J. H.; Li, X.; Li, W.; Li, Z. M.; Li, Y.; Li, C.; Li, X.; Lisa, M. A.; Liu, F.; Ljubicic, T.; Llope, W. J.; Lomnitz, M.; Longacre, R. S.; Luo, X.; Ma, G. L.; Ma, Y. G.; Ma, R.; Ma, L.; Magdy, N.; Majka, R.; Manion, A.; Margetis, S.; Markert, C.; Masui, H.; Matis, H. S.; McDonald, D.; Meehan, K.; Mei, J. C.; Minaev, N. G.; Mioduszewski, S.; Mishra, D.; Mohanty, B.; Mondal, M. M.; Morozov, D. A.; Mustafa, M. K.; Nandi, B. K.; Nasim, Md.; Nayak, T. K.; Nigmatkulov, G.; Niida, T.; Nogach, L. V.; Noh, S. Y.; Novak, J.; Nurushev, S. B.; Odyniec, G.; Ogawa, A.; Oh, K.; Okorokov, V.; Olvitt, D.; Page, B. S.; Pak, R.; Pan, Y. X.; Pandit, Y.; Panebratsev, Y.; Pawlik, B.; Pei, H.; Perkins, C.; Peterson, A.; Pile, P.; Pluta, J.; Poniatowska, K.; Porter, J.; Posik, M.; Poskanzer, A. M.; Pruthi, N. K.; Putschke, J.; Qiu, H.; Quintero, A.; Ramachandran, S.; Raniwala, R.; Raniwala, S.; Ray, R. L.; Ritter, H. G.; Roberts, J. B.; Rogachevskiy, O. V.; Romero, J. L.; Roy, A.; Ruan, L.; Rusnak, J.; Rusnakova, O.; Sahoo, N. R.; Sahu, P. K.; Sakrejda, I.; Salur, S.; Sandweiss, J.; Sarkar, A.; Schambach, J.; Scharenberg, R. P.; Schmah, A. M.; Schmidke, W. B.; Schmitz, N.; Seger, J.; Seyboth, P.; Shah, N.; Shahaliev, E.; Shanmuganathan, P. V.; Shao, M.; Sharma, B.; Sharma, M. K.; Shen, W. Q.; Shi, S. S.; Shou, Q. Y.; Sichtermann, E. P.; Sikora, R.; Simko, M.; Singha, S.; Skoby, M. J.; Smirnov, N.; Smirnov, D.; Song, L.; Sorensen, P.; Spinka, H. M.; Srivastava, B.; Stanislaus, T. D. S.; Stepanov, M.; Strikhanov, M.; Stringfellow, B.; Sumbera, M.; Summa, B.; Sun, Y.; Sun, Z.; Sun, X. M.; Sun, X.; Surrow, B.; Svirida, D. N.; Szelezniak, M. A.; Tang, A. H.; Tang, Z.; Tarnowsky, T.; Tawfik, A.; Thomas, J. H.; Timmins, A. R.; Tlusty, D.; Todoroki, T.; Tokarev, M.; Trentalange, S.; Tribble, R. E.; Tribedy, P.; Tripathy, S. K.; Tsai, O. D.; Ullrich, T.; Underwood, D. G.; Upsal, I.; Van Buren, G.; van Nieuwenhuizen, G.; Vandenbroucke, M.; Varma, R.; Vasiliev, A. N.; Vertesi, R.; Videbæk, F.; Viyogi, Y. P.; Vokal, S.; Voloshin, S. A.; Vossen, A.; Wang, J. S.; Wang, F.; Wang, H.; Wang, G.; Wang, Y.; Wang, Y.; Webb, G.; Webb, J. C.; Wen, L.; Westfall, G. D.; Wieman, H.; Wissink, S. W.; Witt, R.; Wu, Y. F.; Wu; Xiao, Z. G.; Xie, W.; Xin, K.; Xu, H.; Xu, Z.; Xu, Q. H.; Xu, Y. F.; Xu, N.; Yang, S.; Yang, Y.; Yang, Q.; Yang, Y.; Yang, C.; Yang, Y.; Ye, Z.; Ye, Z.; Yepes, P.; Yi, L.; Yip, K.; Yoo, I.-K.; Yu, N.; Zbroszczyk, H.; Zha, W.; Zhang, Y.; Zhang, Z.; Zhang, J. B.; Zhang, J.; Zhang, X. P.; Zhang, S.; Zhang, J.; Zhao, J.; Zhong, C.; Zhou, L.; Zhu, X.; Zoulkarneeva, Y.

2015-12-01

The STAR Collaboration presents for the first time two-dimensional di-hadron correlations with identified leading hadrons in 200 GeV central Au + Au and minimum-bias d + Au collisions to explore hadronization mechanisms in the quark gluon plasma. The enhancement of the jet-like yield for leading pions in Au + Au data with respect to the d + Au reference and the absence of such an enhancement for leading non-pions (protons and kaons) are discussed within the context of a quark recombination scenario. The correlated yield at large angles, specifically in the ridge region, is found to be significantly higher for leading non-pions than pions. The consistencies of the constituent quark scaling, azimuthal harmonic model and a mini-jet modification model description of the data are tested, providing further constraints on hadronization.

Identifying and assessing highly hazardous drugs within quality risk management programs.

PubMed

Sussman, Robert G; Schatz, Anthony R; Kimmel, Tracy A; Ader, Allan; Naumann, Bruce D; Weideman, Patricia A

2016-08-01

Historically, pharmaceutical industry regulatory guidelines have assigned certain active pharmaceutical ingredients (APIs) to various categories of concern, such as "cytotoxic", "hormones", and "steroids". These categories have been used to identify APIs requiring segregation or dedication in order to prevent cross-contamination and protect the quality and safety of drug products. Since these terms were never defined by regulatory authorities, and many novel pharmacological mechanisms challenge these categories, there is a recognized need to modify the historical use of these terms. The application of a risk-based approach using a health-based limit, such as an acceptable daily exposure (ADE), is more appropriate for the development of a Quality Risk Management Program (QRMP) than the use of categories of concern. The toxicological and pharmacological characteristics of these categories are discussed to help identify and prioritize compounds requiring special attention. Controlling airborne concentrations and the contamination of product contact surfaces in accordance with values derived from quantitative risk assessments can prevent adverse effects in workers and patients, regardless of specific categorical designations to which these APIs have been assigned. The authors acknowledge the movement away from placing compounds into categories and, while not yet universal, the importance of basing QRMPs on compound-specific ADEs and risk assessments. Based on the results of a risk assessment, segregation and dedication may also be required for some compounds to prevent cross contamination during manufacture of APIs. Copyright © 2016 Elsevier Inc. All rights reserved.

Drug withdrawal conceptualized as a stressor

PubMed Central

Chartoff, Elena H.; Carlezon, William A.

2015-01-01

Drug withdrawal is often conceptualized as an aversive state that motivates drug-seeking and drug-taking behaviors in humans. Stress is more difficult to define, but is also frequently associated with aversive states. Here we describe evidence for the simple theory that drug withdrawal is a stress-like state, on the basis of common effects on behavioral, neurochemical, and molecular endpoints. We also describe data suggesting a more complex relationship between drug withdrawal and stress. As one example, we will highlight evidence that, depending on drug class, components of withdrawal can produce effects that have characteristics consistent with mood elevation. In addition, some stressors can act as positive reinforcers, defined as having the ability to increase the probability of a behavior that produces it. As such, accumulating evidence supports the general principles of opponent process theory, whereby processes that have an affective valence are followed in time by an opponent process that has the opposite valence. Throughout, we identify gaps in knowledge and propose future directions for research. A better understanding of the similarities, differences, and overlaps between drug withdrawal and stress will lead to the development of improved treatments for addiction, as well as for a vast array of neuropsychiatric conditions that are triggered or exacerbated by stress. PMID:25083570

[Psychiatric polypharmacy: hazard through drug-drug-interaction and possibilities for prevention].

PubMed

Hahn, M; Braus, D F

2012-09-01

Psychiatric diseases and comorbidity have increased over the past years. Commonly used psychotropic drugs contain a high risk of drug interactions and adverse drug events (ADE). With a frequency of 10-12% psychotropic drugs are, among all pharmaceuticals, the most common cause of hospitalisation due to ADE. During a hospital stay the application of psychotropic drugs can also lead to adverse drug events--sometimes due to drug interactions. Currently, ADEs and drug interactions are the most frequent cause of death for in-patients (18% of all causes of death) with an overall mortality of 0.95%. As studies have shown, hospitals as well as insurers could save a considerable amount of resources by implementing a system with on-ward pharmacists, hereby reducing ADE and re-hospitalisation rates. In recent studies a large amount of current ADEs were rated as preventable. Patient impairment due to ADE is leading to an increase in liability cases with an expected 5% increase of compensation payments in 2011. To evaluate these ADE-related cases, a pharmaceutical assessment should be included in the expert trials, especially since a lack of awareness of medication errors is prevalent. When aiming towards a successful drug therapy, physicians must also consider that cheaper substances may often have an unfavourable drug interaction profile.

NLLSS: Predicting Synergistic Drug Combinations Based on Semi-supervised Learning

PubMed Central

Chen, Ming; Wang, Quanxin; Zhang, Lixin; Yan, Guiying

2016-01-01

Fungal infection has become one of the leading causes of hospital-acquired infections with high mortality rates. Furthermore, drug resistance is common for fungus-causing diseases. Synergistic drug combinations could provide an effective strategy to overcome drug resistance. Meanwhile, synergistic drug combinations can increase treatment efficacy and decrease drug dosage to avoid toxicity. Therefore, computational prediction of synergistic drug combinations for fungus-causing diseases becomes attractive. In this study, we proposed similar nature of drug combinations: principal drugs which obtain synergistic effect with similar adjuvant drugs are often similar and vice versa. Furthermore, we developed a novel algorithm termed Network-based Laplacian regularized Least Square Synergistic drug combination prediction (NLLSS) to predict potential synergistic drug combinations by integrating different kinds of information such as known synergistic drug combinations, drug-target interactions, and drug chemical structures. We applied NLLSS to predict antifungal synergistic drug combinations and showed that it achieved excellent performance both in terms of cross validation and independent prediction. Finally, we performed biological experiments for fungal pathogen Candida albicans to confirm 7 out of 13 predicted antifungal synergistic drug combinations. NLLSS provides an efficient strategy to identify potential synergistic antifungal combinations. PMID:27415801

Strategic incorporation of fluorine in the drug discovery of new-generation antitubercular agents targeting bacterial cell division protein FtsZ⋆

PubMed Central

Ojima, Iwao; Awasthi, Divya; Wei, Longfei; Haranahalli, Krupanandan

2016-01-01

This article presents an account of our research on the discovery and development of new-generation fluorine-containing antibacterial agents against drug-resistant tuberculosis, targeting FtsZ. FtsZ is an essential protein for bacterial cell division and a highly promising therapeutic target for antibacterial drug discovery. Through design, synthesis and semi-HTP screening of libraries of novel benzimidazoles, followed by SAR studies, we identified highly potent lead compounds. However, these lead compounds were found to lack sufficient metabolic and plasma stabilities. Accordingly, we have performed extensive study on the strategic incorporation of fluorine into lead compounds to improve pharmacological properties. This study has led to the development of highly efficacious fluorine-containing benzimidazoles as potential drug candidates. We have also performed computational docking analysis of these novel FtsZ inhibitors to identify their putative binding site. Based on the structural data and docking analysis, a plausible mode-of-action for this novel class of FtsZ inhibitors is proposed. PMID:28555087

Lead in rice: analysis of baseline lead levels in market and field collected rice grains.

PubMed

Norton, Gareth J; Williams, Paul N; Adomako, Eureka E; Price, Adam H; Zhu, Yongguan; Zhao, Fang-Jie; McGrath, Steve; Deacon, Claire M; Villada, Antia; Sommella, Alessia; Lu, Ying; Ming, Lei; De Silva, P Mangala C S; Brammer, Hugh; Dasgupta, Tapash; Islam, M Rafiqul; Meharg, Andrew A

2014-07-01

In a large scale survey of rice grains from markets (13 countries) and fields (6 countries), a total of 1578 rice grain samples were analysed for lead. From the market collected samples, only 0.6% of the samples exceeded the Chinese and EU limit of 0.2 μg g(-1) lead in rice (when excluding samples collected from known contaminated/mine impacted regions). When evaluating the rice grain samples against the Food and Drug Administration's (FDA) provisional total tolerable intake (PTTI) values for children and pregnant women, it was found that only people consuming large quantities of rice were at risk of exceeding the PTTI from rice alone. Furthermore, 6 field experiments were conducted to evaluate the proportion of the variation in lead concentration in rice grains due to genetics. A total of 4 of the 6 field experiments had significant differences between genotypes, but when the genotypes common across all six field sites were assessed, only 4% of the variation was explained by genotype, with 9.5% and 11% of the variation explained by the environment and genotype by environment interaction respectively. Further work is needed to identify the sources of lead contamination in rice, with detailed information obtained on the locations and environments where the rice is sampled, so that specific risk assessments can be performed. Copyright © 2014 Elsevier B.V. All rights reserved.

Drug abuse-related accidents leading to emergency department visits at two medical centers.

PubMed

Chen, Isaac Chun-Jen; Hung, Dong-Zong; Hsu, Chi-Ho; Wu, Ming-Ling; Deng, Jou-Fang; Chang, Chin-Yu; Shih, Hsin-Chin; Liu, Chen-Chi; Wang, Chien-Ying; Wen, Yi-Szu; Wu, Jackson Jer-Kan; Huang, Mu-Shun; Yang, Chen-Chang

2012-05-01

Drug abuse is becoming more prevalent in Taiwan, as evidenced by increasing reports of drug trafficking and drug abuse-related criminal activity, and the wide use of more contemporary illicit drugs. Consequently, drug abuse-related accidents are also expected to occur with greater frequency. However, no study has yet specifically evaluated the prevalence, pattern, and outcomes of drug abuse-related accidents among patients visiting emergency departments (EDs) in Taiwan. We conducted an ambidirectional study with patients who visited the EDs of Taipei Veterans General Hospital (TVGH) and China Medical University Hospital (CMUH) due to drug abuse-related accidents from January 2007 through September 2009. Information on the patients' baseline characteristics and clinical outcomes was collected and analyzed. During the study period, a total of 166 patients visited the EDs of one of the two study hospitals due to drug abuse-related accidents. This yielded a prevalence of drug abuse of 0.1% among all patients visiting the ED due to accident and/or trauma. Fifty-six out of the 166 patients visited the ED at TVGH, most patients being between 21 and 40 years old. Opioids (41.1%) were the drugs most commonly abused by the patients, followed by benzodiazepines (32.1%). More than two-thirds of the patients (n=38, 67.9%) required hospitalization, and three patients died (5.4%). In contrast, 110 patients with drug abuse-related accidents visited the ED at CMUH during the study period. Most of these subjects had abused benzodiazepines (69.1%), were between 21 and 40 years old, and were female. Fewer than one-fifth of the patients (n=19, 17.3%) required hospitalization, with no deaths reported. There were significant between-hospital differences in terms of patient gender, drugs of choice, injury mechanisms, method and time of the ED visit, triage levels, and need for hospitalization. Although the prevalence of drug abuse-related accidents was low, and only three patient deaths

Cathepsin B is a New Drug Target for Traumatic Brain Injury Therapeutics: Evidence for E64d as a Promising Lead Drug Candidate

PubMed Central

Hook, Gregory; Jacobsen, J. Steven; Grabstein, Kenneth; Kindy, Mark; Hook, Vivian

2015-01-01

There is currently no therapeutic drug treatment for traumatic brain injury (TBI) despite decades of experimental clinical trials. This may be because the mechanistic pathways for improving TBI outcomes have yet to be identified and exploited. As such, there remains a need to seek out new molecular targets and their drug candidates to find new treatments for TBI. This review presents supporting evidence for cathepsin B, a cysteine protease, as a potentially important drug target for TBI. Cathepsin B expression is greatly up-regulated in TBI animal models, as well as in trauma patients. Importantly, knockout of the cathepsin B gene in TBI mice results in substantial improvements of TBI-caused deficits in behavior, pathology, and biomarkers, as well as improvements in related injury models. During the process of TBI-induced injury, cathepsin B likely escapes the lysosome, its normal subcellular location, into the cytoplasm or extracellular matrix (ECM) where the unleashed proteolytic power causes destruction via necrotic, apoptotic, autophagic, and activated glia-induced cell death, together with ECM breakdown and inflammation. Significantly, chemical inhibitors of cathepsin B are effective for improving deficits in TBI and related injuries including ischemia, cerebral bleeding, cerebral aneurysm, edema, pain, infection, rheumatoid arthritis, epilepsy, Huntington’s disease, multiple sclerosis, and Alzheimer’s disease. The inhibitor E64d is unique among cathepsin B inhibitors in being the only compound to have demonstrated oral efficacy in a TBI model and prior safe use in man and as such it is an excellent tool compound for preclinical testing and clinical compound development. These data support the conclusion that drug development of cathepsin B inhibitors for TBI treatment should be accelerated. PMID:26388830

Early Probe and Drug Discovery in Academia: A Minireview.

PubMed

Roy, Anuradha

2018-02-09

Drug discovery encompasses processes ranging from target selection and validation to the selection of a development candidate. While comprehensive drug discovery work flows are implemented predominantly in the big pharma domain, early discovery focus in academia serves to identify probe molecules that can serve as tools to study targets or pathways. Despite differences in the ultimate goals of the private and academic sectors, the same basic principles define the best practices in early discovery research. A successful early discovery program is built on strong target definition and validation using a diverse set of biochemical and cell-based assays with functional relevance to the biological system being studied. The chemicals identified as hits undergo extensive scaffold optimization and are characterized for their target specificity and off-target effects in in vitro and in animal models. While the active compounds from screening campaigns pass through highly stringent chemical and Absorption, Distribution, Metabolism, and Excretion (ADME) filters for lead identification, the probe discovery involves limited medicinal chemistry optimization. The goal of probe discovery is identification of a compound with sub-µM activity and reasonable selectivity in the context of the target being studied. The compounds identified from probe discovery can also serve as starting scaffolds for lead optimization studies.

Drug discovery in tuberculosis. New drug targets and antimycobacterial agents.

PubMed

Campaniço, André; Moreira, Rui; Lopes, Francisca

2018-04-25

Tuberculosis (TB) remains a major health problem worldwide. The infectious agent, Mycobacterium tuberculosis, has a unique ability to survive within the host, alternating between active and latent disease states, and escaping the immune system defences. The extended duration of anti-TB regimens and the increasing prevalence of multidrug- (MDR) and extensively drug-resistant (XDR) M. tuberculosis strains have created an urgent need for new antibiotics active against drug-resistant organisms and that can shorten standard therapy. However, despite success in identifying active compounds through phenotypic screens, the conversion of hits into novel chemical series and ultimately into clinical candidates is hampered by the poor efficacy in eliminating M. tuberculosis within different host compartments, including macrophages, as well as a lack of knowledge about the specific target(s) inhibited and/or upregulated. The current status of anti-TB lead generation has much improved over the last decade, as exemplified by the recent approval of bedaquiline and delamanid to treat MDR-TB and XDR-TB. This review provides a critical analysis on the strategies used to progress hit compounds into viable lead candidates, and how emerging targets may play a role in TB drug discovery in the near future. Four new relevant targets are addressed: the enoyl-acyl carrier protein reductase, InhA; the transmembrane transport protein large, MmpL3; the decaprenylphospho-beta-d-ribofuranose 2-oxidase, DprE1; and the ubiquinol-cytochrome C reductase, QcrB. Validated hit compounds for each target are presented and explored, and the medicinal chemistry strategies to expand SAR around novel chemotypes analyzed. In addition, very recent emerging targets are also discussed. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

Drug membrane interaction and the importance for drug transport, distribution, accumulation, efficacy and resistance.

PubMed

Seydel, J K; Coats, E A; Cordes, H P; Wiese, M

1994-10-01

Some aspects of drug membrane interaction and its influence on drug transport, accumulation, efficacy and resistance have been discussed. The interactions manifest themselves macroscopically in changes in the physical and thermodynamic properties of "pure membranes" or bilayers. As various amounts of foreign molecules enter the membrane, in particular the main gel to liquid crystalline phase transition can be dramatically changed. This may change permeability, cell-fusion, cell resistance and may also lead to changes in conformation of the embedded receptor proteins. Furthermore, specific interactions with lipids may lead to drug accumulation in membranes and thus to much larger concentrations at the active site than present in the surrounding water phase. The lipid environment may also lead to changes in the preferred conformation of drug molecules. These events are directly related to drug efficacy. The determination of essential molecular criteria for the interaction could be used to design new and more selective therapeutics. This excursion in some aspects of drug membrane interaction underlines the importance of lipids and their interaction with drug molecules for our understanding of drug action, but this is not really a new thought but has been formulated in 1884 by THUDICUM: "Phospholipids are the centre, life and chemical soul of all bioplasm whatsoever, that of plants as well as of animals".

Prescription Drug Abuse

MedlinePlus

... what the doctor prescribed, it is called prescription drug abuse. It could be Taking a medicine that ... purpose, such as getting high Abusing some prescription drugs can lead to addiction. These include opioids, sedatives, ...

The First Negative Allosteric Modulator for Dopamine D2 and D3 Receptors, SB269652 May Lead to a New Generation of Antipsychotic Drugs.

PubMed

Rossi, Mario; Fasciani, Irene; Marampon, Francesco; Maggio, Roberto; Scarselli, Marco

2017-06-01

D 2 and D 3 dopamine receptors belong to the largest family of cell surface proteins in eukaryotes, the G protein-coupled receptors (GPCRs). Considering their crucial physiologic functions and their relatively accessible cellular locations, GPCRs represent one of the most important classes of therapeutic targets. Until recently, the only strategy to develop drugs regulating GPCR activity was through the identification of compounds that directly acted on the orthosteric sites for endogenous ligands. However, many efforts have recently been made to identify small molecules that are able to interact with allosteric sites. These sites are less well-conserved, therefore allosteric ligands have greater selectivity on the specific receptor. Strikingly, the use of allosteric modulators can provide specific advantages, such as an increased selectivity for GPCR subunits and the ability to introduce specific beneficial therapeutic effects without disrupting the integrity of complex physiologically regulated networks. In 2010, our group unexpectedly found that N -[(1r,4r)-4-[2-(7-cyano-1,2,3,4-tetrahydroisoquinolin-2-yl)ethyl]cyclohexyl]-1H-indole-2-carboxamide (SB269652), a compound supposed to interact with the orthosteric binding site of dopamine receptors, was actually a negative allosteric modulator of D 2 - and D 3 -receptor dimers, thus identifying the first allosteric small molecule acting on these important therapeutic targets. This review addresses the progress in understanding the molecular mechanisms of interaction between the negative modulator SB269652 and D 2 and D 3 dopamine receptor monomers and dimers, and surveys the prospects for developing new dopamine receptor allosteric drugs with SB269652 as the leading compound. U.S. Government work not protected by U.S. copyright.

Longitudinal whole genome analysis of pre and post drug treatment Mycobacterium tuberculosis isolates reveals progressive steps to drug resistance.

PubMed

Datta, Gargi; Nieto, Luisa M; Davidson, Rebecca M; Mehaffy, Carolina; Pederson, Caroline; Dobos, Karen M; Strong, Michael

2016-05-01

Tuberculosis (TB) is one of the leading causes of death due to an infectious disease in the world. Understanding the mechanisms of drug resistance has become pivotal in the detection and treatment of newly emerging resistant TB cases. We have analyzed three pairs of Mycobacterium tuberculosis strains pre- and post-drug treatment to identify mutations involved in the progression of resistance to the drugs rifampicin and isoniazid. In the rifampicin resistant strain, we confirmed a mutation in rpoB (S450L) that is known to confer resistance to rifampicin. We discovered a novel L101R mutation in the katG gene of an isoniazid resistant strain, which may directly contribute to isoniazid resistance due to the proximity of the mutation to the katG isoniazid-activating site. Another isoniazid resistant strain had a rare mutation in the start codon of katG. We also identified a number of mutations in each longitudinal pair, such as toxin-antitoxin mutations that may influence the progression towards resistance or may play a role in compensatory fitness. These findings improve our knowledge of drug resistance progression during therapy and provide a methodology to monitor longitudinal strains using whole genome sequencing, polymorphism comparison, and functional annotation. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

The SADI Personal Health Lens: A Web Browser-Based System for Identifying Personally Relevant Drug Interactions.

PubMed

Vandervalk, Ben; McCarthy, E Luke; Cruz-Toledo, José; Klein, Artjom; Baker, Christopher J O; Dumontier, Michel; Wilkinson, Mark D

2013-04-05

The Web provides widespread access to vast quantities of health-related information that can improve quality-of-life through better understanding of personal symptoms, medical conditions, and available treatments. Unfortunately, identifying a credible and personally relevant subset of information can be a time-consuming and challenging task for users without a medical background. The objective of the Personal Health Lens system is to aid users when reading health-related webpages by providing warnings about personally relevant drug interactions. More broadly, we wish to present a prototype for a novel, generalizable approach to facilitating interactions between a patient, their practitioner(s), and the Web. We utilized a distributed, Semantic Web-based architecture for recognizing personally dangerous drugs consisting of: (1) a private, local triple store of personal health information, (2) Semantic Web services, following the Semantic Automated Discovery and Integration (SADI) design pattern, for text mining and identifying substance interactions, (3) a bookmarklet to trigger analysis of a webpage and annotate it with personalized warnings, and (4) a semantic query that acts as an abstract template of the analytical workflow to be enacted by the system. A prototype implementation of the system is provided in the form of a Java standalone executable JAR file. The JAR file bundles all components of the system: the personal health database, locally-running versions of the SADI services, and a javascript bookmarklet that triggers analysis of a webpage. In addition, the demonstration includes a hypothetical personal health profile, allowing the system to be used immediately without configuration. Usage instructions are provided. The main strength of the Personal Health Lens system is its ability to organize medical information and to present it to the user in a personalized and contextually relevant manner. While this prototype was limited to a single knowledge domain

The SADI Personal Health Lens: A Web Browser-Based System for Identifying Personally Relevant Drug Interactions

PubMed Central

Vandervalk, Ben; McCarthy, E Luke; Cruz-Toledo, José; Klein, Artjom; Baker, Christopher J O; Dumontier, Michel

2013-01-01

Background The Web provides widespread access to vast quantities of health-related information that can improve quality-of-life through better understanding of personal symptoms, medical conditions, and available treatments. Unfortunately, identifying a credible and personally relevant subset of information can be a time-consuming and challenging task for users without a medical background. Objective The objective of the Personal Health Lens system is to aid users when reading health-related webpages by providing warnings about personally relevant drug interactions. More broadly, we wish to present a prototype for a novel, generalizable approach to facilitating interactions between a patient, their practitioner(s), and the Web. Methods We utilized a distributed, Semantic Web-based architecture for recognizing personally dangerous drugs consisting of: (1) a private, local triple store of personal health information, (2) Semantic Web services, following the Semantic Automated Discovery and Integration (SADI) design pattern, for text mining and identifying substance interactions, (3) a bookmarklet to trigger analysis of a webpage and annotate it with personalized warnings, and (4) a semantic query that acts as an abstract template of the analytical workflow to be enacted by the system. Results A prototype implementation of the system is provided in the form of a Java standalone executable JAR file. The JAR file bundles all components of the system: the personal health database, locally-running versions of the SADI services, and a javascript bookmarklet that triggers analysis of a webpage. In addition, the demonstration includes a hypothetical personal health profile, allowing the system to be used immediately without configuration. Usage instructions are provided. Conclusions The main strength of the Personal Health Lens system is its ability to organize medical information and to present it to the user in a personalized and contextually relevant manner. While this

Di-hadron correlations with identified leading hadrons in 200 GeV Au + Au and d + Au collisions at STAR

DOE PAGES

Adamczyk, L.

2015-10-23

The STAR Collaboration presents for the first time two-dimensional di-hadron correlations with identified leading hadrons in 200 GeV central Au + Au and minimum-bias d + Au collisions to explore hadronization mechanisms in the quark gluon plasma. The enhancement of the jet-like yield for leading pions in Au + Au data with respect to the d + Au reference and the absence of such an enhancement for leading non-pions (protons and kaons) are discussed within the context of a quark recombination scenario. The correlated yield at large angles, specifically in the ridge region, is found to be significantly higher formore » leading non-pions than pions. As a result, the consistencies of the constituent quark scaling, azimuthal harmonic model and a mini-jet modification model description of the data are tested, providing further constraints on hadronization.« less

Screening strategies to identify new chemical diversity for drug development to treat kinetoplastid infections.

PubMed

Don, Rob; Ioset, Jean-Robert

2014-01-01

The Drugs for Neglected Diseases initiative (DNDi) has defined and implemented an early discovery strategy over the last few years, in fitting with its virtual R&D business model. This strategy relies on a medium- to high-throughput phenotypic assay platform to expedite the screening of compound libraries accessed through its collaborations with partners from the pharmaceutical industry. We review the pragmatic approaches used to select compound libraries for screening against kinetoplastids, taking into account screening capacity. The advantages, limitations and current achievements in identifying new quality series for further development into preclinical candidates are critically discussed, together with attractive new approaches currently under investigation.

21 CFR 870.3620 - Pacemaker lead adaptor.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Pacemaker lead adaptor. 870.3620 Section 870.3620...) MEDICAL DEVICES CARDIOVASCULAR DEVICES Cardiovascular Prosthetic Devices § 870.3620 Pacemaker lead adaptor. (a) Identification. A pacemaker lead adaptor is a device used to adapt a pacemaker lead so that it...

21 CFR 870.3620 - Pacemaker lead adaptor.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Pacemaker lead adaptor. 870.3620 Section 870.3620...) MEDICAL DEVICES CARDIOVASCULAR DEVICES Cardiovascular Prosthetic Devices § 870.3620 Pacemaker lead adaptor. (a) Identification. A pacemaker lead adaptor is a device used to adapt a pacemaker lead so that it...

21 CFR 870.3620 - Pacemaker lead adaptor.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Pacemaker lead adaptor. 870.3620 Section 870.3620...) MEDICAL DEVICES CARDIOVASCULAR DEVICES Cardiovascular Prosthetic Devices § 870.3620 Pacemaker lead adaptor. (a) Identification. A pacemaker lead adaptor is a device used to adapt a pacemaker lead so that it...

21 CFR 870.3620 - Pacemaker lead adaptor.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Pacemaker lead adaptor. 870.3620 Section 870.3620...) MEDICAL DEVICES CARDIOVASCULAR DEVICES Cardiovascular Prosthetic Devices § 870.3620 Pacemaker lead adaptor. (a) Identification. A pacemaker lead adaptor is a device used to adapt a pacemaker lead so that it...

Recommendations for Selecting Drug-Drug Interactions for Clinical Decision Support

PubMed Central

Tilson, Hugh; Hines, Lisa E.; McEvoy, Gerald; Weinstein, David M.; Hansten, Philip D.; Matuszewski, Karl; le Comte, Marianne; Higby-Baker, Stefanie; Hanlon, Joseph T.; Pezzullo, Lynn; Vieson, Kathleen; Helwig, Amy L.; Huang, Shiew-Mei; Perre, Anthony; Bates, David W.; Poikonen, John; Wittie, Michael A.; Grizzle, Amy J.; Brown, Mary; Malone, Daniel C.

2016-01-01

Purpose To recommend principles for including drug-drug interactions (DDIs) in clinical decision support. Methods A conference series was conducted to improve clinical decision support (CDS) for DDIs. The Content Workgroup met monthly by webinar from January 2013 to February 2014, with two in-person meetings to reach consensus. The workgroup consisted of 20 experts in pharmacology, drug information, and CDS from academia, government agencies, health information (IT) vendors, and healthcare organizations. Workgroup members addressed four key questions: (1) What process should be used to develop and maintain a standard set of DDIs?; (2) What information should be included in a knowledgebase of standard DDIs?; (3) Can/should a list of contraindicated drug pairs be established?; and (4) How can DDI alerts be more intelligently filtered? Results To develop and maintain a standard set of DDIs for CDS in the United States, we recommend a transparent, systematic, and evidence-driven process with graded recommendations by a consensus panel of experts and oversight by a national organization. We outline key DDI information needed to help guide clinician decision-making. We recommend judicious classification of DDIs as contraindicated, as only a small set of drug combinations are truly contraindicated. Finally, we recommend more research to identify methods to safely reduce repetitive and less relevant alerts. Conclusion A systematic ongoing process is necessary to select DDIs for alerting clinicians. We anticipate that our recommendations can lead to consistent and clinically relevant content for interruptive DDIs, and thus reduce alert fatigue and improve patient safety. PMID:27045070

Advancing cancer drug discovery towards more agile development of targeted combination therapies.

PubMed

Carragher, Neil O; Unciti-Broceta, Asier; Cameron, David A

2012-01-01

Current drug-discovery strategies are typically 'target-centric' and are based upon high-throughput screening of large chemical libraries against nominated targets and a selection of lead compounds with optimized 'on-target' potency and selectivity profiles. However, high attrition of targeted agents in clinical development suggest that combinations of targeted agents will be most effective in treating solid tumors if the biological networks that permit cancer cells to subvert monotherapies are identified and retargeted. Conventional drug-discovery and development strategies are suboptimal for the rational design and development of novel drug combinations. In this article, we highlight a series of emerging technologies supporting a less reductionist, more agile, drug-discovery and development approach for the rational design, validation, prioritization and clinical development of novel drug combinations.

Identification of anti-filarial leads against aspartate semialdehyde dehydrogenase of Wolbachia endosymbiont of Brugia malayi: combined molecular docking and molecular dynamics approaches.

PubMed

Amala, Mathimaran; Rajamanikandan, Sundaraj; Prabhu, Dhamodharan; Surekha, Kanagarajan; Jeyakanthan, Jeyaraman

2018-02-06

Lymphatic filariasis is a debilitating vector borne parasitic disease that infects human lymphatic system by nematode Brugia malayi. Currently available anti-filarial drugs are effective only on the larval stages of parasite. So far, no effective drugs are available for humans to treat filarial infections. In this regard, aspartate semialdehyde dehydrogenase (ASDase) in lysine biosynthetic pathway from Wolbachia endosymbiont Brugia malayi represents an attractive therapeutic target for the development of novel anti-filarial agents. In this present study, molecular modeling combined with molecular dynamics simulations and structure-based virtual screening were performed to identify potent lead molecules against ASDase. Based on Glide score, toxicity profile, binding affinity and mode of interactions with the ASDase, five potent lead molecules were selected. The molecular docking and dynamics results revealed that the amino acid residues Arg103, Asn133, Cys134, Gln161, Ser164, Lys218, Arg239, His246, and Asn321 plays a crucial role in effective binding of Top leads into the active site of ASDase. The stability of the ASDase-lead complexes was confirmed by running the 30 ns molecular dynamics simulations. The pharmacokinetic properties of the identified lead molecules are in the acceptable range. Furthermore, density functional theory and binding free energy calculations were performed to rank the lead molecules. Thus, the identified lead molecules can be used for the development of anti-filarial agents to combat the pathogenecity of Brugia malayi.

Do MCI criteria in drug trials accurately identify subjects with predementia Alzheimer's disease?

PubMed Central

Visser, P; Scheltens, P; Verhey, F

2005-01-01

Background: Drugs effective in Alzheimer-type dementia have been tested in subjects with mild cognitive impairment (MCI) because these are supposed to have Alzheimer's disease in the predementia stage. Objectives: To investigate whether MCI criteria used in these drug trials can accurately diagnose subjects with predementia Alzheimer's disease. Methods: MCI criteria of the Gal-Int 11 study, InDDEx study, ADCS memory impairment study, ampakine CX 516 study, piracetam study, and Merck rofecoxib study were applied retrospectively in a cohort of 150 non-demented subjects from a memory clinic. Forty two had progressed to Alzheimer type dementia during a five year follow up period and were considered to have predementia Alzheimer's disease at baseline. Outcome measures were the odds ratio, sensitivity, specificity, and positive and negative predictive value. Results: The odds ratio of the MCI criteria for predementia Alzheimer's disease varied between 0.84 and 11. Sensitivity varied between 0.46 and 0.83 and positive predictive value between 0.43 and 0.76. None of the criteria combined a high sensitivity with a high positive predictive value. Exclusion criteria for depression led to an increase in positive predictive value and specificity at the cost of sensitivity. In subjects older than 65 years the positive predictive value was higher than in younger subjects. Conclusions: The diagnostic accuracy of MCI criteria used in trials for predementia Alzheimer's disease is low to moderate. Their use may lead to inclusion of many patients who do not have predementia Alzheimer's disease or to exclusion of many who do. Subjects with moderately severe depression should not be excluded from trials in order not to reduce the sensitivity. PMID:16170074

Kinome expression profiling of human neuroblastoma tumors identifies potential drug targets for ultra high-risk patients.

PubMed

Russo, Roberta; Cimmino, Flora; Pezone, Lucia; Manna, Francesco; Avitabile, Marianna; Langella, Concetta; Koster, Jan; Casale, Fiorina; Raia, Maddalena; Viola, Giampietro; Fischer, Matthias; Iolascon, Achille; Capasso, Mario

2017-10-01

Neuroblastoma (NBL) accounts for >7% of malignancies in patients younger than 15 years. Low- and intermediate-risk patients exhibit excellent or good prognosis after treatment, whereas for high-risk (HR) patients, the estimated 5-year survival rates is still <40%. The ability to stratify HR patients that will not respond to standard treatment strategies is critical for informed treatment decisions. In this study, we have generated a specific kinome gene signature, named Kinome-27, which is able to identify a subset of HR-NBL tumors, named ultra-HR NBL, with highly aggressive clinical behavior that not adequately respond to standard treatments. We have demonstrated that NBL cell lines expressing the same kinome signature of ultra-HR tumors (ultra-HR-like cell lines) may be selectively targeted by the use of two drugs [suberoylanilide hydroxamic acid (SAHA) and Radicicol], and that the synergic combination of these drugs is able to block the ultra-HR-like cells in G2/M phase of cell cycle. The use of our signature in clinical practice will allow identifying patients with negative outcome, which would benefit from new and more personalized treatments. Preclinical in vivo studies are needed to consolidate the SAHA and Radicicol treatment in ultra-HR NBL patients. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Exposure Matching of Pediatric Anti-infective Drugs: Review of Drugs Submitted to the Food and Drug Administration for Pediatric Approval

PubMed Central

Zimmerman, Kanecia; Putera, Martin; Hornik, Christoph P.; Smith, P. Brian; Benjamin, Daniel K.; Mulugeta, Yeruk; Burckart, Gilbert J.; Cohen-Wolkowiez, Michael; Gonzalez, Daniel

2016-01-01

Purpose Over the last decade, few novel antibiotics have been approved by the Food and Drug Administration (FDA) for pediatric use. For most anti-infective agents, including antibiotics, extrapolation of efficacy from adults to children is possible if the disease and therapeutic exposures are similar between the 2 populations. This approach reduces the number of studies required in children, but relies heavily on exposure matching between children and adults. Failures in exposure matching can lead to delays in pediatric approvals of new anti-infective agents. We sought to determine the extent of exposure matching, defined by a comparison of area under the concentration-time curve, between children and adults, for anti-infective drug products submitted to the FDA for approval. Methods We reviewed anti-infective submissions to the FDA (2002–2014) for pediatric indication. We included drug products administered via oral, intravenous, or intramuscular administration routes, and those with AUC estimates for children in available FDA reports. Our main outcome of interest was the proportion of drugs with median (or mean) pediatric AUC within 20% of the median (or mean) reported adult value. Findings We identified 29 drug products that met inclusion criteria, 14 (48%) of which had mean (or median) AUCs of all submitted age groups within 20% of that in adults. Only route of administration and drug class were associated with pediatric AUC within 20% of adult AUC. Implications Future research is needed to define criteria for and predictors of successful exposure matching of anti-infectives between children and adults. PMID:27364807

Exposure Matching of Pediatric Anti-infective Drugs: Review of Drugs Submitted to the Food and Drug Administration for Pediatric Approval.

PubMed

Zimmerman, Kanecia; Putera, Martin; Hornik, Christoph P; Brian Smith, P; Benjamin, Daniel K; Mulugeta, Yeruk; Burckart, Gilbert J; Cohen-Wolkowiez, Michael; Gonzalez, Daniel

2016-09-01

Over the last decade, few new antibiotics have been approved by the Food and Drug Administration (FDA) for pediatric use. For most anti-infective agents, including antibiotics, extrapolation of efficacy from adults to children is possible if the disease and therapeutic exposures are similar between the 2 populations. This approach reduces the number of studies required in children, but relies heavily on exposure matching between children and adults. Failures in exposure matching can lead to delays in pediatric approvals of new anti-infective agents. We sought to determine the extent of exposure matching, defined by a comparison of area under the concentration-time curve, between children and adults, for anti-infective drug products submitted to the FDA for approval. We reviewed anti-infective submissions to the FDA (2002-2014) for pediatric indication. We included drug products administered via oral, intravenous, or intramuscular administration routes, and those with AUC estimates for children in available FDA reports. Our main outcome of interest was the proportion of drugs with median (or mean) pediatric AUC within 20% of the median (or mean) reported adult value. We identified 29 drug products that met inclusion criteria, 14 (48%) of which had mean (or median) AUCs of all submitted age groups within 20% of that in adults. Only route of administration and drug class were associated with pediatric AUC within 20% of adult AUC. Future research is needed to define criteria for and predictors of successful exposure matching of anti-infectives between children and adults. Published by Elsevier Inc.

Drug decriminalization and the price of illicit drugs.

PubMed

Félix, Sónia; Portugal, Pedro

2017-01-01

This study is an empirical assessment of the impact of the drug decriminalization policy followed by Portugal in July 2001, on the price of illicit drugs. The analysis is performed using a difference-in-differences approach and the Synthetic Control Method in order to construct a synthetic control unit from a convex combination of countries. The results suggest that the prices of opiates and cocaine in the post-treatment period did not decrease in the sequence of the policy change. We conclude that the drug decriminalization policy seems to have caused no harm through lower illicit drugs prices, which would lead to higher drug usage and dependence. Copyright © 2016 Elsevier B.V. All rights reserved.

Drug-induced gingival overgrowth: The nemesis of gingiva unravelled.

PubMed

Bharti, Vipin; Bansal, Chhaya

2013-03-01

Drug-induced gingival overgrowth or enlargement manifests as abnormal growth of the gingiva due to an adverse drug reaction (ADR) in patients treated with anticonvulsants, immunosuppressants, and calcium channel blockers. As gingival enlargement develops, it affects the normal oral hygiene practice and may interfere with masticatory functions. It gradually becomes a source of pain and the condition often leads to disfiguration. Within the group of patients that develop this unwanted effect, there appears to be variability in the extent and severity of the gingival changes. It would seem pertinent to identify and explore possible risk factors and relating them with the treatment plan. This article throws light on respective drugs and their association with gingival overgrowth and approaches to treatment based on current knowledge and investigative observations.

Identifying Perceptions That Contribute to the Development of Successful Project Lead the Way Pre-Engineering Programs in Utah

ERIC Educational Resources Information Center

McMullin, Keith

2013-01-01

Many secondary schools in Utah have adopted the Project Lead the Way (PLTW) pre-engineering program. Little research has been conducted in Utah to show how successful these programs are or what factors are perceived to contribute to that success. This research is about defining PLTW program success and identifying factors perceived to improve…

21 CFR 882.1410 - Electroencephalograph electrode/lead tester.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Electroencephalograph electrode/lead tester. 882.1410 Section 882.1410 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES NEUROLOGICAL DEVICES Neurological Diagnostic Devices § 882.1410...

21 CFR 882.1410 - Electroencephalograph electrode/lead tester.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Electroencephalograph electrode/lead tester. 882.1410 Section 882.1410 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES NEUROLOGICAL DEVICES Neurological Diagnostic Devices § 882.1410...

21 CFR 870.2350 - Electrocardiograph lead switching adaptor.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Electrocardiograph lead switching adaptor. 870.2350 Section 870.2350 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES CARDIOVASCULAR DEVICES Cardiovascular Monitoring Devices § 870.2350...

21 CFR 870.2350 - Electrocardiograph lead switching adaptor.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Electrocardiograph lead switching adaptor. 870.2350 Section 870.2350 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES CARDIOVASCULAR DEVICES Cardiovascular Monitoring Devices § 870.2350...

Drug discovery based on genetic and metabolic findings in schizophrenia.

PubMed

Dwyer, Donard S; Weeks, Kathrine; Aamodt, Eric J

2008-11-01

Recent progress in the genetics of schizophrenia provides the rationale for re-evaluating causative factors and therapeutic strategies for this disease. Here, we review the major candidate susceptibility genes and relate the aberrant function of these genes to defective regulation of energy metabolism in the schizophrenic brain. Disturbances in energy metabolism potentially lead to neurodevelopmental deficits, impaired function of the mature nervous system and failure to maintain neurites/dendrites and synaptic connections. Current antipsychotic drugs do not specifically address these underlying deficits; therefore, a new generation of more effective medications is urgently needed. Novel targets for future drug discovery are identified in this review. The coordinated application of structure-based drug design, systems biology and research on model organisms may greatly facilitate the search for next-generation antipsychotic drugs.

Life in the fast lane: high-throughput chemistry for lead generation and optimisation.

PubMed

Hunter, D

2001-01-01

The pharmaceutical industry has come under increasing pressure due to regulatory restrictions on the marketing and pricing of drugs, competition, and the escalating costs of developing new drugs. These forces can be addressed by the identification of novel targets, reductions in the development time of new drugs, and increased productivity. Emphasis has been placed on identifying and validating new targets and on lead generation: the response from industry has been very evident in genomics and high throughput screening, where new technologies have been applied, usually coupled with a high degree of automation. The combination of numerous new potential biological targets and the ability to screen large numbers of compounds against many of these targets has generated the need for large diverse compound collections. To address this requirement, high-throughput chemistry has become an integral part of the drug discovery process. Copyright 2002 Wiley-Liss, Inc.

Classification and evaluation of the pharmacodynamics of psychotropic drugs by single-lead pharmaco-EEG, EEG mapping and tomography (LORETA).

PubMed

Saletu, B; Anderer, P; Saletu-Zyhlarz, G M; Arnold, O; Pascual-Marqui, R D

2002-01-01

Utilizing computer-assisted quantitative analyses of human scalp-recorded electroencephalogram (EEG) in combination with certain statistical procedures (quantitative pharmaco-EEG) and mapping techniques (pharmaco-EEG mapping), it is possible to classify psychotropic substances and objectively evaluate their bioavailability at the target organ: the human brain. Specifically, one may determine at an early stage of drug development whether a drug is effective on the central nervous system (CNS) compared with placebo, what its clinical efficacy will be like, at which dosage it acts, when it acts and the equipotent dosages of different galenic formulations. Pharmaco-EEG profiles and maps of neuroleptics, antidepressants, tranquilizers, hypnotics, psychostimulants and nootropics/cognition-enhancing drugs will be described in this paper. Methodological problems, as well as the relationships between acute and chronic drug effects, alterations in normal subjects and patients, CNS effects, therapeutic efficacy and pharmacokinetic and pharmacodynamic data will be discussed. In recent times, imaging of drug effects on the regional brain electrical activity of healthy subjects by means of EEG tomography such as low-resolution electromagnetic tomography (LORETA) has been used for identifying brain areas predominantly involved in psychopharmacological action. This will be demonstrated for the representative drugs of the four main psychopharmacological classes, such as 3 mg haloperidol for neuroleptics, 20 mg citalopram for antidepressants, 2 mg lorazepam for tranquilizers and 20 mg methylphenidate for psychostimulants. LORETA demonstrates that these psychopharmacological classes affect brain structures differently.

Missing Fragments: Detecting Cooperative Binding in Fragment-Based Drug Design

PubMed Central

2012-01-01

The aim of fragment-based drug design (FBDD) is to identify molecular fragments that bind to alternate subsites within a given binding pocket leading to cooperative binding when linked. In this study, the binding of fragments to human phenylethanolamine N-methyltransferase is used to illustrate how (a) current protocols may fail to detect fragments that bind cooperatively, (b) theoretical approaches can be used to validate potential hits, and (c) apparent false positives obtained when screening against cocktails of fragments may in fact indicate promising leads. PMID:24900472

CNS drug development: part III: future directions.

PubMed

Preskorn, Sheldon H

2011-01-01

This column, the third in a series on central nervous system (CNS) drug development, discusses advances during the first decade of the 21st century and directions the field may take in the next 10 years. By identifying many possible new drug targets, the human genome project has created the potential to develop novel central nervous system (CNS) drugs with new mechanisms of action. At the same time, this proliferation of possible new targets has complicated the drug development process, since research has not yet provided guidance as to which targets may be most fruitful. This and other factors (eg, increasing regulatory requirements) have increased the cost and complexity of the drug development process. In addition, as more is learned about the biology of psychiatric illnesses, syndromes may be subdivided into more specific entities that are better understood from a pathophysiological and pathoetiological perspective. This is likely to lead to development of more targeted treatments focused on underlying causes of illness as well as prevention. The development of drugs for Alzheimer's disease is discussed as a possible model for future CNS drug development. We are at the beginning of an era when it is likely that the way in which CNS drugs are developed will need to be rethought, which will call for flexibility and creativity on the part of both drug developers and clinical researchers.

Optimized hydrophobic interactions and hydrogen bonding at the target-ligand interface leads the pathways of drug-designing.

PubMed

Patil, Rohan; Das, Suranjana; Stanley, Ashley; Yadav, Lumbani; Sudhakar, Akulapalli; Varma, Ashok K

2010-08-16

Weak intermolecular interactions such as hydrogen bonding and hydrophobic interactions are key players in stabilizing energetically-favored ligands, in an open conformational environment of protein structures. However, it is still poorly understood how the binding parameters associated with these interactions facilitate a drug-lead to recognize a specific target and improve drugs efficacy. To understand this, comprehensive analysis of hydrophobic interactions, hydrogen bonding and binding affinity have been analyzed at the interface of c-Src and c-Abl kinases and 4-amino substituted 1H-pyrazolo [3, 4-d] pyrimidine compounds. In-silico docking studies were performed, using Discovery Studio software modules LigandFit, CDOCKER and ZDOCK, to investigate the role of ligand binding affinity at the hydrophobic pocket of c-Src and c-Abl kinase. Hydrophobic and hydrogen bonding interactions of docked molecules were compared using LigPlot program. Furthermore, 3D-QSAR and MFA calculations were scrutinized to quantify the role of weak interactions in binding affinity and drug efficacy. The in-silico method has enabled us to reveal that a multi-targeted small molecule binds with low affinity to its respective targets. But its binding affinity can be altered by integrating the conformationally favored functional groups at the active site of the ligand-target interface. Docking studies of 4-amino-substituted molecules at the bioactive cascade of the c-Src and c-Abl have concluded that 3D structural folding at the protein-ligand groove is also a hallmark for molecular recognition of multi-targeted compounds and for predicting their biological activity. The results presented here demonstrate that hydrogen bonding and optimized hydrophobic interactions both stabilize the ligands at the target site, and help alter binding affinity and drug efficacy.

Optimized Hydrophobic Interactions and Hydrogen Bonding at the Target-Ligand Interface Leads the Pathways of Drug-Designing

PubMed Central

Stanley, Ashley; Yadav, Lumbani; Sudhakar, Akulapalli; Varma, Ashok K.

2010-01-01

Background Weak intermolecular interactions such as hydrogen bonding and hydrophobic interactions are key players in stabilizing energetically-favored ligands, in an open conformational environment of protein structures. However, it is still poorly understood how the binding parameters associated with these interactions facilitate a drug-lead to recognize a specific target and improve drugs efficacy. To understand this, comprehensive analysis of hydrophobic interactions, hydrogen bonding and binding affinity have been analyzed at the interface of c-Src and c-Abl kinases and 4-amino substituted 1H-pyrazolo [3, 4-d] pyrimidine compounds. Methodology In-silico docking studies were performed, using Discovery Studio software modules LigandFit, CDOCKER and ZDOCK, to investigate the role of ligand binding affinity at the hydrophobic pocket of c-Src and c-Abl kinase. Hydrophobic and hydrogen bonding interactions of docked molecules were compared using LigPlot program. Furthermore, 3D-QSAR and MFA calculations were scrutinized to quantify the role of weak interactions in binding affinity and drug efficacy. Conclusions The in-silico method has enabled us to reveal that a multi-targeted small molecule binds with low affinity to its respective targets. But its binding affinity can be altered by integrating the conformationally favored functional groups at the active site of the ligand-target interface. Docking studies of 4-amino-substituted molecules at the bioactive cascade of the c-Src and c-Abl have concluded that 3D structural folding at the protein-ligand groove is also a hallmark for molecular recognition of multi-targeted compounds and for predicting their biological activity. The results presented here demonstrate that hydrogen bonding and optimized hydrophobic interactions both stabilize the ligands at the target site, and help alter binding affinity and drug efficacy. PMID:20808434

Psychotic and Bipolar Disorders: Antipsychotic Drugs.

PubMed

Holder, Sarah D; Edmunds, Alaina L; Morgan, Sherri

2017-04-01

Antipsychotic drugs block dopamine receptors and are used to manage psychosis as well as other mental illnesses that may or may not have psychotic features, such as bipolar disorders and major depressive disorder. First-generation antipsychotic drugs are more likely to cause adverse effects such as extrapyramidal symptoms and tardive dyskinesia. Adverse effects of second-generation antipsychotic drugs typically are related to metabolic abnormalities such as weight gain, abnormal blood glucose levels, and elevated lipid levels. Neuroleptic malignant syndrome is a rare but serious adverse effect of antipsychotic drugs that causes mental status changes, hyperthermia, and generalized rigidity. Timely diagnosis is essential due to a high risk of related morbidities if the syndrome remains untreated. Some adverse effects of antipsychotics can be identified and managed so that patients can continue beneficial therapy while minimizing the physiologic consequences. Patients taking antipsychotic drugs should be monitored regularly for adverse effects. Antipsychotics are also associated with potential drug interactions, the most lethal being prolongation of the QT interval, which can lead to fatal arrhythmias. Antipsychotic drugs can be used in special populations, such as pregnant women, children, and elderly patients, per recommendation from a mental health subspecialist. Written permission from the American Academy of Family Physicians is required for reproduction of this material in whole or in part in any form or medium.

Realizing drug repositioning by adapting a recommendation system to handle the process.

PubMed

Ozsoy, Makbule Guclin; Özyer, Tansel; Polat, Faruk; Alhajj, Reda

2018-04-12

Drug repositioning is the process of identifying new targets for known drugs. It can be used to overcome problems associated with traditional drug discovery by adapting existing drugs to treat new discovered diseases. Thus, it may reduce associated risk, cost and time required to identify and verify new drugs. Nowadays, drug repositioning has received more attention from industry and academia. To tackle this problem, researchers have applied many different computational methods and have used various features of drugs and diseases. In this study, we contribute to the ongoing research efforts by combining multiple features, namely chemical structures, protein interactions and side-effects to predict new indications of target drugs. To achieve our target, we realize drug repositioning as a recommendation process and this leads to a new perspective in tackling the problem. The utilized recommendation method is based on Pareto dominance and collaborative filtering. It can also integrate multiple data-sources and multiple features. For the computation part, we applied several settings and we compared their performance. Evaluation results show that the proposed method can achieve more concentrated predictions with high precision, where nearly half of the predictions are true. Compared to other state of the art methods described in the literature, the proposed method is better at making right predictions by having higher precision. The reported results demonstrate the applicability and effectiveness of recommendation methods for drug repositioning.

Identifying predictive features in drug response using machine learning: opportunities and challenges.

PubMed

Vidyasagar, Mathukumalli

2015-01-01

This article reviews several techniques from machine learning that can be used to study the problem of identifying a small number of features, from among tens of thousands of measured features, that can accurately predict a drug response. Prediction problems are divided into two categories: sparse classification and sparse regression. In classification, the clinical parameter to be predicted is binary, whereas in regression, the parameter is a real number. Well-known methods for both classes of problems are briefly discussed. These include the SVM (support vector machine) for classification and various algorithms such as ridge regression, LASSO (least absolute shrinkage and selection operator), and EN (elastic net) for regression. In addition, several well-established methods that do not directly fall into machine learning theory are also reviewed, including neural networks, PAM (pattern analysis for microarrays), SAM (significance analysis for microarrays), GSEA (gene set enrichment analysis), and k-means clustering. Several references indicative of the application of these methods to cancer biology are discussed.

21 CFR 882.1410 - Electroencephalograph electrode/lead tester.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Electroencephalograph electrode/lead tester. 882... Electroencephalograph electrode/lead tester. (a) Identification. An electroencephalograph electrode/lead tester is a device used for testing the impedance (resistance to alternating current) of the electrode and lead...

21 CFR 882.1410 - Electroencephalograph electrode/lead tester.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Electroencephalograph electrode/lead tester. 882... Electroencephalograph electrode/lead tester. (a) Identification. An electroencephalograph electrode/lead tester is a device used for testing the impedance (resistance to alternating current) of the electrode and lead...

21 CFR 882.1410 - Electroencephalograph electrode/lead tester.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Electroencephalograph electrode/lead tester. 882... Electroencephalograph electrode/lead tester. (a) Identification. An electroencephalograph electrode/lead tester is a device used for testing the impedance (resistance to alternating current) of the electrode and lead...

The current state of GPCR-based drug discovery to treat metabolic disease.

PubMed

Sloop, Kyle W; Emmerson, Paul J; Statnick, Michael A; Willard, Francis S

2018-02-02

One approach of modern drug discovery is to identify agents that enhance or diminish signal transduction cascades in various cell types and tissues by modulating the activity of GPCRs. This strategy has resulted in the development of new medicines to treat many conditions, including cardiovascular disease, psychiatric disorders, HIV/AIDS, certain forms of cancer and Type 2 diabetes mellitus (T2DM). These successes justify further pursuit of GPCRs as disease targets and provide key learning that should help guide identifying future therapeutic agents. This report reviews the current landscape of GPCR drug discovery with emphasis on efforts aimed at developing new molecules for treating T2DM and obesity. We analyse historical efforts to generate GPCR-based drugs to treat metabolic disease in terms of causal factors leading to success and failure in this endeavour. © 2018 The British Pharmacological Society.

Immunogenetic mechanisms leading to thyroid autoimmunity: recent advances in identifying susceptibility genes and regions.

PubMed

Brand, Oliver J; Gough, Stephen C L

2011-12-01

The autoimmune thyroid diseases (AITD) include Graves' disease (GD) and Hashimoto's thyroiditis (HT), which are characterised by a breakdown in immune tolerance to thyroid antigens. Unravelling the genetic architecture of AITD is vital to better understanding of AITD pathogenesis, required to advance therapeutic options in both disease management and prevention. The early whole-genome linkage and candidate gene association studies provided the first evidence that the HLA region and CTLA-4 represented AITD risk loci. Recent improvements in; high throughput genotyping technologies, collection of larger disease cohorts and cataloguing of genome-scale variation have facilitated genome-wide association studies and more thorough screening of candidate gene regions. This has allowed identification of many novel AITD risk genes and more detailed association mapping. The growing number of confirmed AITD susceptibility loci, implicates a number of putative disease mechanisms most of which are tightly linked with aspects of immune system function. The unprecedented advances in genetic study will allow future studies to identify further novel disease risk genes and to identify aetiological variants within specific gene regions, which will undoubtedly lead to a better understanding of AITD patho-physiology.

Immunogenetic Mechanisms Leading to Thyroid Autoimmunity: Recent Advances in Identifying Susceptibility Genes and Regions

PubMed Central

Brand, Oliver J; Gough, Stephen C.L

2011-01-01

The autoimmune thyroid diseases (AITD) include Graves’ disease (GD) and Hashimoto’s thyroiditis (HT), which are characterised by a breakdown in immune tolerance to thyroid antigens. Unravelling the genetic architecture of AITD is vital to better understanding of AITD pathogenesis, required to advance therapeutic options in both disease management and prevention. The early whole-genome linkage and candidate gene association studies provided the first evidence that the HLA region and CTLA-4 represented AITD risk loci. Recent improvements in; high throughput genotyping technologies, collection of larger disease cohorts and cataloguing of genome-scale variation have facilitated genome-wide association studies and more thorough screening of candidate gene regions. This has allowed identification of many novel AITD risk genes and more detailed association mapping. The growing number of confirmed AITD susceptibility loci, implicates a number of putative disease mechanisms most of which are tightly linked with aspects of immune system function. The unprecedented advances in genetic study will allow future studies to identify further novel disease risk genes and to identify aetiological variants within specific gene regions, which will undoubtedly lead to a better understanding of AITD patho-physiology. PMID:22654554

Residual Complexity Does Impact Organic Chemistry and Drug Discovery: The Case of Rufomyazine and Rufomycin.

PubMed

Choules, Mary P; Klein, Larry L; Lankin, David C; McAlpine, James B; Cho, Sang-Hyun; Cheng, Jinhua; Lee, Hanki; Suh, Joo-Won; Jaki, Birgit U; Franzblau, Scott G; Pauli, Guido F

2018-05-24

Residual complexity (RC) involves the impact of subtle but critical structural and biological features on drug lead validation, including unexplained effects related to unidentified impurities. RC commonly plagues drug discovery efforts due to the inherent imperfections of chromatographic separation methods. The new diketopiperazine, rufomyazine (6), and the previously known antibiotic, rufomycin (7), represent a prototypical case of RC that (almost) resulted in the misassignment of biological activity. The case exemplifies that impurities well below the natural abundance of 13 C (1.1%) can be highly relevant and calls for advanced analytical characterization of drug leads with extended molar dynamic ranges of >1:1,000 using qNMR and LC-MS. Isolated from an actinomycete strain, 6 was originally found to be active against Mycobacterium tuberculosis with a minimum inhibitory concentration (MIC) of 2 μg/mL and high selectivity. As a part of lead validation, the dipeptide was synthesized and surprisingly found to be inactive. The initially observed activity was eventually attributed to a very minor contamination (0.24% [m/m]) with a highly active cyclic peptide (MIC ∼ 0.02 μM), subsequently identified as an analogue of 7. This study illustrates the serious implications RC can exert on organic chemistry and drug discovery, and what efforts are vital to improve lead validation and efficiency, especially in NP-related drug discovery programs.

New genetic findings lead the way to a better understanding of fundamental mechanisms of drug hypersensitivity

PubMed Central

Pirmohamed, Munir; Ostrov, David A.; Park, B. Kevin

2015-01-01

Drug hypersensitivity reactions are an important clinical problem for both health care and industry. Recent advances in genetics have identified a number of HLA alleles associated with a range of these adverse reactions predominantly affecting the skin but also other organs, such as the liver. The associations between abacavir hypersensitivity and HLA-B*57:01 and carbamazepine-induced Stevens-Johnson syndrome and HLA-B*15:02 have been implemented in clinical practice. There are many different mechanisms proposed in the pathogenesis of drug hypersensitivity reactions, including the hapten hypothesis, direct binding to T-cell receptors (the pharmacologic interaction hypothesis), and peptide-binding displacement. A problem with all the hypotheses is that they are largely based on in vitro findings, with little direct in vivo evidence. Although most studies have focused on individual mechanisms, it is perhaps more important to consider them all as being complementary, potentially occurring at the same time with the same drug in the same patient. This might at least partly account for the heterogeneity of the immune response seen in different patients. There is a need to develop novel methodologies to evaluate how the in vitro mechanisms relate to the in vivo situation and how the highly consistent genetic findings with different HLA alleles can be more consistently used for both prediction and prevention of these serious adverse reactions. PMID:26254050

A survey of antiepileptic drug responses identifies drugs with potential efficacy for seizure control in Wolf-Hirschhorn syndrome.

PubMed

Ho, Karen S; Markham, Leah M; Twede, Hope; Lortz, Amanda; Olson, Lenora M; Sheng, Xiaoming; Weng, Cindy; Wassman, E Robert; Newcomb, Tara; Wassman, E Robert; Carey, John C; Battaglia, Agatino

2018-04-01

Seizures are present in over 90% of infants and children with Wolf-Hirschhorn syndrome (WHS). When present, they significantly affect quality of life. The goal of this study was to use caregiver reports to describe the comparative efficacies of commonly used antiepileptic medications in a large population of individuals with WHS. A web-based, confidential caregiver survey was developed to capture seizure semiology and a chronologic record of seizure treatments as well as responses to each treatment. Adverse events for each drug were also cataloged. We received 141 complete survey responses (47% response rate) describing the seizures of individuals ranging in age from 4months to 61years (90 females: 51 males). Using the Early Childhood Epilepsy Severity Scale (E-Chess), WHS-associated seizures are demonstrably severe regardless of deletion size. The best-performing antiepileptic drugs (AEDs) for controlling seizures in this cohort were broad spectrum drugs clobazam, levetiracetam, and lamotrigine; whereas, the three commonly used carboxamide class drugs: carbamazepine, phenytoin, and oxcarbazepine, were reported to have little effect on, or even exacerbate, seizures. The carboxamide class drugs, along with phenobarbital and topiramate, were also associated with the highest rate of intolerance due to cooccurrence of adverse events. Levetiracetam, clobazam, and clonazepam demonstrated higher tolerability and comparatively less severe adverse events (Wilcoxon rank sum comparison between performance of levetiracetam and carboxamide class drugs gives a p<0.0001 after multiple comparison adjustment). This is the largest survey to date assessing WHS seizures. This study design is susceptible to possible bias, as the data are largely drawn from caregiver report and investigators had limited access to medical records. Despite this, our data suggest that the genetic etiology of seizures, together with an accurate electroclinical delineation, are important components of drug

Drug discovery with an RBM20 dependent titin splice reporter identifies cardenolides as lead structures to improve cardiac filling.

PubMed

Liss, Martin; Radke, Michael H; Eckhard, Jamina; Neuenschwander, Martin; Dauksaite, Vita; von Kries, Jens-Peter; Gotthardt, Michael

2018-01-01

Diastolic dysfunction is increasingly prevalent in our ageing society and an important contributor to heart failure. The giant protein titin could serve as a therapeutic target, as its elastic properties are a main determinant of cardiac filling in diastole. This study aimed to develop a high throughput pharmacological screen to identify small molecules that affect titin isoform expression through differential inclusion of exons encoding the elastic PEVK domains. We used a dual luciferase splice reporter assay that builds on the titin splice factor RBM20 to screen ~34,000 small molecules and identified several compounds that inhibit the exclusion of PEVK exons. These compounds belong to the class of cardenolides and affect RBM20 dependent titin exon exclusion but did not affect RBFOX1 mediated splicing of FMNL3. We provide evidence that cardenolides do not bind to the RNA interacting domain of RBM20, but reduce RBM20 protein levels and alter transcription of select splicing factors that interact with RBM20. Cardenolides affect titin isoform expression. Understanding their mode of action and harnessing the splice effects through chemical modifications that suppress the effects on ion homeostasis and more selectively affect cardiac splicing has the potential to improve cardiac filling and thus help patients with diastolic heart failure, for which currently no targeted therapy exists.

21 CFR 870.2350 - Electrocardiograph lead switching adaptor.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Electrocardiograph lead switching adaptor. 870... Electrocardiograph lead switching adaptor. (a) Identification. An electrocardiograph lead switching adaptor is a passive switching device to which electrocardiograph limb and chest leads may be attached. This device is...

21 CFR 870.2350 - Electrocardiograph lead switching adaptor.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Electrocardiograph lead switching adaptor. 870... Electrocardiograph lead switching adaptor. (a) Identification. An electrocardiograph lead switching adaptor is a passive switching device to which electrocardiograph limb and chest leads may be attached. This device is...

21 CFR 870.2350 - Electrocardiograph lead switching adaptor.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Electrocardiograph lead switching adaptor. 870... Electrocardiograph lead switching adaptor. (a) Identification. An electrocardiograph lead switching adaptor is a passive switching device to which electrocardiograph limb and chest leads may be attached. This device is...

A High Content Drug Screen Identifies Ursolic Acid as an Inhibitor of Amyloid β Protein Interactions with Its Receptor CD36*

PubMed Central

Wilkinson, Kim; Boyd, Justin D.; Glicksman, Marcie; Moore, Kathryn J.; El Khoury, Joseph

2011-01-01

A pathological hallmark of Alzheimer disease (AD) is deposition of amyloid β (Aβ) in the brain. Aβ binds to microglia via a receptor complex that includes CD36 leading to production of proinflammatory cytokines and neurotoxic reactive oxygen species and subsequent neurodegeneration. Interruption of Aβ binding to CD36 is a potential therapeutic strategy for AD. To identify pharmacologic inhibitors of Aβ binding to CD36, we developed a 384-well plate assay for binding of fluorescently labeled Aβ to Chinese hamster ovary cells stably expressing human CD36 (CHO-CD36) and screened an Food and Drug Administration-approved compound library. The assay was optimized based on the cells' tolerance to dimethyl sulfoxide, Aβ concentration, time required for Aβ binding, reproducibility, and signal-to-background ratio. Using this assay, we identified four compounds as potential inhibitors of Aβ binding to CD36. These compounds were ursolic acid, ellipticine, zoxazolamine, and homomoschatoline. Of these compounds, only ursolic acid, a naturally occurring pentacyclic triterpenoid, successfully inhibited binding of Aβ to CHO-CD36 cells in a dose-dependent manner. The ursolic acid effect reached a plateau at ∼20 μm, with a maximal inhibition of 64%. Ursolic acid also blocked binding of Aβ to microglial cells and subsequent ROS production. Our data indicate that cell-based high-content screening of small molecule libraries for their ability to block binding of Aβ to its receptors is a useful tool to identify novel inhibitors of receptors involved in AD pathogenesis. Our data also suggest that ursolic acid is a potential therapeutic agent for AD via its ability to block Aβ-CD36 interactions. PMID:21835916

Drug Delivery of the Future: Chasing the Invisible Gorilla

PubMed Central

Park, Kinam

2015-01-01

For more than 60 years drug delivery systems have produced numerous controlled release formulations helping patients improve compliance and maximize the drug efficacy. Development of new controlled drug delivery systems was very productive during the period 1950-1980. The productivity, as measured by the number of clinically used formulations, dropped significantly during 1980-2010. This reduced productivity needs to be understood so that the future development of drug delivery systems can be accelerated and prolific again. This requires critical evaluation of the current drug delivery field, so that the factors inhibiting rapid progress can be identified and resolved. The current drug delivery field is faced with an invisible gorilla syndrome, i.e., seeing a gorilla when it is not present and missing a gorilla when it actually exists. Overcoming this syndrome requires a new way of thinking, questioning the status quo. Advances in drug delivery technologies occur by an evolutionary process, and thus, the more trials and errors lead to faster advances. The drug delivery area needs to nurture the environment where vastly different ideas can be tested, and all data, positive or negative, need to be exchanged freely as they have equal importance. PMID:26519857

Uridine monophosphate kinase as potential target for tuberculosis: from target to lead identification.

PubMed

Arvind, Akanksha; Jain, Vaibhav; Saravanan, Parameswaran; Mohan, C Gopi

2013-12-01

Mycobacterium tuberculosis (Mtb) is a causative agent of tuberculosis (TB) disease, which has affected approximately 2 billion people worldwide. Due to the emergence of resistance towards the existing drugs, discovery of new anti-TB drugs is an important global healthcare challenge. To address this problem, there is an urgent need to identify new drug targets in Mtb. In the present study, the subtractive genomics approach has been employed for the identification of new drug targets against TB. Screening the Mtb proteome using the Database of Essential Genes (DEG) and human proteome resulted in the identification of 60 key proteins which have no eukaryotic counterparts. Critical analysis of these proteins using Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathways database revealed uridine monophosphate kinase (UMPK) enzyme as a potential drug target for developing novel anti-TB drugs. Homology model of Mtb-UMPK was constructed for the first time on the basis of the crystal structure of E. coli-UMPK, in order to understand its structure-function relationships, and which would in turn facilitate to perform structure-based inhibitor design. Furthermore, the structural similarity search was carried out using physiological inhibitor UTP of Mtb-UMPK to virtually screen ZINC database. Retrieved hits were further screened by implementing several filters like ADME and toxicity followed by molecular docking. Finally, on the basis of the Glide docking score and the mode of binding, 6 putative leads were identified as inhibitors of this enzyme which can potentially emerge as future drugs for the treatment of TB.

Drug supply strategies, constraints and prospects in Nigeria.

PubMed

Yusuff, K B; Tayo, F

2004-12-01

The study set out to identify the strategies for public drug supply in Nigeria, assess its functionality, and recommend appropriate means to ensure regular availability of safe, efficacious, good quality and affordable essential drugs at public health facilities. The investigation was carried out at the Directorate of Pharmaceutical services, Federal Ministry of Health (F.M.O.H) Abuja and Federal Medical Stores, Oshodi, Lagos. Semi-structured interview was conducted with key informants at the Department of Food & Drugs, Drug procurement unit and Central Medical store using structured questionnaires and direct informants answers. Our study shows that public drug supply in Nigeria is governed by a National Drug Policy (NDP) which was introduced in 1990 and it is yet to be reviewed after ten years. We also identified the Central Medical Store (CMS) system as the current public drug supply strategy in Nigeria. Public drug supply is mainly financed by governments and this is inadequate to ensure sustained availability of essential drugs. The major procurement methods in use are open tender and direct procurement. These methods as presently operated suffer from late order placement, delay in payment and poor supplier lead-time mainly attributable to lateness in payment for previous drug supplies. These have contributed to stock out of essential drugs at public health facilities. Major losses due to expiration and spoilage are recorded at both central and peripheral storage points despite adequacy of storage facilities and personnel. Road transportation was the major mode of drug distribution from central to peripheral storage points and shortage of vehicle was a key factor affecting drug distribution. There was an apparent lack of a functioning drug management information system to effectively coordinate public drug supply and there are no definite systems that monitor and evaluate staff performance. The CMS strategy currently used for public drug supply in Nigeria has

Drugs, money, and power: the Canadian drug shortage.

PubMed

Kaposy, Chris

2014-03-01

This article describes the shortage of generic injectable medications in Canada that affected hospitals in 2012. It traces the events leading up to the drug shortage, the causes of the shortage, and the responses by health administrators, pharmacists, and ethicists. The article argues that generic drug shortages are an ethical problem because health care organizations and governments have an obligation to avoid exposing patients to resource scarcity. The article also discusses some options governments could pursue in order to secure the drug supply and thereby fulfill their ethical obligations.

High-throughput screen of drug repurposing library identifies inhibitors of Sarcocystis neurona growth.

PubMed

Bowden, Gregory D; Land, Kirkwood M; O'Connor, Roberta M; Fritz, Heather M

2018-04-01

The apicomplexan parasite Sarcocystis neurona is the primary etiologic agent of equine protozoal myeloencephalitis (EPM), a serious neurologic disease of horses. Many horses in the U.S. are at risk of developing EPM; approximately 50% of all horses in the U.S. have been exposed to S. neurona and treatments for EPM are 60-70% effective. Advancement of treatment requires new technology to identify new drugs for EPM. To address this critical need, we developed, validated, and implemented a high-throughput screen to test 725 FDA-approved compounds from the NIH clinical collections library for anti-S. neurona activity. Our screen identified 18 compounds with confirmed inhibitory activity against S. neurona growth, including compounds active in the nM concentration range. Many identified inhibitory compounds have well-defined mechanisms of action, making them useful tools to study parasite biology in addition to being potential therapeutic agents. In comparing the activity of inhibitory compounds identified by our screen to that of other screens against other apicomplexan parasites, we found that most compounds (15/18; 83%) have activity against one or more related apicomplexans. Interestingly, nearly half (44%; 8/18) of the inhibitory compounds have reported activity against dopamine receptors. We also found that dantrolene, a compound already formulated for horses with a peak plasma concentration of 37.8 ± 12.8 ng/ml after 500 mg dose, inhibits S. neurona parasites at low concentrations (0.065 μM [0.036-0.12; 95% CI] or 21.9 ng/ml [12.1-40.3; 95% CI]). These studies demonstrate the use of a new tool for discovering new chemotherapeutic agents for EPM and potentially providing new reagents to elucidate biologic pathways required for successful S. neurona infection. Copyright © 2018. Published by Elsevier Ltd.

Drug-micronutrient interactions: food for thought and thought for action.

PubMed

Karadima, Vasiliki; Kraniotou, Christina; Bellos, George; Tsangaris, George Th

2016-01-01

Micronutrients are indispensable for a variety of vital functions. Micronutrient deficiencies are a global problem concerning two billion people. In most cases, deficiencies are treatable with supplementation of the elements in lack. Drug-nutrient interactions can also lead to micronutrient reduce or depletion by various pathways. Supplementation of the elements and long-term fortification programs for populations at risk can prevent and restore the related deficiencies. Within the context of Predictive, Preventive, and Personalized Medicine, a multi-professional network should be developed in order to identify, manage, and prevent drug-micronutrient interactions that can potentially result to micronutrient deficiencies.

Caveat emptor: Erroneous safety information about opioids in online drug-information compendia.

PubMed

Talwar, Sonia R; Randhawa, Amarita S; Dankiewicz, Erica H; Crudele, Nancy T; Haddox, J David

2016-01-01

Healthcare professionals and consumers refer to online drug-information compendia (eg, Epocrates and WebMD) to learn about prescription medications, including opioid analgesics. With the significant risks associated with opioids, including abuse, misuse, and addiction, any of which can result in life-threatening overdose, it is important for those seeking information from online compendia to have access to current, accurate, and complete drug information to help support clinical treatment decisions. Although compendia are informative, readily available, and user friendly, studies have shown that they may contain errors. To review and identify misinformation in drug summaries of online drug-information compendia for selected opioid analgesic products and submit content corrections to the respective editors. Between 2011 and 2013, drug summaries for Purdue's prescription opioid analgesic products from seven leading online drug-information compendia were systematically reviewed, and the requests for corrections were retrospectively categorized and classified. At least 2 months following requests, the same compendia were then reexamined to assess the degree of error resolution. A total of 859 errors were identified, with the greatest percentage in Safety and Patient Education categories. Across the seven compendia, the complete or partial resolution of errors was 34 percent; therefore, nearly two thirds of the identified errors remain. The results of this analysis, consistent with past studies, demonstrate that online drug-information compendia may contain inaccurate information. Healthcare professionals and consumers must be informed of potential misinformation so they may consider using multiple resources to obtain accurate and current drug information, thereby helping to ensure safer use of prescription medications, such as opioids.

Photo-affinity labelling and biochemical analyses identify the target of trypanocidal simplified natural product analogues

PubMed Central

Tulloch, Lindsay B.; Menzies, Stefanie K.; Fraser, Andrew L.; Gould, Eoin R.; King, Elizabeth F.; Zacharova, Marija K.; Florence, Gordon J.

2017-01-01

Current drugs to treat African sleeping sickness are inadequate and new therapies are urgently required. As part of a medicinal chemistry programme based upon the simplification of acetogenin-type ether scaffolds, we previously reported the promising trypanocidal activity of compound 1, a bis-tetrahydropyran 1,4-triazole (B-THP-T) inhibitor. This study aims to identify the protein target(s) of this class of compound in Trypanosoma brucei to understand its mode of action and aid further structural optimisation. We used compound 3, a diazirine- and alkyne-containing bi-functional photo-affinity probe analogue of our lead B-THP-T, compound 1, to identify potential targets of our lead compound in the procyclic form T. brucei. Bi-functional compound 3 was UV cross-linked to its target(s) in vivo and biotin affinity or Cy5.5 reporter tags were subsequently appended by Cu(II)-catalysed azide-alkyne cycloaddition. The biotinylated protein adducts were isolated with streptavidin affinity beads and subsequent LC-MSMS identified the FoF1-ATP synthase (mitochondrial complex V) as a potential target. This target identification was confirmed using various different approaches. We show that (i) compound 1 decreases cellular ATP levels (ii) by inhibiting oxidative phosphorylation (iii) at the FoF1-ATP synthase. Furthermore, the use of GFP-PTP-tagged subunits of the FoF1-ATP synthase, shows that our compounds bind specifically to both the α- and β-subunits of the ATP synthase. The FoF1-ATP synthase is a target of our simplified acetogenin-type analogues. This mitochondrial complex is essential in both procyclic and bloodstream forms of T. brucei and its identification as our target will enable further inhibitor optimisation towards future drug discovery. Furthermore, the photo-affinity labeling technique described here can be readily applied to other drugs of unknown targets to identify their modes of action and facilitate more broadly therapeutic drug design in any pathogen or

Towards Personalized Medicine: Leveraging Patient Similarity and Drug Similarity Analytics

PubMed Central

Zhang, Ping; Wang, Fei; Hu, Jianying; Sorrentino, Robert

2014-01-01

The rapid adoption of electronic health records (EHR) provides a comprehensive source for exploratory and predictive analytic to support clinical decision-making. In this paper, we investigate how to utilize EHR to tailor treatments to individual patients based on their likelihood to respond to a therapy. We construct a heterogeneous graph which includes two domains (patients and drugs) and encodes three relationships (patient similarity, drug similarity, and patient-drug prior associations). We describe a novel approach for performing a label propagation procedure to spread the label information representing the effectiveness of different drugs for different patients over this heterogeneous graph. The proposed method has been applied on a real-world EHR dataset to help identify personalized treatments for hypercholesterolemia. The experimental results demonstrate the effectiveness of the approach and suggest that the combination of appropriate patient similarity and drug similarity analytics could lead to actionable insights for personalized medicine. Particularly, by leveraging drug similarity in combination with patient similarity, our method could perform well even on new or rarely used drugs for which there are few records of known past performance. PMID:25717413

Tuning hERG out: Antitarget QSAR Models for Drug Development

PubMed Central

Braga, Rodolpho C.; Alves, Vinícius M.; Silva, Meryck F. B.; Muratov, Eugene; Fourches, Denis; Tropsha, Alexander; Andrade, Carolina H.

2015-01-01

Several non-cardiovascular drugs have been withdrawn from the market due to their inhibition of hERG K+ channels that can potentially lead to severe heart arrhythmia and death. As hERG safety testing is a mandatory FDA-required procedure, there is a considerable interest for developing predictive computational tools to identify and filter out potential hERG blockers early in the drug discovery process. In this study, we aimed to generate predictive and well-characterized quantitative structure–activity relationship (QSAR) models for hERG blockage using the largest publicly available dataset of 11,958 compounds from the ChEMBL database. The models have been developed and validated according to OECD guidelines using four types of descriptors and four different machine-learning techniques. The classification accuracies discriminating blockers from non-blockers were as high as 0.83–0.93 on external set. Model interpretation revealed several SAR rules, which can guide structural optimization of some hERG blockers into non-blockers. We have also applied the generated models for screening the World Drug Index (WDI) database and identify putative hERG blockers and non-blockers among currently marketed drugs. The developed models can reliably identify blockers and non-blockers, which could be useful for the scientific community. A freely accessible web server has been developed allowing users to identify putative hERG blockers and non-blockers in chemical libraries of their interest (http://labmol.farmacia.ufg.br/predherg). PMID:24805060

Fragment-to-Lead Medicinal Chemistry Publications in 2015.

PubMed

Johnson, Christopher N; Erlanson, Daniel A; Murray, Christopher W; Rees, David C

2017-01-12

Fragment-based drug discovery (FBDD) is now well-established as a technology for generating new chemical leads and drugs. This Miniperspective provides a tabulated overview of the fragment-to-lead literature published in the year 2015, together with a commentary on trends observed across the FBDD field during this time. It is hoped that this tabulated summary will provide a useful point of reference for both FBDD practitioners and the wider medicinal chemistry community.

Crystal Structure of an Integron Gene Cassette-Associated Protein from Vibrio cholerae Identifies a Cationic Drug-Binding Module

DOE Office of Scientific and Technical Information (OSTI.GOV)

Deshpande, Chandrika N.; Harrop, Stephen J.; Boucher, Yan

2012-02-15

The direct isolation of integron gene cassettes from cultivated and environmental microbial sources allows an assessment of the impact of the integron/gene cassette system on the emergence of new phenotypes, such as drug resistance or virulence. A structural approach is being exploited to investigate the modularity and function of novel integron gene cassettes. We report the 1.8 {angstrom} crystal structure of Cass2, an integron-associated protein derived from an environmental V. cholerae. The structure defines a monomeric beta-barrel protein with a fold related to the effector-binding portion of AraC/XylS transcription activators. The closest homologs of Cass2 are multi-drug binding proteins, suchmore » as BmrR. Consistent with this, a binding pocket made up of hydrophobic residues and a single glutamate side chain is evident in Cass2, occupied in the crystal form by polyethylene glycol. Fluorescence assays demonstrate that Cass2 is capable of binding cationic drug compounds with submicromolar affinity. The Cass2 module possesses a protein interaction surface proximal to its drug-binding cavity with features homologous to those seen in multi-domain transcriptional regulators. Genetic analysis identifies Cass2 to be representative of a larger family of independent effector-binding proteins associated with lateral gene transfer within Vibrio and closely-related species. We propose that the Cass2 family not only has capacity to form functional transcription regulator complexes, but represents possible evolutionary precursors to multi-domain regulators associated with cationic drug compounds.« less

Post-mortem review of fentanyl-related overdose deaths among identified drug users in Southern Bavaria, Germany, 2005-2014.

PubMed

Sinicina, Inga; Sachs, Hans; Keil, Wolfgang

2017-11-01

Two decades ago, there were only single case reports on deaths in Europe following the consumption of illicitly manufactured fentanyl by problem drug users. Today, lethal fentanyl intoxication is now no longer a rarity. Since 2005, a rapid increase of lethal fentanyl-related intoxications in the drug scene has been observed at the Institute of Legal Medicine, Ludwig Maximilians University, Munich. We hypothesized that this rise is the result of the launch of fentanyl matrix patches in Germany in 2004, their broad acceptance, their diversion from the regulated supply chain, and incautious prescription by medical care providers. Post-mortem toxicological reports were reviewed for lethal fentanyl-related intoxications between 2004 und 2014. Blood and tissue samples were tested by GC/MS or LC-MS/MS. The results of police investigations, autopsy reports, and the database of the Institute of Legal Medicine, LMU, were analysed to identify problem drug users and to detect the source of fentanyl as well as the routes of administration. Between 2005 and 2014, 242 overdose victims with post-mortem toxicological detection of fentanyl were found. In the majority of cases, fentanyl matrix patches were the source of fentanyl. The onset of fentanyl-related deaths coincided with the launch of transdermal fentanyl matrix patches in Germany in 2004. Several approaches, such as providing drug users with information on the possible risks of fentanyl consumption, education of medical caregivers, and also monitoring of the prescription of fentanyl patches, are required to reduce the number of fentanyl-related deaths in drug addicts. Copyright © 2017 Elsevier B.V. All rights reserved.

How do Australian news media depict illicit drug issues? An analysis of print media reporting across and between illicit drugs, 2003-2008.

PubMed

Hughes, Caitlin Elizabeth; Lancaster, Kari; Spicer, Bridget

2011-07-01

Media reporting on illicit issues has been frequently criticised for being sensationalised, biased and narrow. Yet, there have been few broad and systematic analyses of the nature of reporting. Using a large sample and methods commonly adopted in media communications analysis this paper sought to identify the dominant media portrayals used to denote illicit drugs in Australian newspapers and to compare and contrast portrayals across drug types. A retrospective content analysis of Australian print media was carried out over the period 2003-2008 from a sample comprised of 11 newspapers. Articles that contained one or more mention of five different drugs (or derivatives) were identified: cannabis, amphetamines, ecstasy, cocaine and heroin. A sub-sample of 4397 articles was selected for media content analysis (with 2045 selected for full content analysis) and a large number of text elements coded for each. Key elements included topic, explicit or implicit messages about the consequences of drugs/use and three value dimensions: overall tone, whether drugs were portrayed as a crisis issue and moral evaluations of drugs/use. The dominant media portrayals depicted law enforcement or criminal justice action (55%), but most articles were reported in a neutral manner, in the absence of crisis framings. Portrayals differed between drugs, with some containing more narrow frames and more explicit moral evaluations than others. For example, heroin was disproportionately framed as a drug that will lead to legal problems. In contrast, ecstasy and cocaine were much more likely to emphasise health and social problems. Media reporting on illicit drugs is heavily distorted towards crime and deviance framings, but may be less overtly sensationalised, biased and narrowly framed than previously suggested. This is not to suggest there is no sensationalism or imbalance, but this appears more associated with particular drug types and episodes of heightened public concern. Copyright © 2011

Shifting from the single- to the multitarget paradigm in drug discovery

PubMed Central

Medina-Franco, José L.; Giulianotti, Marc A.; Welmaker, Gregory S.; Houghten, Richard A.

2013-01-01

Increasing evidence that several drug compounds exert their effects through interactions with multiple targets is boosting the development of research fields that challenge the data reductionism approach. In this article, we review and discuss the concepts of drug repurposing, polypharmacology, chemogenomics, phenotypic screening and highthroughput in vivo testing of mixture-based libraries in an integrated manner. These research fields offer alternatives to the current paradigm of drug discovery, from a one target–one drug model to a multiple-target approach. Furthermore, the goals of lead identification are being expanded accordingly to identify not only ‘key’ compounds that fit with a single-target ‘lock’, but also ‘master key’ compounds that favorably interact with multiple targets (i.e. operate a set of desired locks to gain access to the expected clinical effects). PMID:23340113

OptForce: An Optimization Procedure for Identifying All Genetic Manipulations Leading to Targeted Overproductions

PubMed Central

Ranganathan, Sridhar; Suthers, Patrick F.; Maranas, Costas D.

2010-01-01

Computational procedures for predicting metabolic interventions leading to the overproduction of biochemicals in microbial strains are widely in use. However, these methods rely on surrogate biological objectives (e.g., maximize growth rate or minimize metabolic adjustments) and do not make use of flux measurements often available for the wild-type strain. In this work, we introduce the OptForce procedure that identifies all possible engineering interventions by classifying reactions in the metabolic model depending upon whether their flux values must increase, decrease or become equal to zero to meet a pre-specified overproduction target. We hierarchically apply this classification rule for pairs, triples, quadruples, etc. of reactions. This leads to the identification of a sufficient and non-redundant set of fluxes that must change (i.e., MUST set) to meet a pre-specified overproduction target. Starting with this set we subsequently extract a minimal set of fluxes that must actively be forced through genetic manipulations (i.e., FORCE set) to ensure that all fluxes in the network are consistent with the overproduction objective. We demonstrate our OptForce framework for succinate production in Escherichia coli using the most recent in silico E. coli model, iAF1260. The method not only recapitulates existing engineering strategies but also reveals non-intuitive ones that boost succinate production by performing coordinated changes on pathways distant from the last steps of succinate synthesis. PMID:20419153

Healthcare professionals' agreement on clinical relevance of drug-related problems among elderly patients.

PubMed

Bech, Christine Flagstad; Frederiksen, Tine; Villesen, Christine Tilsted; Højsted, Jette; Nielsen, Per Rotbøll; Kjeldsen, Lene Juel; Nørgaard, Lotte Stig; Christrup, Lona Louring

2018-02-01

Background Disagreement among healthcare professionals on the clinical relevance of drug-related problems can lead to suboptimal treatment and increased healthcare costs. Elderly patients with chronic non-cancer pain and comorbidity are at increased risk of drug related problems compared to other patient groups due to complex medication regimes and transition of care. Objective To investigate the agreement among healthcare professionals on their classification of clinical relevance of drug-related problems in elderly patients with chronic non-cancer pain and comorbidity. Setting Multidisciplinary Pain Centre, Rigshospitalet, Copenhagen, Denmark. Method A pharmacist performed medication review on elderly patients with chronic non-cancer pain and comorbidity, identified their drug-related problems and classified these problems in accordance with an existing categorization system. A five-member clinical panel rated the drug-related problems' clinical relevance in accordance with a five-level rating scale, and their agreement was compared using Fleiss' κ. Main outcome measure Healthcare professionals' agreement on clinical relevance of drug related problems, using Fleiss' κ. Results Thirty patients were included in the study. A total of 162 drug related problems were identified, out of which 54% were of lower clinical relevance (level 0-2) and 46% of higher clinical relevance (level 3-4). Only slight agreement (κ = 0.12) was found between the panellists' classifications of clinical relevance using a five-level rating scale. Conclusion The clinical pharmacist identified drug related problems of lower and higher clinical relevance. Poor overall agreement on the severity of the drug related problems was found among the panelists.

Drug administration adjustments for elderly patients with dysphagia: A case report.

PubMed

Mastroianni, Patrícia de Carvalho; Forgerini, Marcela

2018-01-01

An elderly patient, aged 76 years, diagnosed with dysphagia, depression, hypothyroidism, Alzheimer's disease and mild cognitive deficit, was identified with sertraline and levothyroxine- drug-related problems. Medication Therapy Management (MTM) was used to adjust therapy to the patient's needs by macerating sertraline tablets and solubilizing them in 10-30 mL of orange juice. The patient was advised to take levothyroxine after fasting. Six months later, pharmaceutical follow-up identified an increase in the Mini-Mental State Exam score from 22 to 26 and a decrease in the Clinical Dementia Rating (CDR) scale score from 1.0 to 0.5 in conjunction with mood and physical improvements, as well as a significant decrease in aggressiveness and agitation. Cognitive deficit may be a result of poor drug administration procedures, leading to drug ineffectiveness. Optimizing levothyroxine and sertraline administration, based on knowledge of their physicochemical properties, improves their clinical effectiveness, including the cognition of patients with Alzheimer's disease and dysphagia.

Drug-resistant gram-negative uropathogens: A review.

PubMed

Khoshnood, Saeed; Heidary, Mohsen; Mirnejad, Reza; Bahramian, Aghil; Sedighi, Mansour; Mirzaei, Habibollah

2017-10-01

Urinary tract infection(UTI) caused by Gram-negative bacteria is the second most common infectious presentation in community medical practice. Approximately 150 million people are diagnosed with UTI each year worldwide. Drug resistance in Gram-negative uropathogens is a major global concern which can lead to poor clinical outcomes including treatment failure, development of bacteremia, requirement for intravenous therapy, hospitalization, and extended length of hospital stay. The mechanisms of drug resistance in these bacteria are important due to they are often not identified by routine susceptibility tests and have an exceptional potential for outbreaks. Treatment of UTIs depends on the access to effective drugs, which is now threatened by antibiotic resistant Gram-negative uropathogens. Although several effective antibiotics with activity against highly resistant Gram-negatives are available, there is not a unique antibiotic with activity against the high variety of resistance. Therefore, antimicrobial susceptibility tests, correlation between clinicians and laboratories, development of more rapid diagnostic methods, and continuous monitoring of drug resistance are urgent priorities. In this review, we will discuss about the current global status of drug-resistant Gram-negative uropathogens and their mechanisms of drug resistance to provide new insights into their treatment options. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Three classes of glucocerebrosidase inhibitors identified by quantitative high-throughput screening are chaperone leads for Gaucher disease

PubMed Central

Zheng, Wei; Padia, Janak; Urban, Daniel J.; Jadhav, Ajit; Goker-Alpan, Ozlem; Simeonov, Anton; Goldin, Ehud; Auld, Douglas; LaMarca, Mary E.; Inglese, James; Austin, Christopher P.; Sidransky, Ellen

2007-01-01

Gaucher disease is an autosomal recessive lysosomal storage disorder caused by mutations in the glucocerebrosidase gene. Missense mutations result in reduced enzyme activity that may be due to misfolding, raising the possibility of small-molecule chaperone correction of the defect. Screening large compound libraries by quantitative high-throughput screening (qHTS) provides comprehensive information on the potency, efficacy, and structure–activity relationships (SAR) of active compounds directly from the primary screen, facilitating identification of leads for medicinal chemistry optimization. We used qHTS to rapidly identify three structural series of potent, selective, nonsugar glucocerebrosidase inhibitors. The three structural classes had excellent potencies and efficacies and, importantly, high selectivity against closely related hydrolases. Preliminary SAR data were used to select compounds with high activity in both enzyme and cell-based assays. Compounds from two of these structural series increased N370S mutant glucocerebrosidase activity by 40–90% in patient cell lines and enhanced lysosomal colocalization, indicating chaperone activity. These small molecules have potential as leads for chaperone therapy for Gaucher disease, and this paradigm promises to accelerate the development of leads for other rare genetic disorders. PMID:17670938

Does the cancer drugs fund lead to faster uptake of cost-effective drugs? A time-trend analysis comparing England and Wales.

PubMed

Chamberlain, C; Collin, S M; Stephens, P; Donovan, J; Bahl, A; Hollingworth, W

2014-10-28

The Cancer Drugs Fund (CDF) provides £200 million annually in England for 'anti-cancer' drugs. We used a controlled pre-/post-intervention design to compare IMS Health dispensing data for 15 cancer drugs (2007-2012) in England vs Wales, stratified by pre-CDF NICE drug approval status (rejected, mixed recommendations, recommended, not appraised). The CDF was associated with increased prescribing in England for three of five drugs rejected or with mixed NICE recommendations. The prescribing volume ratios (PVR) ranged from 1.29 (95% CI 1.00, 1.67) for sorafenib to 3.28 (2.59, 4.14) for bevacizumab (NICE rejected) and 0.93 (0.81, 1.06) and 1.35 (1.21, 1.49) for sunitinib and imatinib respectively (mixed recommendations). Post CDF prescribing in England increased for both drugs awaiting NICE appraisal pre-CDF (lapatinib PVR=7.44 (5.81, 9.54), panitumumab PVR=5.40 (1.20, 24.42)) and subsequently rejected. The CDF was not associated with increased prescribing in England of NICE-recommended drugs. The three most recently launched, subsequently recommended drugs were adopted faster in Wales (from pazopanib PVR=0.51 (0.28, 0.96) to abiraterone PVR=0.78 (0.61-0.99)). These data indicate that the CDF is used to access drugs deemed not cost-effective by NICE. The CDF did not expedite access to new cost-effective cancer agents prior to NICE approval.

Indolealkylamines: biotransformations and potential drug-drug interactions.

PubMed

Yu, Ai-Ming

2008-06-01

Indolealkylamine (IAA) drugs are 5-hydroxytryptamine (5-HT or serotonin) analogs that mainly act on the serotonin system. Some IAAs are clinically utilized for antimigraine therapy, whereas other substances are notable as drugs of abuse. In the clinical evaluation of antimigraine triptan drugs, studies on their biotransformations and pharmacokinetics would facilitate the understanding and prevention of unwanted drug-drug interactions (DDIs). A stable, principal metabolite of an IAA drug of abuse could serve as a useful biomarker in assessing intoxication of the IAA substance. Studies on the metabolism of IAA drugs of abuse including lysergic acid amides, tryptamine derivatives and beta-carbolines are therefore emerging. An important role for polymorphic cytochrome P450 2D6 (CYP2D6) in the metabolism of IAA drugs of abuse has been revealed by recent studies, suggesting that variations in IAA metabolism, pharmaco- or toxicokinetics and dynamics can arise from distinct CYP2D6 status, and CYP2D6 polymorphism may represent an additional risk factor in the use of these IAA drugs. Furthermore, DDIs with IAA agents could occur additively at the pharmaco/toxicokinetic and dynamic levels, leading to severe or even fatal serotonin toxicity. In this review, the metabolism and potential DDIs of these therapeutic and abused IAA drugs are described.

Pharmacogenomic biomarker information in drug labels approved by the United States food and drug administration: prevalence of related drug use.

PubMed

Frueh, Felix W; Amur, Shashi; Mummaneni, Padmaja; Epstein, Robert S; Aubert, Ronald E; DeLuca, Teresa M; Verbrugge, Robert R; Burckart, Gilbert J; Lesko, Lawrence J

2008-08-01

To review the labels of United States Food and Drug Administration (FDA)-approved drugs to identify those that contain pharmacogenomic biomarker information, and to collect prevalence information on the use of those drugs for which pharmacogenomic information is included in the drug labeling. Retrospective analysis. The Physicians' Desk Reference Web site, Drugs@FDA Web site, and manufacturers' Web sites were used to identify drug labels containing pharmacogenomic information, and the prescription claims database of a large pharmacy benefits manager (insuring > 55 million individuals in the United States) was used to obtain drug utilization data. Pharmacogenomic biomarkers were defined, FDA-approved drug labels containing this information were identified, and utilization of these drugs was determined. Of 1200 drug labels reviewed for the years 1945-2005, 121 drug labels contained pharmacogenomic information based on a key word search and follow-up screening. Of those, 69 labels referred to human genomic biomarkers, and 52 referred to microbial genomic biomarkers. Of the labels referring to human biomarkers, 43 (62%) pertained to polymorphisms in cytochrome P450 (CYP) enzyme metabolism, with CYP2D6 being most common. Of 36.1 million patients whose prescriptions were processed by a large pharmacy benefits manager in 2006, about 8.8 million (24.3%) received one or more drugs with human genomic biomarker information in the drug label. Nearly one fourth of all outpatients received one or more drugs that have pharmacogenomic information in the label for that drug. The incorporation and appropriate use of pharmacogenomic information in drug labels should be tested for its ability to improve drug use and safety in the United States.

Drug-induced status epilepticus.

PubMed

Cock, Hannah R

2015-08-01

Drug-induced status epilepticus (SE) is a relatively uncommon phenomenon, probably accounting for less than 5% of all SE cases, although limitations in case ascertainment and establishing causation substantially weaken epidemiological estimates. Some antiepileptic drugs, particularly those with sodium channel or GABA(γ-aminobutyric acid)-ergic properties, frequently exacerbate seizures and may lead to SE if used inadvertently in generalized epilepsies or less frequently in other epilepsies. Tiagabine seems to have a particular propensity for triggering nonconvulsive SE sometimes in patients with no prior history of seizures. In therapeutic practice, SE is most commonly seen in association with antibiotics (cephalosporins, quinolones, and some others) and immunotherapies/chemotherapies, the latter often in the context of a reversible encephalopathy syndrome. Status epilepticus following accidental or intentional overdoses, particularly of antidepressants or other psychotropic medications, has also featured prominently in the literature: whilst there are sometimes fatal consequences, this is more commonly because of cardiorespiratory or metabolic complications than as a result of seizure activity. A high index of suspicion is required in identifying those at risk and in recognizing potential clues from the presentation, but even with a careful analysis of patient and drug factors, establishing causation can be difficult. In addition to eliminating the potential trigger, management should be as for SE in any other circumstances, with the exception that phenobarbitone is recommended as a second-line treatment for suspected toxicity-related SE where the risk of cardiovascular complications is higher anyways and may be exacerbated by phenytoin. There are also specific recommendations/antidotes in some situations. The outcome of drug-induced status epilepticus is mostly good when promptly identified and treated, though less so in the context of overdoses. This article is

21 CFR 25.44 - Lead and cooperating agencies.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 1 2011-04-01 2011-04-01 false Lead and cooperating agencies. 25.44 Section 25.44... ENVIRONMENTAL IMPACT CONSIDERATIONS Preparation of Environmental Documents § 25.44 Lead and cooperating agencies... which will be the lead agency and which will be the cooperating agencies. The responsibilities of lead...

21 CFR 25.44 - Lead and cooperating agencies.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 1 2013-04-01 2013-04-01 false Lead and cooperating agencies. 25.44 Section 25.44... ENVIRONMENTAL IMPACT CONSIDERATIONS Preparation of Environmental Documents § 25.44 Lead and cooperating agencies... which will be the lead agency and which will be the cooperating agencies. The responsibilities of lead...

21 CFR 872.1850 - Lead-lined position indicator.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Lead-lined position indicator. 872.1850 Section... (CONTINUED) MEDICAL DEVICES DENTAL DEVICES Diagnostic Devices § 872.1850 Lead-lined position indicator. (a) Identification. A lead-lined position indicator is a cone-shaped device lined with lead that is attached to a...

21 CFR 25.44 - Lead and cooperating agencies.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 1 2012-04-01 2012-04-01 false Lead and cooperating agencies. 25.44 Section 25.44... ENVIRONMENTAL IMPACT CONSIDERATIONS Preparation of Environmental Documents § 25.44 Lead and cooperating agencies... which will be the lead agency and which will be the cooperating agencies. The responsibilities of lead...

21 CFR 872.1850 - Lead-lined position indicator.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Lead-lined position indicator. 872.1850 Section... (CONTINUED) MEDICAL DEVICES DENTAL DEVICES Diagnostic Devices § 872.1850 Lead-lined position indicator. (a) Identification. A lead-lined position indicator is a cone-shaped device lined with lead that is attached to a...

21 CFR 25.44 - Lead and cooperating agencies.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 1 2014-04-01 2014-04-01 false Lead and cooperating agencies. 25.44 Section 25.44... ENVIRONMENTAL IMPACT CONSIDERATIONS Preparation of Environmental Documents § 25.44 Lead and cooperating agencies... which will be the lead agency and which will be the cooperating agencies. The responsibilities of lead...

21 CFR 872.1850 - Lead-lined position indicator.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Lead-lined position indicator. 872.1850 Section... (CONTINUED) MEDICAL DEVICES DENTAL DEVICES Diagnostic Devices § 872.1850 Lead-lined position indicator. (a) Identification. A lead-lined position indicator is a cone-shaped device lined with lead that is attached to a...

21 CFR 872.1850 - Lead-lined position indicator.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Lead-lined position indicator. 872.1850 Section... (CONTINUED) MEDICAL DEVICES DENTAL DEVICES Diagnostic Devices § 872.1850 Lead-lined position indicator. (a) Identification. A lead-lined position indicator is a cone-shaped device lined with lead that is attached to a...

Single-cell mRNA sequencing identifies subclonal heterogeneity in anti-cancer drug responses of lung adenocarcinoma cells.

PubMed

Kim, Kyu-Tae; Lee, Hye Won; Lee, Hae-Ock; Kim, Sang Cheol; Seo, Yun Jee; Chung, Woosung; Eum, Hye Hyeon; Nam, Do-Hyun; Kim, Junhyong; Joo, Kyeung Min; Park, Woong-Yang

2015-06-19

Intra-tumoral genetic and functional heterogeneity correlates with cancer clinical prognoses. However, the mechanisms by which intra-tumoral heterogeneity impacts therapeutic outcome remain poorly understood. RNA sequencing (RNA-seq) of single tumor cells can provide comprehensive information about gene expression and single-nucleotide variations in individual tumor cells, which may allow for the translation of heterogeneous tumor cell functional responses into customized anti-cancer treatments. We isolated 34 patient-derived xenograft (PDX) tumor cells from a lung adenocarcinoma patient tumor xenograft. Individual tumor cells were subjected to single cell RNA-seq for gene expression profiling and expressed mutation profiling. Fifty tumor-specific single-nucleotide variations, including KRAS(G12D), were observed to be heterogeneous in individual PDX cells. Semi-supervised clustering, based on KRAS(G12D) mutant expression and a risk score representing expression of 69 lung adenocarcinoma-prognostic genes, classified PDX cells into four groups. PDX cells that survived in vitro anti-cancer drug treatment displayed transcriptome signatures consistent with the group characterized by KRAS(G12D) and low risk score. Single-cell RNA-seq on viable PDX cells identified a candidate tumor cell subgroup associated with anti-cancer drug resistance. Thus, single-cell RNA-seq is a powerful approach for identifying unique tumor cell-specific gene expression profiles which could facilitate the development of optimized clinical anti-cancer strategies.

Recent Translational Findings on Impulsivity in Relation to Drug Abuse

PubMed Central

Weafer, Jessica; Mitchell, Suzanne H.

2015-01-01

Impulsive behavior is strongly implicated in drug abuse, as both a cause and a consequence of drug use. To understand how impulsive behaviors lead to and result from drug use, translational evidence from both human and non-human animal studies is needed. Here, we review recent (2009 or later) studies that have investigated two major components of impulsive behavior, inhibitory control and impulsive choice, across preclinical and clinical studies. We concentrate on the stop-signal task as the measure of inhibitory control and delay discounting as the measure of impulsive choice. Consistent with previous reports, recent studies show greater impulsive behavior in drug users compared with non-users. Additionally, new evidence supports the prospective role of impulsive behavior in drug abuse, and has begun to identify the neurobiological mechanisms underlying impulsive behavior. We focus on the commonalities and differences in findings between preclinical and clinical studies, and suggest future directions for translational research. PMID:25678985

Pharmacogenetics of drug-drug interaction and drug-drug-gene interaction: a systematic review on CYP2C9, CYP2C19 and CYP2D6.

PubMed

Bahar, Muh Akbar; Setiawan, Didik; Hak, Eelko; Wilffert, Bob

2017-05-01

Currently, most guidelines on drug-drug interaction (DDI) neither consider the potential effect of genetic polymorphism in the strength of the interaction nor do they account for the complex interaction caused by the combination of DDI and drug-gene interaction (DGI) where there are multiple biotransformation pathways, which is referred to as drug-drug-gene interaction (DDGI). In this systematic review, we report the impact of pharmacogenetics on DDI and DDGI in which three major drug-metabolizing enzymes - CYP2C9, CYP2C19 and CYP2D6 - are central. We observed that several DDI and DDGI are highly gene-dependent, leading to a different magnitude of interaction. Precision drug therapy should take pharmacogenetics into account when drug interactions in clinical practice are expected.

New genetic findings lead the way to a better understanding of fundamental mechanisms of drug hypersensitivity.

PubMed

Pirmohamed, Munir; Ostrov, David A; Park, B Kevin

2015-08-01

Drug hypersensitivity reactions are an important clinical problem for both health care and industry. Recent advances in genetics have identified a number of HLA alleles associated with a range of these adverse reactions predominantly affecting the skin but also other organs, such as the liver. The associations between abacavir hypersensitivity and HLA-B*57:01 and carbamazepine-induced Stevens-Johnson syndrome and HLA-B*15:02 have been implemented in clinical practice. There are many different mechanisms proposed in the pathogenesis of drug hypersensitivity reactions, including the hapten hypothesis, direct binding to T-cell receptors (the pharmacologic interaction hypothesis), and peptide-binding displacement. A problem with all the hypotheses is that they are largely based on in vitro findings, with little direct in vivo evidence. Although most studies have focused on individual mechanisms, it is perhaps more important to consider them all as being complementary, potentially occurring at the same time with the same drug in the same patient. This might at least partly account for the heterogeneity of the immune response seen in different patients. There is a need to develop novel methodologies to evaluate how the in vitro mechanisms relate to the in vivo situation and how the highly consistent genetic findings with different HLA alleles can be more consistently used for both prediction and prevention of these serious adverse reactions. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Biomarkers of adverse drug reactions.

PubMed

Carr, Daniel F; Pirmohamed, Munir

2018-02-01

Adverse drug reactions can be caused by a wide range of therapeutics. Adverse drug reactions affect many bodily organ systems and vary widely in severity. Milder adverse drug reactions often resolve quickly following withdrawal of the casual drug or sometimes after dose reduction. Some adverse drug reactions are severe and lead to significant organ/tissue injury which can be fatal. Adverse drug reactions also represent a financial burden to both healthcare providers and the pharmaceutical industry. Thus, a number of stakeholders would benefit from development of new, robust biomarkers for the prediction, diagnosis, and prognostication of adverse drug reactions. There has been significant recent progress in identifying predictive genomic biomarkers with the potential to be used in clinical settings to reduce the burden of adverse drug reactions. These have included biomarkers that can be used to alter drug dose (for example, Thiopurine methyltransferase (TPMT) and azathioprine dose) and drug choice. The latter have in particular included human leukocyte antigen (HLA) biomarkers which identify susceptibility to immune-mediated injuries to major organs such as skin, liver, and bone marrow from a variety of drugs. This review covers both the current state of the art with regard to genomic adverse drug reaction biomarkers. We also review circulating biomarkers that have the potential to be used for both diagnosis and prognosis, and have the added advantage of providing mechanistic information. In the future, we will not be relying on single biomarkers (genomic/non-genomic), but on multiple biomarker panels, integrated through the application of different omics technologies, which will provide information on predisposition, early diagnosis, prognosis, and mechanisms. Impact statement • Genetic and circulating biomarkers present significant opportunities to personalize patient therapy to minimize the risk of adverse drug reactions. ADRs are a significant heath issue

"Not just eliminating the mosquito but draining the swamp": A critical geopolitics of Turkish Monitoring Center for Drugs and Drug Addiction and Turkey's approach to illicit drugs.

PubMed

Evered, Kyle T; Evered, Emine Ö

2016-07-01

In the 1970s, Turkey ceased to be a significant producer state of illicit drugs, but it continued to serve as a key route for the trade of drugs between East and West. Over the past decade, however, authorities identified two concerns beyond its continued transit state status. These reported problems entail both new modes of production and a rising incidence of drug abuse within the nation-state - particularly among its youth. Amid these developments, new law enforcement institutions emerged and acquired European sponsorship, leading to the establishment of TUBİM (the Turkish Monitoring Center for Drugs and Drug Addiction). Coordinating with and reporting to the European Union agency EMCDDA (the European Monitoring Center for Drugs and Drug Addiction), TUBİM's primary assigned duties entail the collection and analysis of data on drug abuse, trafficking, and prevention, the geographic identification of sites of concern (e.g. consumption, drug-related crimes, and peoples undergoing treatment), and the production of annual national reports. In this article, we examine the geopolitical origins of TUBİM as Turkey's central apparatus for confronting drug problems and its role as a vehicle for policy development, interpretation, and enforcement. In doing so, we emphasize the political and spatial dimensions inherent to the country's institutional and policy-driven approaches to contend with drug-related problems, and we assess how this line of attack reveals particular ambiguities in mission when evaluated from scales at world regional, national, and local levels. In sum, we assess how Turkey's new institutional and legislative landscapes condition the state's engagements with drug use, matters of user's health, and policy implementation at local scales and amid ongoing political developments. Copyright © 2016 Elsevier B.V. All rights reserved.

Whole-Transcriptome and -Genome Analysis of Extensively Drug-Resistant Mycobacterium tuberculosis Clinical Isolates Identifies Downregulation of ethA as a Mechanism of Ethionamide Resistance

PubMed Central

de Welzen, Lynne; Eldholm, Vegard; Maharaj, Kashmeel; Manson, Abigail L.; Earl, Ashlee M.

2017-01-01

ABSTRACT Genetics-based drug susceptibility testing has improved the diagnosis of drug-resistant tuberculosis but is limited by our lack of knowledge of all resistance mechanisms. Next-generation sequencing has assisted in identifying the principal genetic mechanisms of resistance for many drugs, but a significant proportion of phenotypic drug resistance is unexplained genetically. Few studies have formally compared the transcriptomes of susceptible and resistant Mycobacterium tuberculosis strains. We carried out comparative whole-genome transcriptomics of extensively drug-resistant (XDR) clinical isolates using RNA sequencing (RNA-seq) to find novel transcription-mediated mechanisms of resistance. We identified a promoter mutation (t to c) at position −11 (t−11c) relative to the start codon of ethA that reduces the expression of a monooxygenase (EthA) that activates ethionamide. (In this article, nucleotide changes are lowercase and amino acid substitutions are uppercase.) Using a flow cytometry-based reporter assay, we show that the reduced transcription of ethA is not due to transcriptional repression by ethR. Clinical strains harboring this mutation were resistant to ethionamide. Other ethA promoter mutations were identified in a global genomic survey of resistant M. tuberculosis strains. These results demonstrate a new mechanism of ethionamide resistance that can cause high-level resistance when it is combined with other ethionamide resistance-conferring mutations. Our study revealed many other genes which were highly up- or downregulated in XDR strains, including a toxin-antitoxin module (mazF5 mazE5) and tRNAs (leuX and thrU). This suggests that global transcriptional modifications could contribute to resistance or the maintenance of bacterial fitness have also occurred in XDR strains. PMID:28993337

Drug Discovery Prospect from Untapped Species: Indications from Approved Natural Product Drugs

PubMed Central

Qin, Chu; Tao, Lin; Liu, Xin; Shi, Zhe; Zhang, Cun Long; Tan, Chun Yan; Chen, Yu Zong; Jiang, Yu Yang

2012-01-01

Due to extensive bioprospecting efforts of the past and technology factors, there have been questions about drug discovery prospect from untapped species. We analyzed recent trends of approved drugs derived from previously untapped species, which show no sign of untapped drug-productive species being near extinction and suggest high probability of deriving new drugs from new species in existing drug-productive species families and clusters. Case histories of recently approved drugs reveal useful strategies for deriving new drugs from the scaffolds and pharmacophores of the natural product leads of these untapped species. New technologies such as cryptic gene-cluster exploration may generate novel natural products with highly anticipated potential impact on drug discovery. PMID:22808057

Emory University: MEDICI (Mining Essentiality Data to Identify Critical Interactions) for Cancer Drug Target Discovery and Development | Office of Cancer Genomics

Cancer.gov

The CTD2 Center at Emory University has developed a computational methodology to combine high-throughput knockdown data with known protein network topologies to infer the importance of protein-protein interactions (PPIs) for the survival of cancer cells.  Applying these data to the Achilles shRNA results, the CCLE cell line characterizations, and known and newly identified PPIs provides novel insights for potential new drug targets for cancer therapies and identifies important PPI hubs.

Computational approaches for drug discovery.

PubMed

Hung, Che-Lun; Chen, Chi-Chun

2014-09-01

Cellular proteins are the mediators of multiple organism functions being involved in physiological mechanisms and disease. By discovering lead compounds that affect the function of target proteins, the target diseases or physiological mechanisms can be modulated. Based on knowledge of the ligand-receptor interaction, the chemical structures of leads can be modified to improve efficacy, selectivity and reduce side effects. One rational drug design technology, which enables drug discovery based on knowledge of target structures, functional properties and mechanisms, is computer-aided drug design (CADD). The application of CADD can be cost-effective using experiments to compare predicted and actual drug activity, the results from which can used iteratively to improve compound properties. The two major CADD-based approaches are structure-based drug design, where protein structures are required, and ligand-based drug design, where ligand and ligand activities can be used to design compounds interacting with the protein structure. Approaches in structure-based drug design include docking, de novo design, fragment-based drug discovery and structure-based pharmacophore modeling. Approaches in ligand-based drug design include quantitative structure-affinity relationship and pharmacophore modeling based on ligand properties. Based on whether the structure of the receptor and its interaction with the ligand are known, different design strategies can be seed. After lead compounds are generated, the rule of five can be used to assess whether these have drug-like properties. Several quality validation methods, such as cost function analysis, Fisher's cross-validation analysis and goodness of hit test, can be used to estimate the metrics of different drug design strategies. To further improve CADD performance, multi-computers and graphics processing units may be applied to reduce costs. © 2014 Wiley Periodicals, Inc.

In Silico Chemogenomics Drug Repositioning Strategies for Neglected Tropical Diseases.

PubMed

Andrade, Carolina Horta; Neves, Bruno Junior; Melo-Filho, Cleber Camilo; Rodrigues, Juliana; Silva, Diego Cabral; Braga, Rodolpho Campos; Cravo, Pedro Vitor Lemos

2018-03-08

Only ~1% of all drug candidates against Neglected Tropical Diseases (NTDs) have reached clinical trials in the last decades, underscoring the need for new, safe and effective treatments. In such context, drug repositioning, which allows finding novel indications for approved drugs whose pharmacokinetic and safety profiles are already known, is emerging as a promising strategy for tackling NTDs. Chemogenomics is a direct descendent of the typical drug discovery process that involves the systematic screening of chemical compounds against drug targets in high-throughput screening (HTS) efforts, for the identification of lead compounds. However, different to the one-drug-one-target paradigm, chemogenomics attempts to identify all potential ligands for all possible targets and diseases. In this review, we summarize current methodological development efforts in drug repositioning that use state-of-the-art computational ligand- and structure-based chemogenomics approaches. Furthermore, we highlighted the recent progress in computational drug repositioning for some NTDs, based on curation and modeling of genomic, biological, and chemical data. Additionally, we also present in-house and other successful examples and suggest possible solutions to existing pitfalls. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Clinical coding of prospectively identified paediatric adverse drug reactions--a retrospective review of patient records.

PubMed

Bellis, Jennifer R; Kirkham, Jamie J; Nunn, Anthony J; Pirmohamed, Munir

2014-12-17

National Health Service (NHS) hospitals in the UK use a system of coding for patient episodes. The coding system used is the International Classification of Disease (ICD-10). There are ICD-10 codes which may be associated with adverse drug reactions (ADRs) and there is a possibility of using these codes for ADR surveillance. This study aimed to determine whether ADRs prospectively identified in children admitted to a paediatric hospital were coded appropriately using ICD-10. The electronic admission abstract for each patient with at least one ADR was reviewed. A record was made of whether the ADR(s) had been coded using ICD-10. Of 241 ADRs, 76 (31.5%) were coded using at least one ICD-10 ADR code. Of the oncology ADRs, 70/115 (61%) were coded using an ICD-10 ADR code compared with 6/126 (4.8%) non-oncology ADRs (difference in proportions 56%, 95% CI 46.2% to 65.8%; p < 0.001). The majority of ADRs detected in a prospective study at a paediatric centre would not have been identified if the study had relied on ICD-10 codes as a single means of detection. Data derived from administrative healthcare databases are not reliable for identifying ADRs by themselves, but may complement other methods of detection.

Personalizing Drug Selection Using Advanced Clinical Decision Support

PubMed Central

Pestian, John; Spencer, Malik; Matykiewicz, Pawel; Zhang, Kejian; Vinks, Alexander A.; Glauser, Tracy

2009-01-01

This article describes the process of developing an advanced pharmacogenetics clinical decision support at one of the United States’ leading pediatric academic medical centers. This system, called CHRISTINE, combines clinical and genetic data to identify the optimal drug therapy when treating patients with epilepsy or Attention Deficit Hyperactivity Disorder. In the discussion a description of clinical decision support systems is provided, along with an overview of neurocognitive computing and how it is applied in this setting. PMID:19898682

Get the Lead Out: Illinois Childhood Lead Poisoning Surveillance Report, 2001.

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