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Sample records for danish qsar database

  1. The Danish Collaborative Bacteraemia Network (DACOBAN) database

    PubMed Central

    Gradel, Kim Oren; Schønheyder, Henrik Carl; Arpi, Magnus; Knudsen, Jenny Dahl; Østergaard, Christian; Søgaard, Mette

    2014-01-01

    The Danish Collaborative Bacteraemia Network (DACOBAN) research database includes microbiological data obtained from positive blood cultures from a geographically and demographically well-defined population serviced by three clinical microbiology departments (1.7 million residents, 32% of the Danish population). The database also includes data on comorbidity from the Danish National Patient Registry, vital status from the Danish Civil Registration System, and clinical data on 31% of nonselected records in the database. Use of the unique civil registration number given to all Danish residents enables linkage to additional registries for specific research projects. The DACOBAN database is continuously updated, and it currently comprises 39,292 patients with 49,951 bacteremic episodes from 2000 through 2011. The database is part of an international network of population-based bacteremia registries from five developed countries on three continents. The main purpose of the DACOBAN database is to study surveillance, risk, and prognosis. Sex- and age-specific data on background populations enables the computation of incidence rates. In addition, the high number of patients facilitates studies of rare microorganisms. Thus far, studies on Staphylococcus aureus, enterococci, computer algorithms for the classification of bacteremic episodes, and prognosis and risk in relation to socioeconomic factors have been published. PMID:25258557

  2. QSAR Modeling Using Large-Scale Databases: Case Study for HIV-1 Reverse Transcriptase Inhibitors.

    PubMed

    Tarasova, Olga A; Urusova, Aleksandra F; Filimonov, Dmitry A; Nicklaus, Marc C; Zakharov, Alexey V; Poroikov, Vladimir V

    2015-07-27

    Large-scale databases are important sources of training sets for various QSAR modeling approaches. Generally, these databases contain information extracted from different sources. This variety of sources can produce inconsistency in the data, defined as sometimes widely diverging activity results for the same compound against the same target. Because such inconsistency can reduce the accuracy of predictive models built from these data, we are addressing the question of how best to use data from publicly and commercially accessible databases to create accurate and predictive QSAR models. We investigate the suitability of commercially and publicly available databases to QSAR modeling of antiviral activity (HIV-1 reverse transcriptase (RT) inhibition). We present several methods for the creation of modeling (i.e., training and test) sets from two, either commercially or freely available, databases: Thomson Reuters Integrity and ChEMBL. We found that the typical predictivities of QSAR models obtained using these different modeling set compilation methods differ significantly from each other. The best results were obtained using training sets compiled for compounds tested using only one method and material (i.e., a specific type of biological assay). Compound sets aggregated by target only typically yielded poorly predictive models. We discuss the possibility of "mix-and-matching" assay data across aggregating databases such as ChEMBL and Integrity and their current severe limitations for this purpose. One of them is the general lack of complete and semantic/computer-parsable descriptions of assay methodology carried by these databases that would allow one to determine mix-and-matchability of result sets at the assay level. PMID:26046311

  3. Human intestinal transporter database: QSAR modeling and virtual profiling of drug uptake, efflux and interactions

    PubMed Central

    Sedykh, Alexander; Fourches, Denis; Duan, Jianmin; Hucke, Oliver; Garneau, Michel; Zhu, Hao; Bonneau, Pierre; Tropsha, Alexander

    2013-01-01

    Purpose Membrane transporters mediate many biological effects of chemicals and play a major role in pharmacokinetics and drug resistance. The selection of viable drug candidates among biologically active compounds requires the assessment of their transporter interaction profiles. Methods Using public sources, we have assembled and curated the largest, to our knowledge, human intestinal transporter database (>5,000 interaction entries for >3,700 molecules). This data was used to develop thoroughly validated classification Quantitative Structure-Activity Relationship (QSAR) models of transport and/or inhibition of several major transporters including MDR1, BCRP, MRP1-4, PEPT1, ASBT, OATP2B1, OCT1, and MCT1. Results & Conclusions QSAR models have been developed with advanced machine learning techniques such as Support Vector Machines, Random Forest, and k Nearest Neighbors using Dragon and MOE chemical descriptors. These models afforded high external prediction accuracies of 71–100% estimated by 5-fold external validation, and showed hit retrieval rates with up to 20-fold enrichment in the virtual screening of DrugBank compounds. The compendium of predictive QSAR models developed in this study can be used for virtual profiling of drug candidates and/or environmental agents with the optimal transporter profiles. PMID:23269503

  4. Construction and analysis of a human hepatotoxicity database suitable for QSAR modeling using post-market safety data.

    PubMed

    Zhu, Xiao; Kruhlak, Naomi L

    2014-07-01

    Drug-induced liver injury (DILI) is one of the most common drug-induced adverse events (AEs) leading to life-threatening conditions such as acute liver failure. It has also been recognized as the single most common cause of safety-related post-market withdrawals or warnings. Efforts to develop new predictive methods to assess the likelihood of a drug being a hepatotoxicant have been challenging due to the complexity and idiosyncrasy of clinical manifestations of DILI. The FDA adverse event reporting system (AERS) contains post-market data that depict the morbidity of AEs. Here, we developed a scalable approach to construct a hepatotoxicity database using post-market data for the purpose of quantitative structure-activity relationship (QSAR) modeling. A set of 2029 unique and modelable drug entities with 13,555 drug-AE combinations was extracted from the AERS database using 37 hepatotoxicity-related query preferred terms (PTs). In order to determine the optimal classification scheme to partition positive from negative drugs, a manually-curated DILI calibration set composed of 105 negatives and 177 positives was developed based on the published literature. The final classification scheme combines hepatotoxicity-related PT data with supporting information that optimize the predictive performance across the calibration set. Data for other toxicological endpoints related to liver injury such as liver enzyme abnormalities, cholestasis, and bile duct disorders, were also extracted and classified. Collectively, these datasets can be used to generate a battery of QSAR models that assess a drug's potential to cause DILI. PMID:24721472

  5. Existing data sources for clinical epidemiology: The Danish National Database of Reimbursed Prescriptions

    PubMed Central

    Johannesdottir, Sigrun Alba; Horváth-Puhó, Erzsébet; Ehrenstein, Vera; Schmidt, Morten; Pedersen, Lars; Sørensen, Henrik Toft

    2012-01-01

    The Danish health care system provides partial reimbursement of most prescription medications in Denmark. The dispensation of prescription medications is registered in administrative databases. Each time a prescription is redeemed at a pharmacy, an electronic record is generated with information related to the user, prescriber, the pharmacy, and the dispensed drug. The National Health Service gathers this information for administration of the drug reimbursement plan. Recently, this information became the basis for the establishment of a new research database, the Danish National Database of Reimbursed Prescriptions (DNDRP). In this paper, we review the content, coverage, quality, linkage, access, and research possibilities of this new database. The database encompasses the reimbursement records of all reimbursed drugs sold in community pharmacies and hospital-based outpatient pharmacies in Denmark since 2004. On average, approximately 3.5 million users are recorded in the database each year. During the coverage period, the number of annual prescription redemptions increased by 15%. Most dispensed prescriptions are in the categories “alimentary tract and metabolism”, “cardiovascular system”, “nervous system”, and “respiratory system”. Individuals are identified by the unique central personal registration (CPR) number assigned to all persons born in or immigrating to Denmark. The new database fully complies with Denmark’s Act on Processing of Personal Data, while avoiding additional restrictions imposed on data use at the Danish National Prescription Registry, administered by Statistics Denmark. Most importantly, CPR numbers are reversibly encrypted, which allows re-identification of drug users; furthermore, the data access is possible outside the servers of Statistics Denmark. These features open additional opportunities for international collaboration, validation studies, studies on adverse drug effects requiring review of medical records, studies

  6. Linkage between the Danish National Health Service Prescription Database, the Danish Fetal Medicine Database, and other Danish registries as a tool for the study of drug safety in pregnancy

    PubMed Central

    Pedersen, Lars H; Petersen, Olav B; Nørgaard, Mette; Ekelund, Charlotte; Pedersen, Lars; Tabor, Ann; Sørensen, Henrik T

    2016-01-01

    A linked population-based database is being created in Denmark for research on drug safety during pregnancy. It combines information from the Danish National Health Service Prescription Database (with information on all prescriptions reimbursed in Denmark since 2004), the Danish Fetal Medicine Database, the Danish National Registry of Patients, and the Medical Birth Registry. The new linked database will provide validated information on malformations diagnosed both prenatally and postnatally. The cohort from 2008 to 2014 will comprise 589,000 pregnancies with information on 424,000 pregnancies resulting in live-born children, ∼420,000 pregnancies undergoing prenatal ultrasound scans, 65,000 miscarriages, and 92,000 terminations. It will be updated yearly with information on ∼80,000 pregnancies. The cohort will enable identification of drug exposures associated with severe malformations, not only based on malformations diagnosed after birth but also including those having led to termination of pregnancy or miscarriage. Such combined data will provide a unique source of information for research on the safety of medications used during pregnancy. PMID:27274312

  7. Exploring barriers for health visitors' adaption of the Danish children's database.

    PubMed

    Pape-Haugaard, Louise; Haugaard, Karin; Carøe, Per; Høstgaard, Anna Marie

    2013-01-01

    Denmark has unique health informatics databases such as "The Children's Database" (CDB), which since 2009 has held data on all Danish children from birth until 17 years of age. In the current set-up a number of potential sources of error exist - both technical and human - which means that the data is flawed. The objective of this paper is both to clarify errors in the database and to enlighten the underlying mechanisms causing these errors. This is done through an ethnographic study using participant observations, interviews and workshops. Errors are documented through statistical analysis. The data show redundant records. This redundancy can be explained by multiple transmissions conducted by end users or systems, or a lack of validation methods in the National CDB. In our results three types of cases are presented: from health visitors at school, from health visitors visiting families and from health visitors at central health offices. PMID:23920857

  8. Database on Danish population-based registers for public health and welfare research.

    PubMed

    Sortsø, Camilla; Thygesen, Lau Caspar; Brønnum-Hansen, Henrik

    2011-07-01

    Population-based studies with information from registers can take place in Denmark due to linkage between registers at the individual level by means of a unique personal identification number (CPR-number), which all persons with residence in Denmark have. Registers with information on health can be linked to other population registers containing information on, for example, transfer payments, education, housing, income, and socioeconomic position. This article introduces a database and search engine, which is available for public health and welfare researchers as an aid to seek information on the content of important Danish registers. PMID:21898917

  9. Existing data sources for clinical epidemiology: the Danish Patient Compensation Association database

    PubMed Central

    Tilma, Jens; Nørgaard, Mette; Mikkelsen, Kim Lyngby; Johnsen, Søren Paaske

    2015-01-01

    Any patient in the Danish health care system who experiences a treatment injury can make a compensation claim to the Danish Patient Compensation Association (DPCA) free of charge. The aim of this paper is to describe the DPCA database as a source of data for epidemiological research. Data to DPCA are collected prospectively on all claims and include information on patient factors and health records, system factors, and administrative data. Approval of claims is based on injury due to the principle of treatment below experienced specialist standard or intolerable, unexpected extensiveness of injury. Average processing time of a compensation claim is 6–8 months. Data collection is nationwide and started in 1992. The patient’s central registration system number, a unique personal identifier, allows for data linkage to other registries such as the Danish National Patient Registry. The DPCA data are accessible for research following data usage permission and make it possible to analyze all claims or specific subgroups to identify predictors, outcomes, etc. DPCA data have until now been used only in few studies but could be a useful data source in future studies of health care-related injuries. PMID:26229505

  10. Reusable data in public health data-bases-problems encountered in Danish Children's Database.

    PubMed

    Høstgaard, Anna Marie; Pape-Haugaard, Louise

    2012-01-01

    Denmark have unique health informatics databases e.g. "The Children's Database", which since 2009 holds data on all Danish children from birth until 17 years of age. In the current set-up a number of potential sources of errors exist - both technical and human-which means that the data is flawed. This gives rise to erroneous statistics and makes the data unsuitable for research purposes. In order to make the data usable, it is necessary to develop new methods for validating the data generation process at the municipal/regional/national level. In the present ongoing research project, two research areas are combined: Public Health Informatics and Computer Science, and both ethnographic as well as system engineering research methods are used. The project is expected to generate new generic methods and knowledge about electronic data collection and transmission in different social contexts and by different social groups and thus to be of international importance, since this is sparsely documented in the Public Health Informatics perspective. This paper presents the preliminary results, which indicate that health information technology used ought to be subject for redesign, where a thorough insight into the work practices should be point of departure. PMID:22874263

  11. QSAR Methods.

    PubMed

    Gini, Giuseppina

    2016-01-01

    In this chapter, we introduce the basis of computational chemistry and discuss how computational methods have been extended to some biological properties and toxicology, in particular. Since about 20 years, chemical experimentation is more and more replaced by modeling and virtual experimentation, using a large core of mathematics, chemistry, physics, and algorithms. Then we see how animal experiments, aimed at providing a standardized result about a biological property, can be mimicked by new in silico methods. Our emphasis here is on toxicology and on predicting properties through chemical structures. Two main streams of such models are available: models that consider the whole molecular structure to predict a value, namely QSAR (Quantitative Structure Activity Relationships), and models that find relevant substructures to predict a class, namely SAR. The term in silico discovery is applied to chemical design, to computational toxicology, and to drug discovery. We discuss how the experimental practice in biological science is moving more and more toward modeling and simulation. Such virtual experiments confirm hypotheses, provide data for regulation, and help in designing new chemicals. PMID:27311459

  12. History and successes of QSAR in environmental applications

    SciTech Connect

    Veith, G.D.

    1994-12-31

    The history of the development of relationships between chemical structure and chemical behavior for assessing the safety of chemicals is marked by the struggle with timidity that so many areas of science face. Despite a continuous stream of successes for estimating properties and biological activity of chemicals from their structure, the field of QSAR has been met forcibly by the skeptics. In failing to articulate the potential savings in term of costs land test animals, QSAR researchers have enabled the skeptics to prevent a strategic QSAR program from being formed in either the private or the public sectors. QSAR must generate systematic, reference databases for the intrinsic properties of chemicals. Partitioning is such an intrinsic property. QSAR has succeeded not only in calculating hydrophobicity descriptors that control partitioning, but also in using these descriptors in counties relationships for specific endpoints. QSAR has also developed databases for potency. So many structure-toxicity relationships have been published that the potency of over 75 percent of all chemicals produced worldwide can be estimated without further animal testing. Biochemical persistence, as evidenced in biodegradability and/or tissue metabolism, lags behind due, in part, to a shortage of systematic databases. Several interesting approaches will be discussed. Finally, intrinsic reactivity and the selectivity of chemicals among competing interactions must be modeled. Since chemical reactivity holds the key to identifying genotoxic chemicals and other highly toxic chemicals, reactivity models are urgently needed. Recent QSAR advances for some forms of reactivity will be discussed.

  13. Preoperative airway assessment - experience gained from a multicentre cluster randomised trial and the Danish Anaesthesia Database.

    PubMed

    Nørskov, Anders Kehlet

    2016-05-01

    Difficulties with airway management in relation to general anaesthesia have been a challenge for the anaesthesiologist since the birth of anaesthesia. Massive landmark improvements have been made and general anaesthesia is now regarded as a safe procedure. However, rare, difficult airway management still occurs and it prompts increased risk of morbidity and mortality - especially when not anticipated. Several preoperative risk factors for airway difficulties have been identified, yet none have convincing diagnostic accuracy as stand alone tests. Combining several risk factors increase the predictive value of the test and multivariable risk models have been developed. The Simplified Airway Risk Index (SARI) is a predictive model developed for anticipation of a difficult direct laryngoscopy. However, neither the diagnostic accuracy of the SARI nor of any other model has been tested prospectively and compared with existing practice for airway assessment in a randomised trial setting. The first objective of this thesis was to quantify the proportion of unanticipated difficult intubation and difficult mask ventilation in Denmark. The second objective was to design a cluster randomised trial, using state of the art methodology, in order to test the clinical impact of using the SARI for preoperative airway assessment compared with a clinical judgement based on usual practice for airway assessment. Finally, to test if implementation of the SARI would reduce the proportion of unanticipated difficult intubation compared with usual care for airway assessment. This thesis is based on data from the Danish Anaesthesia Database (DAD). Paper 1 presents an observational cohort study on 188,064 patients who underwent tracheal intubation from 2008 to 2011. Data on the anaesthesiologists' preoperative anticipations of airway difficulties was compared with actual airway management conditions, thus enabling an estimation of the proportion of unanticipated difficulties with intubation

  14. Ligand Biological Activity Predictions Using Fingerprint-Based Artificial Neural Networks (FANN-QSAR)

    PubMed Central

    Myint, Kyaw Z.; Xie, Xiang-Qun

    2015-01-01

    This chapter focuses on the fingerprint-based artificial neural networks QSAR (FANN-QSAR) approach to predict biological activities of structurally diverse compounds. Three types of fingerprints, namely ECFP6, FP2, and MACCS, were used as inputs to train the FANN-QSAR models. The results were benchmarked against known 2D and 3D QSAR methods, and the derived models were used to predict cannabinoid (CB) ligand binding activities as a case study. In addition, the FANN-QSAR model was used as a virtual screening tool to search a large NCI compound database for lead cannabinoid compounds. We discovered several compounds with good CB2 binding affinities ranging from 6.70 nM to 3.75 μM. The studies proved that the FANN-QSAR method is a useful approach to predict bioactivities or properties of ligands and to find novel lead compounds for drug discovery research. PMID:25502380

  15. QSAR Models at the US FDA/NCTR.

    PubMed

    Hong, Huixiao; Chen, Minjun; Ng, Hui Wen; Tong, Weida

    2016-01-01

    Quantitative structure-activity relationship (QSAR) has been used in the scientific research community for many decades and applied to drug discovery and development in the industry. QSAR technologies are advancing fast and attracting possible applications in regulatory science. To facilitate the development of reliable QSAR models, the FDA had invested a lot of efforts in constructing chemical databases with a variety of efficacy and safety endpoint data, as well as in the development of computational algorithms. In this chapter, we briefly describe some of the often used databases developed at the FDA such as EDKB (Endocrine Disruptor Knowledge Base), EADB (Estrogenic Activity Database), LTKB (Liver Toxicity Knowledge Base), and CERES (Chemical Evaluation and Risk Estimation System) and the technologies adopted by the agency such as Mold(2) program for calculation of a large and diverse set of molecular descriptors and decision forest algorithm for QSAR model development. We also summarize some QSAR models that have been developed for safety evaluation of the FDA-regulated products. PMID:27311476

  16. Development of quantitative structure activity relationship (QSAR) model for disinfection byproduct (DBP) research: A review of methods and resources.

    PubMed

    Chen, Baiyang; Zhang, Tian; Bond, Tom; Gan, Yiqun

    2015-12-15

    Quantitative structure-activity relationship (QSAR) models are tools for linking chemical activities with molecular structures and compositions. Due to the concern about the proliferating number of disinfection byproducts (DBPs) in water and the associated financial and technical burden, researchers have recently begun to develop QSAR models to investigate the toxicity, formation, property, and removal of DBPs. However, there are no standard procedures or best practices regarding how to develop QSAR models, which potentially limit their wide acceptance. In order to facilitate more frequent use of QSAR models in future DBP research, this article reviews the processes required for QSAR model development, summarizes recent trends in QSAR-DBP studies, and shares some important resources for QSAR development (e.g., free databases and QSAR programs). The paper follows the four steps of QSAR model development, i.e., data collection, descriptor filtration, algorithm selection, and model validation; and finishes by highlighting several research needs. Because QSAR models may have an important role in progressing our understanding of DBP issues, it is hoped that this paper will encourage their future use for this application. PMID:26142156

  17. Automatic generation of alignments for 3D QSAR analyses.

    PubMed

    Jewell, N E; Turner, D B; Willett, P; Sexton, G J

    2001-01-01

    Many 3D QSAR methods require the alignment of the molecules in a dataset, which can require a fair amount of manual effort in deciding upon a rational basis for the superposition. This paper describes the use of FBSS, a program for field-based similarity searching in chemical databases, for generating such alignments automatically. The CoMFA and CoMSIA experiments with several literature datasets show that the QSAR models resulting from the FBSS alignments are broadly comparable in predictive performance with the models resulting from manual alignments. PMID:11774998

  18. Molecular Fingerprint-based Artificial Neural Networks QSAR for Ligand Biological Activity Predictions

    PubMed Central

    Myint, Kyaw-Zeyar; Wang, Lirong; Tong, Qin; Xie, Xiang-Qun

    2012-01-01

    In this manuscript, we have reported a novel 2D fingerprint-based artificial neural network QSAR (FANN-QSAR) method in order to effectively predict biological activities of structurally diverse chemical ligands. Three different types of fingerprints, namely ECFP6, FP2 and MACCS, were used in FANN-QSAR algorithm development, and FANN-QSAR models were compared to known 3D and 2D QSAR methods using five data sets previously reported. In addition, the derived models were used to predict GPCR cannabinoid ligand binding affinities using our manually curated cannabinoid ligand database containing 1699 structurally diverse compounds with reported cannabinoid receptor subtype CB2 activities. To demonstrate its useful applications, the established FANN-QSAR algorithm was used as a virtual screening tool to search a large NCI compound database for lead cannabinoid compounds and we have discovered several compounds with good CB2 binding affinities ranging from 6.70 nM to 3.75 μM. To the best of our knowledge, this is the first report for a fingerprint-based neural network approach validated with a successful virtual screening application in identifying lead compounds. The studies proved that the FANN-QSAR method is a useful approach to predict bioactivities or properties of ligands and to find novel lead compounds for drug discovery research. PMID:22937990

  19. The Microbial Database for Danish wastewater treatment plants with nutrient removal (MiDas-DK) - a tool for understanding activated sludge population dynamics and community stability.

    PubMed

    Mielczarek, A T; Saunders, A M; Larsen, P; Albertsen, M; Stevenson, M; Nielsen, J L; Nielsen, P H

    2013-01-01

    Since 2006 more than 50 Danish full-scale wastewater treatment plants with nutrient removal have been investigated in a project called 'The Microbial Database for Danish Activated Sludge Wastewater Treatment Plants with Nutrient Removal (MiDas-DK)'. Comprehensive sets of samples have been collected, analyzed and associated with extensive operational data from the plants. The community composition was analyzed by quantitative fluorescence in situ hybridization (FISH) supported by 16S rRNA amplicon sequencing and deep metagenomics. MiDas-DK has been a powerful tool to study the complex activated sludge ecosystems, and, besides many scientific articles on fundamental issues on mixed communities encompassing nitrifiers, denitrifiers, bacteria involved in P-removal, hydrolysis, fermentation, and foaming, the project has provided results that can be used to optimize the operation of full-scale plants and carry out trouble-shooting. A core microbial community has been defined comprising the majority of microorganisms present in the plants. Time series have been established, providing an overview of temporal variations in the different plants. Interestingly, although most microorganisms were present in all plants, there seemed to be plant-specific factors that controlled the population composition thereby keeping it unique in each plant over time. Statistical analyses of FISH and operational data revealed some correlations, but less than expected. MiDas-DK (www.midasdk.dk) will continue over the next years and we hope the approach can inspire others to make similar projects in other parts of the world to get a more comprehensive understanding of microbial communities in wastewater engineering. PMID:23752384

  20. 3D-QSAR studies on Plasmodium falciparam proteins: a mini-review.

    PubMed

    Divakar, Selva; Hariharan, Sivaram

    2015-01-01

    3D-QSAR has become a very important tool in the field of Drug Discovery, especially in important areas like malarial research. The 3D-QSAR is principally a ligand-based drug design but the bioactive conformation of the ligand can also be taken into account in constructing a 3D-QSAR model. The induction of receptor-based 3D-QSAR has been proven to give more robust statistical models. In this review, we have discussed the various 3D-QSAR works done so far which were aimed at combating malaria caused by Plasmodium falciparam. We have also discussed the various enzymes/receptors (targets) in Plasmodium falciparam for which the 3D-QSAR had been generated. The enzymes - wild and mutated dihydrofolate reductase, enoyl acyl protein carrier protein reductase, farnesyltransferase, cytochrome bc1, and falcipains were the major targets for pharmacophore-based drug design. Apart from the above-mentioned targets there were many scaffolds for which the target macromolecule was undefined and could have single/multiple targets. The generated 3D-QSAR model can be used to identify hits by screening the pharmacophore against a chemical library. In this review, the hits identified against various targets of plasmodium falciparam that have been discussed along with their basic scaffold. The various software programs and chemical databases that have been used in the generation of 3D-QSAR and screening were given. From this review, we understand that there is a considerable need to develop novel scaffolds that are different from the existing ligands to overcome cross-resistance. PMID:25543683

  1. New public QSAR model for carcinogenicity

    PubMed Central

    2010-01-01

    Background One of the main goals of the new chemical regulation REACH (Registration, Evaluation and Authorization of Chemicals) is to fulfill the gaps in data concerned with properties of chemicals affecting the human health. (Q)SAR models are accepted as a suitable source of information. The EU funded CAESAR project aimed to develop models for prediction of 5 endpoints for regulatory purposes. Carcinogenicity is one of the endpoints under consideration. Results Models for prediction of carcinogenic potency according to specific requirements of Chemical regulation were developed. The dataset of 805 non-congeneric chemicals extracted from Carcinogenic Potency Database (CPDBAS) was used. Counter Propagation Artificial Neural Network (CP ANN) algorithm was implemented. In the article two alternative models for prediction carcinogenicity are described. The first model employed eight MDL descriptors (model A) and the second one twelve Dragon descriptors (model B). CAESAR's models have been assessed according to the OECD principles for the validation of QSAR. For the model validity we used a wide series of statistical checks. Models A and B yielded accuracy of training set (644 compounds) equal to 91% and 89% correspondingly; the accuracy of the test set (161 compounds) was 73% and 69%, while the specificity was 69% and 61%, respectively. Sensitivity in both cases was equal to 75%. The accuracy of the leave 20% out cross validation for the training set of models A and B was equal to 66% and 62% respectively. To verify if the models perform correctly on new compounds the external validation was carried out. The external test set was composed of 738 compounds. We obtained accuracy of external validation equal to 61.4% and 60.0%, sensitivity 64.0% and 61.8% and specificity equal to 58.9% and 58.4% respectively for models A and B. Conclusion Carcinogenicity is a particularly important endpoint and it is expected that QSAR models will not replace the human experts opinions

  2. The formation and design of the 'Acute Admission Database'- a database including a prospective, observational cohort of 6279 patients triaged in the emergency department in a larger Danish hospital

    PubMed Central

    2012-01-01

    Background Management and care of the acutely ill patient has improved over the last years due to introduction of systematic assessment and accelerated treatment protocols. We have, however, sparse knowledge of the association between patient status at admission to hospital and patient outcome. A likely explanation is the difficulty in retrieving all relevant information from one database. The objective of this article was 1) to describe the formation and design of the 'Acute Admission Database', and 2) to characterize the cohort included. Methods All adult patients triaged at the Emergency Department at Hillerød Hospital and admitted either to the observationary unit or to a general ward in-hospital were prospectively included during a period of 22 weeks. The triage system used was a Danish adaptation of the Swedish triage system, ADAPT. Data from 3 different data sources was merged using a unique identifier, the Central Personal Registry number; 1) Data from patient admission; time and date, vital signs, presenting complaint and triage category, 2) Blood sample results taken at admission, including a venous acid-base status, and 3) Outcome measures, e.g. length of stay, admission to Intensive Care Unit, and mortality within 7 and 28 days after admission. Results In primary triage, patients were categorized as red (4.4%), orange (25.2%), yellow (38.7%) and green (31.7%). Abnormal vital signs were present at admission in 25% of the patients, most often temperature (10.5%), saturation of peripheral oxygen (9.2%), Glasgow Coma Score (6.6%) and respiratory rate (4.8%). A venous acid-base status was obtained in 43% of all patients. The majority (78%) had a pH within the normal range (7.35-7.45), 15% had acidosis (pH < 7.35) and 7% had alkalosis (pH > 7.45). Median length of stay was 2 days (range 1-123). The proportion of patients admitted to Intensive Care Unit was 1.6% (95% CI 1.2-2.0), 1.8% (95% CI 1.5-2.2) died within 7 days, and 4.2% (95% CI 3.7-4.7) died within

  3. Combinatorial QSAR Modeling of Rat Acute Toxicity by Oral Exposure

    EPA Science Inventory

    Quantitative Structure-Activity Relationship (QSAR) toxicity models have become popular tools for identifying potential toxic compounds and prioritizing candidates for animal toxicity tests. However, few QSAR studies have successfully modeled large, diverse mammalian toxicity end...

  4. QSAR models for reproductive toxicity and endocrine disruption in regulatory use – a preliminary investigation†

    PubMed Central

    Jensen, G.E.; Niemelä, J.R.; Wedebye, E.B.; Nikolov, N.G.

    2008-01-01

    A special challenge in the new European Union chemicals legislation, Registration, Evaluation and Authorisation of Chemicals, will be the toxicological evaluation of chemicals for reproductive toxicity. Use of valid quantitative structure–activity relationships (QSARs) is a possibility under the new legislation. This article focuses on a screening exercise by use of our own and commercial QSAR models for identification of possible reproductive toxicants. Three QSAR models were used for reproductive toxicity for the endpoints teratogenic risk to humans (based on animal tests, clinical data and epidemiological human studies), dominant lethal effect in rodents (in vivo) and Drosophila melanogaster sex-linked recessive lethal effect. A structure set of 57,014 European Inventory of Existing Chemical Substances (EINECS) chemicals was screened. A total of 5240 EINECS chemicals, corresponding to 9.2%, were predicted as reproductive toxicants by one or more of the models. The chemicals predicted positive for reproductive toxicity will be submitted to the Danish Environmental Protection Agency as scientific input for a future updated advisory classification list with advisory classifications for concern for humans owing to possible developmental toxic effects: Xn (Harmful) and R63 (Possible risk of harm to the unborn child). The chemicals were also screened in three models for endocrine disruption. PMID:19061080

  5. Modeling Liver-Related Adverse Effects of Drugs Using kNN QSAR Method

    PubMed Central

    Rodgers, Amie D.; Zhu, Hao; Fourches, Dennis; Rusyn, Ivan; Tropsha, Alexander

    2010-01-01

    Adverse effects of drugs (AEDs) continue to be a major cause of drug withdrawals both in development and post-marketing. While liver-related AEDs are a major concern for drug safety, there are few in silico models for predicting human liver toxicity for drug candidates. We have applied the Quantitative Structure Activity Relationship (QSAR) approach to model liver AEDs. In this study, we aimed to construct a QSAR model capable of binary classification (active vs. inactive) of drugs for liver AEDs based on chemical structure. To build QSAR models, we have employed an FDA spontaneous reporting database of human liver AEDs (elevations in activity of serum liver enzymes), which contains data on approximately 500 approved drugs. Approximately 200 compounds with wide clinical data coverage, structural similarity and balanced (40/60) active/inactive ratio were selected for modeling and divided into multiple training/test and external validation sets. QSAR models were developed using the k nearest neighbor method and validated using external datasets. Models with high sensitivity (>73%) and specificity (>94%) for prediction of liver AEDs in external validation sets were developed. To test applicability of the models, three chemical databases (World Drug Index, Prestwick Chemical Library, and Biowisdom Liver Intelligence Module) were screened in silico and the validity of predictions was determined, where possible, by comparing model-based classification with assertions in publicly available literature. Validated QSAR models of liver AEDs based on the data from the FDA spontaneous reporting system can be employed as sensitive and specific predictors of AEDs in pre-clinical screening of drug candidates for potential hepatotoxicity in humans. PMID:20192250

  6. QSAR as a random event: modeling of nanoparticles uptake in PaCa2 cancer cells.

    PubMed

    Toropov, Andrey A; Toropova, Alla P; Puzyn, Tomasz; Benfenati, Emilio; Gini, Giuseppina; Leszczynska, Danuta; Leszczynski, Jerzy

    2013-06-01

    Quantitative structure-property/activity relationships (QSPRs/QSARs) are a tool to predict various endpoints for various substances. The "classic" QSPR/QSAR analysis is based on the representation of the molecular structure by the molecular graph. However, simplified molecular input-line entry system (SMILES) gradually becomes most popular representation of the molecular structure in the databases available on the Internet. Under such circumstances, the development of molecular descriptors calculated directly from SMILES becomes attractive alternative to "classic" descriptors. The CORAL software (http://www.insilico.eu/coral) is provider of SMILES-based optimal molecular descriptors which are aimed to correlate with various endpoints. We analyzed data set on nanoparticles uptake in PaCa2 pancreatic cancer cells. The data set includes 109 nanoparticles with the same core but different surface modifiers (small organic molecules). The concept of a QSAR as a random event is suggested in opposition to "classic" QSARs which are based on the only one distribution of available data into the training and the validation sets. In other words, five random splits into the "visible" training set and the "invisible" validation set were examined. The SMILES-based optimal descriptors (obtained by the Monte Carlo technique) for these splits are calculated with the CORAL software. The statistical quality of all these models is good. PMID:23566368

  7. QSAR Studies of Copper Azamacrocycles and Thiosemicarbazones

    PubMed Central

    Wolohan, Peter; Yoo, Jeongsoo; Welch, Michael J.; Reichert, David E.

    2008-01-01

    Genetic algorithms (GA) were used to develop specific copper metal-ligand force field parameters for the MM3 force field, from a combination of crystallographic structures and ab initio calculations. These new parameters produced results in good agreement with experiment and previously reported copper metal-ligand parameters for the AMBER force field. The MM3 parameters were then used to develop several Quantitative Structure Activity Relationship (QSAR) models. A successful QSAR for predicting the lipophilicity (logPow) of several classes of Cu(II) chelating ligands, was built using a training set of thirty-two Cu(II) radiometal complexes and six simple molecular descriptors. The QSAR exhibited a correlation between the predicted and experimental logPow with a r2 = 0.95, q2 = 0.92. When applied to an external test set of eleven Cu(II) complexes the QSAR preformed with great accuracy; r2 = 0.93 and a q2 = 0.91 utilizing a leave-one-out cross-validation analysis. Additional QSAR models were developed to predict the biodistribution of a smaller set of Cu(II) bis(thiosemicarbazone) complexes. PMID:16107156

  8. Integration of QSAR and in vitro toxicology.

    PubMed Central

    Barratt, M D

    1998-01-01

    The principles of quantitative structure-activity relationships (QSAR) are based on the premise that the properties of a chemical are implicit in its molecular structure. Therefore, if a mechanistic hypothesis can be proposed linking a group of related chemicals with a particular toxic end point, the hypothesis can be used to define relevant parameters to establish a QSAR. Ways in which QSAR and in vitro toxicology can complement each other in development of alternatives to live animal experiments are described and illustrated by examples from acute toxicological end points. Integration of QSAR and in vitro methods is examined in the context of assessing mechanistic competence and improving the design of in vitro assays and the development of prediction models. The nature of biological variability is explored together with its implications for the selection of sets of chemicals for test development, optimization, and validation. Methods are described to support the use of data from in vivo tests that do not meet today's stringent requirements of acceptability. Integration of QSAR and in vitro methods into strategic approaches for the replacement, reduction, and refinement of the use of animals is described with examples. PMID:9599692

  9. Predictive QSAR modeling of phosphodiesterase 4 inhibitors.

    PubMed

    Kovalishyn, Vasyl; Tanchuk, Vsevolod; Charochkina, Larisa; Semenuta, Ivan; Prokopenko, Volodymyr

    2012-02-01

    A series of diverse organic compounds, phosphodiesterase type 4 (PDE-4) inhibitors, have been modeled using a QSAR-based approach. 48 QSAR models were compared by following the same procedure with different combinations of descriptors and machine learning methods. QSAR methodologies used random forests and associative neural networks. The predictive ability of the models was tested through leave-one-out cross-validation, giving a Q² = 0.66-0.78 for regression models and total accuracies Ac=0.85-0.91 for classification models. Predictions for the external evaluation sets obtained accuracies in the range of 0.82-0.88 (for active/inactive classifications) and Q² = 0.62-0.76 for regressions. The method showed itself to be a potential tool for estimation of IC₅₀ of new drug-like candidates at early stages of drug development. PMID:22023934

  10. Inferring multi-target QSAR models with taxonomy-based multi-task learning

    PubMed Central

    2013-01-01

    Background A plethora of studies indicate that the development of multi-target drugs is beneficial for complex diseases like cancer. Accurate QSAR models for each of the desired targets assist the optimization of a lead candidate by the prediction of affinity profiles. Often, the targets of a multi-target drug are sufficiently similar such that, in principle, knowledge can be transferred between the QSAR models to improve the model accuracy. In this study, we present two different multi-task algorithms from the field of transfer learning that can exploit the similarity between several targets to transfer knowledge between the target specific QSAR models. Results We evaluated the two methods on simulated data and a data set of 112 human kinases assembled from the public database ChEMBL. The relatedness between the kinase targets was derived from the taxonomy of the humane kinome. The experiments show that multi-task learning increases the performance compared to training separate models on both types of data given a sufficient similarity between the tasks. On the kinase data, the best multi-task approach improved the mean squared error of the QSAR models of 58 kinase targets. Conclusions Multi-task learning is a valuable approach for inferring multi-target QSAR models for lead optimization. The application of multi-task learning is most beneficial if knowledge can be transferred from a similar task with a lot of in-domain knowledge to a task with little in-domain knowledge. Furthermore, the benefit increases with a decreasing overlap between the chemical space spanned by the tasks. PMID:23842210

  11. QSAR DataBank - an approach for the digital organization and archiving of QSAR model information

    PubMed Central

    2014-01-01

    Background Research efforts in the field of descriptive and predictive Quantitative Structure-Activity Relationships or Quantitative Structure–Property Relationships produce around one thousand scientific publications annually. All the materials and results are mainly communicated using printed media. The printed media in its present form have obvious limitations when they come to effectively representing mathematical models, including complex and non-linear, and large bodies of associated numerical chemical data. It is not supportive of secondary information extraction or reuse efforts while in silico studies poses additional requirements for accessibility, transparency and reproducibility of the research. This gap can and should be bridged by introducing domain-specific digital data exchange standards and tools. The current publication presents a formal specification of the quantitative structure-activity relationship data organization and archival format called the QSAR DataBank (QsarDB for shorter, or QDB for shortest). Results The article describes QsarDB data schema, which formalizes QSAR concepts (objects and relationships between them) and QsarDB data format, which formalizes their presentation for computer systems. The utility and benefits of QsarDB have been thoroughly tested by solving everyday QSAR and predictive modeling problems, with examples in the field of predictive toxicology, and can be applied for a wide variety of other endpoints. The work is accompanied with open source reference implementation and tools. Conclusions The proposed open data, open source, and open standards design is open to public and proprietary extensions on many levels. Selected use cases exemplify the benefits of the proposed QsarDB data format. General ideas for future development are discussed. PMID:24910716

  12. QSAR-Driven Discovery of Novel Chemical Scaffolds Active against Schistosoma mansoni.

    PubMed

    Melo-Filho, Cleber C; Dantas, Rafael F; Braga, Rodolpho C; Neves, Bruno J; Senger, Mario R; Valente, Walter C G; Rezende-Neto, João M; Chaves, Willian T; Muratov, Eugene N; Paveley, Ross A; Furnham, Nicholas; Kamentsky, Lee; Carpenter, Anne E; Silva-Junior, Floriano P; Andrade, Carolina H

    2016-07-25

    Schistosomiasis is a neglected tropical disease that affects millions of people worldwide. Thioredoxin glutathione reductase of Schistosoma mansoni (SmTGR) is a validated drug target that plays a crucial role in the redox homeostasis of the parasite. We report the discovery of new chemical scaffolds against S. mansoni using a combi-QSAR approach followed by virtual screening of a commercial database and confirmation of top ranking compounds by in vitro experimental evaluation with automated imaging of schistosomula and adult worms. We constructed 2D and 3D quantitative structure-activity relationship (QSAR) models using a series of oxadiazoles-2-oxides reported in the literature as SmTGR inhibitors and combined the best models in a consensus QSAR model. This model was used for a virtual screening of Hit2Lead set of ChemBridge database and allowed the identification of ten new potential SmTGR inhibitors. Further experimental testing on both shistosomula and adult worms showed that 4-nitro-3,5-bis(1-nitro-1H-pyrazol-4-yl)-1H-pyrazole (LabMol-17) and 3-nitro-4-{[(4-nitro-1,2,5-oxadiazol-3-yl)oxy]methyl}-1,2,5-oxadiazole (LabMol-19), two compounds representing new chemical scaffolds, have high activity in both systems. These compounds will be the subjects for additional testing and, if necessary, modification to serve as new schistosomicidal agents. PMID:27253773

  13. Virtual Screening and Molecular Design Based on Hierarchical Qsar Technology

    NASA Astrophysics Data System (ADS)

    Kuz'min, Victor E.; Artemenko, A. G.; Muratov, Eugene N.; Polischuk, P. G.; Ognichenko, L. N.; Liahovsky, A. V.; Hromov, A. I.; Varlamova, E. V.

    This chapter is devoted to the hierarchical QSAR technology (HiT QSAR) based on simplex representation of molecular structure (SiRMS) and its application to different QSAR/QSPR tasks. The essence of this technology is a sequential solution (with the use of the information obtained on the previous steps) of the QSAR paradigm by a series of enhanced models based on molecular structure description (in a specific order from 1D to 4D). Actually, it's a system of permanently improved solutions. Different approaches for domain applicability estimation are implemented in HiT QSAR. In the SiRMS approach every molecule is represented as a system of different simplexes (tetratomic fragments with fixed composition, structure, chirality, and symmetry). The level of simplex descriptors detailed increases consecutively from the 1D to 4D representation of the molecular structure. The advantages of the approach presented are an ability to solve QSAR/QSPR tasks for mixtures of compounds, the absence of the "molecular alignment" problem, consideration of different physical-chemical properties of atoms (e.g., charge, lipophilicity), and the high adequacy and good interpretability of obtained models and clear ways for molecular design. The efficiency of HiT QSAR was demonstrated by its comparison with the most popular modern QSAR approaches on two representative examination sets. The examples of successful application of the HiT QSAR for various QSAR/QSPR investigations on the different levels (1D-4D) of the molecular structure description are also highlighted. The reliability of developed QSAR models as the predictive virtual screening tools and their ability to serve as the basis of directed drug design was validated by subsequent synthetic, biological, etc. experiments. The HiT QSAR is realized as the suite of computer programs termed the "HiT QSAR" software that so includes powerful statistical capabilities and a number of useful utilities.

  14. CURRENT PRACTICES IN QSAR DEVELOPMENT AND APPLICATIONS

    EPA Science Inventory

    Current Practices in QSAR Development and Applications

    Although it is commonly assumed that the structure and properties of a single chemical determines its activity in a particular biological system, it is only through study of how biological activity varies with changes...

  15. Trust, but verify: On the importance of chemical structure curation in cheminformatics and QSAR modeling research

    PubMed Central

    Fourches, Denis; Muratov, Eugene; Tropsha, Alexander

    2010-01-01

    Molecular modelers and cheminformaticians typically analyze experimental data generated by other scientists. Consequently, when it comes to data accuracy, cheminformaticians are always at the mercy of data providers who may inadvertently publish (partially) erroneous data. Thus, dataset curation is crucial for any cheminformatics analysis such as similarity searching, clustering, QSAR modeling, virtual screening, etc., especially nowadays when the availability of chemical datasets in public domain has skyrocketed in recent years. Despite the obvious importance of this preliminary step in the computational analysis of any dataset, there appears to be no commonly accepted guidance or set of procedures for chemical data curation. The main objective of this paper is to emphasize the need for a standardized chemical data curation strategy that should be followed at the onset of any molecular modeling investigation. Herein, we discuss several simple but important steps for cleaning chemical records in a database including the removal of a fraction of the data that cannot be appropriately handled by conventional cheminformatics techniques. Such steps include the removal of inorganic and organometallic compounds, counterions, salts and mixtures; structure validation; ring aromatization; normalization of specific chemotypes; curation of tautomeric forms; and the deletion of duplicates. To emphasize the importance of data curation as a mandatory step in data analysis, we discuss several case studies where chemical curation of the original “raw” database enabled the successful modeling study (specifically, QSAR analysis) or resulted in a significant improvement of model's prediction accuracy. We also demonstrate that in some cases rigorously developed QSAR models could be even used to correct erroneous biological data associated with chemical compounds. We believe that good practices for curation of chemical records outlined in this paper will be of value to all

  16. Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds

    SciTech Connect

    Alves, Vinicius M.; Muratov, Eugene; Fourches, Denis; Strickland, Judy; Kleinstreuer, Nicole; Tropsha, Alexander

    2015-04-15

    Repetitive exposure to a chemical agent can induce an immune reaction in inherently susceptible individuals that leads to skin sensitization. Although many chemicals have been reported as skin sensitizers, there have been very few rigorously validated QSAR models with defined applicability domains (AD) that were developed using a large group of chemically diverse compounds. In this study, we have aimed to compile, curate, and integrate the largest publicly available dataset related to chemically-induced skin sensitization, use this data to generate rigorously validated and QSAR models for skin sensitization, and employ these models as a virtual screening tool for identifying putative sensitizers among environmental chemicals. We followed best practices for model building and validation implemented with our predictive QSAR workflow using Random Forest modeling technique in combination with SiRMS and Dragon descriptors. The Correct Classification Rate (CCR) for QSAR models discriminating sensitizers from non-sensitizers was 71–88% when evaluated on several external validation sets, within a broad AD, with positive (for sensitizers) and negative (for non-sensitizers) predicted rates of 85% and 79% respectively. When compared to the skin sensitization module included in the OECD QSAR Toolbox as well as to the skin sensitization model in publicly available VEGA software, our models showed a significantly higher prediction accuracy for the same sets of external compounds as evaluated by Positive Predicted Rate, Negative Predicted Rate, and CCR. These models were applied to identify putative chemical hazards in the Scorecard database of possible skin or sense organ toxicants as primary candidates for experimental validation. - Highlights: • It was compiled the largest publicly-available skin sensitization dataset. • Predictive QSAR models were developed for skin sensitization. • Developed models have higher prediction accuracy than OECD QSAR Toolbox. • Putative

  17. 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. PMID:26669717

  18. Toxico-Cheminformatics and QSPR Modeling of the Carcinogenic Potency Database

    EPA Science Inventory

    Report on the development of a tiered, confirmatory scheme for prediction of chemical carcinogenicity based on QSAR studies of compounds with available mutagenic and carcinogenic data. For 693 such compounds from the Carcinogenic Potency Database characterized molecular topologic...

  19. Residual-QSAR. Implications for genotoxic carcinogenesis

    PubMed Central

    2011-01-01

    Introduction Both main types of carcinogenesis, genotoxic and epigenetic, were examined in the context of non-congenericity and similarity, respectively, for the structure of ligand molecules, emphasizing the role of quantitative structure-activity relationship ((Q)SAR) studies in accordance with OECD (Organization for Economic and Cooperation Development) regulations. The main purpose of this report involves electrophilic theory and the need for meaningful physicochemical parameters to describe genotoxicity by a general mechanism. Residual-QSAR Method The double or looping multiple linear correlation was examined by comparing the direct and residual structural information against the observed activity. A self-consistent equation of observed-computed activity was assumed to give maximum correlation efficiency for those situations in which the direct correlations gave non-significant statistical information. Alternatively, it was also suited to describe slow and apparently non-noticeable cancer phenomenology, with special application to non-congeneric molecules involved in genotoxic carcinogenesis. Application and Discussions The QSAR principles were systematically applied to a given pool of molecules with genotoxic activity in rats to elucidate their carcinogenic mechanisms. Once defined, the endpoint associated with ligand-DNA interaction was used to select variables that retained the main Hansch physicochemical parameters of hydrophobicity, polarizability and stericity, computed by the custom PM3 semiempirical quantum method. The trial and test sets of working molecules were established by implementing the normal Gaussian principle of activities that applies when the applicability domain is not restrained to the congeneric compounds, as in the present study. The application of the residual, self-consistent QSAR method and the factor (or average) method yielded results characterized by extremely high and low correlations, respectively, with the latter resembling

  20. Toward a general predictive QSAR model for gamma-secretase inhibitors.

    PubMed

    Ajmani, Subhash; Janardhan, Sridhara; Viswanadhan, Vellarkad N

    2013-08-01

    Gamma secretase (GS) is an appealing drug target for Alzheimer disease and cancer because of its central role in the processing of amyloid precursor protein and the notch family of proteins. In the absence of three-dimensional structure of GS, there is an urgent need for new methods for the prediction and screening of GS inhibitors, for facilitating discovery of novel GS inhibitors. The present study reports QSAR studies on diverse chemical classes comprising 233 compounds collected from the ChEMBL database. Herein, continuous [PLS regression and neural-network (NN)] and categorical QSAR models (NN and linear discriminant analysis) were developed to obtain pertinent descriptors responsible for variation of GS inhibitor potency. Also, SAR within various chemical classes of compounds is analyzed with respect to important QSAR descriptors, which revealed the significance of electronegative substitutions on aryl rings (PEOE3) in determining variation of GS inhibitor potency. Furthermore, substitution of acyclic amines with N-substituted cyclic amines appears to be favorable for enhancing GS inhibitor potency by increasing the values of sssN_Cnt and number of aliphatic rings. The models developed are statistically significant and improve our understanding of compounds contributing toward GS inhibitor potency and aid in the rational design of novel potent GS inhibitors. PMID:23612850

  1. Prediction of acute mammalian toxicity using QSAR methods: a case study of sulfur mustard and its breakdown products.

    PubMed

    Ruiz, Patricia; Begluitti, Gino; Tincher, Terry; Wheeler, John; Mumtaz, Moiz

    2012-01-01

    Predicting toxicity quantitatively, using Quantitative Structure Activity Relationships (QSAR), has matured over recent years to the point that the predictions can be used to help identify missing comparison values in a substance's database. In this manuscript we investigate using the lethal dose that kills fifty percent of a test population (LD₅₀) for determining relative toxicity of a number of substances. In general, the smaller the LD₅₀ value, the more toxic the chemical, and the larger the LD₅₀ value, the lower the toxicity. When systemic toxicity and other specific toxicity data are unavailable for the chemical(s) of interest, during emergency responses, LD₅₀ values may be employed to determine the relative toxicity of a series of chemicals. In the present study, a group of chemical warfare agents and their breakdown products have been evaluated using four available rat oral QSAR LD₅₀ models. The QSAR analysis shows that the breakdown products of Sulfur Mustard (HD) are predicted to be less toxic than the parent compound as well as other known breakdown products that have known toxicities. The QSAR estimated break down products LD₅₀ values ranged from 299 mg/kg to 5,764 mg/kg. This evaluation allows for the ranking and toxicity estimation of compounds for which little toxicity information existed; thus leading to better risk decision making in the field. PMID:22842643

  2. DYNAMIC 3D QSAR TECHNIQUES: APPLICATIONS IN TOXICOLOGY

    EPA Science Inventory

    Two dynamic techniques recently developed to account for conformational flexibility of chemicals in 3D QSARs are presented. In addition to the impact of conformational flexibility of chemicals in 3D QSAR models, the applicability of various molecular descriptors is discussed. The...

  3. (Q)SAR: A Tool for the Toxicologist.

    PubMed

    Steinbach, Thomas; Gad-McDonald, Samantha; Kruhlak, Naomi; Powley, Mark; Greene, Nigel

    2015-01-01

    A continuing education (CE) course at the 2014 American College of Toxicology annual meeting covered the topic of (Quantitative) Structure-Activity Relationships [(Q)SAR]. The (Q)SAR methodologies use predictive computer modeling based on predefined rules to describe the relationship between chemical structure and a chemical's associated biological activity or statistical tools to find correlations between biologic activity and the molecular structure or properties of a compound. The (Q)SAR has applications in risk assessment, drug discovery, and regulatory decision making. Pressure within industry to reduce the cost of drug development and societal pressure for government regulatory agencies to produce more accurate and timely risk assessment of drugs and chemicals have necessitated the use of (Q)SAR. Producing a high-quality (Q)SAR model depends on many factors including the choice of statistical methods and descriptors, but first and foremost the quality of the data input into the model. Understanding how a (Q)SAR model is developed and applied is critical to the successful use of such a tool. The CE session covered the basic principles of (Q)SAR, practical applications of these computational models in toxicology, how regulatory agencies use and interpret (Q)SAR models, and potential pitfalls of using them. PMID:25979517

  4. Discovery of potent adenosine A2a antagonists as potential anti-Parkinson disease agents. Non-linear QSAR analyses integrated with pharmacophore modeling.

    PubMed

    Khanfar, Mohammad A; Al-Qtaishat, Saja; Habash, Maha; Taha, Mutasem O

    2016-07-25

    Adenosine A2A receptor antagonists are of great interest in the treatment for Parkinson's disease. In this study, we combined extensive pharmacophore modeling and quantitative structure-activity relationship (QSAR) analysis to explore the structural requirements for potent Adenosine A2A antagonists. Genetic function algorithm (GFA) joined with k nearest neighbor (kNN) analyses were applied to build predictive QSAR models. Successful pharmacophores were complemented with exclusion spheres to improve their receiver operating characteristic curve (ROC) profiles. Best QSAR models and their associated pharmacophore hypotheses were validated by identification of several novel Adenosine A2A antagonist leads retrieved from the National Cancer Institute (NCI) structural database. The most potent hit illustrated IC50 value of 545.7 nM. PMID:27216633

  5. Fish acute toxicity syndromes and their use in the QSAR approach to hazard assessment

    SciTech Connect

    McKim, J.M.; Bradbury, S.P.; Niemi, G.J.

    1987-04-01

    Implementation of the Toxic Substances Control Act of 1977 creates the need to reliably establish testing priorities because laboratory resources are limited and the number of industrial chemicals requiring evaluation is overwhelming. The use of quantitative structure activity relationship (QSAR) models as rapid and predictive screening tools to select more potentially hazardous chemicals for in-depth laboratory evaluation has been proposed. Further implementation and refinement of quantitative structure-toxicity relationships in aqueous toxicology and hazard assessment requires the development of a mode-of-action database. With such a database, a qualitative structure-activity relationship can be formulated to assign the proper mode of action, and respective QSAR, to a given chemical structure. In this review, the development of fish acute toxicity syndromes (FATS), which are toxic-response sets based on various behavioral and physiological-biochemical measurements, and their projected use in the mode-of-action database are outlined. Using behavioral parameters monitored in the fathead minnow during acute toxicity testing, FATS associated with acetylcholinesterase (AChE) inhibitors and narcotics could be reliably predicted. However, compounds classified as oxidative phosphorylation uncouplers or stimulants could not be resolved. Refinement of this approach by using respiratory-cardiovascular responses in the rainbow trout, enabled FATS associated with AChE inhibitors, convulsants, narcotics, respiratory blockers, respiratory membrane irritants, and uncouplers to be correctly predicted.

  6. Extending (Q)SARs to incorporate proprietary knowledge for regulatory purposes: A case study using aromatic amine mutagenicity.

    PubMed

    Ahlberg, Ernst; Amberg, Alexander; Beilke, Lisa D; Bower, David; Cross, Kevin P; Custer, Laura; Ford, Kevin A; Van Gompel, Jacky; Harvey, James; Honma, Masamitsu; Jolly, Robert; Joossens, Elisabeth; Kemper, Raymond A; Kenyon, Michelle; Kruhlak, Naomi; Kuhnke, Lara; Leavitt, Penny; Naven, Russell; Neilan, Claire; Quigley, Donald P; Shuey, Dana; Spirkl, Hans-Peter; Stavitskaya, Lidiya; Teasdale, Andrew; White, Angela; Wichard, Joerg; Zwickl, Craig; Myatt, Glenn J

    2016-06-01

    Statistical-based and expert rule-based models built using public domain mutagenicity knowledge and data are routinely used for computational (Q)SAR assessments of pharmaceutical impurities in line with the approach recommended in the ICH M7 guideline. Knowledge from proprietary corporate mutagenicity databases could be used to increase the predictive performance for selected chemical classes as well as expand the applicability domain of these (Q)SAR models. This paper outlines a mechanism for sharing knowledge without the release of proprietary data. Primary aromatic amine mutagenicity was selected as a case study because this chemical class is often encountered in pharmaceutical impurity analysis and mutagenicity of aromatic amines is currently difficult to predict. As part of this analysis, a series of aromatic amine substructures were defined and the number of mutagenic and non-mutagenic examples for each chemical substructure calculated across a series of public and proprietary mutagenicity databases. This information was pooled across all sources to identify structural classes that activate or deactivate aromatic amine mutagenicity. This structure activity knowledge, in combination with newly released primary aromatic amine data, was incorporated into Leadscope's expert rule-based and statistical-based (Q)SAR models where increased predictive performance was demonstrated. PMID:26879463

  7. Discovery of new potent human protein tyrosine phosphatase inhibitors via pharmacophore and QSAR analysis followed by in silico screening.

    PubMed

    Taha, Mutasem O; Bustanji, Yasser; Al-Bakri, Amal G; Yousef, Al-Motassem; Zalloum, Waleed A; Al-Masri, Ihab M; Atallah, Naji

    2007-03-01

    A pharmacophoric model was developed for human protein tyrosine phosphatase 1B (h-PTP 1B) inhibitors utilizing the HipHop-REFINE module of CATALYST software. Subsequently, genetic algorithm and multiple linear regression analysis were employed to select an optimal combination of physicochemical descriptors and pharmacophore hypothesis that yield consistent QSAR equation of good predictive potential (r = 0.87,F-statistic = 69.13,r(BS)2 = 0.76,r(LOO)2 = 0.68). The validity of the QSAR equation and the associated pharmacophoric hypothesis was experimentally established by the identification of five new h-PTP 1B inhibitors retrieved from the National Cancer Institute (NCI) database. PMID:17035054

  8. Comparison of a neural net-based QSAR algorithm (PCANN) with Hologram- and multiple linear regression-based QSAR approaches: application to 1,4-dihydropyridine-based calcium channel antagonists.

    PubMed

    Viswanadhan, V N; Mueller, G A; Basak, S C; Weinstein, J N

    2001-01-01

    A QSAR algorithm (PCANN) has been developed and applied to a set of calcium channel blockers which are of special interest because of their role in cardiac disease and also because many of them interact with P-glycoprotein, a membrane protein associated with multidrug resistance to anticancer agents. A database of 46 1,4-dihydropyridines with known Ca2+ channel binding affinities was employed for the present analysis. The QSAR algorithm can be summarized as follows: (1) a set of 90 graph theoretic and information theoretic descriptors representing various structural and topological characteristics was calculated for each of the 1,4-dihydropyridines and (2) principal component analysis (PCA) was used to compress these 90 into the eight best orthogonal composite descriptors for the database. These eight sufficed to explain 96% of the variance in the original descriptor set. (3) Two important empirical descriptors, the Leo-Hansch lipophilic constant and the Hammet electronic parameter, were added to the list of eight. (4) The 10 resulting descriptors were used as inputs to a back-propagation neural network whose output was the predicted binding affinity. (5) The predictive ability of the network was assessed by cross-validation. A comparison of the present approach with two other QSAR approaches (multiple linear regression using the same variables and a Hologram QSAR model) is made and shows that the PCANN approach can yield better predictions, once the right network configuration is identified. The present approach (PCANN) may prove useful for rapid assessment of the potential for biological activity when dealing with large chemical libraries. PMID:11410024

  9. Using Toxicological Evidence from QSAR Models in Practice

    EPA Science Inventory

    The new generation of QSAR models provides supporting documentation in addition to the predicted toxicological value. Such information enables the toxicologist to explore the properties of chemical substances and to review and increase the reliability of toxicity predictions. Thi...

  10. SEDIMENT-ASSOCIATED REACTIONS OF AROMATIC AMINES: QSAR DEVELOPMENT

    EPA Science Inventory

    Despite the common occurrence of the aromatic amine functional group in environmental contaminants, few quantitative structure-activity relationships (QSARs) have been developed to predict sorption kinetics for aromatic amines in natural soils and sediments. Towards the goal of d...

  11. Quantitative Structure-Activity Relationships (QSARs) - Applications and Methodology

    NASA Astrophysics Data System (ADS)

    Cronin, Mark T. D.

    The aim of this introduction is to describe briefly the applications and methodologies involved in (Q)SAR and relate these to the various chapters in this volume. This chapter gives the reader an overview of how, why and where in silico methods, including (Q)SAR, have been utilized to predict endpoints as diverse as those from pharmacology and toxicology. It provides an illustration of how all the various topics in this book interweave to form a single coherent area of science.

  12. QSAR based docking studies of marine algal anticancer compounds as inhibitors of protein kinase B (PKBβ).

    PubMed

    Davis, G Dicky John; Vasanthi, A Hannah Rachel

    2015-08-30

    Marine algae are prolific source of bioactive secondary metabolites and are found to be active against different cancer cell lines. QSAR studies will explicate the significance of a particular class of descriptor in eliciting anticancer activity against a cancer type. Marine algal compounds showing anticancer activity against six different cancer cell lines namely MCF-7, A431, HeLa, HT-29, P388 and A549 taken from Seaweed metabolite database were subjected to comprehensive QSAR modeling studies. A hybrid-GA (genetic algorithm) optimization technique for descriptor space reduction and multiple linear regression analysis (MLR) approach was used as fitness functions. Cell lines HeLa and MCF-7 showed good statistical quality (R(2)∼0.75, Q(2)∼0.65) followed by A431, HT29 and P388 cell lines with reasonable statistical values (R(2)∼0.70, Q(2)∼0.60). The models developed were interpretable, with good statistical and predictive significance. Molecular descriptor analyses revealed that Baumann's alignment-independent topological descriptors had a major role in variation of activity along with other descriptors. Incidentally, earlier QSAR analysis on a variety of chemically diverse PKBα inhibitors revealed Baumann's alignment-independent topological descriptors that differentiated the molecules binding to Protein kinase B (PKBα) kinase or PH domain, hence a docking study of two crystal structures of PKBβ was performed for identification of novel ATP-competitive inhibitors of PKBβ. Five compounds had a good docking score and Callophycin A showed better ligand efficiency than other PKBβ inhibitors. Furthermore in silico pharmacokinetic and toxicity studies also showed that Callophycin A had a high drug score (0.85) compared to the other inhibitors. These results encourages discovering novel inhibitors for cancer therapeutic targets by screening metabolites from marine algae. PMID:25936945

  13. The Danish vaccination register.

    PubMed

    Grove Krause, T; Jakobsen, S; Haarh, M; Mølbak, K

    2012-01-01

    Immunisation information systems (IIS) are valuable tools for monitoring vaccination coverage and for estimating vaccine effectiveness and safety. Since 2009, an advanced IIS has been developed in Denmark and will be implemented during 2012–14. This IIS is based on a database existing since 2000. The reporting of all administered vaccinations including vaccinations outside the national programme will become mandatory. Citizens will get access to data about their own vaccinations and healthcare personnel will get access to information on the vaccinations of their patients. A national concept of identification, a national solution combining a personal code and a card with codes, ensures easy and secure access to the register. From the outset, the IIS will include data on childhood vaccinations administered from 1996 and onwards. All Danish citizens have a unique identifier, a so called civil registration number, which allows the linking of information on vaccinations coming from different electronic data sources. The main challenge will be to integrate the IIS with the different electronic patient record systems currently existing at general practitioner, vaccination clinic and hospital level thereby avoiding double-entry. A need has been identified for an updated international classification of vaccine products on the market. Such a classification would also be useful for the future exchange of data on immunisations from IIS between countries. PMID:22551494

  14. Prediction of binding affinity and efficacy of thyroid hormone receptor ligands using QSAR and structure-based modeling methods

    SciTech Connect

    Politi, Regina; Rusyn, Ivan; Tropsha, Alexander

    2014-10-01

    The thyroid hormone receptor (THR) is an important member of the nuclear receptor family that can be activated by endocrine disrupting chemicals (EDC). Quantitative Structure–Activity Relationship (QSAR) models have been developed to facilitate the prioritization of THR-mediated EDC for the experimental validation. The largest database of binding affinities available at the time of the study for ligand binding domain (LBD) of THRβ was assembled to generate both continuous and classification QSAR models with an external accuracy of R{sup 2} = 0.55 and CCR = 0.76, respectively. In addition, for the first time a QSAR model was developed to predict binding affinities of antagonists inhibiting the interaction of coactivators with the AF-2 domain of THRβ (R{sup 2} = 0.70). Furthermore, molecular docking studies were performed for a set of THRβ ligands (57 agonists and 15 antagonists of LBD, 210 antagonists of the AF-2 domain, supplemented by putative decoys/non-binders) using several THRβ structures retrieved from the Protein Data Bank. We found that two agonist-bound THRβ conformations could effectively discriminate their corresponding ligands from presumed non-binders. Moreover, one of the agonist conformations could discriminate agonists from antagonists. Finally, we have conducted virtual screening of a chemical library compiled by the EPA as part of the Tox21 program to identify potential THRβ-mediated EDCs using both QSAR models and docking. We concluded that the library is unlikely to have any EDC that would bind to the THRβ. Models developed in this study can be employed either to identify environmental chemicals interacting with the THR or, conversely, to eliminate the THR-mediated mechanism of action for chemicals of concern. - Highlights: • This is the largest curated dataset for ligand binding domain (LBD) of the THRβ. • We report the first QSAR model for antagonists of AF-2 domain of THRβ. • A combination of QSAR and docking enables

  15. In silico exploration of c-KIT inhibitors by pharmaco-informatics methodology: pharmacophore modeling, 3D QSAR, docking studies, and virtual screening.

    PubMed

    Chaudhari, Prashant; Bari, Sanjay

    2016-02-01

    c-KIT is a component of the platelet-derived growth factor receptor family, classified as type-III receptor tyrosine kinase. c-KIT has been reported to be involved in, small cell lung cancer, other malignant human cancers, and inflammatory and autoimmune diseases associated with mast cells. Available c-KIT inhibitors suffer from tribulations of growing resistance or cardiac toxicity. A combined in silico pharmacophore and structure-based virtual screening was performed to identify novel potential c-KIT inhibitors. In the present study, five molecules from the ZINC database were retrieved as new potential c-KIT inhibitors, using Schrödinger's Maestro 9.0 molecular modeling suite. An atom-featured 3D QSAR model was built using previously reported c-KIT inhibitors containing the indolin-2-one scaffold. The developed 3D QSAR model ADHRR.24 was found to be significant (R2 = 0.9378, Q2 = 0.7832) and instituted to be sufficiently robust with good predictive accuracy, as confirmed through external validation approaches, Y-randomization and GH approach [GH score 0.84 and Enrichment factor (E) 4.964]. The present QSAR model was further validated for the OECD principle 3, in that the applicability domain was calculated using a "standardization approach." Molecular docking of the QSAR dataset molecules and final ZINC hits were performed on the c-KIT receptor (PDB ID: 3G0E). Docking interactions were in agreement with the developed 3D QSAR model. Model ADHRR.24 was explored for ligand-based virtual screening followed by in silico ADME prediction studies. Five molecules from the ZINC database were obtained as potential c-KIT inhibitors with high in -silico predicted activity and strong key binding interactions with the c-KIT receptor. PMID:26416560

  16. Use of QSARs in international decision-making frameworks to predict health effects of chemical substances.

    PubMed Central

    Cronin, Mark T D; Jaworska, Joanna S; Walker, John D; Comber, Michael H I; Watts, Christopher D; Worth, Andrew P

    2003-01-01

    This article is a review of the use of quantitative (and qualitative) structure-activity relationships (QSARs and SARs) by regulatory agencies and authorities to predict acute toxicity, mutagenicity, carcinogenicity, and other health effects. A number of SAR and QSAR applications, by regulatory agencies and authorities, are reviewed. These include the use of simple QSAR analyses, as well as the use of multivariate QSARs, and a number of different expert system approaches. PMID:12896862

  17. Prediction of binding affinity and efficacy of thyroid hormone receptor ligands using QSAR and structure based modeling methods

    PubMed Central

    Politi, Regina; Rusyn, Ivan; Tropsha, Alexander

    2016-01-01

    The thyroid hormone receptor (THR) is an important member of the nuclear receptor family that can be activated by endocrine disrupting chemicals (EDC). Quantitative Structure-Activity Relationship (QSAR) models have been developed to facilitate the prioritization of THR-mediated EDC for the experimental validation. The largest database of binding affinities available at the time of the study for ligand binding domain (LBD) of THRβ was assembled to generate both continuous and classification QSAR models with an external accuracy of R2=0.55 and CCR=0.76, respectively. In addition, for the first time a QSAR model was developed to predict binding affinities of antagonists inhibiting the interaction of coactivators with the AF-2 domain of THRβ (R2=0.70). Furthermore, molecular docking studies were performed for a set of THRβ ligands (57 agonists and 15 antagonists of LBD, 210 antagonists of the AF-2 domain, supplemented by putative decoys/non-binders) using several THRβ structures retrieved from the Protein Data Bank. We found that two agonist-bound THRβ conformations could effectively discriminate their corresponding ligands from presumed non-binders. Moreover, one of the agonist conformations could discriminate agonists from antagonists. Finally, we have conducted virtual screening of a chemical library compiled by the EPA as part of the Tox21 program to identify potential THRβ-mediated EDCs using both QSAR models and docking. We concluded that the library is unlikely to have any EDC that would bind to the THRβ. Models developed in this study can be employed either to identify environmental chemicals interacting with the THR or, conversely, to eliminate the THR-mediated mechanism of action for chemicals of concern. PMID:25058446

  18. Combinatorial Pharmacophore-Based 3D-QSAR Analysis and Virtual Screening of FGFR1 Inhibitors

    PubMed Central

    Zhou, Nannan; Xu, Yuan; Liu, Xian; Wang, Yulan; Peng, Jianlong; Luo, Xiaomin; Zheng, Mingyue; Chen, Kaixian; Jiang, Hualiang

    2015-01-01

    The fibroblast growth factor/fibroblast growth factor receptor (FGF/FGFR) signaling pathway plays crucial roles in cell proliferation, angiogenesis, migration, and survival. Aberration in FGFRs correlates with several malignancies and disorders. FGFRs have proved to be attractive targets for therapeutic intervention in cancer, and it is of high interest to find FGFR inhibitors with novel scaffolds. In this study, a combinatorial three-dimensional quantitative structure-activity relationship (3D-QSAR) model was developed based on previously reported FGFR1 inhibitors with diverse structural skeletons. This model was evaluated for its prediction performance on a diverse test set containing 232 FGFR inhibitors, and it yielded a SD value of 0.75 pIC50 units from measured inhibition affinities and a Pearson’s correlation coefficient R2 of 0.53. This result suggests that the combinatorial 3D-QSAR model could be used to search for new FGFR1 hit structures and predict their potential activity. To further evaluate the performance of the model, a decoy set validation was used to measure the efficiency of the model by calculating EF (enrichment factor). Based on the combinatorial pharmacophore model, a virtual screening against SPECS database was performed. Nineteen novel active compounds were successfully identified, which provide new chemical starting points for further structural optimization of FGFR1 inhibitors. PMID:26110383

  19. Benchmarking the Predictive Power of Ligand Efficiency Indices in QSAR.

    PubMed

    Cortes-Ciriano, Isidro

    2016-08-22

    Compound physicochemical properties favoring in vitro potency are not always correlated to desirable pharmacokinetic profiles. Therefore, using potency (i.e., IC50) as the main criterion to prioritize candidate drugs at early stage drug discovery campaigns has been questioned. Yet, the vast majority of the virtual screening models reported in the medicinal chemistry literature predict the biological activity of compounds by regressing in vitro potency on topological or physicochemical descriptors. Two studies published in this journal showed that higher predictive power on external molecules can be achieved by using ligand efficiency indices as the dependent variable instead of a metric of potency (IC50) or binding affinity (Ki). The present study aims at filling the shortage of a thorough assessment of the predictive power of ligand efficiency indices in QSAR. To this aim, the predictive power of 11 ligand efficiency indices has been benchmarked across four algorithms (Gradient Boosting Machines, Partial Least Squares, Random Forest, and Support Vector Machines), two descriptor types (Morgan fingerprints, and physicochemical descriptors), and 29 data sets collected from the literature and ChEMBL database. Ligand efficiency metrics led to the highest predictive power on external molecules irrespective of the descriptor type or algorithm used, with an R(2)test difference of ∼0.3 units and a this difference ∼0.4 units when modeling small data sets and a normalized RMSE decrease of >0.1 units in some cases. Polarity indices, such as SEI and NSEI, led to higher predictive power than metrics based on molecular size, i.e., BEI, NBEI, and LE. LELP, which comprises a polarity factor (cLogP) and a size parameter (LE) constantly led to the most predictive models, suggesting that these two properties convey a complementary predictive signal. Overall, this study suggests that using ligand efficiency indices as the dependent variable might be an efficient strategy to model

  20. The Odense University Pharmacoepidemiological Database (OPED)

    Cancer.gov

    The Odense University Pharmacoepidemiological Database is one of two large prescription registries in Denmark and covers a stable population that is representative of the Danish population as a whole.

  1. Variable selection for QSAR by artificial ant colony systems.

    PubMed

    Izrailev, S; Agrafiotis, D K

    2002-01-01

    Derivation of quantitative structure-activity relationships (QSAR) usually involves computational models that relate a set of input variables describing the structural properties of the molecules for which the activity has been measured to the output variable representing activity. Many of the input variables may be correlated, and it is therefore often desirable to select an optimal subset of the input variables that results in the most predictive model. In this paper we describe an optimization technique for variable selection based on artificial ant colony systems. The algorithm is inspired by the behavior of real ants, which are able to find the shortest path between a food source and their nest using deposits of pheromone as a communication agent. The underlying basic self-organizing principle is exploited for the construction of parsimonious QSAR models based on neural networks for several classical QSAR data sets. PMID:12184383

  2. QSAR Modeling: Where have you been? Where are you going to?

    PubMed Central

    Cherkasov, Artem; Muratov, Eugene N.; Fourches, Denis; Varnek, Alexandre; Baskin, Igor I.; Cronin, Mark; Dearden, John; Gramatica, Paola; Martin, Yvonne C.; Todeschini, Roberto; Consonni, Viviana; Kuz'min, Victor E.; Cramer, Richard; Benigni, Romualdo; Yang, Chihae; Rathman, James; Terfloth, Lothar; Gasteiger, Johann; Richard, Ann; Tropsha, Alexander

    2014-01-01

    Quantitative Structure-Activity Relationship modeling is one of the major computational tools employed in medicinal chemistry. However, throughout its entire history it has drawn both praise and criticism concerning its reliability, limitations, successes, and failures. In this paper, we discuss: (i) the development and evolution of QSAR; (ii) the current trends, unsolved problems, and pressing challenges; and (iii) several novel and emerging applications of QSAR modeling. Throughout this discussion, we provide guidelines for QSAR development, validation, and application, which are summarized in best practices for building rigorously validated and externally predictive QSAR models. We hope that this Perspective will help communications between computational and experimental chemists towards collaborative development and use of QSAR models. We also believe that the guidelines presented here will help journal editors and reviewers apply more stringent scientific standards to manuscripts reporting new QSAR studies, as well as encourage the use of high quality, validated QSARs for regulatory decision making. PMID:24351051

  3. QSAR modeling: where have you been? Where are you going to?

    PubMed

    Cherkasov, Artem; Muratov, Eugene N; Fourches, Denis; Varnek, Alexandre; Baskin, Igor I; Cronin, Mark; Dearden, John; Gramatica, Paola; Martin, Yvonne C; Todeschini, Roberto; Consonni, Viviana; Kuz'min, Victor E; Cramer, Richard; Benigni, Romualdo; Yang, Chihae; Rathman, James; Terfloth, Lothar; Gasteiger, Johann; Richard, Ann; Tropsha, Alexander

    2014-06-26

    Quantitative structure-activity relationship modeling is one of the major computational tools employed in medicinal chemistry. However, throughout its entire history it has drawn both praise and criticism concerning its reliability, limitations, successes, and failures. In this paper, we discuss (i) the development and evolution of QSAR; (ii) the current trends, unsolved problems, and pressing challenges; and (iii) several novel and emerging applications of QSAR modeling. Throughout this discussion, we provide guidelines for QSAR development, validation, and application, which are summarized in best practices for building rigorously validated and externally predictive QSAR models. We hope that this Perspective will help communications between computational and experimental chemists toward collaborative development and use of QSAR models. We also believe that the guidelines presented here will help journal editors and reviewers apply more stringent scientific standards to manuscripts reporting new QSAR studies, as well as encourage the use of high quality, validated QSARs for regulatory decision making. PMID:24351051

  4. Substructural QSAR approaches and topological pharmacophores.

    PubMed Central

    Franke, R; Huebel, S; Streich, W J

    1985-01-01

    For large and diverse data sets, simple QSAR methods based on linear and additive models can no longer be applied. In such cases topological methods using descriptors directly derivable from two-dimensional chemical structures provide a useful alternative. The results of such analyses can be used for lead optimization, to guide biological testing and even aid in the design of novel compounds. Various types of topological descriptors and algorithms are briefly discussed. Which of those is to be selected depends on the objective of the investigation and the properties of the data set. Two new methods, LOGANA and LOCON, are discussed in some more detail. With the help of these methods, substructural patterns ("topological pharmacophores") characteristic of compounds possessing a certain biological property can be evaluated. Both methods are designed in such a way that full use can be made of the data handling capacity of computers while maintaining an optimal impact of the experience of the researcher. They are model-free and do not require any mathematical knowledge. While LOGANA deals with semiquantitative or even qualitative biological data, LOCON can be applied to activity data on a continuous scale. The basic procedure in both cases consists in the stepwise combination of substructural descriptors by the logical operations "and," "or" and "not." With a simple example the utility of the methods is demonstrated. PMID:3905376

  5. Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds.

    PubMed

    Alves, Vinicius M; Muratov, Eugene; Fourches, Denis; Strickland, Judy; Kleinstreuer, Nicole; Andrade, Carolina H; Tropsha, Alexander

    2015-04-15

    Repetitive exposure to a chemical agent can induce an immune reaction in inherently susceptible individuals that leads to skin sensitization. Although many chemicals have been reported as skin sensitizers, there have been very few rigorously validated QSAR models with defined applicability domains (AD) that were developed using a large group of chemically diverse compounds. In this study, we have aimed to compile, curate, and integrate the largest publicly available dataset related to chemically-induced skin sensitization, use this data to generate rigorously validated and QSAR models for skin sensitization, and employ these models as a virtual screening tool for identifying putative sensitizers among environmental chemicals. We followed best practices for model building and validation implemented with our predictive QSAR workflow using Random Forest modeling technique in combination with SiRMS and Dragon descriptors. The Correct Classification Rate (CCR) for QSAR models discriminating sensitizers from non-sensitizers was 71-88% when evaluated on several external validation sets, within a broad AD, with positive (for sensitizers) and negative (for non-sensitizers) predicted rates of 85% and 79% respectively. When compared to the skin sensitization module included in the OECD QSAR Toolbox as well as to the skin sensitization model in publicly available VEGA software, our models showed a significantly higher prediction accuracy for the same sets of external compounds as evaluated by Positive Predicted Rate, Negative Predicted Rate, and CCR. These models were applied to identify putative chemical hazards in the Scorecard database of possible skin or sense organ toxicants as primary candidates for experimental validation. PMID:25560674

  6. Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds

    PubMed Central

    Alves, Vinicius M.; Muratov, Eugene; Fourches, Denis; Strickland, Judy; Kleinstreuer, Nicole; Andrade, Carolina H.; Tropsha, Alexander

    2015-01-01

    Repetitive exposure to a chemical agent can induce an immune reaction in inherently susceptible individuals that leads to skin sensitization. Although many chemicals have been reported as skin sensitizers, there have been very few rigorously validated QSAR models with defined applicability domains (AD) that were developed using a large group of chemically diverse compounds. In this study, we have aimed to compile, curate, and integrate the largest publicly available dataset related to chemically-induced skin sensitization, use this data to generate rigorously validated and QSAR models for skin sensitization, and employ these models as a virtual screening tool for identifying putative sensitizers among environmental chemicals. We followed best practices for model building and validation implemented with our predictive QSAR workflow using random forest modeling technique in combination with SiRMS and Dragon descriptors. The Correct Classification Rate (CCR) for QSAR models discriminating sensitizers from non-sensitizers were 71–88% when evaluated on several external validation sets, within a broad AD, with positive (for sensitizers) and negative (for non-sensitizers) predicted rates of 85% and 79% respectively. When compared to the skin sensitization module included in the OECD QSAR toolbox as well as to the skin sensitization model in publicly available VEGA software, our models showed a significantly higher prediction accuracy for the same sets of external compounds as evaluated by Positive Predicted Rate, Negative Predicted Rate, and CCR. These models were applied to identify putative chemical hazards in the ScoreCard database of possible skin or sense organ toxicants as primary candidates for experimental validation. PMID:25560674

  7. QSAR and docking studies of anthraquinone derivatives by similarity cluster prediction.

    PubMed

    Harsa, Alexandra M; Harsa, Teodora E; Diudea, Mircea V

    2016-06-01

    Forty anthraquinone derivatives have been downloaded from PubChem database and investigated in a quantitative structure-activity relationships (QSAR) study. The models describing log P and LD50 of this set were built up on the hypermolecule scheme that mimics the investigated receptor space; the models were validated by the leave-one-out procedure, in the external test set and in a new version of prediction by using similarity clusters. Molecular docking approach using Lamarckian Genetic Algorithm was made on this class of anthraquinones with respect to 3Q3B receptor. The best scored molecules in the docking assay were used as leaders in the similarity clustering procedure. It is demonstrated that the LD50 data of this set of anthraquinones are related to the binding energies of anthraquinone ligands to the 3Q3B receptor. PMID:26018421

  8. Development and implementation of (Q)SAR modeling within the CHARMMing Web-user interface

    PubMed Central

    Weidlich, Iwona E.; Pevzner, Yuri; Miller, Benjamin T.; Filippov, Igor V.; Woodcock, H. Lee; Brooks, Bernard R.

    2014-01-01

    Recent availability of large publicly accessible databases of chemical compounds and their biological activities (PubChem, ChEMBL) has inspired us to develop a Web-based tool for SAR and QSAR modeling to add to the services provided by CHARMMing (www.charmming.org). This new module implements some of the most recent advances in modern machine learning algorithms – Random Forest, Support Vector Machine (SVM), Stochastic Gradient Descent, Gradient Tree Boosting etc. A user can import training data from Pubchem Bioassay data collections directly from our interface or upload his or her own SD files which contain structures and activity information to create new models (either categorical or numerical). A user can then track the model generation process and run models on new data to predict activity. PMID:25362883

  9. Prediction of rodent carcinogenic potential of naturally occurring chemicals in the human diet using high-throughput QSAR predictive modeling

    SciTech Connect

    Valerio, Luis G. . E-mail: luis.valerio@FDA.HHS.gov; Arvidson, Kirk B.; Chanderbhan, Ronald F.; Contrera, Joseph F.

    2007-07-01

    , comprised primarily of pharmaceutical, industrial and some natural products developed under an FDA-MDL cooperative research and development agreement (CRADA). The predictive performance for this group of dietary natural products and the control group was 97% sensitivity and 80% concordance. Specificity was marginal at 53%. This study finds that the in silico QSAR analysis employing this software's rodent carcinogenicity database is capable of identifying the rodent carcinogenic potential of naturally occurring organic molecules found in the human diet with a high degree of sensitivity. It is the first study to demonstrate successful QSAR predictive modeling of naturally occurring carcinogens found in the human diet using an external validation test. Further test validation of this software and expansion of the training data set for dietary chemicals will help to support the future use of such QSAR methods for screening and prioritizing the risk of dietary chemicals when actual animal data are inadequate, equivocal, or absent.

  10. Neuronal nicotinic acetylcholine receptor agonists: pharmacophores, evolutionary QSAR and 3D-QSAR models.

    PubMed

    Nicolotti, Orazio; Altomare, Cosimo; Pellegrini-Calace, Marialuisa; Carotti, Angelo

    2004-01-01

    Neuronal nicotinic acetylcholine ion channel receptors (nAChRs) exist as several subtypes and are involved in a variety of functions and disorders of the central nervous system (CNS), such as Alzheimer's and Parkinson's diseases. The lack of reliable information on the 3D structure of nAChRs prompted us to focus efforts on pharmacophore and structure-affinity relationships (SAFIRs). The use of DISCO (DIStance COmparison) and Catalyst/HipHop led to the formulation of a pharmacophore that is made of three geometrically unrelated features: (i) an ammonium head involved in coulombic and/or H-bond interactions, (ii) a lone pair of a pyridine nitrogen or a carbonyl oxygen, as H-bond acceptor site, and (iii) a hydrophobic molecular region generally constituted by aliphatic cycles. The quantitative SAFIR (QSAFIR) study was carried out on about three hundred nicotinoid agonists, and coherent results were obtained from classical Hansch-type approach, 3D QSAFIRs, based on Comparative Molecular Field Analysis (CoMFA), and trade-off models generated by Multi-objective Genetic QSAR (MoQSAR), a novel evolutionary software that makes use of Genetic Programming (GP) and multi-objective optimization (MO). Within each congeneric series, Hansch-type equations revealed detrimental steric effects as the major factors modulating the receptor affinity, whereas CoMFA allowed us to merge progressively single-class models in a more global one, whose robustness was supported by crossvalidation, high prediction statistics and satisfactory predictions of the affinity data of a true external ligand set (r(2)(pred) = 0.796). Next, MoQSAR was used to analyze a data set of 58 highly active nicotinoids characterized by 56 descriptors, that are log P, MR and 54 low inter-correlated WHIM (Weighted Holistic Invariant Molecular) indices. Equivalent QSAFIR models, that represent different compromises between structural model complexity, fitting and internal model complexity, were found. Our attention was

  11. Novel HIV-1 Integrase Inhibitor Development by Virtual Screening Based on QSAR Models.

    PubMed

    Guasch, Laura; Zakharov, Alexey V; Tarasova, Olga A; Poroikov, Vladimir V; Liao, Chenzhong; Nicklaus, Marc C

    2016-01-01

    HIV-1 integrase (IN) plays an important role in the life cycle of HIV and is responsible for integration of the virus into the human genome. We present computational approaches used to design novel HIV-1 IN inhibitors. We created an IN inhibitor database by collecting experimental data from the literature. We developed quantitative structure-activity relationship (QSAR) models of HIV-1 IN strand transfer (ST) inhibitors using this database. The prediction accuracy of these models was estimated by external 5-fold cross-validation as well as with an additional validation set of 308 structurally distinct compounds from the publicly accessible BindingDB database. The validated models were used to screen a small combinatorial library of potential synthetic candidates to identify hits, with a subsequent docking approach applied to further filter out compounds to arrive at a small set of potential HIV-1 IN inhibitors. As result, 236 compounds with good druglikeness properties and with correct docking poses were identified as potential candidates for synthesis. One of the six compounds finally chosen for synthesis was experimentally confirmed to inhibit the ST reaction with an IC50(ST) of 37 µM. The IN inhibitor database is available for download from http://cactus.nci.nih.gov/download/iidb/. PMID:26268340

  12. Multiobjective optimization in quantitative structure-activity relationships: deriving accurate and interpretable QSARs.

    PubMed

    Nicolotti, Orazio; Gillet, Valerie J; Fleming, Peter J; Green, Darren V S

    2002-11-01

    Deriving quantitative structure-activity relationship (QSAR) models that are accurate, reliable, and easily interpretable is a difficult task. In this study, two new methods have been developed that aim to find useful QSAR models that represent an appropriate balance between model accuracy and complexity. Both methods are based on genetic programming (GP). The first method, referred to as genetic QSAR (or GPQSAR), uses a penalty function to control model complexity. GPQSAR is designed to derive a single linear model that represents an appropriate balance between the variance and the number of descriptors selected for the model. The second method, referred to as multiobjective genetic QSAR (MoQSAR), is based on multiobjective GP and represents a new way of thinking of QSAR. Specifically, QSAR is considered as a multiobjective optimization problem that comprises a number of competitive objectives. Typical objectives include model fitting, the total number of terms, and the occurrence of nonlinear terms. MoQSAR results in a family of equivalent QSAR models where each QSAR represents a different tradeoff in the objectives. A practical consideration often overlooked in QSAR studies is the need for the model to promote an understanding of the biochemical response under investigation. To accomplish this, chemically intuitive descriptors are needed but do not always give rise to statistically robust models. This problem is addressed by the addition of a further objective, called chemical desirability, that aims to reward models that consist of descriptors that are easily interpretable by chemists. GPQSAR and MoQSAR have been tested on various data sets including the Selwood data set and two different solubility data sets. The study demonstrates that the MoQSAR method is able to find models that are at least as good as models derived using standard statistical approaches and also yields models that allow a medicinal chemist to trade statistical robustness for chemical

  13. AQUATIC TOXICITY MODE OF ACTION STUDIES APPLIED TO QSAR DEVELOPMENT

    EPA Science Inventory

    A series of QSAR models for predicting fish acute lethality were developed using systematically collected data on more than 600 chemicals. These models were developed based on the assumption that chemicals producing toxicity through a common mechanism will have commonality in the...

  14. Are the Chemical Structures in your QSAR Correct?

    EPA Science Inventory

    Quantitative structure-activity relationships (QSARs) are used to predict many different endpoints, utilize hundreds and even thousands of different parameters (or descriptors), and are created using a variety of approaches. The one thing they all have in common is the assumptio...

  15. SAR/QSAR methods in public health practice

    SciTech Connect

    Demchuk, Eugene Ruiz, Patricia; Chou, Selene; Fowler, Bruce A.

    2011-07-15

    Methods of (Quantitative) Structure-Activity Relationship ((Q)SAR) modeling play an important and active role in ATSDR programs in support of the Agency mission to protect human populations from exposure to environmental contaminants. They are used for cross-chemical extrapolation to complement the traditional toxicological approach when chemical-specific information is unavailable. SAR and QSAR methods are used to investigate adverse health effects and exposure levels, bioavailability, and pharmacokinetic properties of hazardous chemical compounds. They are applied as a part of an integrated systematic approach in the development of Health Guidance Values (HGVs), such as ATSDR Minimal Risk Levels, which are used to protect populations exposed to toxic chemicals at hazardous waste sites. (Q)SAR analyses are incorporated into ATSDR documents (such as the toxicological profiles and chemical-specific health consultations) to support environmental health assessments, prioritization of environmental chemical hazards, and to improve study design, when filling the priority data needs (PDNs) as mandated by Congress, in instances when experimental information is insufficient. These cases are illustrated by several examples, which explain how ATSDR applies (Q)SAR methods in public health practice.

  16. FISH ACUTE TOXICITY SYNDROMES: APPLICATION TO THE DEVELOPMENT OF MECHANISM-SPECIFIC QSARS (QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIPS)

    EPA Science Inventory

    Predictive models based on quantitative structure activity relationships (QSARs), are used as rapid screening tools to identify potentially hazardous chemicals. Several QSARs are now available that predict the acute toxicity of narcotic-industrial chemicals. Predictions for compo...

  17. A Historical Excursus on the Statistical Validation Parameters for QSAR Models: A Clarification Concerning Metrics and Terminology.

    PubMed

    Gramatica, Paola; Sangion, Alessandro

    2016-06-27

    In the last years, external validation of QSAR models was the subject of intensive debate in the scientific literature. Different groups have proposed different metrics to find "the best" parameter to characterize the external predictivity of a QSAR model. This editorial summarizes the history of parameter development for the external QSAR model validation and suggests, once again, the concurrent use of several different metrics to assess the real predictive capability of QSAR models. PMID:27218604

  18. Primary rat hepatocytes in chemical testing and QSAR predictive applicability.

    PubMed

    Tichý, Milon; Pokorná, Adéla; Hanzlíková, Iveta; Nerudová, Jana; Tumová, Jana; Uzlová, Rút

    2010-02-01

    Primary rat hepatocytes were used to test acute toxicities of 16 neutral aliphatic alcohols, ketones and esters. Their effects on cell viability and metabolic function (ureogenesis, i.e. biotransformation of ornithine to urea) were measured and expressed as EC50 values. Log EC50 values from both tests correlated with the log partition coefficients for the chemicals between n-octanol and water and log P(ow)-based QSAR models were derived. Log EC50 (viability) tightly correlates with log EC50 (ureogenesis): log EC50 (viability)=0.91 log EC50 (ureogenesis)+0.06. Each of these toxic indices can be substituted by the other one. The toxic indices for both cell viability and metabolic disorder can be estimated using log EC50 for movement inhibition in the oligochaete Tubifex tubifex and the respective QSAR equation. It eliminates a usage of rats. Their correlations were proved and justified. PMID:19735719

  19. Atomic softness-based QSAR study of testosterone

    NASA Astrophysics Data System (ADS)

    Srivastava, H. K.; Pasha, F. A.; Singh, P. P.

    Ionization potential of an atom in a molecule, electron affinity of an atom in a molecule, and quantum chemical descriptor atomic softness values En‡-based quantitative structure-activity relationship (QSAR) study of testosterone derivatives have been done with the help of PM3 calculations on WinMOPAC 7.21 software. The 3D modeling and geometry optimization of all the compounds have been done with the help of PCMODEL software. The biological activities of testosterone derivatives have been taken from literature. The predicted values of biological activity with the help of multiple linear regression (MLR) analysis is very close to observed biological activity. The cross-validation coefficient and correlation coefficient also indicate that the QSAR model is valuable. Regression analysis shows a very good relationship with biological activity and En‡ values. With the help of these values, prediction of the biological activity of any unknown compound is possible.

  20. Acute toxicity and QSAR of chlorophenols on Daphnia magna

    SciTech Connect

    Devillers, J.; Chambon, P.

    1986-10-01

    Chlorophenols which are released into natural waters from various industrial processes and from agricultural uses have been recognized as a group of chemical substances potentially hazardous to the aquatic environment. Therefore it is important to estimate their toxic impact on biota. Thus, the scope of this research was to obtain acute toxicity data for seventeen chlorophenols towards Daphnia magna and to explore the possibilities of deriving QSAR's (quantitative structure-activity relationship) from the above values.

  1. Mechanism-Based QSAR Modeling of Skin Sensitization.

    PubMed

    Dearden, J C; Hewitt, M; Roberts, D W; Enoch, S J; Rowe, P H; Przybylak, K R; Vaughan-Williams, G D; Smith, M L; Pillai, G G; Katritzky, A R

    2015-10-19

    Many chemicals can induce skin sensitization, and there is a pressing need for non-animal methods to give a quantitative indication of potency. Using two large published data sets of skin sensitizers, we have allocated each sensitizing chemical to one of 10 mechanistic categories and then developed good QSAR models for the seven categories that have a sufficient number of chemicals to allow modeling. Both internal and external validation checks showed that each model had good predictivity. PMID:26382665

  2. Molecular quantum similarity and the fundamentals of QSAR.

    PubMed

    Besalú, Emili; Gironés, Xavier; Amat, Lluís; Carbó-Dorca, Ramon

    2002-05-01

    A general overview on quantum similarity and applications to QSAR is presented. The concepts regarding quantum similarity from its theoretical foundation and consecutive development, involving mathematical formulation and similarity measures, are presented and complemented with application examples. The practical part, based on the well-known Crammer 31 steroids set, covers approximate quantum similarity calculations, molecular superposition, and statistics. In this way, the reader will find both basic general information and applicability of quantum similarity. PMID:12020166

  3. Quantum chemical parameters in QSAR: what do I use when?

    USGS Publications Warehouse

    Hickey, James P.

    1996-01-01

    This chapter provides a brief overview of the numerous quantum chemical parameters that have been/are currently being used in quantitative structure activity relationships (QSAR), along with a representative bibliography. The parameters will be grouped according to their mechanistic interpretations, and representative biological and physical chemical applications will be mentioned. Parmater computation methods and the appropriate software are highlighted, as are sources for software.

  4. Alert-QSAR. Implications for Electrophilic Theory of Chemical Carcinogenesis

    PubMed Central

    Putz, Mihai V.; Ionaşcu, Cosmin; Putz, Ana-Maria; Ostafe, Vasile

    2011-01-01

    Given the modeling and predictive abilities of quantitative structure activity relationships (QSARs) for genotoxic carcinogens or mutagens that directly affect DNA, the present research investigates structural alert (SA) intermediate-predicted correlations ASA of electrophilic molecular structures with observed carcinogenic potencies in rats (observed activity, A = Log[1/TD50], i.e., ASA=f(X1SA,X2SA,…)). The present method includes calculation of the recently developed residual correlation of the structural alert models, i.e., ARASA=f(A−ASA,X1SA,X2SA,…). We propose a specific electrophilic ligand-receptor mechanism that combines electronegativity with chemical hardness-associated frontier principles, equality of ligand-reagent electronegativities and ligand maximum chemical hardness for highly diverse toxic molecules against specific receptors in rats. The observed carcinogenic activity is influenced by the induced SA-mutagenic intermediate effect, alongside Hansch indices such as hydrophobicity (LogP), polarizability (POL) and total energy (Etot), which account for molecular membrane diffusion, ionic deformation, and stericity, respectively. A possible QSAR mechanistic interpretation of mutagenicity as the first step in genotoxic carcinogenesis development is discussed using the structural alert chemoinformation and in full accordance with the Organization for Economic Co-operation and Development QSAR guidance principles. PMID:21954348

  5. Rate constants of hydroxyl radical oxidation of polychlorinated biphenyls in the gas phase: A single-descriptor based QSAR and DFT study.

    PubMed

    Yang, Zhihui; Luo, Shuang; Wei, Zongsu; Ye, Tiantian; Spinney, Richard; Chen, Dong; Xiao, Ruiyang

    2016-04-01

    The second-order rate constants (k) of hydroxyl radical (·OH) with polychlorinated biphenyls (PCBs) in the gas phase are of scientific and regulatory importance for assessing their global distribution and fate in the atmosphere. Due to the limited number of measured k values, there is a need to model the k values for unknown PCBs congeners. In the present study, we developed a quantitative structure-activity relationship (QSAR) model with quantum chemical descriptors using a sequential approach, including correlation analysis, principal component analysis, multi-linear regression, validation, and estimation of applicability domain. The result indicates that the single descriptor, polarizability (α), plays an important role in determining the reactivity with a global standardized function of lnk = -0.054 × α ‒ 19.49 at 298 K. In order to validate the QSAR predicted k values and expand the current k value database for PCBs congeners, an independent method, density functional theory (DFT), was employed to calculate the kinetics and thermodynamics of the gas-phase ·OH oxidation of 2,4',5-trichlorobiphenyl (PCB31), 2,2',4,4'-tetrachlorobiphenyl (PCB47), 2,3,4,5,6-pentachlorobiphenyl (PCB116), 3,3',4,4',5,5'-hexachlorobiphenyl (PCB169), and 2,3,3',4,5,5',6-heptachlorobiphenyl (PCB192) at 298 K at B3LYP/6-311++G**//B3LYP/6-31 + G** level of theory. The QSAR predicted and DFT calculated k values for ·OH oxidation of these PCB congeners exhibit excellent agreement with the experimental k values, indicating the robustness and predictive power of the single-descriptor based QSAR model we developed. PMID:26748251

  6. Deciphering the Structural Requirements of Nucleoside Bisubstrate Analogues for Inhibition of MbtA in Mycobacterium tuberculosis: A FB-QSAR Study and Combinatorial Library Generation for Identifying Potential Hits.

    PubMed

    Maganti, Lakshmi; Das, Sanjit Kumar; Mascarenhas, Nahren Manuel; Ghoshal, Nanda

    2011-10-01

    The re-emergence of tuberculosis infections, which are resistant to conventional drug therapy, has steadily risen in the last decade. Inhibitors of aryl acid adenylating enzyme known as MbtA, involved in siderophore biosynthesis in Mycobacterium tuberculosis, are being explored as potential antitubercular agents. The ability to identify fragments that interact with a biological target is a key step in fragment based drug design (FBDD). To expand the boundaries of quantitative structure activity relationship (QSAR) paradigm, we have proposed a Fragment Based QSAR methodology, referred here in as FB-QSAR, for deciphering the structural requirements of a series of nucleoside bisubstrate analogs for inhibition of MbtA, a key enzyme involved in siderophore biosynthetic pathway. For the development of FB-QSAR models, statistical techniques such as stepwise multiple linear regression (SMLR), genetic function approximation (GFA) and GFAspline were used. The predictive ability of the generated models was validated using different statistical metrics, and similarity-based coverage estimation was carried out to define applicability boundaries. To aid the creation of novel antituberculosis compounds, a bioisosteric database was enumerated using the combichem approach endorsed mining in a lead-like chemical space. The generated library was screened using an integrated in-silico approach and potential hits identified. PMID:27468106

  7. Developing a QSAR model for hepatotoxicity screening of the active compounds in traditional Chinese medicines.

    PubMed

    Huang, Shan-Han; Tung, Chun-Wei; Fülöp, Ferenc; Li, Jih-Heng

    2015-04-01

    The perception that natural substances are deemed safe has made traditional Chinese medicine (TCM) popular in the treatment and prevention of disease globally. However, such an assumption is often misleading owing to a lack of scientific validation. To assess the safety of TCM, in silico screening provides major advantages over the classical laboratory approaches in terms of resource- and time-saving and full reproducibility. To screen the hepatotoxicity of the active compounds of TCMs, a quantitative structure-activity relationship (QSAR) model was firstly established by utilizing drugs from the Liver Toxicity Knowledge Base. These drugs were annotated with drug-induced liver injury information obtained from clinical trials and post-marketing surveillance. The performance of the model after nested 10-fold cross-validation was 79.1%, 91.2%, 53.8% for accuracy, sensitivity, and specificity, respectively. The external validation of 91 well-known ingredients of common herbal medicines yielded a high accuracy (87%). After screening the TCM Database@Taiwan, the world's largest TCM database, a total of 6853 (74.8%) ingredients were predicted to have hepatotoxic potential. The one-hundred chemical ingredients predicted to have the highest hepatotoxic potential by our model were further verified by published literatures. Our study indicated that this model can serve as a complementary tool to evaluate the safety of TCM. PMID:25660478

  8. ITERATIVE PROCESS OF QSAR BUILDING AND STRATEGIC TESTING: PREDICTING ER BINDING AFFINITY

    EPA Science Inventory

    Basic principles of QSAR model development and application are discussed. The most difficult step in QSAR application for regulatory use may be determining when a model is sufficiently improved to provide predictions for a specified chemical domain of regulatory concern. The iter...

  9. A MODE-OF-ACTION-BASED QSAR APPROACH TO IMPROVE UNDERSTANDING OF DEVELOPMENTAL TOXICITY

    EPA Science Inventory

    QSAR models of developmental toxicity (devtox) have met with limited regulatory acceptance due to the use of ill-defined endpoints, lack of biological interpretability, and poor model performance. More generally, the lack of biological inference of many QSAR models is often due t...

  10. Variable prospective financing in the Danish hospital sector and the development of a Danish case-mix system.

    PubMed

    Ankjaer-Jensen, Anni; Rosling, Pernille; Bilde, Lone

    2006-08-01

    This article aims to describe and assess the Danish case-mix system, the cost accounting applied in setting national tariffs and the introduction of variable, prospective payment in the Danish hospital sector. The tariffs are calculated as a national average from hospital data gathered in a national cost database. However, uncertainty, mainly resulting from the definition of cost centres at the individual hospital, implies that the cost weights may not fully reflect the hospital treatment cost. As variable prospective payment of hospitals currently only applies to 20% of a hospital's budget, the incentives and the effects on productivity, quality and equality are still limited. PMID:17016932

  11. Danish auroral science history

    NASA Astrophysics Data System (ADS)

    Stauning, P.

    2011-01-01

    Danish auroral science history begins with the early auroral observations made by the Danish astronomer Tycho Brahe during the years from 1582 to 1601 preceding the Maunder minimum in solar activity. Included are also the brilliant observations made by another astronomer, Ole Rømer, from Copenhagen in 1707, as well as the early auroral observations made from Greenland by missionaries during the 18th and 19th centuries. The relations between auroras and geomagnetic variations were analysed by H. C. Ørsted, who also played a vital role in the development of Danish meteorology that came to include comprehensive auroral observations from Denmark, Iceland and Greenland as well as auroral and geomagnetic research. The very important auroral investigations made by Sophus Tromholt are outlined. His analysis from 1880 of auroral observations from Greenland prepared for the significant contributions from the Danish Meteorological Institute, DMI, (founded in 1872) to the first International Polar Year 1882/83, where an expedition headed by Adam Paulsen was sent to Greenland to conduct auroral and geomagnetic observations. Paulsen's analyses of the collected data gave many important results but also raised many new questions that gave rise to auroral expeditions to Iceland in 1899 to 1900 and to Finland in 1900 to 1901. Among the results from these expeditions were 26 unique paintings of the auroras made by the artist painter, Harald Moltke. The expedition to Finland was headed by Dan la Cour, who later as director of the DMI came to be in charge of the comprehensive international geomagnetic and auroral observations made during the Second International Polar Year in 1932/33. Finally, the article describes the important investigations made by Knud Lassen during, among others, the International Geophysical Year 1957/58 and during the International Quiet Sun Year (IQSY) in 1964/65. With his leadership the auroral and geomagnetic research at DMI reached a high international

  12. The Danish National Lymphoma Registry: Coverage and Data Quality

    PubMed Central

    Arboe, Bente; El-Galaly, Tarec Christoffer; Clausen, Michael Roost; Munksgaard, Peter Svenssen; Stoltenberg, Danny; Nygaard, Mette Kathrine; Klausen, Tobias Wirenfeldt; Christensen, Jacob Haaber; Gørløv, Jette Sønderskov; Brown, Peter de Nully

    2016-01-01

    Background The Danish National Lymphoma Register (LYFO) prospectively includes information on all lymphoma patients newly diagnosed at hematology departments in Denmark. The validity of the clinical information in the LYFO has never been systematically assessed. Aim To test the coverage and data quality of the LYFO. Methods The coverage was tested by merging data of the LYFO with the Danish Cancer Register and the Danish National Patient Register, respectively. The validity of the LYFO was assessed by crosschecking with information from medical records in subgroups of patients. A random sample of 3% (N = 364) was made from all patients in the LYFO. In addition, four subtypes of lymphomas were validated: CNS lymphomas, diffuse large B-cell lymphomas, peripheral T-cell lymphomas, and Hodgkin lymphomas. A total of 1,706 patients from the period 2000–2012 were included. The positive predictive values (PPVs) and completeness of selected variables were calculated for each subgroup and for the entire cohort of patients. Results The comparison of data from the LYFO with the Danish Cancer Register and the Danish National Patient Register revealed a high coverage. In addition, the data quality was good with high PPVs (87% to 100%), and high completeness (92% to 100%). Conclusion The LYFO is a unique, nationwide clinical database characterized by high validity, good coverage and prospective data entry. It represents a valuable resource for future lymphoma research. PMID:27336800

  13. A novel QSAR model of Salmonella mutagenicity and its application in the safety assessment of drug impurities

    SciTech Connect

    Valencia, Antoni; Prous, Josep; Mora, Oscar; Sadrieh, Nakissa; Valerio, Luis G.

    2013-12-15

    As indicated in ICH M7 draft guidance, in silico predictive tools including statistically-based QSARs and expert analysis may be used as a computational assessment for bacterial mutagenicity for the qualification of impurities in pharmaceuticals. To address this need, we developed and validated a QSAR model to predict Salmonella t. mutagenicity (Ames assay outcome) of pharmaceutical impurities using Prous Institute's Symmetry℠, a new in silico solution for drug discovery and toxicity screening, and the Mold2 molecular descriptor package (FDA/NCTR). Data was sourced from public benchmark databases with known Ames assay mutagenicity outcomes for 7300 chemicals (57% mutagens). Of these data, 90% was used to train the model and the remaining 10% was set aside as a holdout set for validation. The model's applicability to drug impurities was tested using a FDA/CDER database of 951 structures, of which 94% were found within the model's applicability domain. The predictive performance of the model is acceptable for supporting regulatory decision-making with 84 ± 1% sensitivity, 81 ± 1% specificity, 83 ± 1% concordance and 79 ± 1% negative predictivity based on internal cross-validation, while the holdout dataset yielded 83% sensitivity, 77% specificity, 80% concordance and 78% negative predictivity. Given the importance of having confidence in negative predictions, an additional external validation of the model was also carried out, using marketed drugs known to be Ames-negative, and obtained 98% coverage and 81% specificity. Additionally, Ames mutagenicity data from FDA/CFSAN was used to create another data set of 1535 chemicals for external validation of the model, yielding 98% coverage, 73% sensitivity, 86% specificity, 81% concordance and 84% negative predictivity. - Highlights: • A new in silico QSAR model to predict Ames mutagenicity is described. • The model is extensively validated with chemicals from the FDA and the public domain. • Validation tests

  14. Synthesis, antimycobacterial activity evaluation, and QSAR studies of chalcone derivatives.

    PubMed

    Sivakumar, P M; Seenivasan, S Prabu; Kumar, Vanaja; Doble, Mukesh

    2007-03-15

    In order to develop relatively small molecules as antimycobacterial agents, twenty-five chalcones were synthesized, their activity was evaluated, and quantitative structure-activity relationship (QSAR) was developed. The synthesis was based on the Claisen-Schimdt scheme and the resultant compounds were tested for antitubercular activity by luciferase reporter phage (LRP) assay. Compound C(24) was found to be the most active ( approximately 99%) in this series based on the percentage reduction in Relative Light Units at both 50 and 100 microg/ml levels, followed by compound C(21). Four compounds at the 50 microg/ml and eight compounds at the 100 microg/ml showed activity above 90% level. QSAR model was developed between activity and spatial, topological, and ADME descriptors for the 50 microg/ml data. The statistical measures such as r, r(2), q(2), and F values obtained for the training set were in acceptable range and hence this relationship was used for the test set. The predictive ability of the model is satisfactory (q(2)=0.56) and it can be used for designing similar group of compounds. PMID:17276682

  15. Predicting chemical ocular toxicity using a combinatorial QSAR approach.

    PubMed

    Solimeo, Renee; Zhang, Jun; Kim, Marlene; Sedykh, Alexander; Zhu, Hao

    2012-12-17

    Regulatory agencies require testing of chemicals and products to protect workers and consumers from potential eye injury hazards. Animal screening, such as the rabbit Draize test, for potential environmental toxicants is time-consuming and costly. Therefore, virtual screening using computational models to tag potential ocular toxicants is attractive to toxicologists and policy makers. We have developed quantitative structure-activity relationship (QSAR) models for a set of small molecules with animal ocular toxicity data compiled by the National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods. The data set was initially curated by removing duplicates, mixtures, and inorganics. The remaining 75 compounds were used to develop QSAR models. We applied both k nearest neighbor and random forest statistical approaches in combination with Dragon and Molecular Operating Environment descriptors. Developed models were validated on an external set of 34 compounds collected from additional sources. The external correct classification rates (CCR) of all individual models were between 72 and 87%. Furthermore, the consensus model, based on the prediction average of individual models, showed additional improvement (CCR = 0.93). The validated models could be used to screen external chemical libraries and prioritize chemicals for in vivo screening as potential ocular toxicants. PMID:23148656

  16. Neural network-based QSAR and insecticide discovery: spinetoram.

    PubMed

    Sparks, Thomas C; Crouse, Gary D; Dripps, James E; Anzeveno, Peter; Martynow, Jacek; Deamicis, Carl V; Gifford, James

    2008-01-01

    Improvements in the efficacy and spectrum of the spinosyns, novel fermentation derived insecticide, has long been a goal within Dow AgroSciences. As large and complex fermentation products identifying specific modifications to the spinosyns likely to result in improved activity was a difficult process, since most modifications decreased the activity. A variety of approaches were investigated to identify new synthetic directions for the spinosyn chemistry including several explorations of the quantitative structure activity relationships (QSAR) of spinosyns, which initially were unsuccessful. However, application of artificial neural networks (ANN) to the spinosyn QSAR problem identified new directions for improved activity in the chemistry, which subsequent synthesis and testing confirmed. The ANN-based analogs coupled with other information on substitution effects resulting from spinosyn structure activity relationships lead to the discovery of spinetoram (XDE-175). Launched in late 2007, spinetoram provides both improved efficacy and an expanded spectrum while maintaining the exceptional environmental and toxicological profile already established for the spinosyn chemistry. PMID:18344004

  17. Predicting activities without computing descriptors: graph machines for QSAR.

    PubMed

    Goulon, A; Picot, T; Duprat, A; Dreyfus, G

    2007-01-01

    We describe graph machines, an alternative approach to traditional machine-learning-based QSAR, which circumvents the problem of designing, computing and selecting molecular descriptors. In that approach, which is similar in spirit to recursive networks, molecules are considered as structured data, represented as graphs. For each example of the data set, a mathematical function (graph machine) is built, whose structure reflects the structure of the molecule under consideration; it is the combination of identical parameterised functions, called "node functions" (e.g. a feedforward neural network). The parameters of the node functions, shared both within and across the graph machines, are adjusted during training with the "shared weights" technique. Model selection is then performed by traditional cross-validation. Therefore, the designer's main task consists in finding the optimal complexity for the node function. The efficiency of this new approach has been demonstrated in many QSAR or QSPR tasks, as well as in modelling the activities of complex chemicals (e.g. the toxicity of a family of phenols or the anti-HIV activities of HEPT derivatives). It generally outperforms traditional techniques without requiring the selection and computation of descriptors. PMID:17365965

  18. QSAR study of anti-prion activity of 2-aminothiazoles

    PubMed Central

    Mandi, Prasit; Nantasenamat, Chanin; Srungboonmee, Kakanand; Isarankura-Na-Ayudhya, Chartchalerm; Prachayasittikul, Virapong

    2012-01-01

    2-aminothiazoles is a class of compounds capable of treating life-threatening prion diseases. QSAR studies on a set of forty-seven 2-aminothiazole derivatives possessing anti-prion activity were performed using multivariate analysis, which comprised of multiple linear regression (MLR), artificial neural network (ANN) and support vector machine (SVM). The results indicated that MLR afforded reasonable performance with a correlation coefficient (r) and root mean squared error (RMSE) of 0.9073 and 0.2977, respectively, as obtained from leave-one-out cross-validation (LOO-CV). More sophisticated learning methods such as SVM provided models with the highest accuracy with r and RMSE of 0.9471 and 0.2264, respectively, while ANN gave reasonable performance with r and RMSE of 0.9023 and 0.3043, respectively, as obtained LOO-CV calculations. Descriptor analysis from the regression coefficients of the MLR model suggested that compounds should be asymmetrical molecule with low propensity to form hydrogen bonds and high frequency of N content at topological distance 02 in order to provide good activities. Insights from QSAR studies is anticipated to be useful in the design of novel derivatives based on the 2-aminothiazole scaffold as potent therapeutic agents against prion diseases. PMID:27418919

  19. GTM-Based QSAR Models and Their Applicability Domains.

    PubMed

    Gaspar, H A; Baskin, I I; Marcou, G; Horvath, D; Varnek, A

    2015-06-01

    In this paper we demonstrate that Generative Topographic Mapping (GTM), a machine learning method traditionally used for data visualisation, can be efficiently applied to QSAR modelling using probability distribution functions (PDF) computed in the latent 2-dimensional space. Several different scenarios of the activity assessment were considered: (i) the "activity landscape" approach based on direct use of PDF, (ii) QSAR models involving GTM-generated on descriptors derived from PDF, and, (iii) the k-Nearest Neighbours approach in 2D latent space. Benchmarking calculations were performed on five different datasets: stability constants of metal cations Ca(2+) , Gd(3+) and Lu(3+) complexes with organic ligands in water, aqueous solubility and activity of thrombin inhibitors. It has been shown that the performance of GTM-based regression models is similar to that obtained with some popular machine-learning methods (random forest, k-NN, M5P regression tree and PLS) and ISIDA fragment descriptors. By comparing GTM activity landscapes built both on predicted and experimental activities, we may visually assess the model's performance and identify the areas in the chemical space corresponding to reliable predictions. The applicability domain used in this work is based on data likelihood. Its application has significantly improved the model performances for 4 out of 5 datasets. PMID:27490381

  20. Synthesis, Biological Evaluation and QSAR Studies of Newer Isoxazole Derivatives.

    PubMed

    Asirvatham, Sahaya; Mahajan, Supriya

    2015-01-01

    A series of newer 3-(4'-methoxyphenyl)-5-substituted phenylisoxazoles derivatives have been synthesized by reacting hydroxylamine hydrochloride with chalcones. The chalcones were formed by reacting different aromatic aldehydes with 4-methoxyacetophenone in presence of aqueos potassium hydroxide (KOH). The purity of all the synthesized compounds was checked by recording their melting points and the retention Factors (Rf) values from thin layer chromatography. The structures of the compounds were characterized by recording their infrared (IR) spectra and confirmed by recording their nuclear magnetic resonance ((1)H NMR) spectra. The acute toxicity study was carried out on all the synthesized compounds and they were screened for their antiinflammatory activity by carrageenan induced rat paw edema method. Anti-inflammatory studies showed statistically significant activity when compared to the control, indomethacin. The two most potent compounds giving good anti-inflammatory activity were further evaluated for their antiulcer activity. The compounds were subjected to quantitative structure activity relationships (QSAR) studies. A close correlation between the observed and the predicted anti-inflammatory activity (Log % inhibition) for the compounds indicated the development of the best QSAR model. The synthesized compounds were found to be non-ulcerogenic as compared to the standard, aspirin. PMID:26265199

  1. PREDICTING TOXICOLOGICAL ENDPOINTS OF CHEMICALS USING QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIPS (QSARS)

    EPA Science Inventory

    Quantitative structure-activity relationships (QSARs) are being developed to predict the toxicological endpoints for untested chemicals similar in structure to chemicals that have known experimental toxicological data. Based on a very large number of predetermined descriptors, a...

  2. Parameters for Pyrethroid Insecticide QSAR and PBPK/PD Models for Human Risk Assessment

    EPA Science Inventory

    This pyrethroid insecticide parameter review is an extension of our interest in developing quantitative structure–activity relationship–physiologically based pharmacokinetic/pharmacodynamic (QSAR-PBPK/PD) models for assessing health risks, which interest started with the organoph...

  3. QSARS FOR PREDICTING REDUCTIVE TRANSFORMATION RATE CONSTANTS OF HALOGENATED AROMATIC HYDROCARBONS IN ANOXIC SEDIMENT SYSTEMS

    EPA Science Inventory

    Quantitative structure-activity relationships (QSARs) are developed relating initial and final pseudo-first-order disappearance rate constants of 45 halogenated aromatic hydrocarbons in anoxic sediments to four readily available molecular descriptors: the carbon-halogen bond stre...

  4. 3-D QSARS FOR RANKING AND PRIORITIZATION OF LARGE CHEMICAL DATASETS: AN EDC CASE STUDY

    EPA Science Inventory

    The COmmon REactivity Pattern (COREPA) approach is a three-dimensional structure activity (3-D QSAR) technique that permits identification and quantification of specific global and local steroelectronic characteristics associated with a chemical's biological activity. It goes bey...

  5. ELECTRONIC FACTOR IN QSAR: MO-PARAMETERS, COMPETING INTERACTIONS, REACTIVITY AND TOXICITY

    EPA Science Inventory

    Reactive chemicals pose unique problems in the development of SAR and QSAR in environmental chemistry and toxicology. odels of the stereoelectronic interactions of reactive toxicants with biological systems require formulation of parameters that quantify the electronic structure ...

  6. 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

  7. Methods for reliability and uncertainty assessment and for applicability evaluations of classification- and regression-based QSARs.

    PubMed Central

    Eriksson, Lennart; Jaworska, Joanna; Worth, Andrew P; Cronin, Mark T D; McDowell, Robert M; Gramatica, Paola

    2003-01-01

    This article provides an overview of methods for reliability assessment of quantitative structure-activity relationship (QSAR) models in the context of regulatory acceptance of human health and environmental QSARs. Useful diagnostic tools and data analytical approaches are highlighted and exemplified. Particular emphasis is given to the question of how to define the applicability borders of a QSAR and how to estimate parameter and prediction uncertainty. The article ends with a discussion regarding QSAR acceptability criteria. This discussion contains a list of recommended acceptability criteria, and we give reference values for important QSAR performance statistics. Finally, we emphasize that rigorous and independent validation of QSARs is an essential step toward their regulatory acceptance and implementation. PMID:12896860

  8. CheS-Mapper 2.0 for visual validation of (Q)SAR models

    PubMed Central

    2014-01-01

    Background Sound statistical validation is important to evaluate and compare the overall performance of (Q)SAR models. However, classical validation does not support the user in better understanding the properties of the model or the underlying data. Even though, a number of visualization tools for analyzing (Q)SAR information in small molecule datasets exist, integrated visualization methods that allow the investigation of model validation results are still lacking. Results We propose visual validation, as an approach for the graphical inspection of (Q)SAR model validation results. The approach applies the 3D viewer CheS-Mapper, an open-source application for the exploration of small molecules in virtual 3D space. The present work describes the new functionalities in CheS-Mapper 2.0, that facilitate the analysis of (Q)SAR information and allows the visual validation of (Q)SAR models. The tool enables the comparison of model predictions to the actual activity in feature space. The approach is generic: It is model-independent and can handle physico-chemical and structural input features as well as quantitative and qualitative endpoints. Conclusions Visual validation with CheS-Mapper enables analyzing (Q)SAR information in the data and indicates how this information is employed by the (Q)SAR model. It reveals, if the endpoint is modeled too specific or too generic and highlights common properties of misclassified compounds. Moreover, the researcher can use CheS-Mapper to inspect how the (Q)SAR model predicts activity cliffs. The CheS-Mapper software is freely available at http://ches-mapper.org. Graphical abstract Comparing actual and predicted activity values with CheS-Mapper.

  9. Identification of putative estrogen receptor-mediated endocrine disrupting chemicals using QSAR- and structure-based virtual screening approaches

    SciTech Connect

    Zhang, Liying; Sedykh, Alexander; Tripathi, Ashutosh; Zhu, Hao; Afantitis, Antreas; Mouchlis, Varnavas D.; Melagraki, Georgia; Rusyn, Ivan; Tropsha, Alexander

    2013-10-01

    Identification of endocrine disrupting chemicals is one of the important goals of environmental chemical hazard screening. We report on the development of validated in silico predictors of chemicals likely to cause estrogen receptor (ER)-mediated endocrine disruption to facilitate their prioritization for future screening. A database of relative binding affinity of a large number of ERα and/or ERβ ligands was assembled (546 for ERα and 137 for ERβ). Both single-task learning (STL) and multi-task learning (MTL) continuous quantitative structure–activity relationship (QSAR) models were developed for predicting ligand binding affinity to ERα or ERβ. High predictive accuracy was achieved for ERα binding affinity (MTL R{sup 2} = 0.71, STL R{sup 2} = 0.73). For ERβ binding affinity, MTL models were significantly more predictive (R{sup 2} = 0.53, p < 0.05) than STL models. In addition, docking studies were performed on a set of ER agonists/antagonists (67 agonists and 39 antagonists for ERα, 48 agonists and 32 antagonists for ERβ, supplemented by putative decoys/non-binders) using the following ER structures (in complexes with respective ligands) retrieved from the Protein Data Bank: ERα agonist (PDB ID: 1L2I), ERα antagonist (PDB ID: 3DT3), ERβ agonist (PDB ID: 2NV7), and ERβ antagonist (PDB ID: 1L2J). We found that all four ER conformations discriminated their corresponding ligands from presumed non-binders. Finally, both QSAR models and ER structures were employed in parallel to virtually screen several large libraries of environmental chemicals to derive a ligand- and structure-based prioritized list of putative estrogenic compounds to be used for in vitro and in vivo experimental validation. - Highlights: • This is the largest curated dataset inclusive of ERα and β (the latter is unique). • New methodology that for the first time affords acceptable ERβ models. • A combination of QSAR and docking enables prediction of affinity and function.

  10. QSAR of Tryptanthrin Analogs via Tunneling Barrier Height Imaging

    NASA Astrophysics Data System (ADS)

    Sriraman, Krishnan

    A new class of potential therapeutic agents, namely indolo[2,1-b]quinazolin-6,12- dione (tryptanthrin), and its analogues, have generated interest due to their broad spectrum of activity against a variety of pathogenic organisms. Little is known about the mechanism of action of tryptanthrins at the cellular and molecular levels. One method that has been employed to understand mechanisms of action and predict biological activities is quantitative structure activity relationship (QSAR). Since previous tryptanthrin studies could not clearly identify the pharmacophore, it was proposed to measure barrier height (BH) energy values for preparing a QSAR vs. IC50 values from the literature. The BH energy values were measured using barrier height spectroscopy which is performed using a scanning tunneling microscope (STM). Topography images (7 x 7 nm size) for tryptanthrin and three of its analogs namely 8-fluorotryptanthrin, 4-aza-8-fluorotryptanthrin, and 4-aza-8-chlorotryptanthrin were collected. Both HOMO and LUMO were collected at an applied bias of +/- 0.8 V and 0.1 nA. Excellent positive bias images (LUMO) of tryptanthrin were collected in which individual molecules and their lobes could be clearly recognized. A comparison with the density functional theory (DFT) calculated image of the LUMO resulted in an excellent match. An interesting outcome of the tryptanthrin LUMO imaging was the arrangement of molecules (parallel alignments) in the image which was explained by considering the intermolecular forces. Excellent BH images with sub-molecular resolution for 4-aza-8-fluorotryptanthrin were observed. BH values were calculated for each of the various lobes in the molecule from the BH image. Preliminary QSAR training sets were constructed using literature values of IC50 for W-2 and D-6 strains of Plasmodium falciparum as well as Leishmanai donovani versus average measured molecular barrier heights. The correlations were found to be fair for all the three pathogens. The

  11. Comparison of MLR, PLS and GA-MLR in QSAR analysis.

    PubMed

    Saxena, A K; Prathipati, P

    2003-01-01

    The use of the internet has evolved in quantitative structure-activity relationship (QSAR) over the past decade with the development of web based activities like the availability of numerous public domain software tools for descriptor calculation and chemometric toolboxes. The importance of chemometrics in QSAR has accelerated in recent years for processing the enormous amount of information in form of predictive mathematical models for large datasets of molecules. With the availability of huge numbers of physicochemical and structural parameters, variable selection became crucial in deriving interpretable and predictive QSAR models. Among several approaches to address this problem, the principle component regression (PCR) and partial least squares (PLS) analyses provide highly predictive QSAR models but being more abstract, they are difficult to understand and interpret. Genetic algorithm (GA) is a stochastic method well suited to the problem of variable selection and to solve optimization problems. Consequently the hybrid approach (GA-MLR) combining GA with multiple linear regression (MLR) may be useful in derivation of highly predictive and interpretable QSAR models. In view of the above, a comparative study of stepwise-MLR, PLS and GA-MLR in deriving QSAR models for datasets of alpha1-adrenoreceptor antagonists and beta3-adrenoreceptor agonists has been carried out using the public domain software Dragon for computing descriptors and free Matlab codes for data modeling. PMID:14758986

  12. A QSAR for the prediction of rate constants for the reaction of VOCs with nitrate radicals.

    PubMed

    Schindler, Michael

    2016-07-01

    A QSAR for the prediction of rate constants for the degradation of volatile organic compounds by nitrate radicals is developed using the Partial Least Squares technique. The QSAR is based on experimental data published in the literature for 260 compounds. They are modeled by a set of calculated descriptors from standard descriptor generation tools and from quantum chemistry. Out of several diversity-based partitionings of the data set a diverse set of 99 compounds turned out to be the optimum choice with regard to simplicity and performance. The final QSAR model is characterized by r(2) = 0.831 (fit) and q(2) = 0.823 (prediction), and by an r(2)pred = 0.862 for the n = 155 external validation set. The QSAR needs 3 latent variables. The most important descriptors for the QSAR are the ionization potential, obtained from density functional theory, and the energy of the highest occupied molecular orbital, which are modulated by fingerprints indicating the presence of specific molecular fragments like functional groups or ring systems. The applicability domain of the new QSAR was studied for some compound classes which are important for the crop protection industry, including (di)hydroxbenzenes and heterocyclic compounds. PMID:27037771

  13. Binding affinity prediction of novel estrogen receptor ligands using receptor-based 3-D QSAR methods.

    PubMed

    Sippl, Wolfgang

    2002-12-01

    We have recently reported the development of a 3-D QSAR model for estrogen receptor ligands showing a significant correlation between calculated molecular interaction fields and experimentally measured binding affinity. The ligand alignment obtained from docking simulations was taken as basis for a comparative field analysis applying the GRID/GOLPE program. Using the interaction field derived with a water probe and applying the smart region definition (SRD) variable selection procedure, a significant and robust model was obtained (q(2)(LOO)=0.921, SDEP=0.345). To further analyze the robustness and the predictivity of the established model several recently developed estrogen receptor ligands were selected as external test set. An excellent agreement between predicted and experimental binding data was obtained indicated by an external SDEP of 0.531. Two other traditionally used prediction techniques were applied in order to check the performance of the receptor-based 3-D QSAR procedure. The interaction energies calculated on the basis of receptor-ligand complexes were correlated with experimentally observed affinities. Also ligand-based 3-D QSAR models were generated using program FlexS. The interaction energy-based model, as well as the ligand-based 3-D QSAR models yielded models with lower predictivity. The comparison with the interaction energy-based model and with the ligand-based 3-D QSAR models, respectively, indicates that the combination of receptor-based and 3-D QSAR methods is able to improve the quality of prediction. PMID:12413831

  14. Use and perceived benefits and barriers of QSAR models for REACH: findings from a questionnaire to stakeholders

    PubMed Central

    2012-01-01

    The ORCHESTRA online questionnaire on “benefits and barriers to the use of QSAR methods” addressed the academic, consultant, regulatory and industry communities potentially interested by QSAR methods in the context of REACH. Replies from more than 60 stakeholders produced some insights on the actual application of QSAR methods, and how to improve their use. Respondents state in majority that they have used QSAR methods. All have some future plans to test or use QSAR methods in accordance with their stakeholder role. The stakeholder respondents cited a total of 28 models, methods or software that they have actually applied. The three most frequently cited suites, used moreover by all the stakeholder categories, are the OECD Toolbox, EPISuite and CAESAR; all are free tools. Results suggest that stereotyped assumptions about the barriers to application of QSAR may be incorrect. Economic costs (including potential delays) are not found to be a major barrier. And only one respondent “prefers” traditional, well-known and accepted toxicological assessment methods. Information and guidance may be the keys to reinforcing use of QSAR models. Regulators appear most interested in obtaining clear explanation of the basis of the models, to provide a solid basis for decisions. Scientists appear most interested in the exploration of the scientific capabilities of the QSAR approach. Industry shows interest in obtaining reassurance that appropriate uses of QSAR will be accepted by regulators. PMID:23244245

  15. IDENTIFICATION OF PUTATIVE ESTROGEN RECEPTOR-MEDIATED ENDOCRINE DISRUPTING CHEMICALS USING QSAR- AND STRUCTURE-BASED VIRTUAL SCREENING APPROACHES

    PubMed Central

    Zhang, Liying; Sedykh, Alexander; Tripathi, Ashutosh; Zhu, Hao; Afantitis, Antreas; Mouchlis, Varnavas D.; Melagraki, Georgia; Rusyn, Ivan; Tropsha, Alexander

    2013-01-01

    Identification of Endocrine Disrupting Chemicals is one of the important goals of environmental chemical hazard screening. We report on the development of validated in silico predictors of chemicals likely to cause Estrogen Receptor (ER)-mediated endocrine disruption to facilitate their prioritization for future screening. A database of relative binding affinity of a large number of ERα and/or ERβ ligands was assembled (546 for ERα and 137 for ERβ). Both single-task learning (STL) and multi-task learning (MTL) continuous Quantitative Structure-Activity Relationships (QSAR) models were developed for predicting ligand binding affinity to ERα or ERβ. High predictive accuracy was achieved for ERα binding affinity (MTL R2=0.71, STL R2=0.73). For ERβ binding affinity, MTL models were significantly more predictive (R2=0.53, p<0.05) than STL models. In addition, docking studies were performed on a set of ER agonists/antagonists (67 agonists and 39 antagonists for ERα, 48 agonists and 32 antagonists for ERβ, supplemented by putative decoys/non-binders) using the following ER structures (in complexes with respective ligands) retrieved from the Protein Data Bank: ERα agonist (PDB ID: 1L2I), ERα antagonist (PDB ID: 3DT3), ERβ agonist (PDB ID: 2NV7), ERβ antagonist (PDB ID: 1L2J). We found that all four ER conformations discriminated their corresponding ligands from presumed non-binders. Finally, both QSAR models and ER structures were employed in parallel to virtually screen several large libraries of environmental chemicals to derive a ligand- and structure-based prioritized list of putative estrogenic compounds to be used for in vitro and in vivo experimental validation. PMID:23707773

  16. Identification of putative estrogen receptor-mediated endocrine disrupting chemicals using QSAR- and structure-based virtual screening approaches.

    PubMed

    Zhang, Liying; Sedykh, Alexander; Tripathi, Ashutosh; Zhu, Hao; Afantitis, Antreas; Mouchlis, Varnavas D; Melagraki, Georgia; Rusyn, Ivan; Tropsha, Alexander

    2013-10-01

    Identification of endocrine disrupting chemicals is one of the important goals of environmental chemical hazard screening. We report on the development of validated in silico predictors of chemicals likely to cause estrogen receptor (ER)-mediated endocrine disruption to facilitate their prioritization for future screening. A database of relative binding affinity of a large number of ERα and/or ERβ ligands was assembled (546 for ERα and 137 for ERβ). Both single-task learning (STL) and multi-task learning (MTL) continuous quantitative structure-activity relationship (QSAR) models were developed for predicting ligand binding affinity to ERα or ERβ. High predictive accuracy was achieved for ERα binding affinity (MTL R(2)=0.71, STL R(2)=0.73). For ERβ binding affinity, MTL models were significantly more predictive (R(2)=0.53, p<0.05) than STL models. In addition, docking studies were performed on a set of ER agonists/antagonists (67 agonists and 39 antagonists for ERα, 48 agonists and 32 antagonists for ERβ, supplemented by putative decoys/non-binders) using the following ER structures (in complexes with respective ligands) retrieved from the Protein Data Bank: ERα agonist (PDB ID: 1L2I), ERα antagonist (PDB ID: 3DT3), ERβ agonist (PDB ID: 2NV7), and ERβ antagonist (PDB ID: 1L2J). We found that all four ER conformations discriminated their corresponding ligands from presumed non-binders. Finally, both QSAR models and ER structures were employed in parallel to virtually screen several large libraries of environmental chemicals to derive a ligand- and structure-based prioritized list of putative estrogenic compounds to be used for in vitro and in vivo experimental validation. PMID:23707773

  17. Prediction of Halocarbon Toxicity from Structure: A Hierarchical QSAR Approach

    SciTech Connect

    Gute, B D; Balasubramanian, K; Geiss, K; Basak, S C

    2003-04-11

    Mathematical structural invariants and quantum theoretical descriptors have been used extensively in quantitative structure-activity relationships (QSARs) for the estimation of pharmaceutical activities, biological properties, physicochemical properties, and the toxicities of chemicals. Recently our research team has explored the relative importance of various levels of chemodescriptors, i.e., topostructural, topochemical, geometrical, and quantum theoretical descriptors, in property estimation. This study examines the contribution of chemodescriptors ranging from topostructural to quantum theoretic calculations up to the Gaussian STO-3G level in the prediction of the toxicity of a set of twenty halocarbons. We also report the results of experimental cell-level toxicity studies on these twenty halocarbons to validate our models.

  18. QSAR study of curcumine derivatives as HIV-1 integrase inhibitors.

    PubMed

    Gupta, Pawan; Sharma, Anju; Garg, Prabha; Roy, Nilanjan

    2013-03-01

    A QSAR study was performed on curcumine derivatives as HIV-1 integrase inhibitors using multiple linear regression. The statistically significant model was developed with squared correlation coefficients (r(2)) 0.891 and cross validated r(2) (r(2) cv) 0.825. The developed model revealed that electronic, shape, size, geometry, substitution's information and hydrophilicity were important atomic properties for determining the inhibitory activity of these molecules. The model was also tested successfully for external validation (r(2) pred = 0.849) as well as Tropsha's test for model predictability. Furthermore, the domain analysis was carried out to evaluate the prediction reliability of external set molecules. The model was statistically robust and had good predictive power which can be successfully utilized for screening of new molecules. PMID:23286784

  19. QSAR and pharmacophore modeling of natural and synthetic antimalarial prodiginines.

    PubMed

    Singh, Baljinder; Vishwakarma, Ram A; Bharate, Sandip B

    2013-09-01

    Prodiginines are a family of linear and cyclic oligopyrrole red-pigmented compounds possessing antibacterial, anticancer and immunosuppressive activities and are produced by actinomycetes and other eubacteria. Recently, prodiginines have been reported to possess potent in vitro as well as in vivo antimalarial activity against chloroquine sensitive D6 and multi-drug resistant Dd2 strains of Plasmodium falciparum. In the present paper, a QSAR and pharmacophore modeling for a series of natural and synthetic prodiginines was performed to find out structural features which are crucial for antimalarial activity against these D6 and Dd2 Plasmodium strains. The study indicated that inertia moment 2 length, Kier Chi6 (path) index, kappa 3 index and Wiener topological index plays important role in antimalarial activity against D6 strain whereas descriptors inertia moment 2 length, ADME H-bond donors, VAMP polarization XX component and VAMP quadpole XZ component play important role in antimalarial activity against Dd2 strain. Furthermore, a five-point pharmacophore (ADHRR) model with one H-bond acceptor (A), one H-bond donor (D), one hydrophobic group (H) and two aromatic rings (R) as pharmacophore features was developed for D6 strain by PHASE module of Schrodinger suite. Similarly a six-point pharmacophore AADDRR was developed for Dd2 strain activity. All developed QSAR models showed good correlation coefficient (r² > 0.7), higher F value (F >20) and excellent predictive power (Q² > 0.6). Developed models will be highly useful for predicting antimalarial activity of new compounds and could help in designing better molecules with enhanced antimalarial activity. Furthermore, calculated ADME properties indicated drug-likeness of prodiginines. PMID:24010933

  20. AZOrange - High performance open source machine learning for QSAR modeling in a graphical programming environment

    PubMed Central

    2011-01-01

    Background Machine learning has a vast range of applications. In particular, advanced machine learning methods are routinely and increasingly used in quantitative structure activity relationship (QSAR) modeling. QSAR data sets often encompass tens of thousands of compounds and the size of proprietary, as well as public data sets, is rapidly growing. Hence, there is a demand for computationally efficient machine learning algorithms, easily available to researchers without extensive machine learning knowledge. In granting the scientific principles of transparency and reproducibility, Open Source solutions are increasingly acknowledged by regulatory authorities. Thus, an Open Source state-of-the-art high performance machine learning platform, interfacing multiple, customized machine learning algorithms for both graphical programming and scripting, to be used for large scale development of QSAR models of regulatory quality, is of great value to the QSAR community. Results This paper describes the implementation of the Open Source machine learning package AZOrange. AZOrange is specially developed to support batch generation of QSAR models in providing the full work flow of QSAR modeling, from descriptor calculation to automated model building, validation and selection. The automated work flow relies upon the customization of the machine learning algorithms and a generalized, automated model hyper-parameter selection process. Several high performance machine learning algorithms are interfaced for efficient data set specific selection of the statistical method, promoting model accuracy. Using the high performance machine learning algorithms of AZOrange does not require programming knowledge as flexible applications can be created, not only at a scripting level, but also in a graphical programming environment. Conclusions AZOrange is a step towards meeting the needs for an Open Source high performance machine learning platform, supporting the efficient development of

  1. Bovine renal lipofuscinosis: Prevalence, genetics and impact on milk production and weight at slaughter in Danish cattle

    PubMed Central

    Agerholm, Jørgen S; Christensen, Knud; Nielsen, Søren Saxmose; Flagstad, Pia

    2009-01-01

    Background Bovine renal lipofuscinosis (BRL) is an incidental finding in cattle at slaughter. Condemnation of the kidneys as unfit for human consumption was until recently considered the only implication of BRL. Recent studies have indicated a negative influence on the health of affected animals. The present study investigated the prevalence, genetics and effect of BRL on milk yield and weight at slaughter. Methods BRL status of slaughter cattle was recorded at four abattoirs during a 2-year-period. Data regarding breed, age, genetic descent, milk yield and weight at slaughter were extracted from the Danish Cattle Database. The prevalence of BRL was estimated stratified by breed and age-group. Furthermore, total milk yield, milk yield in last full lactation and weight at slaughter were compared for BRL-affected and non-affected Danish Holsteins and Danish Red cattle. Results 433,759 bovines were slaughtered and 787 of these had BRL. BRL was mainly diagnosed in Danish Red, Danish Holstein and crossbreds. The age of BRL affected animals varied from 11 months to 13 years, but BRL was rarely diagnosed in cattle less than 2 years of age. The total lifelong energy corrected milk (ECM) yields were 3,136 and 4,083 kg higher for BRL affected Danish Red and Danish Holsteins, respectively. However, the median life span of affected animals was 4.9 months longer, and age-corrected total milk yield was 1,284 kg lower for BRL affected Danish Red cows. These cows produced 318 kg ECM less in their last full lactation. Weight at slaughter was not affected by BRL status. The cases occurred in patterns consistent with autosomal recessive inheritance and several family clusters of BRL were found. Analysis of segregation ratios demonstrated the expected ratio for Danish Red cattle, but not for Danish Holsteins. Conclusion The study confirmed that BRL is a common finding in Danish Holsteins and Danish Red cattle at slaughter. The disorder is associated with increased total milk yield due

  2. In silico screening for identification of novel β-1,3-glucan synthase inhibitors using pharmacophore and 3D-QSAR methodologies.

    PubMed

    Meetei, Potshangbam Angamba; Rathore, R S; Prabhu, N Prakash; Vindal, Vaibhav

    2016-01-01

    The enzyme β-1,3-glucan synthase, which catalyzes the synthesis of β-1,3-glucan, an essential and unique structural component of the fungal cell wall, has been considered as a promising target for the development of less toxic anti-fungal agents. In this study, a robust pharmacophore model was developed and structure activity relationship analysis of 42 pyridazinone derivatives as β-1,3-glucan synthase inhibitors were carried out. A five-point pharmacophore model, consisting of two aromatic rings (R) and three hydrogen bond acceptors (A) was generated. Pharmacophore based 3D-QSAR model was developed for the same reported data sets. The generated 3D-QSAR model yielded a significant correlation coefficient value (R (2) = 0.954) along with good predictive power confirmed by the high value of cross-validated correlation coefficient (Q (2) = 0.827). Further, the pharmacophore model was employed as a 3D search query to screen small molecules database retrieved from ZINC to select new scaffolds. Finally, ADME studies revealed the pharmacokinetic efficiency of these compounds. PMID:27429875

  3. eCounterscreening: using QSAR predictions to prioritize testing for off-target activities and setting the balance between benefit and risk.

    PubMed

    Sheridan, Robert P; McMasters, Daniel R; Voigt, Johannes H; Wildey, Mary Jo

    2015-02-23

    During drug development, compounds are tested against counterscreens, a panel of off-target activities that would be undesirable for a drug to have. Testing every compound against every counterscreen is generally too costly in terms of time and money, and we need to find a rational way of prioritizing counterscreen testing. Here we present the eCounterscreening paradigm, wherein predictions from QSAR models for counterscreen activity are used to generate a recommendation as to whether a specific compound in a specific project should be tested against a specific counterscreen. The rules behind the recommendations, which can be summarized in a risk-benefit plot specific for a counterscreen/project combination, are based on a previously assembled database of prospective QSAR predictions. The recommendations require two user-defined cutoffs: the level of activity in a specific counterscreen that is considered undesirable and the level of risk the chemist is willing to accept that an undesired counterscreen activity will go undetected. We demonstrate in a simulated prospective experiment that eCounterscreening can be used to postpone a large fraction of counterscreen testing and still have an acceptably low risk of undetected counterscreen activity. PMID:25551659

  4. 3D QSAR and docking study of gliptin derivatives as DPP-IV inhibitors.

    PubMed

    Agrawal, Ritesh; Jain, Pratima; Dikshit, Subodh Narayan; Bahare, Radhe Shyam

    2013-05-01

    The article describes the development of a robust pharmacophore model and the investigation of structure activity relationship analysis of 46 xanthine derivatives reported for DPP-IV inhibition using PHASE module of Schrodinger software. The present works also encompasses molecular interaction of 46 xanthine ligand through maestro 8.5 software. The QSAR study comprises AHHR.7 pharmacophore hypothesis, which elaborates the three points, e.g. one hydrogen bond acceptor (A), two hydrophobic rings (H) and one aromatic ring (R). The discrete geometries as pharmacophoric feature were developed and the generated pharmacophore model was used to derive a predictive atom-based 3D QSAR model for the studied data set. The obtained 3D QSAR model has an excellent correlation coefficient value (r(2)= 0.9995) along with good statistical significance which is indicated by high Fisher ratio (F= 8537.4). The model also exhibits good predictive power confirmed by the high value of cross validated correlation coefficient (q(2) = 0.6919). The QSAR model suggests that hydrophobic character is crucial for the DPP-IV inhibitory activity exhibited by these compounds and inclusion of hydrophobic substituents will enhance the DPP-IV inhibition. In addition to the hydrophobic character, electron withdrawing groups positively contribute to the DPP-IV inhibition potency. The findings of the QSAR study provide a set of guidelines for designing compounds with better DPP-IV inhibitory potency. PMID:23305140

  5. Exploring conformational search protocols for ligand-based virtual screening and 3-D QSAR modeling.

    PubMed

    Cappel, Daniel; Dixon, Steven L; Sherman, Woody; Duan, Jianxin

    2015-02-01

    3-D ligand conformations are required for most ligand-based drug design methods, such as pharmacophore modeling, shape-based screening, and 3-D QSAR model building. Many studies of conformational search methods have focused on the reproduction of crystal structures (i.e. bioactive conformations); however, for ligand-based modeling the key question is how to generate a ligand alignment that produces the best results for a given query molecule. In this work, we study different conformation generation modes of ConfGen and the impact on virtual screening (Shape Screening and e-Pharmacophore) and QSAR predictions (atom-based and field-based). In addition, we develop a new search method, called common scaffold alignment, that automatically detects the maximum common scaffold between each screening molecule and the query to ensure identical coordinates of the common core, thereby minimizing the noise introduced by analogous parts of the molecules. In general, we find that virtual screening results are relatively insensitive to the conformational search protocol; hence, a conformational search method that generates fewer conformations could be considered "better" because it is more computationally efficient for screening. However, for 3-D QSAR modeling we find that more thorough conformational sampling tends to produce better QSAR predictions. In addition, significant improvements in QSAR predictions are obtained with the common scaffold alignment protocol developed in this work, which focuses conformational sampling on parts of the molecules that are not part of the common scaffold. PMID:25408244

  6. Assessment of machine learning reliability methods for quantifying the applicability domain of QSAR regression models.

    PubMed

    Toplak, Marko; Močnik, Rok; Polajnar, Matija; Bosnić, Zoran; Carlsson, Lars; Hasselgren, Catrin; Demšar, Janez; Boyer, Scott; Zupan, Blaž; Stålring, Jonna

    2014-02-24

    The vastness of chemical space and the relatively small coverage by experimental data recording molecular properties require us to identify subspaces, or domains, for which we can confidently apply QSAR models. The prediction of QSAR models in these domains is reliable, and potential subsequent investigations of such compounds would find that the predictions closely match the experimental values. Standard approaches in QSAR assume that predictions are more reliable for compounds that are "similar" to those in subspaces with denser experimental data. Here, we report on a study of an alternative set of techniques recently proposed in the machine learning community. These methods quantify prediction confidence through estimation of the prediction error at the point of interest. Our study includes 20 public QSAR data sets with continuous response and assesses the quality of 10 reliability scoring methods by observing their correlation with prediction error. We show that these new alternative approaches can outperform standard reliability scores that rely only on similarity to compounds in the training set. The results also indicate that the quality of reliability scoring methods is sensitive to data set characteristics and to the regression method used in QSAR. We demonstrate that at the cost of increased computational complexity these dependencies can be leveraged by integration of scores from various reliability estimation approaches. The reliability estimation techniques described in this paper have been implemented in an open source add-on package ( https://bitbucket.org/biolab/orange-reliability ) to the Orange data mining suite. PMID:24490838

  7. A three-tier QSAR modeling strategy for estimating eye irritation potential of diverse chemicals in rabbit for regulatory purposes.

    PubMed

    Basant, Nikita; Gupta, Shikha; Singh, Kunwar P

    2016-06-01

    Experimental determination of the eye irritation potential (EIP) of chemicals is not only tedious, time and resource intensive, it involves cruelty to test animals. In this study, we have established a three-tier QSAR modeling strategy for estimating the EIP of chemicals for the use of pharmaceutical industry and regulatory agencies. Accordingly, a qualitative (binary classification: irritating, non-irritating), semi-quantitative (four-category classification), and quantitative (regression) QSAR models employing the SDT, DTF, and DTB methods were developed for predicting the EIP of chemicals in accordance with the OECD guidelines. Structural features of chemicals responsible for eye irritation were extracted and used in QSAR analysis. The external predictive power of the developed QSAR models were evaluated through the internal and external validation procedures recommended in QSAR literature. In test data, the two and four category classification QSAR models (DTF, DTB) rendered accuracy of >93%, while the regression QSAR models (DTF, DTB) yielded correlation (R(2)) of >0.92 between the measured and predicted EIPs. Values of various statistical validation coefficients derived for the test data were above their respective threshold limits (except rm(2) in DTF), thus put a high confidence in this analysis. The applicability domain of the constructed QSAR models were defined using the descriptors range and leverage approaches. The QSAR models in this study performed better than any of the previous studies. The results suggest that the developed QSAR models can reliably predict the EIP of diverse chemicals and can be useful tools for screening of candidate molecules in the drug development process. PMID:27018829

  8. Synthesis, antifeedant activity against Coleoptera and 3D QSAR study of alpha-asarone derivatives.

    PubMed

    Łozowicka, B; Kaczyński, P; Magdziarz, T; Dubis, A T

    2014-01-01

    For the first time, a set of 56 compounds representing structural derivatives of naturally occurring alpha-asarone as an antifeedants against stored product pests Sitophilus granarius L., Trogoderma granarium Ev., and Tribolium confusum Duv., were subjected to the 3D QSAR studies. Three-dimensional quantitative structure-activity relationships (3D-QSAR) for 56 compounds, including 15 newly synthesized, were performed using comparative molecular field analysis s-CoMFA and SOM-CoMSA techniques. QSAR was conducted based on a combination of biological activity (against Coleoptera larvae and beetles) and various geometrical, topological, quantum-mechanical, electronic, and chromatographic descriptors. The CoMSA formalism coupled with IVE (CoMSA-IVE) allowed us to obtain highly predictive models for Trogoderma granarium Ev. larvae. We have found that this novel method indicates a clear molecular basis for activity and lipophilicity. This investigation will facilitate optimization of the design of new potential antifeedants. PMID:24601760

  9. Subjectless Sentences in Child Danish.

    ERIC Educational Resources Information Center

    Hamann, Cornelia; Plunkett, Kim

    1998-01-01

    Examined data for two Danish children to determine subject omission, verb usage, and sentence subjects. Found that children exhibit asymmetry in subject omission according to verb type as subjects are omitted from main verb utterances more frequently than from copula utterances. Concluded that treatment of child subject omission should involve…

  10. Nature and Nationhood: Danish Perspectives

    ERIC Educational Resources Information Center

    Schnack, Karsten

    2009-01-01

    In this paper, I shall discuss Danish perspectives on nature, showing the interdependence of conceptions of "nature" and "nationhood" in the formations of a particular cultural community. Nature, thus construed, is never innocent of culture and cannot therefore simply be "restored" to some pristine, pre-lapsarian state. On the other hand,…

  11. QSAR Accelerated Discovery of Potent Ice Recrystallization Inhibitors

    NASA Astrophysics Data System (ADS)

    Briard, Jennie G.; Fernandez, Michael; de Luna, Phil; Woo, Tom. K.; Ben, Robert N.

    2016-05-01

    Ice recrystallization is the main contributor to cell damage and death during the cryopreservation of cells and tissues. Over the past five years, many small carbohydrate-based molecules were identified as ice recrystallization inhibitors and several were shown to reduce cryoinjury during the cryopreservation of red blood cells (RBCs) and hematopoietic stems cells (HSCs). Unfortunately, clear structure-activity relationships have not been identified impeding the rational design of future compounds possessing ice recrystallization inhibition (IRI) activity. A set of 124 previously synthesized compounds with known IRI activities were used to calibrate 3D-QSAR classification models using GRid INdependent Descriptors (GRIND) derived from DFT level quantum mechanical calculations. Partial least squares (PLS) model was calibrated with 70% of the data set which successfully identified 80% of the IRI active compounds with a precision of 0.8. This model exhibited good performance in screening the remaining 30% of the data set with 70% of active additives successfully recovered with a precision of ~0.7 and specificity of 0.8. The model was further applied to screen a new library of aryl-alditol molecules which were then experimentally synthesized and tested with a success rate of 82%. Presented is the first computer-aided high-throughput experimental screening for novel IRI active compounds.

  12. QSAR for toxicity of organic chemicals to luminescent bacteria

    SciTech Connect

    Devillers, J.; Bintein, S.; Karcher, W.

    1994-12-31

    Over the last decade, there have been increasing pressures to review and reduce the use of laboratory animals for toxicity testing. For ethical and economic reasons, various techniques have been developed and proposed as potential alternatives for some of the whole animal toxicity assays. One assay proposed as an alternative to animal testing is the luminescent bacteria toxicity test, provided under the trade name of Microtox{reg_sign} test. This test has been widely used to estimate the toxicity of agricultural, pharmaceutical, and industrial chemicals producing a large amount of valuable toxicity results. Under these conditions, from a critical analysis of the literature, it has been possible to constitute a large data bank of more than 1,000 organic chemicals for deriving a general QSAR model for the Microtox test. Due to the heterogeneity of the data sets, the molecules were described by means of the modified autocorrelation method. The autocorrelation vectors were generated from atomic contributions encoding the hydrophobicity of the molecules. The validity of the model has been widely discussed and its implications in terms of hazard assessment have been also underlined.

  13. 2-AZETIDINONE DERIVATIVES: SYNTHESIS, ANTIMICROBIAL, ANTICANCER EVALUATION AND QSAR STUDIES.

    PubMed

    Deep, Aakash; Kumar, Pradeep; Narasimhan, Balasubramanian; Lim, Siong Meng; Ramasamy, Kalavathy; Mishra, Rakesh Kumar; Mani, Vasudevan

    2016-01-01

    A series of 2-azetidinone derivatives was synthesized from hippuric acid and evaluated for its in vitro antimicrobial and anticancer activities. Antimicrobial properties of the title compounds were investigated against Gram positive and Gram negative bacterial as well as fungal strains. Anticancer activity was performed against breast cancer (MCF7) cell lines. Antimicrobial activity results revealed that N-{2-[3-chloro-2-(2- chlorophenyl)-4-oxoazetidin-1-ylamino]-2-oxoethyl}benzamide (4) was found to be the most potent antimicrobial agent. Results of anticancer study indicated that the synthesized compounds exhibited average anticancer potential and N-[2-(3-chloro-2-oxo-4-styrylazetidin-1-ylamino)-2-oxoethyl]benzamide (17) was found to be most potent anticancer agent against breast cancer (MCF7) cell lines. QSAR models indicated that the antibacterial, antifungal and the overall antimicrobial activities of the synthesized compounds were governed by topological parameters, Balaban index (J) and valence zero and first order molecular connectivity indices (⁰χv and ¹χv). PMID:27008802

  14. QSAR Accelerated Discovery of Potent Ice Recrystallization Inhibitors.

    PubMed

    Briard, Jennie G; Fernandez, Michael; De Luna, Phil; Woo, Tom K; Ben, Robert N

    2016-01-01

    Ice recrystallization is the main contributor to cell damage and death during the cryopreservation of cells and tissues. Over the past five years, many small carbohydrate-based molecules were identified as ice recrystallization inhibitors and several were shown to reduce cryoinjury during the cryopreservation of red blood cells (RBCs) and hematopoietic stems cells (HSCs). Unfortunately, clear structure-activity relationships have not been identified impeding the rational design of future compounds possessing ice recrystallization inhibition (IRI) activity. A set of 124 previously synthesized compounds with known IRI activities were used to calibrate 3D-QSAR classification models using GRid INdependent Descriptors (GRIND) derived from DFT level quantum mechanical calculations. Partial least squares (PLS) model was calibrated with 70% of the data set which successfully identified 80% of the IRI active compounds with a precision of 0.8. This model exhibited good performance in screening the remaining 30% of the data set with 70% of active additives successfully recovered with a precision of ~0.7 and specificity of 0.8. The model was further applied to screen a new library of aryl-alditol molecules which were then experimentally synthesized and tested with a success rate of 82%. Presented is the first computer-aided high-throughput experimental screening for novel IRI active compounds. PMID:27216585

  15. QSAR Accelerated Discovery of Potent Ice Recrystallization Inhibitors

    PubMed Central

    Briard, Jennie G.; Fernandez, Michael; De Luna, Phil; Woo, Tom. K.; Ben, Robert N.

    2016-01-01

    Ice recrystallization is the main contributor to cell damage and death during the cryopreservation of cells and tissues. Over the past five years, many small carbohydrate-based molecules were identified as ice recrystallization inhibitors and several were shown to reduce cryoinjury during the cryopreservation of red blood cells (RBCs) and hematopoietic stems cells (HSCs). Unfortunately, clear structure-activity relationships have not been identified impeding the rational design of future compounds possessing ice recrystallization inhibition (IRI) activity. A set of 124 previously synthesized compounds with known IRI activities were used to calibrate 3D-QSAR classification models using GRid INdependent Descriptors (GRIND) derived from DFT level quantum mechanical calculations. Partial least squares (PLS) model was calibrated with 70% of the data set which successfully identified 80% of the IRI active compounds with a precision of 0.8. This model exhibited good performance in screening the remaining 30% of the data set with 70% of active additives successfully recovered with a precision of ~0.7 and specificity of 0.8. The model was further applied to screen a new library of aryl-alditol molecules which were then experimentally synthesized and tested with a success rate of 82%. Presented is the first computer-aided high-throughput experimental screening for novel IRI active compounds. PMID:27216585

  16. Quantitative structure-activity relationships (QSARs) for the transformation of organic micropollutants during oxidative water treatment.

    PubMed

    Lee, Yunho; von Gunten, Urs

    2012-12-01

    Various oxidants such as chlorine, chlorine dioxide, ferrate(VI), ozone, and hydroxyl radicals can be applied for eliminating organic micropollutant by oxidative transformation during water treatment in systems such as drinking water, wastewater, and water reuse. Over the last decades, many second-order rate constants (k) have been determined for the reaction of these oxidants with model compounds and micropollutants. Good correlations (quantitative structure-activity relationships or QSARs) are often found between the k-values for an oxidation reaction of closely related compounds (i.e. having a common organic functional group) and substituent descriptor variables such as Hammett or Taft sigma constants. In this study, we developed QSARs for the oxidation of organic and some inorganic compounds and organic micropollutants transformation during oxidative water treatment. A number of 18 QSARs were developed based on overall 412 k-values for the reaction of chlorine, chlorine dioxide, ferrate, and ozone with organic compounds containing electron-rich moieties such as phenols, anilines, olefins, and amines. On average, 303 out of 412 (74%) k-values were predicted by these QSARs within a factor of 1/3-3 compared to the measured values. For HO(·) reactions, some principles and estimation methods of k-values (e.g. the Group Contribution Method) are discussed. The developed QSARs and the Group Contribution Method could be used to predict the k-values for various emerging organic micropollutants. As a demonstration, 39 out of 45 (87%) predicted k-values were found within a factor 1/3-3 compared to the measured values for the selected emerging micropollutants. Finally, it is discussed how the uncertainty in the predicted k-values using the QSARs affects the accuracy of prediction for micropollutant elimination during oxidative water treatment. PMID:22939392

  17. A review on principles, theory and practices of 2D-QSAR.

    PubMed

    Roy, Kunal; Das, Rudra Narayan

    2014-01-01

    The central axiom of science purports the explanation of every natural phenomenon using all possible logics coming from pure as well as mixed scientific background. The quantitative structure-activity relationship (QSAR) analysis is a study correlating the behavioral manifestation of compounds with their structures employing the interdisciplinary knowledge of chemistry, mathematics, biology as well as physics. Several studies have attempted to mathematically correlate the chemistry and property (physicochemical/ biological/toxicological) of molecules using various computationally or experimentally derived quantitative parameters termed as descriptors. The dimensionality of the descriptors depends on the type of algorithm employed and defines the nature of QSAR analysis. The most interesting feature of predictive QSAR models is that the behavior of any new or even hypothesized molecule can be predicted by the use of the mathematical equations. The phrase "2D-QSAR" signifies development of QSAR models using 2D-descriptors. Such predictor variables are the most widely practised ones because of their simple and direct mathematical algorithmic nature involving no time consuming energy computations and having reproducible operability. 2D-descriptors have a deluge of contributions in extracting chemical attributes and they are also capable of representing the 3D molecular features to some extent; although in no case they should be considered as the ultimate one, since they often suffer from the problems of intercorrelation, insufficient chemical information as well as lack of interpretation. However, by following rational approaches, novel 2D-descriptors may be developed to obviate various existing problems giving potential 2D-QSAR equations, thereby solving the innumerable chemical mysteries still unexplored. PMID:25204823

  18. Biofuel Database

    National Institute of Standards and Technology Data Gateway

    Biofuel Database (Web, free access)   This database brings together structural, biological, and thermodynamic data for enzymes that are either in current use or are being considered for use in the production of biofuels.

  19. Electronic Databases.

    ERIC Educational Resources Information Center

    Williams, Martha E.

    1985-01-01

    Presents examples of bibliographic, full-text, and numeric databases. Also discusses how to access these databases online, aids to online retrieval, and several issues and trends (including copyright and downloading, transborder data flow, use of optical disc/videodisc technology, and changing roles in database generation and processing). (JN)

  20. Database Administrator

    ERIC Educational Resources Information Center

    Moore, Pam

    2010-01-01

    The Internet and electronic commerce (e-commerce) generate lots of data. Data must be stored, organized, and managed. Database administrators, or DBAs, work with database software to find ways to do this. They identify user needs, set up computer databases, and test systems. They ensure that systems perform as they should and add people to the…

  1. Nonlinear QSAR modeling for predicting cytotoxicity of ionic liquids in leukemia rat cell line: an aid to green chemicals designing.

    PubMed

    Gupta, Shikha; Basant, Nikita; Singh, Kunwar P

    2015-08-01

    Safety assessment and designing of safer ionic liquids (ILs) are among the priorities of the chemists and toxicologists today. Computational approaches have been considered as appropriate methods for prior safety assessment of chemicals and tools to aid in structural designing. The present study is an attempt to investigate the chemical attributes of a wide variety of ILs towards their cytotoxicity in leukemia rat cell line IPC-81 through the development of nonlinear quantitative structure-activity relationship (QSAR) models in the light of the OECD principles for QSAR development. Here, the cascade correlation network (CCN), probabilistic neural network (PNN), and generalized regression neural networks (GRNN) QSAR models were established for the discrimination of ILs in four categories of cytotoxicity and their end-point prediction using few simple descriptors. The diversity and nonlinearity of the considered dataset were evaluated through computing the Euclidean distance and Brock-Dechert-Scheinkman statistics. The constructed QSAR models were validated with external test data. The predictive power of these models was established through a variety of stringent parameters recommended in QSAR literature. The classification QSARs rendered the accuracy of >86%, and the regression models yielded correlation (R(2)) of >0.90 in test data. The developed QSAR models exhibited high statistical confidence and identified the structural elements of the ILs responsible for their cytotoxicity and, hence, could be useful tools in structural designing of safer and green ILs. PMID:25913312

  2. Use of QSARs in international decision-making frameworks to predict ecologic effects and environmental fate of chemical substances.

    PubMed Central

    Cronin, Mark T D; Walker, John D; Jaworska, Joanna S; Comber, Michael H I; Watts, Christopher D; Worth, Andrew P

    2003-01-01

    This article is a review of the use, by regulatory agencies and authorities, of quantitative structure-activity relationships (QSARs) to predict ecologic effects and environmental fate of chemicals. For many years, the U.S. Environmental Protection Agency has been the most prominent regulatory agency using QSARs to predict the ecologic effects and environmental fate of chemicals. However, as increasing numbers of standard QSAR methods are developed and validated to predict ecologic effects and environmental fate of chemicals, it is anticipated that more regulatory agencies and authorities will find them to be acceptable alternatives to chemical testing. PMID:12896861

  3. USE OF INTERSPECIES CORRELATION ESTIMATIONS TO PREDICT HC5'S BASED ON QSAR

    EPA Science Inventory

    Dyer, S.D., S. Belanger, J. Chaney, D. Versteeg and F. Mayer. In press. Use of Interspecies Correlation Estimations to predict HC5's Based on QSARs (Abstract). To be presented at the SETAC Europe 14th Annual Meeting: Environmental Science Solution: A Pan-European Perspective, 18-...

  4. SAR/QSAR MODELS FOR TOXICITY PREDICTION: APPROACHES AND NEW DIRECTIONS

    EPA Science Inventory

    Abstract

    SAR/QSAR MODELS FOR TOXICITY PREDICTION: APPROACHES AND NEW DIRECTIONS

    Risk assessment typically incorporates some relevant toxicity information upon which to base a sound estimation for a chemical of concern. However, there are many circumstances in whic...

  5. QSAR analysis of antitumor activities of 3,4-ethylenedioxythiphene derivatives

    NASA Astrophysics Data System (ADS)

    Rastija, Vesna; Bajić, Miroslav; Stolić, Ivana; Krstulović, Luka; Jukić, Marijana; Glavaš-Obrovac, Ljubica

    2015-12-01

    QSAR analysis was performed for the antitumor activity of 27 derivatives of 3,4-ethylenedioxythiophene against six carcinoma cell lines. The best models were obtained with surface area (SAG) in combination with lipohilicity (log P) as descriptors. Results have shown that molecules with smaller solvent accessible surface area and higher lipophilicy should have higher biological activity against carcinoma cell.

  6. 3D QSAR of aminophenyl benzamide derivatives as histone deacetylase inhibitors.

    PubMed

    Mahipal; Tanwar, Om Prakash; Karthikeyan, C; Moorthy, N S Hari Narayana; Trivedi, Piyush

    2010-09-01

    The article describes the development of a robust pharmacophore model and the investigation of structure activity relationship analysis of 48 aminophenyl benzamide derivatives reported for Histone Deacetylase (HDAC) inhibition using PHASE module of Schrodinger software. A five point pharmacophore model consisting of two aromatic rings (R), two hydrogen bond donors (D) and one hydrogen bond acceptor (A) with discrete geometries as pharmacophoric features was developed and the generated pharmacophore model was used to derive a predictive atom-based 3D QSAR model for the studied dataset. The obtained 3D QSAR model has an excellent correlation coefficient value (r(2)=0.99) along with good statistical significance as shown by high Fisher ratio (F=631.80). The model also exhibits good predictive power confirmed by the high value of cross validated correlation coefficient (q(2) = 0.85). The QSAR model suggests that hydrophobic character is crucial for the HDAC inhibitory activity exhibited by these compounds and inclusion of hydrophobic substituents will enhance the HDAC inhibition. In addition to the hydrophobic character, hydrogen bond donating groups positively contributes to the HDAC inhibition whereas electron withdrawing groups has a negative influence in HDAC inhibitory potency. The findings of the QSAR study provide a set of guidelines for designing compounds with better HDAC inhibitory potency. PMID:20977417

  7. Developing sensor activity relationships for the JPL electronic nose sensors using molecular modeling and QSAR techniques

    NASA Technical Reports Server (NTRS)

    Shevade, A. V.; Ryan, M. A.; Homer, M. L.; Jewell, A. D.; Zhou, H.; Manatt, K.; Kisor, A. K.

    2005-01-01

    We report a Quantitative Structure-Activity Relationships (QSAR) study using Genetic Function Approximations (GFA) to describe the polymer-carbon composite sensor activities in the JPL Electronic Nose, when exposed to chemical vapors at parts-per-million concentration levels.

  8. Consensus hologram QSAR modeling for the prediction of human intestinal absorption.

    PubMed

    Moda, Tiago L; Andricopulo, Adriano D

    2012-04-15

    Consistent in silico models for ADME properties are useful tools in early drug discovery. Here, we report the hologram QSAR modeling of human intestinal absorption using a dataset of 638 compounds with experimental data associated. The final validated models are consistent and robust for the consensus prediction of this important pharmacokinetic property and are suitable for virtual screening applications. PMID:22425566

  9. QSARs for estimating intrinsic hepatic clearance of organic chemicals in humans.

    PubMed

    Pirovano, Alessandra; Brandmaier, Stefan; Huijbregts, Mark A J; Ragas, Ad M J; Veltman, Karin; Hendriks, A Jan

    2016-03-01

    Quantitative structure-activity relationships (QSARs) were developed to predict the in vitro clearance (CLINT) of xenobiotics metabolised in human hepatocytes (118 compounds) and microsomes (115 compounds). Clearance values were gathered from the scientific literature and multiple linear models were built and validated selecting at most 6 predictors from a pool of over 2000 potential molecular descriptors. For the hepatocytes QSAR, the explained variance (Radj(2)) was 67% and the predictive ability (Rext(2)) was 62%. For the microsomes QSAR, Radj(2) was 50% and Rext(2) 30%. For both liver assays, the most important descriptor relates to electronic properties of the compound. Functional groups of fragments were useful to identify specific compounds that have a deviating reaction rate compared to the others, such as polychlorobiphenyls (PCBs) and organic amides which were poorly metabolised by hepatocytes and microsomes, respectively. For hepatocytes, clearance was predominantly determined by electronic characteristics, while size and shape characteristics were less important and partitioning properties were absent. This may suggest that uptake across the membrane and enzyme binding are not rate-limiting steps. Particularly for hepatocytes the QSAR statistics are encouraging, allowing application of the outcomes in in vitro to in vivo extrapolation. PMID:26874337

  10. QSAR and molecular docking studies on oxindole derivatives as VEGFR-2 tyrosine kinase inhibitors.

    PubMed

    Kang, Cong-Min; Liu, Dong-Qing; Zhao, Xu-Hao; Dai, Ying-Jie; Cheng, Jia-Gao; Lv, Ying-Tao

    2016-01-01

    The three-dimensional quantitative structure-activity relationships (3D-QSAR) were established for 30 oxindole derivatives as vascular endothelial growth factor receptor-2 (VEGFR-2) tyrosine kinase inhibitors by using comparative molecular field analysis (CoMFA) and comparative similarity indices analysis comparative molecular similarity indices analysis (CoMSIA) techniques. With the CoMFA model, the cross-validated value (q(2)) was 0.777, the non-cross-validated value (R(2)) was 0.987, and the external cross-validated value ([Formula: see text]) was 0.72. And with the CoMSIA model, the corresponding q(2), R(2) and [Formula: see text] values were 0.710, 0.988 and 0.78, respectively. Docking studies were employed to bind the inhibitors into the active site to determine the probable binding conformation. The binding mode obtained by molecular docking was in good agreement with the 3D-QSAR results. Based on the QSAR models and the docking binding mode, a set of new VEGFR-2 tyrosine kinase inhibitors were designed, which showed excellent predicting inhibiting potencies. The result revealed that both QSAR models have good predictive capability to guide the design and structural modification of homologic compounds. It is also helpful for further research and development of new VEGFR-2 tyrosine kinase inhibitors. PMID:26416217

  11. Antibacterial Activity of Imidazolium-Based Ionic Liquids Investigated by QSAR Modeling and Experimental Studies.

    PubMed

    Hodyna, Diana; Kovalishyn, Vasyl; Rogalsky, Sergiy; Blagodatnyi, Volodymyr; Petko, Kirill; Metelytsia, Larisa

    2016-09-01

    Predictive QSAR models for the inhibitors of B. subtilis and Ps. aeruginosa among imidazolium-based ionic liquids were developed using literary data. The regression QSAR models were created through Artificial Neural Network and k-nearest neighbor procedures. The classification QSAR models were constructed using WEKA-RF (random forest) method. The predictive ability of the models was tested by fivefold cross-validation; giving q(2) = 0.77-0.92 for regression models and accuracy 83-88% for classification models. Twenty synthesized samples of 1,3-dialkylimidazolium ionic liquids with predictive value of activity level of antimicrobial potential were evaluated. For all asymmetric 1,3-dialkylimidazolium ionic liquids, only compounds containing at least one radical with alkyl chain length of 12 carbon atoms showed high antibacterial activity. However, the activity of symmetric 1,3-dialkylimidazolium salts was found to have opposite relationship with the length of aliphatic radical being maximum for compounds based on 1,3-dioctylimidazolium cation. The obtained experimental results suggested that the application of classification QSAR models is more accurate for the prediction of activity of new imidazolium-based ILs as potential antibacterials. PMID:27086199

  12. QSAR-Assisted Design of an Environmental Catalyst for Enhanced Estrogen Remediation

    PubMed Central

    Colosi, Lisa M.; Huang, Qingguo; Weber, Walter J.

    2010-01-01

    A quantitative structure-activity relationship (QSAR) was used to streamline redesign of a model environmental catalyst, horseradish peroxidase (HRP), for enhanced reactivity towards a target pollutant, steroid hormone 17β-estradiol. This QSAR, embodying relationship between reaction rate and intermolecular binding distance, was used in silico to screen for mutations improving enzyme reactivity. Eight mutations mediating significant reductions in binding distances were expressed in Saccharomyces cerevisiae, and resulting recombinant HRP strains were analyzed to determine Michaelis-Menten parameters during reaction with the target substrate. Enzyme turnover rate, ln(kCAT), exhibited inverse relationship with model-predicted binding distances (R2 = 0.81), consistent with the QSAR. Additional analysis of native substrate degradation by selected mutants yielded unexpected increases in ln(kCAT) that were also inversely correlated (R2 = 1.00) with model-predicted binding distances. This suggests that the mechanism of improvement comprises a nonspecific “opening up” of the active site such that it better accommodates environmental estrogens of any size. The novel QSAR-assisted approach described herein offers specific advantages compared to conventional design strategies, most notably targeting an entire class of pollutants at one time and a flexible hybridization of benefits associated with rational design and directed evolution. Thus, this approach is a promising tool for improving enzyme-mediated environmental remediation. PMID:20797763

  13. Does Rational Selection of Training and Test Sets Improve the Outcome of QSAR Modeling?

    EPA Science Inventory

    Prior to using a quantitative structure activity relationship (QSAR) model for external predictions, its predictive power should be established and validated. In the absence of a true external dataset, the best way to validate the predictive ability of a model is to perform its s...

  14. In Silico Study of In Vitro GPCR Assays by QSAR Modeling.

    PubMed

    Mansouri, Kamel; Judson, Richard S

    2016-01-01

    The US EPA's ToxCast program is screening thousands of chemicals of environmental interest in hundreds of in vitro high-throughput screening (HTS) assays. One goal is to prioritize chemicals for more detailed analyses based on activity in assays that target molecular initiating events (MIEs) of adverse outcome pathways (AOPs). However, the chemical space of interest for environmental exposure is much wider than ToxCast's chemical library. In silico methods such as quantitative structure-activity relationships (QSARs) are proven and cost-effective approaches to predict biological activity for untested chemicals. However, empirical data is needed to build and validate QSARs. ToxCast has developed datasets for about 2000 chemicals ideal for training and testing QSAR models. The overall goal of the present work was to develop QSAR models to fill the data gaps in larger environmental chemical lists. The specific aim of the current work was to build QSAR models for 18 G-protein-coupled receptor (GPCR) assays, part of the aminergic family. Two QSAR modeling strategies were adopted: classification models were developed to separate chemicals into active/non-active classes, and then regression models were built to predict the potency values of the bioassays for the active chemicals. Multiple software programs were used to calculate constitutional, topological, and substructural molecular descriptors from two-dimensional (2D) chemical structures. Model-fitting methods included PLSDA (partial least square discriminant analysis), SVMs (support vector machines), kNNs (k-nearest neighbors), and PLSs (partial least squares). Genetic algorithms (GAs) were applied as a variable selection technique to select the most predictive molecular descriptors for each assay. N-fold cross-validation (CV) coupled with multi-criteria decision-making fitting criteria was used to evaluate the models. Finally, the models were applied to make predictions within the established chemical space limits

  15. Statistical databases

    SciTech Connect

    Kogalovskii, M.R.

    1995-03-01

    This paper presents a review of problems related to statistical database systems, which are wide-spread in various fields of activity. Statistical databases (SDB) are referred to as databases that consist of data and are used for statistical analysis. Topics under consideration are: SDB peculiarities, properties of data models adequate for SDB requirements, metadata functions, null-value problems, SDB compromise protection problems, stored data compression techniques, and statistical data representation means. Also examined is whether the present Database Management Systems (DBMS) satisfy the SDB requirements. Some actual research directions in SDB systems are considered.

  16. Toxicity challenges in environmental chemicals: Prediction of human plasma protein binding through quantitative structure-activity relationship (QSAR) models

    EPA Science Inventory

    The present study explores the merit of utilizing available pharmaceutical data to construct a quantitative structure-activity relationship (QSAR) for prediction of the fraction of a chemical unbound to plasma protein (Fub) in environmentally relevant compounds. Independent model...

  17. QSARS FOR PREDICTING BIOTIC AND ABIOTIC REDUCTIVE TRANSFORMATION RATE CONSTANTS OF HALOGENATED HYDROCARBONS IN ANOXIC SEDIMENT SYSTEMS

    EPA Science Inventory

    Quantitative structure-activity relationships (QSARs) are developed relating biotic and abiotic pseudo-first-order disappearance rate constants of halogenated hydrocarbons in anoxic sediments to a number of readily available molecular descriptors. ased upon knowledge of the under...

  18. 2D and 3D QSAR models for identifying diphenylpyridylethanamine based inhibitors against cholesteryl ester transfer protein.

    PubMed

    Chen, Meimei; Yang, Xuemei; Lai, Xinmei; Gao, Yuxing

    2015-10-15

    Cholesteryl ester transfer protein (CETP) inhibitors hold promise as new agents against coronary heart disease. Molecular modeling techniques such as 2D-QSAR and 3D-QSAR analysis were applied to establish models to distinguish potent and weak CETP inhibitors. 2D and 3D QSAR models-based a series of diphenylpyridylethanamine (DPPE) derivatives (newly identified as CETP inhibitors) were then performed to elucidate structural and physicochemical requirements for higher CETP inhibitory activity. The linear and spline 2D-QSAR models were developed through multiple linear regression (MLR) and support vector machine (SVM) methods. The best 2D-QSAR model obtained by SVM gave a high predictive ability (R(2)train=0.929, R(2)test=0.826, Q(2)LOO=0.780). Also, the 2D-QSAR models uncovered that SlogP_VSA0, E_sol and Vsurf_DW23 were important features in defining activity. In addition, the best 3D-QSAR model presented higher predictive ability (R(2)train=0.958, R(2)test=0.852, Q(2)LOO=0.734) based on comparative molecular field analysis (CoMFA). Meanwhile, the derived contour maps from 3D-QSAR model revealed the significant structural features (steric and electronic effects) required for improving CETP inhibitory activity. Consequently, twelve newly designed DPPE derivatives were proposed to be robust and potent CETP inhibitors. Overall, these derived models may help to design novel DPPE derivatives with better CETP inhibitory activity. PMID:26346366

  19. Database Manager

    ERIC Educational Resources Information Center

    Martin, Andrew

    2010-01-01

    It is normal practice today for organizations to store large quantities of records of related information as computer-based files or databases. Purposeful information is retrieved by performing queries on the data sets. The purpose of DATABASE MANAGER is to communicate to students the method by which the computer performs these queries. This…

  20. Maize databases

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This chapter is a succinct overview of maize data held in the species-specific database MaizeGDB (the Maize Genomics and Genetics Database), and selected multi-species data repositories, such as Gramene/Ensembl Plants, Phytozome, UniProt and the National Center for Biotechnology Information (NCBI), ...

  1. Successful School Principalship in Danish Schools

    ERIC Educational Resources Information Center

    Moos, Lejf; Krejsler, John; Kofod, Klaus Kasper; Jensen, Bent Brandt

    2005-01-01

    Purpose: Aims at conceptualizing and investigating the meaning of good school principalship within the space for manoeuvring that is available within the context of Danish comprehensive schools. The paper aims to present findings from case studies of two Danish schools within the frame of reference. Design/methodology/approach: Outlines the…

  2. Adaptive Neuro-Fuzzy Inference System Applied QSAR with Quantum Chemical Descriptors for Predicting Radical Scavenging Activities of Carotenoids.

    PubMed

    Jhin, Changho; Hwang, Keum Taek

    2015-01-01

    One of the physiological characteristics of carotenoids is their radical scavenging activity. In this study, the relationship between radical scavenging activities and quantum chemical descriptors of carotenoids was determined. Adaptive neuro-fuzzy inference system (ANFIS) applied quantitative structure-activity relationship models (QSAR) were also developed for predicting and comparing radical scavenging activities of carotenoids. Semi-empirical PM6 and PM7 quantum chemical calculations were done by MOPAC. Ionisation energies of neutral and monovalent cationic carotenoids and the product of chemical potentials of neutral and monovalent cationic carotenoids were significantly correlated with the radical scavenging activities, and consequently these descriptors were used as independent variables for the QSAR study. The ANFIS applied QSAR models were developed with two triangular-shaped input membership functions made for each of the independent variables and optimised by a backpropagation method. High prediction efficiencies were achieved by the ANFIS applied QSAR. The R-square values of the developed QSAR models with the variables calculated by PM6 and PM7 methods were 0.921 and 0.902, respectively. The results of this study demonstrated reliabilities of the selected quantum chemical descriptors and the significance of QSAR models. PMID:26474167

  3. Adaptive Neuro-Fuzzy Inference System Applied QSAR with Quantum Chemical Descriptors for Predicting Radical Scavenging Activities of Carotenoids

    PubMed Central

    Jhin, Changho; Hwang, Keum Taek

    2015-01-01

    One of the physiological characteristics of carotenoids is their radical scavenging activity. In this study, the relationship between radical scavenging activities and quantum chemical descriptors of carotenoids was determined. Adaptive neuro-fuzzy inference system (ANFIS) applied quantitative structure-activity relationship models (QSAR) were also developed for predicting and comparing radical scavenging activities of carotenoids. Semi-empirical PM6 and PM7 quantum chemical calculations were done by MOPAC. Ionisation energies of neutral and monovalent cationic carotenoids and the product of chemical potentials of neutral and monovalent cationic carotenoids were significantly correlated with the radical scavenging activities, and consequently these descriptors were used as independent variables for the QSAR study. The ANFIS applied QSAR models were developed with two triangular-shaped input membership functions made for each of the independent variables and optimised by a backpropagation method. High prediction efficiencies were achieved by the ANFIS applied QSAR. The R-square values of the developed QSAR models with the variables calculated by PM6 and PM7 methods were 0.921 and 0.902, respectively. The results of this study demonstrated reliabilities of the selected quantum chemical descriptors and the significance of QSAR models. PMID:26474167

  4. A combined pharmacophore modeling, 3D-QSAR and molecular docking study of substituted bicyclo-[3.3.0]oct-2-enes as liver receptor homolog-1 (LRH-1) agonists

    NASA Astrophysics Data System (ADS)

    Lalit, Manisha; Gangwal, Rahul P.; Dhoke, Gaurao V.; Damre, Mangesh V.; Khandelwal, Kanchan; Sangamwar, Abhay T.

    2013-10-01

    A combined pharmacophore modelling, 3D-QSAR and molecular docking approach was employed to reveal structural and chemical features essential for the development of small molecules as LRH-1 agonists. The best HypoGen pharmacophore hypothesis (Hypo1) consists of one hydrogen-bond donor (HBD), two general hydrophobic (H), one hydrophobic aromatic (HYAr) and one hydrophobic aliphatic (HYA) feature. It has exhibited high correlation coefficient of 0.927, cost difference of 85.178 bit and low RMS value of 1.411. This pharmacophore hypothesis was cross-validated using test set, decoy set and Cat-Scramble methodology. Subsequently, validated pharmacophore hypothesis was used in the screening of small chemical databases. Further, 3D-QSAR models were developed based on the alignment obtained using substructure alignment. The best CoMFA and CoMSIA model has exhibited excellent rncv2 values of 0.991 and 0.987, and rcv2 values of 0.767 and 0.703, respectively. CoMFA predicted rpred2 of 0.87 and CoMSIA predicted rpred2 of 0.78 showed that the predicted values were in good agreement with the experimental values. Molecular docking analysis reveals that π-π interaction with His390 and hydrogen bond interaction with His390/Arg393 is essential for LRH-1 agonistic activity. The results from pharmacophore modelling, 3D-QSAR and molecular docking are complementary to each other and could serve as a powerful tool for the discovery of potent small molecules as LRH-1 agonists.

  5. Genome databases

    SciTech Connect

    Courteau, J.

    1991-10-11

    Since the Genome Project began several years ago, a plethora of databases have been developed or are in the works. They range from the massive Genome Data Base at Johns Hopkins University, the central repository of all gene mapping information, to small databases focusing on single chromosomes or organisms. Some are publicly available, others are essentially private electronic lab notebooks. Still others limit access to a consortium of researchers working on, say, a single human chromosome. An increasing number incorporate sophisticated search and analytical software, while others operate as little more than data lists. In consultation with numerous experts in the field, a list has been compiled of some key genome-related databases. The list was not limited to map and sequence databases but also included the tools investigators use to interpret and elucidate genetic data, such as protein sequence and protein structure databases. Because a major goal of the Genome Project is to map and sequence the genomes of several experimental animals, including E. coli, yeast, fruit fly, nematode, and mouse, the available databases for those organisms are listed as well. The author also includes several databases that are still under development - including some ambitious efforts that go beyond data compilation to create what are being called electronic research communities, enabling many users, rather than just one or a few curators, to add or edit the data and tag it as raw or confirmed.

  6. Causation or only correlation? Application of causal inference graphs for evaluating causality in nano-QSAR models

    NASA Astrophysics Data System (ADS)

    Sizochenko, Natalia; Gajewicz, Agnieszka; Leszczynski, Jerzy; Puzyn, Tomasz

    2016-03-01

    In this paper, we suggest that causal inference methods could be efficiently used in Quantitative Structure-Activity Relationships (QSAR) modeling as additional validation criteria within quality evaluation of the model. Verification of the relationships between descriptors and toxicity or other activity in the QSAR model has a vital role in understanding the mechanisms of action. The well-known phrase ``correlation does not imply causation'' reflects insight statistically correlated with the endpoint descriptor may not cause the emergence of this endpoint. Hence, paradigmatic shifts must be undertaken when moving from traditional statistical correlation analysis to causal analysis of multivariate data. Methods of causal discovery have been applied for broader physical insight into mechanisms of action and interpretation of the developed nano-QSAR models. Previously developed nano-QSAR models for toxicity of 17 nano-sized metal oxides towards E. coli bacteria have been validated by means of the causality criteria. Using the descriptors confirmed by the causal technique, we have developed new models consistent with the straightforward causal-reasoning account. It was proven that causal inference methods are able to provide a more robust mechanistic interpretation of the developed nano-QSAR models.In this paper, we suggest that causal inference methods could be efficiently used in Quantitative Structure-Activity Relationships (QSAR) modeling as additional validation criteria within quality evaluation of the model. Verification of the relationships between descriptors and toxicity or other activity in the QSAR model has a vital role in understanding the mechanisms of action. The well-known phrase ``correlation does not imply causation'' reflects insight statistically correlated with the endpoint descriptor may not cause the emergence of this endpoint. Hence, paradigmatic shifts must be undertaken when moving from traditional statistical correlation analysis to causal

  7. BIOMARKERS DATABASE

    EPA Science Inventory

    This database was developed by assembling and evaluating the literature relevant to human biomarkers. It catalogues and evaluates the usefulness of biomarkers of exposure, susceptibility and effect which may be relevant for a longitudinal cohort study. In addition to describing ...

  8. QSAR Study on Thiazolidine-2,4-dione Derivatives for Antihyperglycemic Activity.

    PubMed

    Prashantha Kumar, B R; Nanjan, M J

    2008-09-01

    A set of seventy four molecules belonging to the class of thioglitazones were subjected to the QSAR analysis for their antihyperglycemic activity. All the molecules were subjected to energy minimization to get 3D structures, followed by conformational analysis to get the conformation of the molecule associated with the least energy and highest stability. Various physico-chemical parameters were then calculated using ALCHEMY 2000 software, namely, thermodynamic parameters, structure-dependant parameters, topological parameters and charge-dependant parameters. Multiple linear regression analysis was carried out on all the molecules. The final equation was developed by choosing optimal combination of descriptors after removing the outliers. Cross validation was performed by leave one out method to arrive at the final QSAR model for the chosen set of molecules to exhibit antihyperglycemic activity. PMID:21394250

  9. DFT-based QSAR models to predict the antimycobacterial activity of chalcones.

    PubMed

    Barua, Nilakshi; Sarmah, Pubalee; Hussain, Iftikar; Deka, Ramesh C; Buragohain, Alak K

    2012-04-01

    In this study, antimycobacterial activity of a set of synthesized chalcone derivatives against Mycobacterium tuberculosis H37Rv was investigated by quantitative structure-activity relationship (QSAR) analysis using density functional theory (DFT) and molecular mechanics (MM+)-based descriptors in both gas and solvent phases. The best molecular descriptors identified were hardness, E(HOMO) , MR(A-4) and MR(B-4') that contributed to the antimycobacterial activity of the chalcones as independent factors. The correlation of these four descriptors with their antimycobacterial activity increases with the inclusion of solvent medium, indicating their importance in studying biological activity. QSAR models revealed that in gas phase, lower values of E(HOMO) , MR(A-4) and MR(B-4') increase the antimycobacterial activity of the chalcone molecules. However, in solvent phase, lower values of E(HOMO) and MR(B-4') and higher values of MR(A-4) increase their activity. PMID:22151277

  10. QSAR studies of macrocyclic diterpenes with P-glycoprotein inhibitory activity.

    PubMed

    Sousa, Inês J; Ferreira, Maria-José U; Molnár, Joseph; Fernandes, Miguel X

    2013-02-14

    Multidrug resistance (MDR) represents a major limitation for cancer chemotherapy. There are several mechanisms of MDR but the most important is associated with P-glycoprotein (P-gp) overexpression. The development of modulators of P-gp that are able to re-establish drug sensitivity of resistant cells has been considered a promising approach for overcoming MDR. Macrocyclic lathyrane and jatrophane-type diterpenes from Euphorbia species were found to be strong MDR reversing agents. In this study we applied quantitative structure-activity relationship (QSAR) methodology in order to identify the most relevant molecular features of macrocyclic diterpenes with P-gp inhibitory activity and to determine which structural modifications can be performed to improve their activity. Using experimental biological data at two concentrations (4 and 40 μg/ml), we developed a QSAR model for a set of 51 bioactive diterpenic compounds which includes lathyrane and jatrophane-type diterpenes and another model just for jatrophanes. The cross-validation correlation values for all diterpenes QSAR models developed for biological activities at compound concentrations of 4 and 40 μg/ml were 0.758 and 0.729, respectively. Regarding the prediction ability, we get R²(pred) values of 0.765 and 0.534 for biological activities at compound concentrations of 4 and 40 μg/ml, respectively. Applying the cross-validation test to jatrophanes QSAR models, we obtained 0.680 and 0.787 for biological activities at compound concentrations of 4 and 40 μg/ml concentrations, respectively. For the same concentrations, the obtained R²(pred) values for jatrophanes models were 0.541 and 0.534, respectively. The obtained models were statistically valid and showed high prediction ability. PMID:23228414

  11. Synthesis and QSAR study of novel anti-inflammatory active mesalazine-metronidazole conjugates.

    PubMed

    Naumov, Roman N; Panda, Siva S; Girgis, Adel S; George, Riham F; Farhat, Michel; Katritzky, Alan R

    2015-06-01

    Novel, mesalazine, metronidazole conjugates 6a-e with amino acid linkers were synthesized utilizing benzotriazole chemistry. Biological data acquired for all the novel bis-conjugates showed (a) some bis-conjugates exhibit comparable anti-inflammatory activity with parent drugs and (b) the potent bis-conjugates show no visible stomach lesions. 3D-pharmacophore and 2D-QSAR modeling support the observed bio-properties. PMID:25937011

  12. QSAR models for the removal of organic micropollutants in four different river water matrices.

    PubMed

    Sudhakaran, Sairam; Calvin, James; Amy, Gary L

    2012-04-01

    Ozonation is an advanced water treatment process used to remove organic micropollutants (OMPs) such as pharmaceuticals and personal care products (PPCPs). In this study, Quantitative Structure Activity Relationship (QSAR) models, for ozonation and advanced oxidation process (AOP), were developed with percent-removal of OMPs by ozonation as the criterion variable. The models focused on PPCPs and pesticides elimination in bench-scale studies done within natural water matrices: Colorado River, Passaic River, Ohio River and Suwannee synthetic water. The OMPs removal for the different water matrices varied depending on the water quality conditions such as pH, DOC, alkalinity. The molecular descriptors used to define the OMPs physico-chemical properties range from one-dimensional (atom counts) to three-dimensional (quantum-chemical). Based on a statistical modeling approach using more than 40 molecular descriptors as predictors, descriptors influencing ozonation/AOP were chosen for inclusion in the QSAR models. The modeling approach was based on multiple linear regression (MLR). Also, a global model based on neural networks was created, compiling OMPs from all the four river water matrices. The chemically relevant molecular descriptors involved in the QSAR models were: energy difference between lowest unoccupied and highest occupied molecular orbital (E(LUMO)-E(HOMO)), electron-affinity (EA), number of halogen atoms (#X), number of ring atoms (#ring atoms), weakly polar component of the solvent accessible surface area (WPSA) and oxygen to carbon ratio (O/C). All the QSAR models resulted in a goodness-of-fit, R(2), greater than 0.8. Internal and external validations were performed on the models. PMID:22245076

  13. Critically Assessing the Predictive Power of QSAR Models for Human Liver Microsomal Stability.

    PubMed

    Liu, Ruifeng; Schyman, Patric; Wallqvist, Anders

    2015-08-24

    To lower the possibility of late-stage failures in the drug development process, an up-front assessment of absorption, distribution, metabolism, elimination, and toxicity is commonly implemented through a battery of in silico and in vitro assays. As in vitro data is accumulated, in silico quantitative structure-activity relationship (QSAR) models can be trained and used to assess compounds even before they are synthesized. Even though it is generally recognized that QSAR model performance deteriorates over time, rigorous independent studies of model performance deterioration is typically hindered by the lack of publicly available large data sets of structurally diverse compounds. Here, we investigated predictive properties of QSAR models derived from an assembly of publicly available human liver microsomal (HLM) stability data using variable nearest neighbor (v-NN) and random forest (RF) methods. In particular, we evaluated the degree of time-dependent model performance deterioration. Our results show that when evaluated by 10-fold cross-validation with all available HLM data randomly distributed among 10 equal-sized validation groups, we achieved high-quality model performance from both machine-learning methods. However, when we developed HLM models based on when the data appeared and tried to predict data published later, we found that neither method produced predictive models and that their applicability was dramatically reduced. On the other hand, when a small percentage of randomly selected compounds from data published later were included in the training set, performance of both machine-learning methods improved significantly. The implication is that 1) QSAR model quality should be analyzed in a time-dependent manner to assess their true predictive power and 2) it is imperative to retrain models with any up-to-date experimental data to ensure maximum applicability. PMID:26170251

  14. Molecular Dynamics Guided Receptor Independent 4D QSAR Studies of Substituted Coumarins as Anticancer Agents.

    PubMed

    Patil, Rajesh; Sawant, Sanjay

    2015-01-01

    The search for newer cytotoxic agents has taken many paths in the recent years and in fact some of these efforts led to the discovery of some potent cytotoxic agents. Though the vast number of targets of tumor progression has been identified recently, kinases remained key targets in drug design. It is well established that inhibition of JNK1, a serine/threonine protein kinase delays tumor formation. Poly hydroxylated chromenone analog, quescetagetin, inhibits JNK1. As a part of design of coumarin based JNK1 inhibitors, docking studies and 4D QSAR studies were carried out. 3- pyrazolyl substituted coumarin derivatives were chosen for these studies. Docking studies revealed that 3-pyrazolyl substituted coumarins make key interactions with residues at active site of JNK1. In order to investigate the structural features required in these inhibitors, 4D QSAR studies using LQTAgrid module were carried out. The 4D QSAR model built with PLS regression on the matrix of variables specific for interaction energies at each grid point around the molecular dynamics generated conformations of individual compounds shows good predictive abilities. The squared correlation coefficient, R(2) for the model is 0.785, R(2) cross-validated (Q(2)) is 0.698, R(2) predicted is 0.701. Most of the descriptors contributing to 4D QSAR model are Coulombic potential energy based descriptors which highlight the importance of specific atoms in coumarin derivatives in generating these electrostatic potential at specific grid points with the -NH3 probe. We rationalize that solvent accessible van der Waals surface area around such compounds is good measure of this Coulombic potential energy and can be exploited in designing more active compounds. PMID:26081557

  15. Variable selection based QSAR modeling on Bisphenylbenzimidazole as Inhibitor of HIV-1 reverse transcriptase.

    PubMed

    Kumar, Surendra; Tiwari, Meena

    2013-11-01

    The emergence of mutant virus in drug therapy for HIV-1 infection has steadily risen in the last decade. Inhibition of reverse transcriptase enzyme has emerged as a novel target for the treatment of HIV infection. The aim to decipher the structural features that interact with receptor, we report a quantitative structure activity relationship (QSAR) study on a dataset of thirty seven compounds belonging to bisphenylbenzimidazoles (BPBIs) as reverse transcriptase inhibitors using enhanced replacement method (ERM), stepwise multiple linear regression (Stepwise-MLR) and genetic function approximation (GFA) method for selecting a subset of relevant descriptors, developing the best multiple linear regression model and defining the QSAR model applicability domain boundaries. The enhanced replacement method was found to give better results r²=0.8542, Q²(loo) = 0.7917, r²pred = 0.7812) at five variables as compared to stepwise MLR and GFA method, evidenced by internal and external validation parameters. The modified r² (r²m) of the training set, test set and whole data set were calculated and are in agreement with the enhanced replacement method. The results of QSAR study rationalize the structural requirement for optimum binding of ligands. The developed QSAR model shows that hydrophobicity, flexibility, three dimensional surface area, volume and shape of molecule are important parameters to be considered for designing new compounds and to decipher reverse transcriptase enzyme inhibition activity of these compounds at molecular level. The applicability domain was defined to find the similar analogs with better prediction power. PMID:23106285

  16. 3D-QSAR and molecular fragment replacement study on diaminopyrimidine and pyrrolotriazine ALK inhibitors

    NASA Astrophysics Data System (ADS)

    Ke, Zhipeng; Lu, Tao; Liu, Haichun; Yuan, Haoliang; Ran, Ting; Zhang, Yanmin; Yao, Sihui; Xiong, Xiao; Xu, Jinxing; Xu, Anyang; Chen, Yadong

    2014-06-01

    Over expression of anaplastic lymphoma kinase (ALK) has been found in many types of cancer, and ALK is a promising therapeutic target for the treatment of cancer. To obtain new potent inhibitors of ALK, we conducted lead optimization using 3D-QSAR modeling and molecular docking investigation of 2,4-diaminopyrimidines and 2,7-disubstituted-pyrrolo[2,1-f][1,2,4]triazine-based compounds. Three favorable 3D-QSAR models (CoMFA with q2, 0.555; r2, 0.939; CoMSIA with q2, 0.625; r2, 0.974; Topomer CoMFA with q2, 0.557; r2 0.756) have been developed to predict the biological activity of novel compounds. Topomer Search was utilized for virtual screening to obtain suitable fragments. The novel compounds generated by molecular fragment replacement (MFR) were evaluated by Topomer CoMFA prediction, Glide (docking) and further evaluated with CoMFA and CoMSIA prediction. 25 novel 2,7-disubstituted-pyrrolo[2,1-f][1,2,4]triazine derivatives as potential ALK inhibitors were finally obtained. In this paper, a combination of CoMFA, CoMSIA and Topomer CoMFA could obtain favorable 3D-QSAR models and suitable fragments for ALK inhibitors optimization. The work flow which comprised 3D-QSAR modeling, Topomer Search, MFR, molecular docking and evaluating criteria could be applied to de novo drug design and the resulted compounds initiate us to further optimize and design new potential ALK inhibitors.

  17. On the number of EINECS compounds that can be covered by (Q)SAR models for acute toxicity.

    PubMed

    Zvinavashe, Elton; Murk, Albertinka J; Rietjens, Ivonne M C M

    2009-01-10

    The new EU legislation for managing chemicals called REACH aims to fill in gaps in toxicity information that exist for the chemicals listed on the European Inventory of Existing Chemical Substances (EINECS). REACH advocates the use of alternatives to animal experimentation including, amongst others, (quantitative) structure-activity relationship models [(Q)SARs] to help fill in the toxicity data gaps. The aim of the present study was to provide a science-based estimate of the number of EINECS compounds that can be covered by (Q)SAR models for acute toxicity. Using the ECOSAR software, 54% of the 100196 EINECS chemicals were classified into 49 classes that can be potentially covered by (Q)SAR models. The largest proportion of the classified compounds (40% of the EINECS list) falls into the classes of non-polar and polar narcotics. Compounds that were not classified include, for example, fish oils, botanical and animal extracts, and crude oil distillates. With rapid improvements in analytical tools, the number of EINECS compounds for which toxicity evaluations may be based on (Q)SAR approaches may be extended by further developing the method recently developed for the safety assessment of natural flavor complexes used as ingredients in food. This method is based on identification of the individual components in a mixture, and judgment of the safety of these identified individual compounds using toxicity information on structurally similar congeners in the respective classes. Such (Q)SAR approaches may be applied to an additional 2938 EINECS compounds, representing botanical and animal extracts, leading to a total estimate of 57% of the EINECS compounds for which (Q)SAR-based approaches may assist in their safety assessment. It is concluded that, despite the fact that individual (Q)SARs may often each cover only a limited number, i.e. less than 1%, of the EINECS compounds, the potential for applying (Q)SAR approaches for safety assessment of EINECS compounds may prove

  18. 3D QSAR studies of hydroxylated polychlorinated biphenyls as potential xenoestrogens.

    PubMed

    Ruiz, Patricia; Ingale, Kundan; Wheeler, John S; Mumtaz, Moiz

    2016-02-01

    Mono-hydroxylated polychlorinated biphenyls (OH-PCBs) are found in human biological samples and lack of data on their potential estrogenic activity has been a source of concern. We have extended our previous in silico 2D QSAR study through the application of advance techniques such as docking and 3D QSAR to gain insights into their estrogen receptor (ERα) binding. The results support our earlier findings that the hydroxyl group is the most important feature on the compounds; its position, orientation and surroundings in the structure are influential for the binding of OH-PCBs to ERα. This study has also revealed the following additional interactions that influence estrogenicity of these chemicals (a) the aromatic interactions of the biphenyl moieties with the receptor, (b) hydrogen bonding interactions of the p-hydroxyl group with key amino acids ARG394 and GLU353, (c) low or no electronegative substitution at para-positions of the p-hydroxyl group, (d) enhanced electrostatic interactions at the meta position on the B ring, and (e) co-planarity of the hydroxyl group on the A ring. In combination the 2D and 3D QSAR approaches have led us to the support conclusion that the hydroxyl group is the most important feature on the OH-PCB influencing the binding to estrogen receptors, and have enhanced our understanding of the mechanistic details of estrogenicity of this class of chemicals. Such in silico computational methods could serve as useful tools in risk assessment of chemicals. PMID:26598992

  19. QSAR studies of benzofuran/benzothiophene biphenyl derivatives as inhibitors of PTPase-1B

    PubMed Central

    Kaushik, D.; Kumar, R.; Saxena, A. K.

    2010-01-01

    Objectives: Insulin resistance is associated with a defect in protein tyrosine phosphorylation in the insulin signal transduction cascade. The PTPase enzyme dephosphorylates the active form of the insulin receptor and thus attenuates its tyrosine kinase activity, therefore, the need for a potent PTPase inhibitor exists, with the intention of which the QSAR was performed. Materials and Methods: Quantitative structure-activity relationship (QSAR) has been established on a series of 106 compounds considering 27 variables, for novel biphenyl analogs, using the SYSTAT (Version 7.0) software, for their protein tyrosine phosphatase (PTPase-1B) inhibitor activity, in order to understand the essential structural requirement for binding with the receptor. Results: Among several regression models, one per series was selected on the basis of a high correlation coefficient (r, 0.86), least standard deviation (s, 0.234), and a high value of significance for the maximum number of subjects (n, 101). Conclusions: The influence of the different physicochemical parameters of the substituents in various positions has been discussed by generating the best QSAR model using multiple regression analysis, and the information thus obtained from the present study can be used to design and predict more potent molecules as PTPase-1B inhibitors, prior to their synthesis. PMID:21814427

  20. More effective dithiocarbamate derivatives inhibiting carbonic anhydrases, generated by QSAR and computational design.

    PubMed

    Avram, Speranta; Milac, Adina Luminita; Carta, Fabrizio; Supuran, Claudiu T

    2013-04-01

    Dithiocarbamates (DTC) are promising compounds with potential applications in antitumoral and glaucoma therapy. Our aim is to understand molecular features affecting DTC interaction with carbonic anhydrases (CAs), zinc-containing enzymes maintaining acid-base balance in blood and other tissues. To this end, we generate QSAR models based on a compound series containing 25 DTC, inhibitors of four human (h) CAs isoforms: hCA I, II, IX and XII. We establish that critical physicochemical parameters for DTC inhibitory activity are: hydrophobic, electronic, steric, topological and shape. The predictive power of our QSAR models is indicated by significant values of statistical coefficients: cross-validated correlation q(2) (0.55-0.73), fitted correlation r(2) (0.75-0.84) and standard error of prediction (0.47-0.23). Based on the established QSAR equations, we analyse 22 new DTC derivatives and identify DTC dicarboxilic acids derivatives and their esters as potentially improved inhibitors of CA I, II, IX and XII. PMID:23116520

  1. Is conformation a fundamental descriptor in QSAR? A case for halogenated anesthetics

    PubMed Central

    Guimarães, Maria C; Duarte, Mariene H; Silla, Josué M

    2016-01-01

    Summary An intriguing question in 3D-QSAR lies on which conformation(s) to use when generating molecular descriptors (MD) for correlation with bioactivity values. This is not a simple task because the bioactive conformation in molecule data sets is usually unknown and, therefore, optimized structures in a receptor-free environment are often used to generate the MD´s. In this case, a wrong conformational choice can cause misinterpretation of the QSAR model. The present computational work reports the conformational analysis of the volatile anesthetic isoflurane (2-chloro-2-(difluoromethoxy)-1,1,1-trifluoroethane) in the gas phase and also in polar and nonpolar implicit and explicit solvents to show that stable minima (ruled by intramolecular interactions) do not necessarily coincide with the bioconformation (ruled by enzyme induced fit). Consequently, a QSAR model based on two-dimensional chemical structures was built and exhibited satisfactory modeling/prediction capability and interpretability, then suggesting that these 2D MD´s can be advantageous over some three-dimensional descriptors. PMID:27340468

  2. Theoretical studies on QSAR and mechanism of 2-indolinone derivatives as tubulin inhibitors

    NASA Astrophysics Data System (ADS)

    Liao, Si Yan; Qian, Li; Miao, Ti Fang; Lu, Hai Liang; Zheng, Kang Cheng

    The theoretical studies on three-dimensional quantitative structure activity relationship (3D-QSAR) and action mechanism of a series of 2-indolinone derivatives as tubulin inhibitors against human breast cancer cell line MDA-MB-231 have been carried out. The established 3D-QSAR model from the comparative molecular field analysis (CoMFA) shows not only significant statistical quality but also predictive ability, with high correlation coefficient (R2 = 0.986) and cross-validation coefficient (q2 = 0.683). In particular, the appropriate binding orientations and conformations of these 2-indolinone derivatives interacting with tubulin are located by docking study, and it is very interesting to find that the plot of the energy scores of these compounds in DOCK versus the corresponding experimental pIC50 values exhibits a considerable linear correlation. Therefore, the inhibition mechanism that 2-indolinone derivatives were regarded as tubulin inhibitors can be theoretically confirmed. Based on such an inhibition mechanism along with 3D-QSAR results, some important factors improving the activities of these compounds were discussed in detail. These factors can be summarized as follows: the H atom adopted as substituent R1, the substituent R2 with higher electropositivity and smaller bulk, the substituents R4-R6 (on the phenyl ring) with higher electropositivity and larger bulk, and so on. These results can offer useful theoretical references for understanding the action mechanism, designing more potent inhibitors, and predicting their activities prior to synthesis.

  3. Assessment of hydroxylated metabolites of polychlorinated biphenyls as potential xenoestrogens: a QSAR comparative analysis∗.

    PubMed

    Ruiz, P; Myshkin, E; Quigley, P; Faroon, O; Wheeler, J S; Mumtaz, M M; Brennan, R J

    2013-01-01

    Alternative methods, including quantitative structure-activity relationships (QSAR), are being used increasingly when appropriate data for toxicity evaluation of chemicals are not available. Approximately 40 mono-hydroxylated polychlorinated biphenyls (OH-PCBs) have been identified in humans. They represent a health and environmental concern because some of them have been shown to have agonist or antagonist interactions with human hormone receptors. This could lead to modulation of steroid hormone receptor pathways and endocrine system disruption. We performed QSAR analyses using available estrogenic activity (human estrogen receptor ER alpha) data for 71 OH-PCBs. The modelling was performed using multiple molecular descriptors including electronic, molecular, constitutional, topological, and geometrical endpoints. Multiple linear regressions and recursive partitioning were used to best fit descriptors. The results show that the position of the hydroxyl substitution, polarizability, and meta adjacent un-substituted carbon pairs at the phenolic ring contribute towards greater estrogenic activity for these chemicals. These comparative QSAR models may be used for predictive toxicity, and identification of health consequences of PCB metabolites that lack empirical data. Such information will help prioritize such molecules for additional testing, guide future basic laboratory research studies, and help the health/risk assessment community understand the complex nature of chemical mixtures. PMID:23557136

  4. QSAR analysis of nitroaromatics' toxicity in Tetrahymena pyriformis: structural factors and possible modes of action

    PubMed Central

    Artemenko, A.G.; Muratov, E. N.; Kuz’min, V.E.; Muratov, N.N.; Varlamova, E.V.; Kuz'mina, A.V.; Gorb, L. G.; Golius, A.; Hill, F.C.; Leszczynski, J.; Tropsha, A.

    2012-01-01

    The Hierarchical Technology for Quantitative Structure - Activity Relationships (HiT QSAR) was applied to 95 diverse nitroaromatic compounds (including some widely known explosives) tested for their toxicity (50% inhibition growth concentration, IGC50) against the ciliate Tetrahymena pyriformis. The dataset was divided into subsets according to putative mechanisms of toxicity. Classification and Regression Trees (CART) approach implemented within HiT QSAR has been used for prediction of mechanism of toxicity for new compounds. The resulting models were shown to have ~80% accuracy for external datasets indicating that the mechanistic dataset division was sensible. Then, Partial Least Squares (PLS) statistical approach was used for the development of 2D QSAR models. Validated PLS models were explored to (i) elucidate the effects of different substituents in nitroaromatic compounds on toxicity; (ii) differentiate compounds by probable mechanisms of toxicity based on their structural descriptors; (iii) analyze the role of various physical-chemical factors responsible for compounds’ toxicity. Models were interpreted in terms of molecular fragments promoting or interfering with toxicity. It was also shown that mutual influence of substituents in benzene ring plays the determining role in toxicity variation. Although chemical mechanism based models were statistically significant and externally predictive (R2ext=0.64 for the external set of 63 nitroaromatics identified after all calculations have been completed), they were also shown to have limited coverage (57% for modeling and 76% for external set). PMID:21714735

  5. QSAR Analysis of 2-Amino or 2-Methyl-1-Substituted Benzimidazoles Against Pseudomonas aeruginosa

    PubMed Central

    Podunavac-Kuzmanović, Sanja O.; Cvetković, Dragoljub D.; Barna, Dijana J.

    2009-01-01

    A set of benzimidazole derivatives were tested for their inhibitory activities against the Gram-negative bacterium Pseudomonas aeruginosa and minimum inhibitory concentrations were determined for all the compounds. Quantitative structure activity relationship (QSAR) analysis was applied to fourteen of the abovementioned derivatives using a combination of various physicochemical, steric, electronic, and structural molecular descriptors. A multiple linear regression (MLR) procedure was used to model the relationships between molecular descriptors and the antibacterial activity of the benzimidazole derivatives. The stepwise regression method was used to derive the most significant models as a calibration model for predicting the inhibitory activity of this class of molecules. The best QSAR models were further validated by a leave one out technique as well as by the calculation of statistical parameters for the established theoretical models. To confirm the predictive power of the models, an external set of molecules was used. High agreement between experimental and predicted inhibitory values, obtained in the validation procedure, indicated the good quality of the derived QSAR models. PMID:19468332

  6. Evaluation and comparison of benchmark QSAR models to predict a relevant REACH endpoint: The bioconcentration factor (BCF)

    SciTech Connect

    Gissi, Andrea; Lombardo, Anna; Roncaglioni, Alessandra; Gadaleta, Domenico; Mangiatordi, Giuseppe Felice; Nicolotti, Orazio; Benfenati, Emilio

    2015-02-15

    The bioconcentration factor (BCF) is an important bioaccumulation hazard assessment metric in many regulatory contexts. Its assessment is required by the REACH regulation (Registration, Evaluation, Authorization and Restriction of Chemicals) and by CLP (Classification, Labeling and Packaging). We challenged nine well-known and widely used BCF QSAR models against 851 compounds stored in an ad-hoc created database. The goodness of the regression analysis was assessed by considering the determination coefficient (R{sup 2}) and the Root Mean Square Error (RMSE); Cooper's statistics and Matthew's Correlation Coefficient (MCC) were calculated for all the thresholds relevant for regulatory purposes (i.e. 100 L/kg for Chemical Safety Assessment; 500 L/kg for Classification and Labeling; 2000 and 5000 L/kg for Persistent, Bioaccumulative and Toxic (PBT) and very Persistent, very Bioaccumulative (vPvB) assessment) to assess the classification, with particular attention to the models' ability to control the occurrence of false negatives. As a first step, statistical analysis was performed for the predictions of the entire dataset; R{sup 2}>0.70 was obtained using CORAL, T.E.S.T. and EPISuite Arnot–Gobas models. As classifiers, ACD and log P-based equations were the best in terms of sensitivity, ranging from 0.75 to 0.94. External compound predictions were carried out for the models that had their own training sets. CORAL model returned the best performance (R{sup 2}{sub ext}=0.59), followed by the EPISuite Meylan model (R{sup 2}{sub ext}=0.58). The latter gave also the highest sensitivity on external compounds with values from 0.55 to 0.85, depending on the thresholds. Statistics were also compiled for compounds falling into the models Applicability Domain (AD), giving better performances. In this respect, VEGA CAESAR was the best model in terms of regression (R{sup 2}=0.94) and classification (average sensitivity>0.80). This model also showed the best regression (R{sup 2

  7. Drug Design for CNS Diseases: Polypharmacological Profiling of Compounds Using Cheminformatic, 3D-QSAR and Virtual Screening Methodologies

    PubMed Central

    Nikolic, Katarina; Mavridis, Lazaros; Djikic, Teodora; Vucicevic, Jelica; Agbaba, Danica; Yelekci, Kemal; Mitchell, John B. O.

    2016-01-01

    HIGHLIGHTS Many CNS targets are being explored for multi-target drug designNew databases and cheminformatic methods enable prediction of primary pharmaceutical target and off-targets of compoundsQSAR, virtual screening and docking methods increase the potential of rational drug design The diverse cerebral mechanisms implicated in Central Nervous System (CNS) diseases together with the heterogeneous and overlapping nature of phenotypes indicated that multitarget strategies may be appropriate for the improved treatment of complex brain diseases. Understanding how the neurotransmitter systems interact is also important in optimizing therapeutic strategies. Pharmacological intervention on one target will often influence another one, such as the well-established serotonin-dopamine interaction or the dopamine-glutamate interaction. It is now accepted that drug action can involve plural targets and that polypharmacological interaction with multiple targets, to address disease in more subtle and effective ways, is a key concept for development of novel drug candidates against complex CNS diseases. A multi-target therapeutic strategy for Alzheimer‘s disease resulted in the development of very effective Multi-Target Designed Ligands (MTDL) that act on both the cholinergic and monoaminergic systems, and also retard the progression of neurodegeneration by inhibiting amyloid aggregation. Many compounds already in databases have been investigated as ligands for multiple targets in drug-discovery programs. A probabilistic method, the Parzen-Rosenblatt Window approach, was used to build a “predictor” model using data collected from the ChEMBL database. The model can be used to predict both the primary pharmaceutical target and off-targets of a compound based on its structure. Several multi-target ligands were selected for further study, as compounds with possible additional beneficial pharmacological activities. Based on all these findings, it is concluded that multipotent

  8. Drug Design for CNS Diseases: Polypharmacological Profiling of Compounds Using Cheminformatic, 3D-QSAR and Virtual Screening Methodologies.

    PubMed

    Nikolic, Katarina; Mavridis, Lazaros; Djikic, Teodora; Vucicevic, Jelica; Agbaba, Danica; Yelekci, Kemal; Mitchell, John B O

    2016-01-01

    HIGHLIGHTS Many CNS targets are being explored for multi-target drug designNew databases and cheminformatic methods enable prediction of primary pharmaceutical target and off-targets of compoundsQSAR, virtual screening and docking methods increase the potential of rational drug design The diverse cerebral mechanisms implicated in Central Nervous System (CNS) diseases together with the heterogeneous and overlapping nature of phenotypes indicated that multitarget strategies may be appropriate for the improved treatment of complex brain diseases. Understanding how the neurotransmitter systems interact is also important in optimizing therapeutic strategies. Pharmacological intervention on one target will often influence another one, such as the well-established serotonin-dopamine interaction or the dopamine-glutamate interaction. It is now accepted that drug action can involve plural targets and that polypharmacological interaction with multiple targets, to address disease in more subtle and effective ways, is a key concept for development of novel drug candidates against complex CNS diseases. A multi-target therapeutic strategy for Alzheimer's disease resulted in the development of very effective Multi-Target Designed Ligands (MTDL) that act on both the cholinergic and monoaminergic systems, and also retard the progression of neurodegeneration by inhibiting amyloid aggregation. Many compounds already in databases have been investigated as ligands for multiple targets in drug-discovery programs. A probabilistic method, the Parzen-Rosenblatt Window approach, was used to build a "predictor" model using data collected from the ChEMBL database. The model can be used to predict both the primary pharmaceutical target and off-targets of a compound based on its structure. Several multi-target ligands were selected for further study, as compounds with possible additional beneficial pharmacological activities. Based on all these findings, it is concluded that multipotent ligands

  9. Experiment Databases

    NASA Astrophysics Data System (ADS)

    Vanschoren, Joaquin; Blockeel, Hendrik

    Next to running machine learning algorithms based on inductive queries, much can be learned by immediately querying the combined results of many prior studies. Indeed, all around the globe, thousands of machine learning experiments are being executed on a daily basis, generating a constant stream of empirical information on machine learning techniques. While the information contained in these experiments might have many uses beyond their original intent, results are typically described very concisely in papers and discarded afterwards. If we properly store and organize these results in central databases, they can be immediately reused for further analysis, thus boosting future research. In this chapter, we propose the use of experiment databases: databases designed to collect all the necessary details of these experiments, and to intelligently organize them in online repositories to enable fast and thorough analysis of a myriad of collected results. They constitute an additional, queriable source of empirical meta-data based on principled descriptions of algorithm executions, without reimplementing the algorithms in an inductive database. As such, they engender a very dynamic, collaborative approach to experimentation, in which experiments can be freely shared, linked together, and immediately reused by researchers all over the world. They can be set up for personal use, to share results within a lab or to create open, community-wide repositories. Here, we provide a high-level overview of their design, and use an existing experiment database to answer various interesting research questions about machine learning algorithms and to verify a number of recent studies.

  10. 2D and 3D-QSAR studies on antiproliferative thiazolidine analogs

    NASA Astrophysics Data System (ADS)

    Liao, Si Yan; Qian, Li; Chen, Jin Can; Lu, Hai Liang; Zheng, Kang Cheng

    Two-dimensional (2D) and three-dimensional (3D) quantitative structure-activity relationships (QSARs) of 22 thiazolidine analogs with antiproliferative activity expressed as pIC50, which is defined as the negative value of the logarithm of necessary molar concentration of these compounds to cause 50% growth inhibition against melanoma cell lines WM-164, have been studied by using a combined method of the DFT, MM2 and statistics for 2D, as well as the comparative molecular field analysis (CoMFA) method for 3D. The established 2D-QSAR model in training set comprised of random 18 compounds shows not only significant statistical quality, but also predictive ability, with the square of adjusted correlation coefficient (R2A = 0.832) and the square of the cross-validation coefficient (q2 = 0.803). The same model was further applied to predict pIC50 values of the four compounds in the test set, and the resulting R2pred reaching 0.784, further confirms that this 2D-QSAR model has high predictive ability. The 3D-QSAR model also shows good correlative and predictive capabilities in terms of R2 (0.956) and q2 (0.615) obtained from CoMFA model. Further, the robustness of the CoMFA model was verified by bootstrapping analysis (100 runs) with R2bs (0.979) and SDbs (0.056). It is very interesting to find that the results from 2D- and 3D-QSAR analyses accord with each other, and they all show that the steric interaction plays a crucial role in determining the cytotoxicities of the compounds, and that selecting a moderate-size or appropriate-hydrophobicity substituent R as well as increasing the negative charges of C4 on phenyl ring at the same time are advantageous to improving the cytotoxicity. Such results can offer some useful theoretical references for directing the molecular design and understanding the action mechanism of this kind of compound with antiproliferative activity.

  11. Solubility Database

    National Institute of Standards and Technology Data Gateway

    SRD 106 IUPAC-NIST Solubility Database (Web, free access)   These solubilities are compiled from 18 volumes (Click here for List) of the International Union for Pure and Applied Chemistry(IUPAC)-NIST Solubility Data Series. The database includes liquid-liquid, solid-liquid, and gas-liquid systems. Typical solvents and solutes include water, seawater, heavy water, inorganic compounds, and a variety of organic compounds such as hydrocarbons, halogenated hydrocarbons, alcohols, acids, esters and nitrogen compounds. There are over 67,500 solubility measurements and over 1800 references.

  12. 3D-QSAR modelling dataset of bioflavonoids for predicting the potential modulatory effect on P-glycoprotein activity.

    PubMed

    Wongrattanakamon, Pathomwat; Lee, Vannajan Sanghiran; Nimmanpipug, Piyarat; Jiranusornkul, Supat

    2016-12-01

    The data is obtained from exploring the modulatory activities of bioflavonoids on P-glycoprotein function by ligand-based approaches. Multivariate Linear-QSAR models for predicting the induced/inhibitory activities of the flavonoids were created. Molecular descriptors were initially used as independent variables and a dependent variable was expressed as pFAR. The variables were then used in MLR analysis by stepwise regression calculation to build the linear QSAR data. The entire dataset consisted of 23 bioflavonoids was used as a training set. Regarding the obtained MLR QSAR model, R of 0.963, R (2)=0.927, [Formula: see text], SEE=0.197, F=33.849 and q (2)=0.927 were achieved. The true predictabilities of QSAR model were justified by evaluation with the external dataset (Table 4). The pFARs of representative flavonoids were predicted by MLR QSAR modelling. The data showed that internal and external validations may generate the same conclusion. PMID:27626051

  13. QSAR study of substituted 2-pyridinyl guanidines as selective urokinase-type plasminogen activator (uPA) inhibitors.

    PubMed

    Karthikeyan, C; Moorthy, N S Hari Narayana; Trivedi, Piyush

    2009-02-01

    A quantitative structure-activity relationship analysis was conducted on two different series of pyridinylguanidines acting as inhibitors of urokinase-type plasminogen activator using QuaSAR descriptors of molecular modeling software MOE. Multiple linear regression analysis following a stepwise scheme was employed to generate QSARs that relate molecular descriptors to uPA inhibitory activity data of the title compounds. Among the several QSARs generated by MLR analysis, the best models were selected on the basis of their statistical significance and predictive potential. The interpretation of the selected QSAR models suggest that uPA inhibitory activity of compounds in series 1 is influenced by their molecular shape, molecular flexibility and halogen atoms in the molecule whereas the uPA inhibitory potency of compounds in series 2 is dependent on molecular lipophilicity, number of double bonds and spatial orientation of bulky substituents in the molecule. PMID:19012070

  14. Drinking Water Treatability Database (Database)

    EPA Science Inventory

    The drinking Water Treatability Database (TDB) will provide data taken from the literature on the control of contaminants in drinking water, and will be housed on an interactive, publicly-available USEPA web site. It can be used for identifying effective treatment processes, rec...

  15. Comparison of Different 2D and 3D-QSAR Methods on Activity Prediction of Histamine H3 Receptor Antagonists.

    PubMed

    Dastmalchi, Siavoush; Hamzeh-Mivehroud, Maryam; Asadpour-Zeynali, Karim

    2012-01-01

    Histamine H3 receptor subtype has been the target of several recent drug development programs. Quantitative structure-activity relationship (QSAR) methods are used to predict the pharmaceutically relevant properties of drug candidates whenever it is applicable. The aim of this study was to compare the predictive powers of three different QSAR techniques, namely, multiple linear regression (MLR), artificial neural network (ANN), and HASL as a 3D QSAR method, in predicting the receptor binding affinities of arylbenzofuran histamine H3 receptor antagonists. Genetic algorithm coupled partial least square as well as stepwise multiple regression methods were used to select a number of calculated molecular descriptors to be used in MLR and ANN-based QSAR studies. Using the leave-group-out cross-validation technique, the performances of the MLR and ANN methods were evaluated. The calculated values for the mean absolute percentage error (MAPE), ranging from 2.9 to 3.6, and standard deviation of error of prediction (SDEP), ranging from 0.31 to 0.36, for both MLR and ANN methods were statistically comparable, indicating that both methods perform equally well in predicting the binding affinities of the studied compounds toward the H3 receptors. On the other hand, the results from 3D-QSAR studies using HASL method were not as good as those obtained by 2D methods. It can be concluded that simple traditional approaches such as MLR method can be as reliable as those of more advanced and sophisticated methods like ANN and 3D-QSAR analyses. PMID:25317190

  16. Flow network QSAR for the prediction of physicochemical properties by mapping an electrical resistance network onto a chemical reaction poset.

    PubMed

    Ivanciuc, Ovidiu; Ivanciuc, Teodora; Klein, Douglas J

    2013-06-01

    Usual quantitative structure-activity relationship (QSAR) models are computed from unstructured input data, by using a vector of molecular descriptors for each chemical in the dataset. Another alternative is to consider the structural relationships between the chemical structures, such as molecular similarity, presence of certain substructures, or chemical transformations between compounds. We defined a class of network-QSAR models based on molecular networks induced by a sequence of substitution reactions on a chemical structure that generates a partially ordered set (or poset) oriented graph that may be used to predict various molecular properties with quantitative superstructure-activity relationships (QSSAR). The network-QSAR interpolation models defined on poset graphs, namely average poset, cluster expansion, and spline poset, were tested with success for the prediction of several physicochemical properties for diverse chemicals. We introduce the flow network QSAR, a new poset regression model in which the dataset of chemicals, represented as a reaction poset, is transformed into an oriented network of electrical resistances in which the current flow results in a potential at each node. The molecular property considered in the QSSAR model is represented as the electrical potential, and the value of this potential at a particular node is determined by the electrical resistances assigned to each edge and by a system of batteries. Each node with a known value for the molecular property is attached to a battery that sets the potential on that node to the value of the respective molecular property, and no external battery is attached to nodes from the prediction set, representing chemicals for which the values of the molecular property are not known or are intended to be predicted. The flow network QSAR algorithm determines the values of the molecular property for the prediction set of molecules by applying Ohm's law and Kirchhoff's current law to the poset

  17. Dependence of QSAR models on the selection of trial descriptor sets: a demonstration using nanotoxicity endpoints of decorated nanotubes.

    PubMed

    Shao, Chi-Yu; Chen, Sing-Zuo; Su, Bo-Han; Tseng, Yufeng J; Esposito, Emilio Xavier; Hopfinger, Anton J

    2013-01-28

    Little attention has been given to the selection of trial descriptor sets when designing a QSAR analysis even though a great number of descriptor classes, and often a greater number of descriptors within a given class, are now available. This paper reports an effort to explore interrelationships between QSAR models and descriptor sets. Zhou and co-workers (Zhou et al., Nano Lett. 2008, 8 (3), 859-865) designed, synthesized, and tested a combinatorial library of 80 surface modified, that is decorated, multi-walled carbon nanotubes for their composite nanotoxicity using six endpoints all based on a common 0 to 100 activity scale. Each of the six endpoints for the 29 most nanotoxic decorated nanotubes were incorporated as the training set for this study. The study reported here includes trial descriptor sets for all possible combinations of MOE, VolSurf, and 4D-fingerprints (FP) descriptor classes, as well as including and excluding explicit spatial contributions from the nanotube. Optimized QSAR models were constructed from these multiple trial descriptor sets. It was found that (a) both the form and quality of the best QSAR models for each of the endpoints are distinct and (b) some endpoints are quite dependent upon 4D-FP descriptors of the entire nanotube-decorator complex. However, other endpoints yielded equally good models only using decorator descriptors with and without the decorator-only 4D-FP descriptors. Lastly, and most importantly, the quality, significance, and interpretation of a QSAR model were found to be critically dependent on the trial descriptor sets used within a given QSAR endpoint study. PMID:23252880

  18. Using particle swarms for the development of QSAR models based on K-nearest neighbor and kernel regression.

    PubMed

    Cedeño, Walter; Agrafiotis, Dimitris K

    2003-01-01

    We describe the application of particle swarms for the development of quantitative structure-activity relationship (QSAR) models based on k-nearest neighbor and kernel regression. Particle swarms is a population-based stochastic search method based on the principles of social interaction. Each individual explores the feature space guided by its previous success and that of its neighbors. Success is measured using leave-one-out (LOO) cross validation on the resulting model as determined by k-nearest neighbor kernel regression. The technique is shown to compare favorably to simulated annealing using three classical data sets from the QSAR literature. PMID:13677491

  19. Quantitative Structure--Activity Relationship (QSAR) for the Oxidation of Trace Organic Contaminants by Sulfate Radical.

    PubMed

    Xiao, Ruiyang; Ye, Tiantian; Wei, Zongsu; Luo, Shuang; Yang, Zhihui; Spinney, Richard

    2015-11-17

    The sulfate radical anion (SO4•–) based oxidation of trace organic contaminants (TrOCs) has recently received great attention due to its high reactivity and low selectivity. In this study, a meta-analysis was conducted to better understand the role of functional groups on the reactivity between SO4•– and TrOCs. The results indicate that compounds in which electron transfer and addition channels dominate tend to exhibit a faster second-order rate constants (kSO4•–) than that of H–atom abstraction, corroborating the SO4•– reactivity and mechanisms observed in the individual studies. Then, a quantitative structure activity relationship (QSAR) model was developed using a sequential approach with constitutional, geometrical, electrostatic, and quantum chemical descriptors. Two descriptors, ELUMO and EHOMO energy gap (ELUMO–EHOMO) and the ratio of oxygen atoms to carbon atoms (#O:C), were found to mechanistically and statistically affect kSO4•– to a great extent with the standardized QSAR model: ln kSO4•– = 26.8–3.97 × #O:C – 0.746 × (ELUMO–EHOMO). In addition, the correlation analysis indicates that there is no dominant reaction channel for SO4•– reactions with various structurally diverse compounds. Our QSAR model provides a robust predictive tool for estimating emerging micropollutants removal using SO4•– during wastewater treatment processes. PMID:26451961

  20. Quantitative structure-activity relationships (QSARs) using the novel marine algal toxicity data of phenols.

    PubMed

    Ertürk, M Doğa; Saçan, Melek Türker; Novic, Marjana; Minovski, Nikola

    2012-09-01

    The present study reports for the first time in its entirety the toxicity of 30 phenolic compounds to marine alga Dunaliella tertiolecta. Toxicity of polar narcotics and respiratory uncouplers was strongly correlated to hydrophobicity as described by the logarithm of the octanol/water partition coefficient (Log P). Compounds expected to act by more reactive mechanisms, particularly hydroquinones, were shown to have toxicity in excess of that predicted by Log P. A quality quantitative structure-activity relationship (QSAR) was obtained with Log P and a 2D autocorrelation descriptor weighted by atomic polarizability (MATS3p) only after the removal of hydroquinones from the data set. In an attempt to model the whole data set including hydroquinones, 3D descriptors were included in the modeling process and three quality QSARs were developed using multiple linear regression (MLR). One of the most significant results of the present study was the superior performance of the consensus MLR model, obtained by averaging the predictions from each individual linear model, which provided excellent prediction accuracy for the test set (Q(test)²=0.94). The four-parameter Counter Propagation Artificial Neural Network (CP ANN) model, which was constructed using four out of six descriptors that appeared in the linear models, also provided an excellent external predictivity (Q(test)²=0.93). The proposed algal QSARs were further tested in their predictivity using an external set comprising toxicity data of 44 chemicals on freshwater alga Pseudokirchneriella subcapitata. The two-parameter global model employing a 3D descriptor (Mor24m) and a charge-related descriptor (C(ortho)) not only had high external predictivity (Q(ext)²=0.74), but it also had excellent external data set coverage (%97). PMID:23085159

  1. QSAR modeling and molecular interaction analysis of natural compounds as potent neuraminidase inhibitors.

    PubMed

    Sun, Jiaying; Mei, Hu

    2016-04-26

    Different QSAR models of 40 natural compounds as neuraminidase inhibitors (NIs) are developed to comprehend chemical-biological interactions and predict activities against neuraminidase (NA) from Clostridium perfringens. Based on the constitutional, topological and conformational descriptors, R(2) and Q(2) values of the obtained SRA model are 0.931 and 0.856. The R(2) and Q(2) values of the constructed HQSAR and almond models are 0.903 and 0.767, 0.904 and 0.511, respectively. Based on the pharmacophore alignment, R(2) and Q(2) values of the optimal CoMSIA model are 0.936 and 0.654. Moreover, Rtest(2) and Qext(2) of values of SRA, HQSAR, almond and CoMSIA models are 0.611 and 0.565, 0.753 and 0.750, 0.612 and 0.582, 0.582 and 0.571, respectively. So, QSAR models have good predictive capability. They can be further used to evaluate and screen new compounds. Moreover, hydrogen bonds and electrostatic factors have high contributions to activities. To understand molecular interactions between natural compounds and NA from Clostridium perfringens, molecular docking is investigated. The docking results elucidate that Arg266, Asp291, Asp328, Tyr485, Glu493, Arg555, Arg615 and Tyr655 are especially the key residues in the active site of 2bf6. Hydrogen bonds and electrostatics are key factors, which impact the interactions between NIs and NA. So, the influential factors of interactions between NIs and NA in the docking results are in agreement with the QSAR results. PMID:27008437

  2. Quasi-QSAR for mutagenic potential of multi-walled carbon-nanotubes.

    PubMed

    Toropov, Andrey A; Toropova, Alla P

    2015-04-01

    Available on the Internet, the CORAL software (http://www.insilico.eu/coral) has been used to build up quasi-quantitative structure-activity relationships (quasi-QSAR) for prediction of mutagenic potential of multi-walled carbon-nanotubes (MWCNTs). In contrast with the previous models built up by CORAL which were based on representation of the molecular structure by simplified molecular input-line entry system (SMILES) the quasi-QSARs based on the representation of conditions (not on the molecular structure) such as concentration, presence (absence) S9 mix, the using (or without the using) of preincubation were encoded by so-called quasi-SMILES. The statistical characteristics of these models (quasi-QSARs) for three random splits into the visible training set and test set and invisible validation set are the following: (i) split 1: n=13, r(2)=0.8037, q(2)=0.7260, s=0.033, F=45 (training set); n=5, r(2)=0.9102, s=0.071 (test set); n=6, r(2)=0.7627, s=0.044 (validation set); (ii) split 2: n=13, r(2)=0.6446, q(2)=0.4733, s=0.045, F=20 (training set); n=5, r(2)=0.6785, s=0.054 (test set); n=6, r(2)=0.9593, s=0.032 (validation set); and (iii) n=14, r(2)=0.8087, q(2)=0.6975, s=0.026, F=51 (training set); n=5, r(2)=0.9453, s=0.074 (test set); n=5, r(2)=0.8951, s=0.052 (validation set). PMID:25465947

  3. A quantitative structure activity relationships (QSAR) analysis of triarylmethane dye tracers

    NASA Astrophysics Data System (ADS)

    Mon, Jarai; Flury, Markus; Harsh, James B.

    2006-01-01

    Dyes are important hydrological tracers. Many different dyes have been proposed as optimal tracers, but none of these dyes can be considered an ideal water tracer. Some dyes are toxic and most sorb to subsurface materials. The objective of this study was to find the molecular structure of an optimal water tracer. We used QSAR to screen a large number of hypothetical molecules, belonging to the class of triarylmethane dyes, in regard to their sorption characteristics to a sandy soil. The QSAR model was based on experimental sorption data obtained from four triarylmethane dyes: C.I. Food Blue 2 (C.I. 42090; Brilliant Blue FCF), C.I. Food Green 3 (C.I. 42053; FD&C Green No. 3), C.I. Acid Blue 7 (C.I. 42080; ORCOacid Blue A 150%), and C.I. Acid Green 9 (C.I. 42100; ORCOacid Fast Green B). Sorption characteristics of the dyes to the sandy soil were expressed with the Langmuir isotherm. Our premise was that dye sorption can be reduced by attachment of sulfonic acid (SO 3) groups to the triarylmethane template. About 70 hypothetical dyes were created and QSAR were used to estimate sorption characteristics. The results indicated that both the position and the number of SO 3 groups affected dye sorption. Sorption decreased with increasing number of SO 3 groups attached to the molecule. Increasing the number of sulfonic acid groups also decreases the toxicity of the compounds. An optimal triarylmethane water tracer contains 4 to 6 SO 3 groups.

  4. QSAR and Docking Studies on Capsazepine Derivatives for Immunomodulatory and Anti-Inflammatory Activity

    PubMed Central

    Shukla, Aparna; Sharma, Pooja; Prakash, Om; Singh, Monika; Kalani, Komal; Khan, Feroz; Bawankule, Dnyaneshwar Umrao; Luqman, Suaib; Srivastava, Santosh Kumar

    2014-01-01

    Capsazepine, an antagonist of capsaicin, is discovered by the structure and activity relationship. In previous studies it has been found that capsazepine has potency for immunomodulation and anti-inflammatory activity and emerging as a favourable target in quest for efficacious and safe anti-inflammatory drug. Thus, a 2D quantitative structural activity relationship (QSAR) model against target tumor necrosis factor-α (TNF-α) was developed using multiple linear regression method (MLR) with good internal prediction (r2 = 0.8779) and external prediction (r2pred = 0.5865) using Discovery Studio v3.5 (Accelrys, USA). The predicted activity was further validated by in vitro experiment. Capsazepine was tested in lipopolysaccharide (LPS) induced inflammation in peritoneal mouse macrophages. Anti-inflammatory profile of capsazepine was assessed by its potency to inhibit the production of inflammatory mediator TNF-α. The in vitro experiment indicated that capsazepine is an efficient anti-inflammatory agent. Since, the developed QSAR model showed significant correlations between chemical structure and anti-inflammatory activity, it was successfully applied in the screening of forty-four virtual derivatives of capsazepine, which finally afforded six potent derivatives, CPZ-29, CPZ-30, CPZ-33, CPZ-34, CPZ-35 and CPZ-36. To gain more insights into the molecular mechanism of action of capsazepine and its derivatives, molecular docking and in silico absorption, distribution, metabolism, excretion and toxicity (ADMET) studies were performed. The results of QSAR, molecular docking, in silico ADMET screening and in vitro experimental studies provide guideline and mechanistic scope for the identification of more potent anti-inflammatory & immunomodulatory drug. PMID:25003344

  5. Analogue-based approaches in anti-cancer compound modelling: the relevance of QSAR models

    PubMed Central

    2011-01-01

    Background QSAR is among the most extensively used computational methodology for analogue-based design. The application of various descriptor classes like quantum chemical, molecular mechanics, conceptual density functional theory (DFT)- and docking-based descriptors for predicting anti-cancer activity is well known. Although in vitro assay for anti-cancer activity is available against many different cell lines, most of the computational studies are carried out targeting insufficient number of cell lines. Hence, statistically robust and extensive QSAR studies against 29 different cancer cell lines and its comparative account, has been carried out. Results The predictive models were built for 266 compounds with experimental data against 29 different cancer cell lines, employing independent and least number of descriptors. Robust statistical analysis shows a high correlation, cross-validation coefficient values, and provides a range of QSAR equations. Comparative performance of each class of descriptors was carried out and the effect of number of descriptors (1-10) on statistical parameters was tested. Charge-based descriptors were found in 20 out of 39 models (approx. 50%), valency-based descriptor in 14 (approx. 36%) and bond order-based descriptor in 11 (approx. 28%) in comparison to other descriptors. The use of conceptual DFT descriptors does not improve the statistical quality of the models in most cases. Conclusion Analysis is done with various models where the number of descriptors is increased from 1 to 10; it is interesting to note that in most cases 3 descriptor-based models are adequate. The study reveals that quantum chemical descriptors are the most important class of descriptors in modelling these series of compounds followed by electrostatic, constitutional, geometrical, topological and conceptual DFT descriptors. Cell lines in nasopharyngeal (2) cancer average R2 = 0.90 followed by cell lines in melanoma cancer (4) with average R2 = 0.81 gave the

  6. Mogens Jansen: An Interview with a Danish Reading Educator.

    ERIC Educational Resources Information Center

    Engberg, Eva

    1985-01-01

    The president of the Danish Association of Reading Teachers discusses the positive effects of international cooperation on reading education, the influence of society's demands on curriculum, and the instinctive features and benefits of Danish Reading instruction. (FL)

  7. Exploring clotrimazole-based pharmacophore: 3D-QSAR studies and synthesis of novel antiplasmodial agents.

    PubMed

    Brogi, Simone; Brindisi, Margherita; Joshi, Bhupendra P; Sanna Coccone, Salvatore; Parapini, Silvia; Basilico, Nicoletta; Novellino, Ettore; Campiani, Giuseppe; Gemma, Sandra; Butini, Stefania

    2015-11-15

    We report herein the generation and validation of a 3D-QSAR model based on a set of antimalarials previously described by us and characterized by a clotrimazole-based pharmacophore. A novel series of derivatives was synthesized and showed activity against Plasmodium falciparum chloroquine-sensitive (CQ-S) and chloroquine-resistant (CQ-R) strains. Gratifyingly, compounds 35a-c showed interesting activity against P. falciparum CQ-R strains with improved predicted physico-chemical properties. PMID:26428874

  8. Synthesis, antimalarial properties and 2D-QSAR studies of novel triazole-quinine conjugates.

    PubMed

    Faidallah, Hassan M; Panda, Siva S; Serrano, Juan C; Girgis, Adel S; Khan, Khalid A; Alamry, Khalid A; Therathanakorn, Tanya; Meyers, Marvin J; Sverdrup, Francis M; Eickhoff, Christopher S; Getchell, Stephen G; Katritzky, Alan R

    2016-08-15

    Click chemistry technique led to novel 1,2,3-triazole-quinine conjugates 8a-g, 10a-o, 11a-h and 13 utilizing benzotriazole-mediated synthetic approach with excellent yields. Some of the synthesized analogs (11a, 11d-h) exhibited antimalarial properties against Plasmodium falciparum strain 3D7 with potency higher than that of quinine (standard reference used) through in vitro standard procedure bio-assay. Statistically significant BMLR-QSAR model describes the bio-properties, validates the observed biological observations and identifies the most important parameters governing bio-activity. PMID:27298002

  9. QSAR studies on benzodiazepine receptor binding of purines and amino acid derivatives.

    PubMed

    Saha, R N; Meera, J; Agrawal, N; Gupta, S P

    1991-01-01

    Quantitative structure-activity relationship (QSAR) studies are reported on the benzodiazepine receptor binding of a series of substituted 9-benzyl-6-dimethylamino-9H-purines and N-(indol-3-ylglyoxylyl)amino acid derivatives. The nitrogen of the five membered heterocyclic ring and the polar substituent in the aromatic ring, present in both series of compounds, form important centres in the binding interaction. We conclude that the receptor must possess a strong nucleophilic centre and a polar site, and that a hydrophobic pocket exists to accommodate hydrophobic moieties. PMID:1654919

  10. Prediction of aromatic amine carcinogenicity: QSAR base on calculated delocalizibility of hypothetical nitrenium ion intermediate

    SciTech Connect

    Purdy, R.

    1995-12-31

    Predictors for the reactivity of primary aromatic amines were hypothesized and tested on a small set of amines. It was found that the delocalizibility on the nitrogen of the previously hypothesized nitrenium ion intermediate was the only good predictor. The strength of this predictor was tested on a larger set of amines and a cut off value for discriminating between carcinogens and noncarcinogens was chosen. This QSAR supports the hypothesis that a nitrenium ion is an intermediate in the activation of primary aromatic amines to active carcinogens.

  11. QSAR study of flavonoids and biflavonoids as influenza H1N1 virus neuraminidase inhibitors.

    PubMed

    Mercader, Andrew G; Pomilio, Alicia B

    2010-05-01

    We performed a predictive analysis based on Quantitative Structure-Activity Relationships (QSAR) of a very important property of flavonoids which is the inhibition (IC50) of influenza H1N1 virus neuraminidase. The best linear model constructed from 20 molecular structures incorporated four molecular descriptors, selected from more than a thousand geometrical, topological, quantum-mechanical and electronic types of descriptors. The obtained model suggests that the activity depends on the electric charges, masses and polarizabilities of the atoms present in the molecule as well as its conformation. The model showed good predictive ability established by the theoretical and external test set validations. PMID:20116898

  12. Adherence to treatment: practice, education and research in Danish community pharmacy

    PubMed Central

    Haugbølle, Lotte S.; Herborg, Hanne

    2009-01-01

    Objective: To describe the practice, education and research concerning medication adherence in Danish community pharmacy. Methods: The authors supplemented their expertise in the area of medication adherence through their contacts with other educators and researchers as well as by conducting searches in the Danish Pharmacy Practice Evidence Database, which provides annually updated literature reviews on intervention research in Danish pharmacy practice. Results: Practice: Medication adherence is the focus of and/or is supported by a large number of services and initiatives used in pharmacy practice such as governmental funding, IT-supported medicine administration systems, dose-dispensing systems, theme years in pharmacies on adherence and concordance, standards for counselling at the counter, pharmacist counselling, medication reviews and inhaler technique assessment. Education: In Denmark, pharmacy and pharmaconomist students are extensively trained in the theory and practice of adherence to therapy. Pharmacy staff can choose from a variety of continuing education and post-graduate programmes which address patient adherence. Research: Nine ongoing and recently completed studies are described. Early research in Denmark comprised primarily smaller, qualitative studies centred on user perspectives, whereas later research has shifted the focus towards larger, quantitative, controlled studies and action-oriented studies focusing on patient groups with chronic diseases (such as diabetes, asthma, coronary vascular diseases). Conclusions: Our analysis has documented that Danish pharmaceutical education and research has focused strongly on adherence to treatment for more than three decades. Adherence initiatives in Danish community pharmacies have developed substantially in the past 5-10 years, and, as pharmacies have prioritised their role in health care and patient safety, this development can be expected to continue in future years. PMID:25136393

  13. The Danish Communicative Developmental Inventories: Validity and Main Developmental Trends

    ERIC Educational Resources Information Center

    Bleses, Dorthe; Vach, Werner; Slott, Malene; Wehberg, Sonja; Thomsen, Pia; Madsen, Thomas O.; Basboll, Hans

    2008-01-01

    This paper presents a large-scale cross-sectional study of Danish children's early language acquisition based on the Danish adaptation of the "MacArthur-Bates Communicative Development Inventories" (CDI). Measures of validity and reliability imply that the Danish adaptation of the American CDI has been adjusted linguistically and culturally in…

  14. The rm2 metrics and regression through origin approach: reliable and useful validation tools for predictive QSAR models (Commentary on 'Is regression through origin useful in external validation of QSAR models?').

    PubMed

    Roy, Kunal; Kar, Supratik

    2014-10-01

    Quantitative structure-activity relationship (QSAR) is an in silico technique which can be used in drug discovery, environmental fate modeling, property and toxicity prediction of chemical entities and regulatory toxicology. The predictive potential of a QSAR model is judged from various validation metrics in order to evaluate how well it is capable to predict endpoint values of new untested compounds. The rm2 group of metrics is one of the stringent validation metrics currently used by the QSAR fraternity in different reports. We scrutinized a recently published paper which raised an issue that the constructed criteria based on regression through origin (RTO) are not optimal and there is a significant difference in the rm2 metrics values computed from different statistical software packages. According to our point of view, the conclusion drawn in this paper appears to be misleading. Any inconsistency in the software algorithms has nothing to do with the calculation of rm2 metrics, as such computation is not limited by the use of any specific software, rather it depends only on fundamental mathematical formulae that are well established. However, it is a concern to the QSAR users that Excel and SPSS can return different results for the metrics using the RTO method. Thus, a proper validation of the software tool is required before its use for computation of any validation metric. PMID:24881556

  15. Estimation of the chemical-induced eye injury using a Weight-of-Evidence (WoE) battery of 21 artificial neural network (ANN) c-QSAR models (QSAR-21): part II: corrosion potential.

    PubMed

    Verma, Rajeshwar P; Matthews, Edwin J

    2015-03-01

    This is part II of an in silico investigation of chemical-induced eye injury that was conducted at FDA's CFSAN. Serious eye damage caused by chemical (eye corrosion) is assessed using the rabbit Draize test, and this endpoint is an essential part of hazard identification and labeling of industrial and consumer products to ensure occupational and consumer safety. There is an urgent need to develop an alternative to the Draize test because EU's 7th amendment to the Cosmetic Directive (EC, 2003; 76/768/EEC) and recast Regulation now bans animal testing on all cosmetic product ingredients and EU's REACH Program limits animal testing for chemicals in commerce. Although in silico methods have been reported for eye irritation (reversible damage), QSARs specific for eye corrosion (irreversible damage) have not been published. This report describes the development of 21 ANN c-QSAR models (QSAR-21) for assessing eye corrosion potential of chemicals using a large and diverse CFSAN data set of 504 chemicals, ADMET Predictor's three sensitivity analyses and ANNE classification functionalities with 20% test set selection from seven different methods. QSAR-21 models were internally and externally validated and exhibited high predictive performance: average statistics for the training, verification, and external test sets of these models were 96/96/94% sensitivity and 91/91/90% specificity. PMID:25510831

  16. Molecular docking based virtual screening of natural compounds as potential BACE1 inhibitors: 3D QSAR pharmacophore mapping and molecular dynamics analysis.

    PubMed

    Kumar, Akhil; Roy, Sudeep; Tripathi, Shubhandra; Sharma, Ashok

    2016-01-01

    Beta-site APP cleaving enzyme1 (BACE1) catalyzes the rate determining step in the generation of Aβ peptide and is widely considered as a potential therapeutic drug target for Alzheimer's disease (AD). Active site of BACE1 contains catalytic aspartic (Asp) dyad and flap. Asp dyad cleaves the substrate amyloid precursor protein with the help of flap. Currently, there are no marketed drugs available against BACE1 and existing inhibitors are mostly pseudopeptide or synthetic derivatives. There is a need to search for a potent inhibitor with natural scaffold interacting with flap and Asp dyad. This study screens the natural database InterBioScreen, followed by three-dimensional (3D) QSAR pharmacophore modeling, mapping, in silico ADME/T predictions to find the potential BACE1 inhibitors. Further, molecular dynamics of selected inhibitors were performed to observe the dynamic structure of protein after ligand binding. All conformations and the residues of binding region were stable but the flap adopted a closed conformation after binding with the ligand. Bond oligosaccharide interacted with the flap as well as catalytic dyad via hydrogen bond throughout the simulation. This led to stabilize the flap in closed conformation and restricted the entry of substrate. Carbohydrates have been earlier used in the treatment of AD because of their low toxicity, high efficiency, good biocompatibility, and easy permeability through the blood-brain barrier. Our finding will be helpful in identify the potential leads to design novel BACE1 inhibitors for AD therapy. PMID:25707809

  17. Fine-Scale Road Stretch Forecasting along Main Danish Roads

    NASA Astrophysics Data System (ADS)

    Mahura, A.; Petersen, C.; Sattler, K.; Sass, B.

    2009-09-01

    and fine height accuracy. The main aim of this study is to research, analyze, develop, and improve the quality of the road condition forecasts by refining, detalization, setting up, and running the fine-scale resolution numerical weather prediction (NWP) model with integration (from high resolution databases) of characteristics and derived parameters of surrounding roads the land-use, terrain, positioning and road properties at road stations/ stretches. The objectives include, at first, research and development of the existing road model based on input from a fine-scale NWP modelling. At second, it is analysis and integration of detailed data and derived parameters at road stations/stretches into the RCM based on available detailed Danish datasets on terrain, GPS positioning, land-use, and road properties. And at third, it is elaboration, testing, evaluation, and implementation of the methods and approaches suitable for forecasting and verification of the RCM performance for fine-scales. The results of this study are applicable for improvement of quality of detailed forecasts at road stretches. This will facilitate the use of data from the road stretch forecasting to automatic adjustment of control of the dosage spread by salting spreaders (i.e. for optimization of the salt amount spreaded in order to prevent the icing/freezing and better timing of salting schedule). It will lead to improvement of the overall safety of the winter road traffic. It will contribute to further development and improvement of the visualization tools for the road stretches forecasting. And it may reduce the environmental impact in the road surroundings due to an optimized spreading of the salt.

  18. Structural and Physico-Chemical Interpretation (SPCI) of QSAR Models and Its Comparison with Matched Molecular Pair Analysis.

    PubMed

    Polishchuk, Pavel; Tinkov, Oleg; Khristova, Tatiana; Ognichenko, Ludmila; Kosinskaya, Anna; Varnek, Alexandre; Kuz'min, Victor

    2016-08-22

    This paper describes the Structural and Physico-Chemical Interpretation (SPCI) approach, which is an extension of a recently reported method for interpretation of quantitative structure-activity relationship (QSAR) models. This approach can efficiently be used to reveal structural motifs and the major physicochemical factors affecting the investigated properties. Its efficacy was demonstrated both on the classical Free-Wilson data set and on several data sets with different end points (permeability of the blood-brain barrier, fibrinogen receptor antagonists, acute oral toxicity). Structure-activity patterns extracted from QSAR models with SPCI were in good correspondence with experimentally observed relationships and molecular docking, regardless of the machine learning method used. Comparison of SPCI with the matched molecular pair (MMP) method clearly shows an advantage of our approach over MMP, especially for small or structurally diverse data sets. The developed approach has been implemented in the SPCI software tool with a graphical user interface, which is publicly available at http://qsar4u.com/pages/sirms_qsar.php . PMID:27419846

  19. Daphnia and fish toxicity of (benzo)triazoles: validated QSAR models, and interspecies quantitative activity-activity modelling.

    PubMed

    Cassani, Stefano; Kovarich, Simona; Papa, Ester; Roy, Partha Pratim; van der Wal, Leon; Gramatica, Paola

    2013-08-15

    Due to their chemical properties synthetic triazoles and benzo-triazoles ((B)TAZs) are mainly distributed to the water compartments in the environment, and because of their wide use the potential effects on aquatic organisms are cause of concern. Non testing approaches like those based on quantitative structure-activity relationships (QSARs) are valuable tools to maximize the information contained in existing experimental data and predict missing information while minimizing animal testing. In the present study, externally validated QSAR models for the prediction of acute (B)TAZs toxicity in Daphnia magna and Oncorhynchus mykiss have been developed according to the principles for the validation of QSARs and their acceptability for regulatory purposes, proposed by the Organization for Economic Co-operation and Development (OECD). These models are based on theoretical molecular descriptors, and are statistically robust, externally predictive and characterized by a verifiable structural applicability domain. They have been applied to predict acute toxicity for over 300 (B)TAZs without experimental data, many of which are in the pre-registration list of the REACH regulation. Additionally, a model based on quantitative activity-activity relationships (QAAR) has been developed, which allows for interspecies extrapolation from daphnids to fish. The importance of QSAR/QAAR, especially when dealing with specific chemical classes like (B)TAZs, for screening and prioritization of pollutants under REACH, has been highlighted. PMID:23702385

  20. MOLECULAR TOPOLOGY AND NARCOSIS - A QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP (QSAR) STUDY OF ALCOHOLS USING COMPLEMENTARY INFORMATION CONTENT (CIC)

    EPA Science Inventory

    A newly formulated information -theoretic topological index - complementary information content (CIC) - defined for the planar chemical graph of molecules is applied in the QSAR studies of congeneric series of alcohols. Results show that CIC can quantitatively predict the LC50 va...

  1. DEVELOPMENT OF QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIPS (QSARS) TO PREDICT TOXICITY FOR A VARIETY OF HUMAN AND ECOLOGICAL ENDPOINTS

    EPA Science Inventory

    In general, the accuracy of a predicted toxicity value increases with increase in similarity between the query chemical and the chemicals used to develop a QSAR model. A toxicity estimation methodology employing this finding has been developed. A hierarchical based clustering t...

  2. The influence of data curation on QSAR Modeling - examining issues of quality versus quantity of data (American Chemical Society)

    EPA Science Inventory

    This presentation will examine the impact of data quality on the construction of QSAR models being developed within the EPA‘s National Center for Computational Toxicology. We have developed a public-facing platform to provide access to predictive models. As part of the work we ha...

  3. In silico evaluation, molecular docking and QSAR analysis of quinazoline-based EGFR-T790M inhibitors.

    PubMed

    Asadollahi-Baboli, M

    2016-08-01

    Mutated epidermal growth factor receptor (EGFR-T790M) inhibitors hold promise as new agents against cancer. Molecular docking and QSAR analysis were performed based on a series of fifty-three quinazoline derivatives to elucidate key structural and physicochemical properties affecting inhibitory activity. Molecular docking analysis identified the true conformations of ligands in the receptor's active pocket. The structural features of the ligands, expressed as molecular descriptors, were derived from the obtained docked conformations. Non-linear and spline QSAR models were developed through novel genetic algorithm and artificial neural network (GA-ANN) and multivariate adaptive regression spline techniques, respectively. The former technique was employed to consider non-linear relation between molecular descriptors and inhibitory activity of quinazoline derivatives. The later technique was also used to describe the non-linearity using basis functions and sub-region equations for each descriptor. Our QSAR model gave a high predictive performance [Formula: see text] and [Formula: see text]) using diverse validation techniques. Eight new compounds were designed using our QSAR model as potent EGFR-T790M inhibitors. Overall, the proposed in silico strategy based on docked derived descriptor and non-linear descriptor subset selection may help design novel quinazoline derivatives with improved EGFR-T790M inhibitory activity. PMID:27209475

  4. A DFT-based toxicity QSAR study of aromatic hydrocarbons to Vibrio fischeri: Consideration of aqueous freely dissolved concentration.

    PubMed

    Wang, Ying; Yang, Xianhai; Wang, Juying; Cong, Yi; Mu, Jingli; Jin, Fei

    2016-05-01

    In the present study, quantitative structure-activity relationship (QSAR) techniques based on toxicity mechanism and density functional theory (DFT) descriptors were adopted to develop predictive models for the toxicity of alkylated and parent aromatic hydrocarbons to Vibrio fischeri. The acute toxicity data of 17 aromatic hydrocarbons from both literature and our experimental results were used to construct QSAR models by partial least squares (PLS) analysis. With consideration of the toxicity process, the partition of aromatic hydrocarbons between water phase and lipid phase and their interaction with the target biomolecule, the optimal QSAR model was obtained by introducing aqueous freely dissolved concentration. The high statistical values of R(2) (0.956) and Q(CUM)(2) (0.942) indicated that the model has good goodness-of-fit, robustness and internal predictive power. The average molecular polarizability (α) and several selected thermodynamic parameters reflecting the intermolecular interactions played important roles in the partition of aromatic hydrocarbons between the water phase and biomembrane. Energy of the highest occupied molecular orbital (E(HOMO)) was the most influential descriptor which dominated the toxicity of aromatic hydrocarbons through the electron-transfer reaction with biomolecules. The results demonstrated that the adoption of freely dissolved concentration instead of nominal concentration was a beneficial attempt for toxicity QSAR modeling of hydrophobic organic chemicals. PMID:26812082

  5. The influence of data curation on QSAR Modeling – examining issues of quality versus quantity of data (SOT)

    EPA Science Inventory

    The construction of QSAR models is critically dependent on the quality of available data. As part of our efforts to develop public platforms to provide access to predictive models, we have attempted to discriminate the influence of the quality versus quantity of data available ...

  6. An examination of data quality on QSAR Modeling in regards to the environmental sciences (UNC-CH talk)

    EPA Science Inventory

    The development of QSAR models is critically dependent on the quality of available data. As part of our efforts to develop public platforms to provide access to predictive models, we have attempted to discriminate the influence of the quality versus quantity of data available to...

  7. Pharmacophore modeling, 3D-QSAR and docking study of 2-phenylpyrimidine analogues as selective PDE4B inhibitors.

    PubMed

    Tripuraneni, Naga Srinivas; Azam, Mohammed Afzal

    2016-04-01

    Pharmacophore modeling, molecular docking, and molecular dynamics (MD) simulation studies have been performed, to explore the putative binding modes of 2-phenylpyrimidine series as PDE4B selective inhibitors. A five point pharmacophore model was developed using 87 molecules having pIC50 ranging from 8.52 to 5.07. The pharmacophore hypothesis yielded a statistically significant 3D-QSAR model, with a high correlation coefficient (R(2)=0.918), cross validation coefficient (Q(2)=0.852), and F value (175) at 4 component PLS factor. The external validation indicated that our QSAR model possessed high predictive power (R(2)=0.70). The generated model was further validated by enrichment studies using the decoy test. To evaluate the effectiveness of docking protocol in flexible docking, we have selected crystallographic bound compound to validate our docking procedure as evident from root mean square deviation. A 10ns molecular dynamics simulation confirmed the docking results of both stability of the 1XMU-ligand complex and the presumed active conformation. Further, similar orientation was observed between the superposition of the conformations of 85 after MD simulation and best XP-docking pose; MD simulation and 3D-QSAR pose; best XP-docking and 3D-QSAR poses. Outcomes of the present study provide insight in designing novel molecules with better PDE4B selective inhibitory activity. PMID:26804643

  8. INFLUENCE OF MATRIX FORMULATION ON DERMAL PERCUTANEOUS ABSORPTION OF TRIAZOLE FUNGICIDES USING QSAR AND PBPK / PD MODELS

    EPA Science Inventory

    The objective of this work is to use the Exposure Related Dose Estimating Model (ERDEM) and quantitative structure-activity relationship (QSAR) models to develop an assessment tool for human exposure assessment to triazole fungicides. A dermal exposure route is used for the physi...

  9. Benefits of statistical molecular design, covariance analysis, and reference models in QSAR: a case study on acetylcholinesterase.

    PubMed

    Andersson, C David; Hillgren, J Mikael; Lindgren, Cecilia; Qian, Weixing; Akfur, Christine; Berg, Lotta; Ekström, Fredrik; Linusson, Anna

    2015-03-01

    Scientific disciplines such as medicinal- and environmental chemistry, pharmacology, and toxicology deal with the questions related to the effects small organic compounds exhort on biological targets and the compounds' physicochemical properties responsible for these effects. A common strategy in this endeavor is to establish structure-activity relationships (SARs). The aim of this work was to illustrate benefits of performing a statistical molecular design (SMD) and proper statistical analysis of the molecules' properties before SAR and quantitative structure-activity relationship (QSAR) analysis. Our SMD followed by synthesis yielded a set of inhibitors of the enzyme acetylcholinesterase (AChE) that had very few inherent dependencies between the substructures in the molecules. If such dependencies exist, they cause severe errors in SAR interpretation and predictions by QSAR-models, and leave a set of molecules less suitable for future decision-making. In our study, SAR- and QSAR models could show which molecular sub-structures and physicochemical features that were advantageous for the AChE inhibition. Finally, the QSAR model was used for the prediction of the inhibition of AChE by an external prediction set of molecules. The accuracy of these predictions was asserted by statistical significance tests and by comparisons to simple but relevant reference models. PMID:25351962

  10. QSAR study of antimicrobial activity of some 3-nitrocoumarins and related compounds.

    PubMed

    Debeljak, Zeljko; Skrbo, Armin; Jasprica, Ivona; Mornar, Ana; Plecko, Vanda; Banjanac, Mihajlo; Medić-Sarić, Marica

    2007-01-01

    A new class of antimicrobial agents, 3-nitrocoumarins and related compounds, has been chosen as a subject of the present study. In order to explore their activity and molecular properties that determine their antimicrobial effects, QSAR models have been proposed. Most of the 64 descriptors used for the development were extracted from semiempirical and density functional theory (DFT) founded calculations. For this study literature data containing results of microbiological activity screening of 33 coumarin derivatives against selected clinical isolates of C. albicans (CA) and S. aureus (SA) have been selected. Multivariate predictive models based on random forests (RF) and two hybrid classification approaches, genetic algorithms (GA) associated with either support vector machines (SVM) or k nearest neighbor (kNN), have been used for establishment of QSARs. An applied feature selection approach enabled two-dimensional linear separation of active and inactive compounds, which was a necessary tool for rational candidate design and descriptor relevance interpretation. Candidate molecules were checked by cross-validated models, and selected derivatives have been synthesized. Their antimicrobial activities were compared to antimicrobial activities of the representative derivatives from the original set in terms of minimal inhibitory concentration (MIC) against chosen SA and CA ATCC strains. High ranking of descriptors consistent with the degree of hydrolytic instability of selected compounds is common to models of antimicrobial activity against both microorganisms. However, descriptor ranking indicates different antimicrobial mechanisms of action of chosen coumarin derivatives against selected microbial species. PMID:17489552

  11. Antibacterial activity and QSAR of chalcones against biofilm-producing bacteria isolated from marine waters.

    PubMed

    Sivakumar, P M; Prabhawathi, V; Doble, M

    2010-04-01

    Biofouling in the marine environment is a major problem. In this study, three marine organisms, namely Bacillus flexus (LD1), Pseudomonas fluorescens (MD3) and Vibrio natriegens (MD6), were isolated from biofilms formed on polymer and metal surfaces immersed in ocean water. Phylogenetic analysis of these three organisms indicated that they were good model systems for studying marine biofouling. The in vitro antifouling activity of 47 synthesized chalcone derivatives was investigated by estimating the minimum inhibitory concentration against these organisms using a twofold dilution technique. Compounds C-5, C-16, C-24, C-33, C-34 and C-37 were found to be the most active. In the majority of the cases it was found that these active compounds had hydroxyl substitutions. A quantitative structure-activity relationship (QSAR) was developed after dividing the total data into training and test sets. The statistical measures r(2), [image omitted] (>0.6) q(2) (>0.5) and the F-ratio were found to be satisfactory. Spatial, structural and electronic descriptors were found to be predominantly affecting the antibiofouling activity of these compounds. Among the spatial descriptors, Jurs descriptors showed their contribution in all the three antibacterial QSARs. PMID:20544550

  12. Synthesis, biological activities, and quantitative structure-activity relationship (QSAR) study of novel camptothecin analogues.

    PubMed

    Wu, Dan; Zhang, Shao-Yong; Liu, Ying-Qian; Wu, Xiao-Bing; Zhu, Gao-Xiang; Zhang, Yan; Wei, Wei; Liu, Huan-Xiang; Chen, An-Liang

    2015-01-01

    In continuation of our program aimed at the development of natural product-based pesticidal agents, three series of novel camptothecin derivatives were designed, synthesized, and evaluated for their biological activities against T. Cinnabarinus, B. brassicae, and B. xylophilus. All of the derivatives showed good-to-excellent activity against three insect species tested, with LC50 values ranging from 0.00761 to 0.35496 mmol/L. Remarkably, all of the compounds were more potent than CPT against T. Cinnabarinus, and compounds 4d and 4c displayed superior activity (LC50 0.00761 mmol/L and 0.00942 mmol/L, respectively) compared with CPT (LC50 0.19719 mmol/L) against T. Cinnabarinus. Based on the observed bioactivities, preliminary structure-activity relationship (SAR) correlations were also discussed. Furthermore, a three-dimensional quantitative structure-activity relationship (3D-QSAR) model using comparative molecular field analysis (CoMFA) was built. The model gave statistically significant results with the cross-validated q2 values of 0.580 and correlation coefficient r2 of 0.991 and  of 0.993. The QSAR analysis indicated that the size of the substituents play an important in the activity of 7-modified camptothecin derivatives. These findings will pave the way for further design, structural optimization, and development of camptothecin-derived compounds as pesticidal agents. PMID:25985362

  13. The Interplay between QSAR/QSPR Studies and Partial Order Ranking and Formal Concept Analyses

    PubMed Central

    Carlsen, Lars

    2009-01-01

    The often observed scarcity of physical-chemical and well as toxicological data hampers the assessment of potentially hazardous chemicals released to the environment. In such cases Quantitative Structure-Activity Relationships/Quantitative Structure-Property Relationships (QSAR/QSPR) constitute an obvious alternative for rapidly, effectively and inexpensively generatng missing experimental values. However, typically further treatment of the data appears necessary, e.g., to elucidate the possible relations between the single compounds as well as implications and associations between the various parameters used for the combined characterization of the compounds under investigation. In the present paper the application of QSAR/QSPR in combination with Partial Order Ranking (POR) methodologies will be reviewed and new aspects using Formal Concept Analysis (FCA) will be introduced. Where POR constitutes an attractive method for, e.g., prioritizing a series of chemical substances based on a simultaneous inclusion of a range of parameters, FCA gives important information on the implications associations between the parameters. The combined approach thus constitutes an attractive method to a preliminary assessment of the impact on environmental and human health by primary pollutants or possibly by a primary pollutant well as a possible suite of transformation subsequent products that may be both persistent in and bioaccumulating and toxic. The present review focus on the environmental – and human health impact by residuals of the rocket fuel 1,1-dimethylhydrazine (heptyl) and its transformation products as an illustrative example. PMID:19468330

  14. Principles and procedures for implementation of ICH M7 recommended (Q)SAR analyses.

    PubMed

    Amberg, Alexander; Beilke, Lisa; Bercu, Joel; Bower, Dave; Brigo, Alessandro; Cross, Kevin P; Custer, Laura; Dobo, Krista; Dowdy, Eric; Ford, Kevin A; Glowienke, Susanne; Van Gompel, Jacky; Harvey, James; Hasselgren, Catrin; Honma, Masamitsu; Jolly, Robert; Kemper, Raymond; Kenyon, Michelle; Kruhlak, Naomi; Leavitt, Penny; Miller, Scott; Muster, Wolfgang; Nicolette, John; Plaper, Andreja; Powley, Mark; Quigley, Donald P; Reddy, M Vijayaraj; Spirkl, Hans-Peter; Stavitskaya, Lidiya; Teasdale, Andrew; Weiner, Sandy; Welch, Dennie S; White, Angela; Wichard, Joerg; Myatt, Glenn J

    2016-06-01

    The ICH M7 guideline describes a consistent approach to identify, categorize, and control DNA reactive, mutagenic, impurities in pharmaceutical products to limit the potential carcinogenic risk related to such impurities. This paper outlines a series of principles and procedures to consider when generating (Q)SAR assessments aligned with the ICH M7 guideline to be included in a regulatory submission. In the absence of adequate experimental data, the results from two complementary (Q)SAR methodologies may be combined to support an initial hazard classification. This may be followed by an assessment of additional information that serves as the basis for an expert review to support or refute the predictions. This paper elucidates scenarios where additional expert knowledge may be beneficial, what such an expert review may contain, and how the results and accompanying considerations may be documented. Furthermore, the use of these principles and procedures to yield a consistent and robust (Q)SAR-based argument to support impurity qualification for regulatory purposes is described in this manuscript. PMID:26877192

  15. A review of quantitative structure activity relationships (QSARs) for assessing the ecotoxicity of phthalate esters

    SciTech Connect

    Parkerton, T.F.

    1995-12-31

    Dialkyl phthalate esters represent an important class of high production volume, industrial chemicals spanning a wide range of chemical properties. Over the last two decades, numerous studies have been conducted to characterize the ecotoxicity of phthalate esters. The purpose of this presentation is to provide a synthesis of the available ecotoxicity literature using a QSAR paradigm. Results from this analysis provide several important insights. First, a mechanistic explanation is provided to account for the general lack of ecotoxicity observed for higher molecular weight phthalates possessing alkyl chains of six or more carbons. Second, studies that appear as outliers are identified due to either experimental artifacts (e.g., physical effects on daphnids due to testing at concentrations exceeding water solubility) or questionable experimental methods (e.g., toxicity tests based on nominal concentrations). Lastly, differences in ecotoxicity between species appear to be due, in part, to differences in test organisms biotransformation capacities. The utility of adopting a QSAR-based approach for risk assessment will be discussed.

  16. Therapeutic index modeling and predictive QSAR of novel thiazolidin-4-one analogs against Toxoplasma gondii.

    PubMed

    Asadollahi-Baboli, M; Mani-Varnosfaderani, A

    2015-04-01

    The main idea of this study was to find predictive quantitative structure-activity relationships (QSAR) for the therapeutic index of 68 thiazolidin-4-one analogs against Toxoplasma gondii. Multivariate adaptive regression spline (MARS) together with Monte-Carlo (MC) sampling was proposed as a reliable descriptor subset selection strategy. Basis functions and knot points are also determined for each selected descriptor using generalized cross validation after frequency analysis. Least squares-support vector regression (LS-SVR) with optimized hyper-parameters was employed as mapping tool due to its promising empirical performance. The models were validated and tested through the use of the external prediction set of compounds, leave-one-out and leave-many-out cross validation methods, applicability domain analysis and Y-randomization. The robustness and accuracy of the QSAR models were confirmed by the satisfactory statistical parameters for the experimentally reported dataset (R(2)p=0.853, Q(2)LOO=0.785, R(2)L20%O=0.742 and r(2)m=0.715) and low standard error values (RMSEp=0.208, RMSELOO=0.321 and RMSEL20%O=0.376). The comprehensive analysis carried out in the present contribution using the proposed strategy can provide a considerable basis for the design and development of novel drug-like molecules against T.gondii. PMID:25661424

  17. Insights on Cytochrome P450 Enzymes and Inhibitors Obtained Through QSAR Studies

    PubMed Central

    Sridhar, Jayalakshmi; Liu, Jiawang; Foroozesh, Maryam; Stevens, Cheryl L. Klein

    2013-01-01

    The cytochrome P450 (CYP) superfamily of heme enzymes play an important role in the metabolism of a large number of endogenous and exogenous compounds, including most of the drugs currently on the market. Inhibitors of CYP enzymes have important roles in the treatment of several disease conditions such as numerous cancers and fungal infections in addition to their critical role in drug-drug interactions. Structure activity relationships (SAR), and three-dimensional quantitative structure activity relationships (3D-QSAR) represent important tools in understanding the interactions of the inhibitors with the active sites of the CYP enzymes. A comprehensive account of the QSAR studies on the major human CYPs 1A1, 1A2, 1B1, 2A6, 2B6, 2C9, 2C19, 2D6, 2E1, 3A4 and a few other CYPs are detailed in this review which will provide us with an insight into the individual/common characteristics of the active sites of these enzymes and the enzyme-inhibitor interactions. PMID:22864238

  18. Approaches to developing alternative and predictive toxicology based on PBPK/PD and QSAR modeling.

    PubMed Central

    Yang, R S; Thomas, R S; Gustafson, D L; Campain, J; Benjamin, S A; Verhaar, H J; Mumtaz, M M

    1998-01-01

    Systematic toxicity testing, using conventional toxicology methodologies, of single chemicals and chemical mixtures is highly impractical because of the immense numbers of chemicals and chemical mixtures involved and the limited scientific resources. Therefore, the development of unconventional, efficient, and predictive toxicology methods is imperative. Using carcinogenicity as an end point, we present approaches for developing predictive tools for toxicologic evaluation of chemicals and chemical mixtures relevant to environmental contamination. Central to the approaches presented is the integration of physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) and quantitative structure--activity relationship (QSAR) modeling with focused mechanistically based experimental toxicology. In this development, molecular and cellular biomarkers critical to the carcinogenesis process are evaluated quantitatively between different chemicals and/or chemical mixtures. Examples presented include the integration of PBPK/PD and QSAR modeling with a time-course medium-term liver foci assay, molecular biology and cell proliferation studies. Fourier transform infrared spectroscopic analyses of DNA changes, and cancer modeling to assess and attempt to predict the carcinogenicity of the series of 12 chlorobenzene isomers. Also presented is an ongoing effort to develop and apply a similar approach to chemical mixtures using in vitro cell culture (Syrian hamster embryo cell transformation assay and human keratinocytes) methodologies and in vivo studies. The promise and pitfalls of these developments are elaborated. When successfully applied, these approaches may greatly reduce animal usage, personnel, resources, and time required to evaluate the carcinogenicity of chemicals and chemical mixtures. Images Figure 6 PMID:9860897

  19. 3D-QSAR and docking studies of flavonoids as potent Escherichia coli inhibitors.

    PubMed

    Fang, Yajing; Lu, Yulin; Zang, Xixi; Wu, Ting; Qi, XiaoJuan; Pan, Siyi; Xu, Xiaoyun

    2016-01-01

    Flavonoids are potential antibacterial agents. However, key substituents and mechanism for their antibacterial activity have not been fully investigated. The quantitative structure-activity relationship (QSAR) and molecular docking of flavonoids relating to potent anti-Escherichia coli agents were investigated. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were developed by using the pIC50 values of flavonoids. The cross-validated coefficient (q(2)) values for CoMFA (0.743) and for CoMSIA (0.708) were achieved, illustrating high predictive capabilities. Selected descriptors for the CoMFA model were ClogP (logarithm of the octanol/water partition coefficient), steric and electrostatic fields, while, ClogP, electrostatic and hydrogen bond donor fields were used for the CoMSIA model. Molecular docking results confirmed that half of the tested flavonoids inhibited DNA gyrase B (GyrB) by interacting with adenosine-triphosphate (ATP) pocket in a same orientation. Polymethoxyl flavones, flavonoid glycosides, isoflavonoids changed their orientation, resulting in a decrease of inhibitory activity. Moreover, docking results showed that 3-hydroxyl, 5-hydroxyl, 7-hydroxyl and 4-carbonyl groups were found to be crucial active substituents of flavonoids by interacting with key residues of GyrB, which were in agreement with the QSAR study results. These results provide valuable information for structure requirements of flavonoids as antibacterial agents. PMID:27049530

  20. Peptide reactivity associated with skin sensitization: The QSAR Toolbox and TIMES compared to the DPRA.

    PubMed

    Urbisch, D; Honarvar, N; Kolle, S N; Mehling, A; Ramirez, T; Teubner, W; Landsiedel, R

    2016-08-01

    The molecular initiating event (MIE) of skin sensitization is the binding of a hapten to dermal proteins. This can be assessed using the in chemico direct peptide reactivity assay (DPRA) or in silico tools such as the QSAR Toolbox and TIMES SS. In this study, the suitability of these methods was analyzed by comparing their results to in vivo sensitization data of LLNA and human studies. Compared to human data, 84% of non-sensitizers and sensitizers yielded consistent results in the DPRA. In silico tools resulted in 'no alert' for 83%-100% of the non-sensitizers, but alerted only 55%-61% of the sensitizers. The inclusion of biotic and abiotic transformation simulations yielded more alerts for sensitizers, but simultaneously dropped the number of non-alerted non-sensitizers. In contrast to the DPRA, in silico tools were more consistent with results of the LLNA than human data. Interestingly, the new "DPRA profilers" (QSAR Toolbox) provided unsatisfactory results. Additionally, the results were combined in the '2 out of 3' prediction model with in vitro data derived from LuSens and h-CLAT. Using DPRA results, the model identified 90% of human sensitizers and non-sensitizers; using in silico results (including abiotic and biotic activations) instead of DPRA results led to a comparable high predictivity. PMID:27090964

  1. An alternative QSAR-based approach for predicting the bioconcentration factor for regulatory purposes.

    PubMed

    Gissi, Andrea; Gadaleta, Domenico; Floris, Matteo; Olla, Stefania; Carotti, Angelo; Novellino, Ettore; Benfenati, Emilio; Nicolotti, Orazio

    2014-01-01

    The REACH (Registration, Evaluation, Authorization and restriction of Chemicals) and BPR (Biocide Product Regulation) regulations strongly promote the use of non-animal testing techniques to evaluate chemical risk. This has renewed the interest towards alternative methods such as QSAR in the regulatory context. The assessment of Bioconcentration Factor (BCF) required by these regulations is expensive, in terms of costs, time, and laboratory animal sacrifices. Herein, we present QSAR models based on the ANTARES dataset, which is a large collection of known and verified experimental BCF data. Among the models developed, the best results were obtained from a nine-descriptor highly predictive model. This model was derived from a training set of 608 chemicals and challenged against a validation and blind set containing 152 and 76 chemicals. The model's robustness was further controlled through several validation strategies and the implementation of a multi-step approach for the applicability domain. Suitable safety margins were used to increase sensitivity. The easy interpretability of the model is ensured by the use of meaningful biokinetics descriptors. The satisfactory predictive power for external compounds suggests that the new models could represent a reliable alternative to the in vivo assay, helping the registrants to fulfill regulatory requirements in compliance with the ethical and economic necessity to reduce animal testing. PMID:24247988

  2. Building on a solid foundation: SAR and QSAR as a fundamental strategy to reduce animal testing.

    PubMed

    Sullivan, K M; Manuppello, J R; Willett, C E

    2014-01-01

    The development of more efficient, ethical, and effective means of assessing the effects of chemicals on human health and the environment was a lifetime goal of Gilman Veith. His work has provided the foundation for the use of chemical structure for informing toxicological assessment by regulatory agencies the world over. Veith's scientific work influenced the early development of the SAR models in use today at the US Environmental Protection Agency. He was the driving force behind the Organisation for Economic Co-operation and Development QSAR Toolbox. Veith was one of a few early pioneers whose vision led to the linkage of chemical structure and biological activity as a means of predicting adverse apical outcomes (known as a mode of action, or an adverse outcome pathway approach), and he understood at an early stage the power that could be harnessed when combining computational and mechanistic biological approaches as a means of avoiding animal testing. Through the International QSAR Foundation he organized like-minded experts to develop non-animal methods and frameworks for the assessment of chemical hazard and risk for the benefit of public and environmental health. Avoiding animal testing was Gil's passion, and his work helped to initiate the paradigm shift in toxicology that is now rendering this feasible. PMID:24773450

  3. Application of random forest approach to QSAR prediction of aquatic toxicity.

    PubMed

    Polishchuk, Pavel G; Muratov, Eugene N; Artemenko, Anatoly G; Kolumbin, Oleg G; Muratov, Nail N; Kuz'min, Victor E

    2009-11-01

    This work is devoted to the application of the random forest approach to QSAR analysis of aquatic toxicity of chemical compounds tested on Tetrahymena pyriformis. The simplex representation of the molecular structure approach implemented in HiT QSAR Software was used for descriptors generation on a two-dimensional level. Adequate models based on simplex descriptors and the RF statistical approach were obtained on a modeling set of 644 compounds. Model predictivity was validated on two external test sets of 339 and 110 compounds. The high impact of lipophilicity and polarizability of investigated compounds on toxicity was determined. It was shown that RF models were tolerant for insertion of irrelevant descriptors as well as for randomization of some part of toxicity values that were representing a "noise". The fast procedure of optimization of the number of trees in the random forest has been proposed. The discussed RF model had comparable or better statistical characteristics than the corresponding PLS or KNN models. PMID:19860412

  4. Comparison of Global Reactivity Descriptors Calculated Using Various Density Functionals: A QSAR Perspective.

    PubMed

    Vijayaraj, R; Subramanian, V; Chattaraj, P K

    2009-10-13

    Conceptual density functional theory (DFT) based global reactivity descriptors are used to understand the relationship between structure, stability, and global chemical reactivity. Furthermore, these descriptors are employed in the development of quantitative structure-activity (QSAR), structure-property (QSPR), and structure-toxicity (QSTR) relationships. However, the predictive power of various relationships depends on the reliable estimates of these descriptors. The basic working equations used to calculate these descriptors contain both the ionization potential and the electron affinity of chosen molecules. Therefore, efficiency of different density functionals (DFs) in predicting the ionization potential and the electron affinity has to be systematically evaluated. With a view to benchmark the method of calculation of global reactivity descriptors, comprehensive calculations have been carried out on a series of chlorinated benzenes using a variety of density functionals employing different basis sets. In addition, to assess the utility of global reactivity descriptors, the relationships between the reactivity-electrophilicity and the structure-toxicity have been developed. The ionization potential and the electron affinity values obtained from M05-2X method using the ΔSCF approach are closer to the corresponding experimental values. This method reliably predicts these electronic properties when compared to the other DFT methods. The analysis of a series of QSTR equations reveals that computationally economic DFT functionals can be effectively and routinely applied in the development of QSAR/QSPR/QSTR. PMID:26631787

  5. Evaluation of a statistics-based Ames mutagenicity QSAR model and interpretation of the results obtained.

    PubMed

    Barber, Chris; Cayley, Alex; Hanser, Thierry; Harding, Alex; Heghes, Crina; Vessey, Jonathan D; Werner, Stephane; Weiner, Sandy K; Wichard, Joerg; Giddings, Amanda; Glowienke, Susanne; Parenty, Alexis; Brigo, Alessandro; Spirkl, Hans-Peter; Amberg, Alexander; Kemper, Ray; Greene, Nigel

    2016-04-01

    The relative wealth of bacterial mutagenicity data available in the public literature means that in silico quantitative/qualitative structure activity relationship (QSAR) systems can readily be built for this endpoint. A good means of evaluating the performance of such systems is to use private unpublished data sets, which generally represent a more distinct chemical space than publicly available test sets and, as a result, provide a greater challenge to the model. However, raw performance metrics should not be the only factor considered when judging this type of software since expert interpretation of the results obtained may allow for further improvements in predictivity. Enough information should be provided by a QSAR to allow the user to make general, scientifically-based arguments in order to assess and overrule predictions when necessary. With all this in mind, we sought to validate the performance of the statistics-based in vitro bacterial mutagenicity prediction system Sarah Nexus (version 1.1) against private test data sets supplied by nine different pharmaceutical companies. The results of these evaluations were then analysed in order to identify findings presented by the model which would be useful for the user to take into consideration when interpreting the results and making their final decision about the mutagenic potential of a given compound. PMID:26708083

  6. Volume learning algorithm artificial neural networks for 3D QSAR studies.

    PubMed

    Tetko, I V; Kovalishyn, V V; Livingstone, D J

    2001-07-19

    The current study introduces a new method, the volume learning algorithm (VLA), for the investigation of three-dimensional quantitative structure-activity relationships (QSAR) of chemical compounds. This method incorporates the advantages of comparative molecular field analysis (CoMFA) and artificial neural network approaches. VLA is a combination of supervised and unsupervised neural networks applied to solve the same problem. The supervised algorithm is a feed-forward neural network trained with a back-propagation algorithm while the unsupervised network is a self-organizing map of Kohonen. The use of both of these algorithms makes it possible to cluster the input CoMFA field variables and to use only a small number of the most relevant parameters to correlate spatial properties of the molecules with their activity. The statistical coefficients calculated by the proposed algorithm for cannabimimetic aminoalkyl indoles were comparable to, or improved, in comparison to the original study using the partial least squares algorithm. The results of the algorithm can be visualized and easily interpreted. Thus, VLA is a new convenient tool for three-dimensional QSAR studies. PMID:11448223

  7. Comparison of Performance of Docking, LIE, Metadynamics and QSAR in Predicting Binding Affinity of Benzenesulfonamides.

    PubMed

    Raškevičius, Vytautas; Kairys, Visvaldas

    2015-01-01

    The design of inhibitors specific for one relevant carbonic anhydrase isozyme is the major challenge in the new therapeutic agents development. Comparative computational chemical structure and biological activity relationship studies on a series of carbonic anhydrase II inhibitors, benzenesulfonamide derivatives, bearing pyrimidine moieties are reported in this paper using docking, Linear Interaction Energy (LIE), Metadynamics and Quantitative Structure Activity Relationship (QSAR) methods. The computed binding affinities were compared with the experimental data with the goal to explore strengths and weaknesses of various approaches applied to the investigated carbonic anhydrase/inhibitor system. From the tested methods initially only QSAR showed promising results (R2=0.83-0.89 between experimentally determined versus predicted pKd values.). Possible reasons for this performance were discussed. A modification of the LIE method was suggested which used an alternative LIE-like equation yielding significantly improved results (R2 between the experimentally determined versus the predicted ΔG(bind) improved from 0.24 to 0.50). PMID:26373640

  8. The QSAR and docking calculations of fullerene derivatives as HIV-1 protease inhibitors

    NASA Astrophysics Data System (ADS)

    Saleh, Noha A.

    2015-02-01

    The inhibition of HIV-1 protease is considered as one of the most important targets for drug design and the deactivation of HIV-1. In the present work, the fullerene surface (C60) is modified by adding oxygen atoms as well as hydroxymethylcarbonyl (HMC) groups to form 6 investigated fullerene derivative compounds. These compounds have one, two, three, four or five O atoms + HMC groups at different positions on phenyl ring. The effect of the repeating of these groups on the ability of suggested compounds to inhibit the HIV protease is studied by calculating both Quantitative Structure Activity Relationship (QSAR) properties and docking simulation. Based on the QSAR descriptors, the solubility and the hydrophilicity of studied fullerene derivatives increased with increasing the number of oxygen atoms + HMC groups in the compound. While docking calculations indicate that, the compound with two oxygen atoms + HMC groups could interact and binds with HIV-1 protease active site. This is could be attributed to the active site residues of HIV-1 protease are hydrophobic except the two aspartic acids. So that, the increase in the hydrophilicity and polarity of the compound is preventing and/or decreasing the hydrophobic interaction between the compound and HIV-1 protease active site.

  9. The QSAR study of flavonoid-metal complexes scavenging rad OH free radical

    NASA Astrophysics Data System (ADS)

    Wang, Bo-chu; Qian, Jun-zhen; Fan, Ying; Tan, Jun

    2014-10-01

    Flavonoid-metal complexes have antioxidant activities. However, quantitative structure-activity relationships (QSAR) of flavonoid-metal complexes and their antioxidant activities has still not been tackled. On the basis of 21 structures of flavonoid-metal complexes and their antioxidant activities for scavenging rad OH free radical, we optimised their structures using Gaussian 03 software package and we subsequently calculated and chose 18 quantum chemistry descriptors such as dipole, charge and energy. Then we chose several quantum chemistry descriptors that are very important to the IC50 of flavonoid-metal complexes for scavenging rad OH free radical through method of stepwise linear regression, Meanwhile we obtained 4 new variables through the principal component analysis. Finally, we built the QSAR models based on those important quantum chemistry descriptors and the 4 new variables as the independent variables and the IC50 as the dependent variable using an Artificial Neural Network (ANN), and we validated the two models using experimental data. These results show that the two models in this paper are reliable and predictable.

  10. The QSAR and docking calculations of fullerene derivatives as HIV-1 protease inhibitors.

    PubMed

    Saleh, Noha A

    2014-10-30

    The inhibition of HIV-1 protease is considered as one of the most important targets for drug design and the deactivation of HIV-1. In the present work, the fullerene surface (C60) is modified by adding oxygen atoms as well as hydroxymethylcarbonyl (HMC) groups to form 6 investigated fullerene derivative compounds. These compounds have one, two, three, four or five O atoms+HMC groups at different positions on phenyl ring. The effect of the repeating of these groups on the ability of suggested compounds to inhibit the HIV protease is studied by calculating both Quantitative Structure Activity Relationship (QSAR) properties and docking simulation. Based on the QSAR descriptors, the solubility and the hydrophilicity of studied fullerene derivatives increased with increasing the number of oxygen atoms+HMC groups in the compound. While docking calculations indicate that, the compound with two oxygen atoms+HMC groups could interact and binds with HIV-1 protease active site. This is could be attributed to the active site residues of HIV-1 protease are hydrophobic except the two aspartic acids. So that, the increase in the hydrophilicity and polarity of the compound is preventing and/or decreasing the hydrophobic interaction between the compound and HIV-1 protease active site. PMID:25459714

  11. The continuous molecular fields approach to building 3D-QSAR models.

    PubMed

    Baskin, Igor I; Zhokhova, Nelly I

    2013-05-01

    The continuous molecular fields (CMF) approach is based on the application of continuous functions for the description of molecular fields instead of finite sets of molecular descriptors (such as interaction energies computed at grid nodes) commonly used for this purpose. These functions can be encapsulated into kernels and combined with kernel-based machine learning algorithms to provide a variety of novel methods for building classification and regression structure-activity models, visualizing chemical datasets and conducting virtual screening. In this article, the CMF approach is applied to building 3D-QSAR models for 8 datasets through the use of five types of molecular fields (the electrostatic, steric, hydrophobic, hydrogen-bond acceptor and donor ones), the linear convolution molecular kernel with the contribution of each atom approximated with a single isotropic Gaussian function, and the kernel ridge regression data analysis technique. It is shown that the CMF approach even in this simplest form provides either comparable or enhanced predictive performance in comparison with state-of-the-art 3D-QSAR methods. PMID:23719959

  12. 3D-QSAR and docking studies of flavonoids as potent Escherichia coli inhibitors

    PubMed Central

    Fang, Yajing; Lu, Yulin; Zang, Xixi; Wu, Ting; Qi, XiaoJuan; Pan, Siyi; Xu, Xiaoyun

    2016-01-01

    Flavonoids are potential antibacterial agents. However, key substituents and mechanism for their antibacterial activity have not been fully investigated. The quantitative structure-activity relationship (QSAR) and molecular docking of flavonoids relating to potent anti-Escherichia coli agents were investigated. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were developed by using the pIC50 values of flavonoids. The cross-validated coefficient (q2) values for CoMFA (0.743) and for CoMSIA (0.708) were achieved, illustrating high predictive capabilities. Selected descriptors for the CoMFA model were ClogP (logarithm of the octanol/water partition coefficient), steric and electrostatic fields, while, ClogP, electrostatic and hydrogen bond donor fields were used for the CoMSIA model. Molecular docking results confirmed that half of the tested flavonoids inhibited DNA gyrase B (GyrB) by interacting with adenosine-triphosphate (ATP) pocket in a same orientation. Polymethoxyl flavones, flavonoid glycosides, isoflavonoids changed their orientation, resulting in a decrease of inhibitory activity. Moreover, docking results showed that 3-hydroxyl, 5-hydroxyl, 7-hydroxyl and 4-carbonyl groups were found to be crucial active substituents of flavonoids by interacting with key residues of GyrB, which were in agreement with the QSAR study results. These results provide valuable information for structure requirements of flavonoids as antibacterial agents. PMID:27049530

  13. Stackfile Database

    NASA Technical Reports Server (NTRS)

    deVarvalho, Robert; Desai, Shailen D.; Haines, Bruce J.; Kruizinga, Gerhard L.; Gilmer, Christopher

    2013-01-01

    This software provides storage retrieval and analysis functionality for managing satellite altimetry data. It improves the efficiency and analysis capabilities of existing database software with improved flexibility and documentation. It offers flexibility in the type of data that can be stored. There is efficient retrieval either across the spatial domain or the time domain. Built-in analysis tools are provided for frequently performed altimetry tasks. This software package is used for storing and manipulating satellite measurement data. It was developed with a focus on handling the requirements of repeat-track altimetry missions such as Topex and Jason. It was, however, designed to work with a wide variety of satellite measurement data [e.g., Gravity Recovery And Climate Experiment -- GRACE). The software consists of several command-line tools for importing, retrieving, and analyzing satellite measurement data.

  14. Development of acute toxicity quantitative structure activity relationships (QSAR) and their use in linear alkylbenzene sulfonate species sensitivity distributions.

    PubMed

    Belanger, Scott E; Brill, Jessica L; Rawlings, Jane M; Price, Brad B

    2016-07-01

    Linear Alkylbenzene Sulfonate (LAS) is high tonnage and widely dispersed anionic surfactant used by the consumer products sector. A range of homologous structures are used in laundry applications that differ primarily on the length of the hydrophobic alkyl chain. This research summarizes the development of a set of acute toxicity QSARs (Quantitative Structure Activity Relationships) for fathead minnows (Pimephales promelas) and daphnids (Daphnia magna, Ceriodaphnia dubia) using accepted test guideline approaches. A series of studies on pure chain length LAS from C10 to C14 were used to develop the QSARs and the robustness of the QSARs was tested by evaluation of two technical mixtures of differing compositions. All QSARs were high quality (R(2) were 0.965-0.997, p < 0.0001). Toxicity normalization employing QSARs is used to interpret a broader array of tests on LAS chain length materials to a diverse group of test organisms with the objective of developing Species Sensitivity Distributions (SSDs) for various chain lengths of interest. Mixtures include environmental distributions measured from exposure monitoring surveys of wastewater effluents, various commercial mixtures, or specific chain lengths. SSD 5th percentile hazardous concentrations (HC5s) ranged from 0.129 to 0.254 mg/L for wastewater effluents containing an average of 11.26-12 alkyl carbons. The SSDs are considered highly robust given the breadth of species (n = 19), use of most sensitive endpoints from true chronic studies and the quality of the underlying statistical properties of the SSD itself. The data continue to indicate a low hazard to the environment relative to expected environmental concentrations. PMID:27105149

  15. Database Marketplace 2002: The Database Universe.

    ERIC Educational Resources Information Center

    Tenopir, Carol; Baker, Gayle; Robinson, William

    2002-01-01

    Reviews the database industry over the past year, including new companies and services, company closures, popular database formats, popular access methods, and changes in existing products and services. Lists 33 firms and their database services; 33 firms and their database products; and 61 company profiles. (LRW)

  16. Trend Analyses of Nitrate in Danish Groundwater

    NASA Astrophysics Data System (ADS)

    Hansen, B.; Thorling, L.; Dalgaard, T.; Erlandsen, M.

    2012-04-01

    This presentation assesses the long-term development in the oxic groundwater nitrate concentration and nitrogen (N) loss due to intensive farming in Denmark. Firstly, up to 20-year time-series from the national groundwater monitoring network enable a statistically systematic analysis of distribution, trends and trend reversals in the groundwater nitrate concentration. Secondly, knowledge about the N surplus in Danish agriculture since 1950 is used as an indicator of the potential loss of N. Thirdly, groundwater recharge CFC (Chlorofluorocarbon) age determination allows linking of the first two dataset. The development in the nitrate concentration of oxic groundwater clearly mirrors the development in the national agricultural N surplus, and a corresponding trend reversal is found in groundwater. Regulation and technical improvements in the intensive farming in Denmark have succeeded in decreasing the N surplus by 40% since the mid 1980s while at the same time maintaining crop yields and increasing the animal production of especially pigs. Trend analyses prove that the youngest (0-15 years old) oxic groundwater shows more pronounced significant downward nitrate trends (44%) than the oldest (25-50 years old) oxic groundwater (9%). This amounts to clear evidence of the effect of reduced nitrate leaching on groundwater nitrate concentrations in Denmark. Are the Danish groundwater monitoring strategy obtimal for detection of nitrate trends? Will the nitrate concentrations in Danish groundwater continue to decrease or are the Danish nitrate concentration levels now appropriate according to the Water Framework Directive?

  17. Escherichia vulneris in a Danish soccer wound.

    PubMed

    Jepsen, C F; Klebe, T M; Prag, J

    1997-01-01

    Escherichia vulneris was isolated from an infected soccer wound, a finding which has not apparently been described in Europe before, but by questioning Danish clinical microbiological laboratories a further 12 cases were discovered. Treatment with simple debridement and cefuroxime quickly eradicated the bacteria in our case. PMID:9255899

  18. Evaluating University Continuing Education: A Danish Case.

    ERIC Educational Resources Information Center

    Thune, Christian

    2002-01-01

    The Danish Evaluation Institute is conducting systematic assessments of three master's programs in public administration, public policy, and public management. They have found that explicit criteria have advantages and disadvantages. Development of criteria attempts to meet the following demands: uniformity, relevance of level, scope, precision,…

  19. Care and Education in the Danish Creche

    ERIC Educational Resources Information Center

    Brostrom, Stig; Hansen, Ole Henrik

    2010-01-01

    This article seeks to identify the relation between policy and lived life, for the small child in the Danish creche. To accomplish this, the article integrates demography, traditions, national curriculum and psychological, educational, and recent developments in research. It is an attempt to reveal knowledge and consequences, by conducting the…

  20. The Danish Free School Tradition under Pressure

    ERIC Educational Resources Information Center

    Olsen, Tore Vincents

    2015-01-01

    The Danish free school tradition has entailed a large degree of associational freedom for non-governmental schools, religious as well as non-religious. Until the late 1990s, the non-governmental schools were under no strict ideological or pedagogical limitations; they could recruit teachers and students according to their own value base, and were…

  1. FDA toxicity databases and real-time data entry

    SciTech Connect

    Arvidson, Kirk B.

    2008-11-15

    Structure-searchable electronic databases are valuable new tools that are assisting the FDA in its mission to promptly and efficiently review incoming submissions for regulatory approval of new food additives and food contact substances. The Center for Food Safety and Applied Nutrition's Office of Food Additive Safety (CFSAN/OFAS), in collaboration with Leadscope, Inc., is consolidating genetic toxicity data submitted in food additive petitions from the 1960s to the present day. The Center for Drug Evaluation and Research, Office of Pharmaceutical Science's Informatics and Computational Safety Analysis Staff (CDER/OPS/ICSAS) is separately gathering similar information from their submissions. Presently, these data are distributed in various locations such as paper files, microfiche, and non-standardized toxicology memoranda. The organization of the data into a consistent, searchable format will reduce paperwork, expedite the toxicology review process, and provide valuable information to industry that is currently available only to the FDA. Furthermore, by combining chemical structures with genetic toxicity information, biologically active moieties can be identified and used to develop quantitative structure-activity relationship (QSAR) modeling and testing guidelines. Additionally, chemicals devoid of toxicity data can be compared to known structures, allowing for improved safety review through the identification and analysis of structural analogs. Four database frameworks have been created: bacterial mutagenesis, in vitro chromosome aberration, in vitro mammalian mutagenesis, and in vivo micronucleus. Controlled vocabularies for these databases have been established. The four separate genetic toxicity databases are compiled into a single, structurally-searchable database for easy accessibility of the toxicity information. Beyond the genetic toxicity databases described here, additional databases for subchronic, chronic, and teratogenicity studies have been prepared.

  2. QSAR screening of 70,983 REACH substances for genotoxic carcinogenicity, mutagenicity and developmental toxicity in the ChemScreen project.

    PubMed

    Wedebye, Eva B; Dybdahl, Marianne; Nikolov, Nikolai G; Jónsdóttir, Svava Ó; Niemelä, Jay R

    2015-08-01

    The ChemScreen project aimed to develop a screening system for reproductive toxicity based on alternative methods. QSARs can, if adequate, contribute to the evaluation of chemical substances under REACH and may in some cases be applied instead of experimental testing to fill data gaps for information requirements. As no testing for reproductive effects should be performed in REACH on known genotoxic carcinogens or germ cell mutagens with appropriate risk management measures implemented, a QSAR pre-screen for 70,983 REACH substances was performed. Sixteen models and three decision algorithms were used to reach overall predictions of substances with potential effects with the following result: 6.5% genotoxic carcinogens, 16.3% mutagens, 11.5% developmental toxicants. These results are similar to findings in earlier QSAR and experimental studies of chemical inventories, and illustrate how QSAR predictions may be used to identify potential genotoxic carcinogens, mutagens and developmental toxicants by high-throughput virtual screening. PMID:25797653

  3. The air quality in Danish urban areas.

    PubMed

    Jensen, F P; Fenger, J

    1994-10-01

    The Danish air pollution abatement is based by and large on emission control. Since the ratification of the international sulfur protocol of 1985, there has been a continuous tightening of the permissible sulfur content in fuels and of the maximum emissions from power plants. As a consequence, the total annual emission of sulfur dioxide (SO2) has been reduced from 450,000 tons in the seventies to 180,000 tons in 1990. This has had a pronounced effect on the SO2 levels in Danish urban areas. Thus, in Copenhagen, the yearly averages have fallen to about 25%. For nitrogen oxides emitted from the power plants, similar regulations are in force. With this legislation, the most important and crucial source of air pollution in Danish urban areas is road traffic. The contribution of nitrogen oxides from national traffic accounts for nearly half the total Danish emission and is increasing steadily; this is consistent with an observed increase of nitrogen oxides in ambient air. The permissible levels of lead in petrol has been reduced drastically. After an introduction of reduced tax on lead-free petrol, it now accounts for more than two-thirds of the total consumption. As a result, the concentration of lead in urban ambient air has been reduced to less than one-sixth. The introduction of 3-way catalytic converters from October 1990 will result in reductions in the emission of a series of pollutants, e.g., lead, volatile organic compounds, carbon monoxide, and nitrogen oxides. In 1980, a Danish air quality monitoring program was established as a cooperative effort between the authorities, the Government, the countries, the municipalities, and the Greater Copenhagen Council.(ABSTRACT TRUNCATED AT 250 WORDS) PMID:7821296

  4. MOAtox: A comprehensive mode of action and acute aquatic toxicity database for predictive model development.

    PubMed

    Barron, M G; Lilavois, C R; Martin, T M

    2015-04-01

    The mode of toxic action (MOA) has been recognized as a key determinant of chemical toxicity and as an alternative to chemical class-based predictive toxicity modeling. However, the development of quantitative structure activity relationship (QSAR) and other models has been limited by the availability of comprehensive high quality MOA and toxicity databases. The current study developed a dataset of MOA assignments for 1213 chemicals that included a diversity of metals, pesticides, and other organic compounds that encompassed six broad and 31 specific MOAs. MOA assignments were made using a combination of high confidence approaches that included international consensus classifications, QSAR predictions, and weight of evidence professional judgment based on an assessment of structure and literature information. A toxicity database of 674 acute values linked to chemical MOA was developed for fish and invertebrates. Additionally, species-specific measured or high confidence estimated acute values were developed for the four aquatic species with the most reported toxicity values: rainbow trout (Oncorhynchus mykiss), fathead minnow (Pimephales promelas), bluegill (Lepomis macrochirus), and the cladoceran (Daphnia magna). Measured acute toxicity values met strict standardization and quality assurance requirements. Toxicity values for chemicals with missing species-specific data were estimated using established interspecies correlation models and procedures (Web-ICE; http://epa.gov/ceampubl/fchain/webice/), with the highest confidence values selected. The resulting dataset of MOA assignments and paired toxicity values are provided in spreadsheet format as a comprehensive standardized dataset available for predictive aquatic toxicology model development. PMID:25700118

  5. Structure-based modeling of dye-fiber affinity with SOM-4D-QSAR paradigm: application to set of anthraquinone derivatives.

    PubMed

    Bak, Andrzej; Wyszomirski, Miroslaw; Magdziarz, Tomasz; Smolinski, Adam; Polanski, Jaroslaw

    2014-01-01

    A comparative structure-affinity study of anthraquinone dyes adsorption on cellulose fibre is presented in this paper. We used receptor-dependent 4D-QSAR methods based on grid and neural (SOM) methodology coupled with IVEPLS procedure. The applied RD 4D-QSAR approach focuses mainly on the ability of mapping dye properties to verify the concept of tinctophore in dye chemistry. Moreover, the stochastic SMV procedure to investigate the predictive ability of the method for a large population of 4D-QSAR models was employed. The obtained findings were compared with the previously published RI 3D/4D-QSAR models for the corresponding anthraquinone trainings sets. The neutral (protonated) and anionic (deprotonated) forms of anthraquinone scaffold were examined in order to deal with the uncertainty of the dye ionization state. The results are comparable to both the neutral and anionic dye sets regardless of the occupancy and charge descriptors applied, respectively. It is worth noting that the SOM-4D-QSAR behaves comparably to the cubic counterpart which is observed in each training/test subset specification (4D-QSAR-Jo vs SOM- 4D-QSARo and 4D-QSAR-Jq vs SOM-4D-QSARq). Additionally, an attempt was made to specify a common set of variables contributing significantly to dye-fiber binding affinity; it was simultaneously performed for some arbitrary chosen SMV models. The presented RD 4D-QSAR methodology together with IVE-PLS procedure provides a robust and predictive modeling technique, which facilitates detailed specification of the molecular motifs significantly contributing to the fiber-dye affinity. PMID:24499310

  6. QSAR analyses of DDT analogues and their in silico validation using molecular docking study against voltage-gated sodium channel of Anopheles funestus.

    PubMed

    Saini, V; Kumar, A

    2014-01-01

    DDT has enjoyed the reputation of a successful pesticide in disease control programme and agricultural practices along with the serious opposition and ban later on due to its biomagnification and toxic action against non-target organisms. The present work was carried out to develop QSAR models for analysing DDT analogues for their pesticidal activity and in silico validation of these models. A 2D-QSAR model was generated using stepwise with multiple regression, and the model with a value of r(2) = 0.7324; q(2) = 0.6215; pred r(2) = 0.7038, containing five descriptors, was selected for further study. The 3D QSAR with CoMFA analysis showed that steric contribution of 21% and electrostatic contribution of about 79% were required for larvicidal activity of DDT analogues. A set of 3430 molecules was generated using the basic DDT skeleton as template, and these were evaluated for their mosquito larvicidal activity using the generated QSAR models and DDT as standard. Eleven molecules were selected for in silico validation of these models. For this, a docking study of the selected molecules against the homology-modelled voltage-gated sodium channel of Anopheles funestus was conducted. The study showed that the activities of these analogues as predicted by 2D-QSAR, 3D-QSAR with CoMFA and dock score were observed to be well correlated. PMID:25271473

  7. The Automatic Light Curves Generated by Danish 1.54m Telescope

    NASA Astrophysics Data System (ADS)

    Skoda, Petr

    2015-12-01

    We present the Ondřejov Southern Photometry Survey, being conducted at the Danish 1.54m telescope in remote observing mode by several groups of Czech stellar astronomers. The automatic astrometry and photometry pipelines run on every CCD frame combined with sophisticated parallelized cross-matching and clustering algorithms result in an on-the-fly generation of light curves of every single object in the field. To allow powerful querying and visualization of current database of more than half billion of measurements, the technology of Virtual Observatory is used, combining IVOA protocols and powerful visualization tools as Aladin, TOPCAT and SPLAT-VO.

  8. Annual incidence, prevalence and transmission characteristics of Streptococcus agalactiae in Danish dairy herds.

    PubMed

    Mweu, Marshal M; Nielsen, Søren S; Halasa, Tariq; Toft, Nils

    2012-10-01

    Contagious mastitis pathogens continue to pose an economic threat to the dairy industry. An understanding of their frequency and transmission dynamics is central to evaluating the effectiveness of control programmes. The objectives of this study were twofold: (1) to estimate the annual herd-level incidence rates and apparent prevalences of Streptococcus agalactiae (S. agalactiae) in the population of Danish dairy cattle herds over a 10-year period from 2000 to 2009 inclusive and (2) to estimate the herd-level entry and exit rates (demographic parameters), the transmission parameter, β, and recovery rate for S. agalactiae infection. Data covering the specified period, on bacteriological culture of all bulk tank milk samples collected annually as part of the mandatory Danish S. agalactiae surveillance scheme, were extracted from the Danish Cattle Database and subsequently analysed. There was an increasing trend in both the incidence and prevalence of S. agalactiae over the study period. Per 100 herd-years the value of β was 54.1 (95% confidence interval [CI] 46.0-63.7); entry rate 0.3 (95% CI 0.2-0.4); infection-related exit rate 7.1 (95% CI 5.6-8.9); non-infection related exit rate 9.2 (95% CI 7.4-11.5) and recovery rate 40.0 (95% CI 36.8-43.5). This study demonstrates a need to tighten the current controls against S. agalactiae in order to lower its incidence. PMID:22560559

  9. Dual Allosteric Effect in Glycine/NMDA Receptor Antagonism: A Comparative QSAR Approach

    PubMed Central

    Sharma, Manish; Gupta, Vipin B.

    2010-01-01

    A comparative Hansch type QSAR study was conducted using multiple regression analysis on various sets of quinoxalines, quinoxalin-4-ones, quinazoline-2-carboxylates, 4-hydroxyquinolin-2(1H)-ones, 2-carboxytetrahydroquinolines, phenyl-hydroxy-quinolones, nitroquinolones and 4-substituted-3-phenylquinolin-2(1H)-ones as selective glycine/NMDA site antagonists. Ten statistically validated equations were developed, which indicated the importance of CMR, Verloop’s sterimol L1 and ClogP parameters in contributing towards biological activity. Interestingly, normal and inverse parabolic relationships were found with CMR in different series, indicating a dual allosteric binding mode in glycine/NMDA antagonism. Equations reveal an optimum CMR of 10 ± 10% is required for good potency of antagonists. Other equations indicate the presence of anionic functionality at 4-position of quinoline/quinolone ring system is not absolutely required for effective binding. The observations are laterally validated and in accordance with previous studies.

  10. Synthesis, Evaluation of Anticancer Activity and QSAR Study of Heterocyclic Esters of Caffeic Acid

    PubMed Central

    Hajmohamad Ebrahim Ketabforoosh, Shima; Amini, Mohsen; Vosooghi, Mohsen; Shafiee, Abbas; Azizi, Ebrahim; Kobarfard, Farzad

    2013-01-01

    Caffeic acid phenethyl ester (CAPE) suppresses the growth of transformed cells such as human breast cancer cells, hepatocarcinoma , myeloid leukemia, colorectal cancer cells, fibrosarcoma, glioma and melanoma. A group of heterocyclic esters of caffeic acid was synthesized using Mitsunobu reaction and the esters were subjected to further structural modification by electrooxidation of the catechol ring of caffeic acid esters in the presence of sodium benzenesulfinate and sodium toluensulfinate as nucleophiles. Both heterocyclic esters of caffeic acid and their arylsulfonyl derivatives were evaluated for their cytotoxic activity against HeLa, SK-OV-3, and HT-29 cancer cell lines. HeLa cells showed the highest sensitivity to the compounds and heterocyclic esters with no substituent on catechol ring showed better activity compared to their substituted counterparts. QSAR studies reemphasized the importance of molecular shape of the compounds for their cytotoxic activity. PMID:24523750

  11. Expert QSAR system for predicting the bioconcentration factor under the REACH regulation.

    PubMed

    Grisoni, Francesca; Consonni, Viviana; Vighi, Marco; Villa, Sara; Todeschini, Roberto

    2016-07-01

    Expert systems are a rational integration of several models that generally aim to exploit their advantages and overcome their drawbacks. This work is founded on our previously published Quantitative Structure-Activity Relationship (QSAR) classification scheme, which detects compounds whose Bioconcentration Factor (BCF) is (1) well predicted by the octanol-water partition coefficient (KOW), (2) underestimated by KOW or (3) overestimated by KOW. The classification scheme served as the starting point to identify and combine the best BCF model for each class among three VEGA models and one KOW-based equation. The rationalized model integration showed stability and surprising performance on unknown data when compared with benchmark BCF models. Model simplicity, transparency and mechanistic interpretation were fostered in order to allow for its application and acceptance within the REACH framework. PMID:27152714

  12. Synthesis, antimycobacterial, antiviral, antimicrobial activity and QSAR studies of N(2)-acyl isonicotinic acid hydrazide derivatives.

    PubMed

    Judge, Vikramjeet; Narasimhan, Balasubramanian; Ahuja, Munish; Sriram, Dharmarajan; Yogeeswari, Perumal; De Clercq, Erik; Pannecouque, Christophe; Balzarini, Jan

    2013-02-01

    A series of N(2)-acyl isonicotinic acid hydrazides (1-17) was synthesized and tested for its in vitro antimycobacterial activity against Mycobacterium tuberculosis and the results indicated that the compound, isonicotinic acid N'- tetradecanoyl-hydrazide (12) was more active than the reference compound isoniazid. The results of antimicrobial activity of the synthesized compounds against S. aureus, B. subtilis, E. coli, C. albicans and A. niger indicated that compounds with dichloro, hydroxyl, tri-iodo and N(2)-tetradecanoyl substituent were the most active ones. The antiviral activity studies depicted that none of the tested compounds were active against DNA or RNA viruses. The multi-target QSAR model was found to be effective in describing the antimicrobial activity of N(2)-acyl isonicotinic acid hydrazides. PMID:22762163

  13. Biological evaluation and 3D-QSAR studies of curcumin analogues as aldehyde dehydrogenase 1 inhibitors.

    PubMed

    Wang, Hui; Du, Zhiyun; Zhang, Changyuan; Tang, Zhikai; He, Yan; Zhang, Qiuyan; Zhao, Jun; Zheng, Xi

    2014-01-01

    Aldehyde dehydrogenase 1 (ALDH1) is reported as a biomarker for identifying some cancer stem cells, and down-regulation or inhibition of the enzyme can be effective in anti-drug resistance and a potent therapeutic for some tumours. In this paper, the inhibitory activity, mechanism mode, molecular docking and 3D-QSAR (three-dimensional quantitative structure activity relationship) of curcumin analogues (CAs) against ALDH1 were studied. Results demonstrated that curcumin and CAs possessed potent inhibitory activity against ALDH1, and the CAs compound with ortho di-hydroxyl groups showed the most potent inhibitory activity. This study indicates that CAs may represent a new class of ALDH1 inhibitor. PMID:24840575

  14. SYNTHESIS, ANTIMICROBIAL, ANTICANCER EVALUATION AND QSAR STUDIES OF THIAZOLIDIN-4-ONE DERIVATIVES.

    PubMed

    Deep, Aakash; Kumar, Pradeep; Narasimhan, Balasubramanian; Lim, Siong Meng; Ramasamy, Kalavathy; Mishra, Rakesh Kumar; Mani, Vasudevan

    2016-01-01

    In this study, a novel series of 4-thiazolidinone derivatives (1-17) was synthesized and evaluated for its in vitro antimicrobial and anticancer potentials. N-(2-(5-(4-nitrobenzylidene)-2-(4-chlorophenyl)-4-oxothia- zolidin-3-ylamino)-2-oxoethyl) benzamide (7, pMICam = 1.86 µM/mL) was found to be the most active antimi- crobial agent. The anticancer study results demonstrated that N-(2-(5-(4-hydroxybenzylidene)-2-(4- methoxyphenyl)-4-oxothiazolidin-3-ylamino)-2-oxoethyl) benzamide (10, IC₅₀ = 18.59 µM) was the most active anticancer agent. QSAR studies indicated the importance of topological parameter, Kier's α third order shape index (κα₃) as well as electronic parameters, cosmic total energy (cos E) and energy of highest occupied molecular orbital (HOMO) in describing the antimicrobial activity of synthesized compounds. PMID:27008804

  15. Synthesis, antimicrobial, anticancer evaluation and QSAR studies of 3/4-bromo benzohydrazide derivatives.

    PubMed

    Kumar, Pradeep; Narasimhan, Balasubramanian; Ramasamy, Kalavathy; Mani, Vasudevan; Mishra, Rakesh Kumar; Majeed, Abu Bakar Abdul

    2015-01-01

    A series 3/4-bromo-N'-(substituted benzylidene/furan-2-ylmethylene/5-oxopentylidene/3- phenylallylidene)benzohydrazides (1-23) was synthesized and characterized by physicochemical and spectral means. The synthesized compounds were screened for their antimicrobial and anticancer potentials. Antimicrobial activity results indicated that compound 12 (pMICam = 1.67 μM/ml) was the most potent antimicrobial agent. The synthesized benzohydrazides were also having good anticancer potential and compound 22 (IC50 = 1.20 μM μM) was found to be the most potent anticancer agent which was more potent than standard drugs, tetrandrine (IC50 = 1.53) and 5- fluorouracil (IC50 = 4.6 μM). QSAR studies indicated that antimicrobial activity of synthesized compounds was best described by electronic parameter, total energy (Te) and topological parameters, valance zero order molecular connectivity index ((0)χ(v)) and Wiener index (W). PMID:25860177

  16. Understanding Substrate Selectivity of Human UDP-glucuronosyltransferases through QSAR modeling and analysis of homologous enzymes

    PubMed Central

    Dong, Dong; Ako, Roland; Hu, Ming; Wu, Baojian

    2015-01-01

    The UDP-glucuronosyltransferase (UGT) enzyme catalyzes the glucuronidation reaction which is a major metabolic and detoxification pathway in humans. Understanding the mechanisms for substrate recognition by UGT assumes great importance in an attempt to predict its contribution to xenobiotic/drug disposition in vivo. Spurred on by this interest, 2D/3D-quantitative structure activity relationships (QSAR) and pharmacophore models have been established in the absence of a complete mammalian UGT crystal structure. This review discusses the recent progress in modeling human UGT substrates including those with multiple sites of glucuronidation. A better understanding of UGT active site contributing to substrate selectivity (and regioselectivity) from the homologous enzymes (i.e., plant and bacterial UGTs, all belong to family 1 of glycosyltransferase (GT1)) is also highlighted, as these enzymes share a common catalytic mechanism and/or overlapping substrate selectivity. PMID:22385482

  17. Quantitative Structure-Activity Relationship (QSAR) of indoloacetamides as inhibitors of human isoprenylcysteine carboxyl methyltransferase

    PubMed Central

    Leow, Jo-Lene; Baron, Rudi; Casey, Patrick C; Go, Mei-Lin

    2007-01-01

    A QSAR is developed for the isoprenylcysteine carboxyl methyltransferase (ICMT) inhibitory activities of a series of indoloacetamides (n = 71) that are structurally related to cysmethynil, a selective ICMT inhibitor. Multivariate analytical tools (principal component analysis and projection to latent structures), multi-linear regression and comparative molecular field analysis (CoMFA) are used to develop a suitably predictive model for the purpose of optimizing and identifying members with more potent inhibitory activity. The resulting model shows that good activity is determined largely by the characteristics of the substituent attached to the indole nitrogen, which should be a lipophilic residue with fairly wide dimensions. In contrast, the substituted phenyl ring attached to the indole ring must be of limited dimensions and lipophilicity. PMID:17157012

  18. QSAR on antiproliferative naphthoquinones based on a conformation-independent approach.

    PubMed

    Duchowicz, Pablo R; Bennardi, Daniel O; Bacelo, Daniel E; Bonifazi, Evelyn L; Rios-Luci, Carla; Padrón, José M; Burton, Gerardo; Misico, Rosana I

    2014-04-22

    The antiproliferative activities of a series of 36 naphthoquinone derivatives were subjected to a Quantitative Structure-Activity Relationships (QSAR) study. For this purpose a panel of four human cancer cell lines was used, namely HBL-100 (breast), HeLa (cervix), SW-1573 (non-small cell lung) and WiDr (colon). A conformation-independent representation of the chemical structure was established in order to avoid leading with the scarce experimental information on X-ray crystal structure of the drug interaction. The 1179 theoretical descriptors derived with E-Dragon and Recon software were simultaneously analyzed through linear regression models based on the Replacement Method variable subset selection technique. The established models were validated and tested through the use of external test sets of compounds, the Leave-One-Out Cross Validation method, Y-Randomization and Applicability Domain analysis. PMID:24631897

  19. The eNanoMapper database for nanomaterial safety information

    PubMed Central

    Chomenidis, Charalampos; Doganis, Philip; Fadeel, Bengt; Grafström, Roland; Hardy, Barry; Hastings, Janna; Hegi, Markus; Jeliazkov, Vedrin; Kochev, Nikolay; Kohonen, Pekka; Munteanu, Cristian R; Sarimveis, Haralambos; Smeets, Bart; Sopasakis, Pantelis; Tsiliki, Georgia; Vorgrimmler, David; Willighagen, Egon

    2015-01-01

    Summary Background: The NanoSafety Cluster, a cluster of projects funded by the European Commision, identified the need for a computational infrastructure for toxicological data management of engineered nanomaterials (ENMs). Ontologies, open standards, and interoperable designs were envisioned to empower a harmonized approach to European research in nanotechnology. This setting provides a number of opportunities and challenges in the representation of nanomaterials data and the integration of ENM information originating from diverse systems. Within this cluster, eNanoMapper works towards supporting the collaborative safety assessment for ENMs by creating a modular and extensible infrastructure for data sharing, data analysis, and building computational toxicology models for ENMs. Results: The eNanoMapper database solution builds on the previous experience of the consortium partners in supporting diverse data through flexible data storage, open source components and web services. We have recently described the design of the eNanoMapper prototype database along with a summary of challenges in the representation of ENM data and an extensive review of existing nano-related data models, databases, and nanomaterials-related entries in chemical and toxicogenomic databases. This paper continues with a focus on the database functionality exposed through its application programming interface (API), and its use in visualisation and modelling. Considering the preferred community practice of using spreadsheet templates, we developed a configurable spreadsheet parser facilitating user friendly data preparation and data upload. We further present a web application able to retrieve the experimental data via the API and analyze it with multiple data preprocessing and machine learning algorithms. Conclusion: We demonstrate how the eNanoMapper database is used to import and publish online ENM and assay data from several data sources, how the “representational state transfer

  20. Overlap in Bibliographic Databases.

    ERIC Educational Resources Information Center

    Hood, William W.; Wilson, Concepcion S.

    2003-01-01

    Examines the topic of Fuzzy Set Theory to determine the overlap of coverage in bibliographic databases. Highlights include examples of comparisons of database coverage; frequency distribution of the degree of overlap; records with maximum overlap; records unique to one database; intra-database duplicates; and overlap in the top ten databases.…

  1. 5D-QSAR for spirocyclic sigma1 receptor ligands by Quasar receptor surface modeling.

    PubMed

    Oberdorf, Christoph; Schmidt, Thomas J; Wünsch, Bernhard

    2010-07-01

    Based on a contiguous and structurally as well as biologically diverse set of 87 sigma(1) ligands, a 5D-QSAR study was conducted in which a quasi-atomistic receptor surface modeling approach (program package Quasar) was applied. The superposition of the ligands was performed with the tool Pharmacophore Elucidation (MOE-package), which takes all conformations of the ligands into account. This procedure led to four pharmacophoric structural elements with aromatic, hydrophobic, cationic and H-bond acceptor properties. Using the aligned structures a 3D-model of the ligand binding site of the sigma(1) receptor was obtained, whose general features are in good agreement with previous assumptions on the receptor structure, but revealed some novel insights since it represents the receptor surface in more detail. Thus, e.g., our model indicates the presence of an H-bond acceptor moiety in the binding site as counterpart to the ligands' cationic ammonium center, rather than a negatively charged carboxylate group. The presented QSAR model is statistically valid and represents the biological data of all tested compounds, including a test set of 21 ligands not used in the modeling process, with very good to excellent accuracy [q(2) (training set, n=66; leave 1/3 out) = 0.84, p(2) (test set, n=21)=0.64]. Moreover, the binding affinities of 13 further spirocyclic sigma(1) ligands were predicted with reasonable accuracy (mean deviation in pK(i) approximately 0.8). Thus, in addition to novel insights into the requirements for binding of spirocyclic piperidines to the sigma(1) receptor, the presented model can be used successfully in the rational design of new sigma(1) ligands. PMID:20427100

  2. 3D QSAR studies on substituted benzimidazole derivatives as angiotensin II-AT1 receptor antagonist.

    PubMed

    Vyas, Vivek K; Ghate, Manjunath; Chintha, Chetan; Patel, Paresh

    2013-09-01

    This study investigated 3D quantitative structure-activity relationships (QSAR) for a range of substituted benzimidazole derivatives as AngII-AT1 receptor antagonists by comparative molecular field analysis (CoMFA) and comparative molecular similarity indices (CoMSIA). The alignment strategy was used for these compounds by means of Distill function defined in SYBYL X 1.2. The best CoMFA and CoMSIA models were obtained for the training set compounds was statistically significant with leave-one-out (LOO) validation correlation coefficient (q²) of 0.613 and 0.622, cross validated coefficient (r²cv) of 0.617 and 0.607, respectively and conventional coefficient (r²ncv) of 0.886 and 0.859, respectively. Both the models were validated by a test set of 18 compounds giving satisfactory predicted correlation coefficient (r²pred) of 0.714 and 0.549 for CoMFA and CoMSIA models, respectively. Generated 3D QSAR models were used for the prediction of pIC50 of an external dataset of 10 compounds for predictive validation, which gave conventional r² of 0.893 for CoMFA model, and 0.774 for CoMSIA model. We identified some key features in substituted benzimidazole derivatives, such as the importance of lipophilicity and H-bonding at 2- and 5, 6, 7- position of benzimidazole ring, respectively, for good antagonistic activity. CoMFA and CoMSIA models generated in this work provide useful information for the design of new compounds and helped in prediction of antagonistic activity. PMID:24010938

  3. Molecular Determinants of Juvenile Hormone Action as Revealed by 3D QSAR Analysis in Drosophila

    PubMed Central

    Beňo, Milan; Farkaš, Robert

    2009-01-01

    Background Postembryonic development, including metamorphosis, of many animals is under control of hormones. In Drosophila and other insects these developmental transitions are regulated by the coordinate action of two principal hormones, the steroid ecdysone and the sesquiterpenoid juvenile hormone (JH). While the mode of ecdysone action is relatively well understood, the molecular mode of JH action remains elusive. Methodology/Principal Findings To gain more insights into the molecular mechanism of JH action, we have tested the biological activity of 86 structurally diverse JH agonists in Drosophila melanogaster. The results were evaluated using 3D QSAR analyses involving CoMFA and CoMSIA procedures. Using this approach we have generated both computer-aided and species-specific pharmacophore fingerprints of JH and its agonists, which revealed that the most active compounds must possess an electronegative atom (oxygen or nitrogen) at both ends of the molecule. When either of these electronegative atoms are replaced by carbon or the distance between them is shorter than 11.5 Å or longer than 13.5 Å, their biological activity is dramatically decreased. The presence of an electron-deficient moiety in the middle of the JH agonist is also essential for high activity. Conclusions/Significance The information from 3D QSAR provides guidelines and mechanistic scope for identification of steric and electrostatic properties as well as donor and acceptor hydrogen-bonding that are important features of the ligand-binding cavity of a JH target protein. In order to refine the pharmacophore analysis and evaluate the outcomes of the CoMFA and CoMSIA study we used pseudoreceptor modeling software PrGen to generate a putative binding site surrogate that is composed of eight amino acid residues corresponding to the defined molecular interactions. PMID:19547707

  4. Autocorrelation descriptor improvements for QSAR: 2DA_Sign and 3DA_Sign.

    PubMed

    Sliwoski, Gregory; Mendenhall, Jeffrey; Meiler, Jens

    2016-03-01

    Quantitative structure-activity relationship (QSAR) is a branch of computer aided drug discovery that relates chemical structures to biological activity. Two well established and related QSAR descriptors are two- and three-dimensional autocorrelation (2DA and 3DA). These descriptors encode the relative position of atoms or atom properties by calculating the separation between atom pairs in terms of number of bonds (2DA) or Euclidean distance (3DA). The sums of all values computed for a given small molecule are collected in a histogram. Atom properties can be added with a coefficient that is the product of atom properties for each pair. This procedure can lead to information loss when signed atom properties are considered such as partial charge. For example, the product of two positive charges is indistinguishable from the product of two equivalent negative charges. In this paper, we present variations of 2DA and 3DA called 2DA_Sign and 3DA_Sign that avoid information loss by splitting unique sign pairs into individual histograms. We evaluate these variations with models trained on nine datasets spanning a range of drug target classes. Both 2DA_Sign and 3DA_Sign significantly increase model performance across all datasets when compared with traditional 2DA and 3DA. Lastly, we find that limiting 3DA_Sign to maximum atom pair distances of 6 Å instead of 12 Å further increases model performance, suggesting that conformational flexibility may hinder performance with longer 3DA descriptors. Consistent with this finding, limiting the number of bonds in 2DA_Sign from 11 to 5 fails to improve performance. PMID:26721261

  5. Probing the origins of aromatase inhibitory activity of disubstituted coumarins via QSAR and molecular docking

    PubMed Central

    Worachartcheewan, Apilak; Suvannang, Naravut; Prachayasittikul, Supaluk; Prachayasittikul, Virapong; Nantasenamat, Chanin

    2014-01-01

    This study investigated the quantitative structure-activity relationship (QSAR) of imidazole derivatives of 4,7-disubstituted coumarins as inhibitors of aromatase, a potential therapeutic protein target for the treatment of breast cancer. Herein, a series of 3,7- and 4,7-disubstituted coumarin derivatives (1-34) with R1 and R2 substituents bearing aromatase inhibitory activity were modeled as a function of molecular and quantum chemical descriptors derived from low-energy conformer geometrically optimized at B3LYP/6-31G(d) level of theory. Insights on origins of aromatase inhibitory activity was afforded by the computed set of 7 descriptors comprising of F10[N-O], Inflammat-50, Psychotic-80, H-047, BELe1, B10[C-O] and MAXDP. Such significant descriptors were used for QSAR model construction and results indicated that model 4 afforded the best statistical performance. Good predictive performance were achieved as verified from the internal (comprising the training and the leave-one-out cross-validation (LOO-CV) sets) and external sets affording the following statistical parameters: R2Tr = 0.9576 and RMSETr = 0.0958 for the training set; Q2CV = 0.9239 and RMSECV = 0.1304 for the LOO-CV set as well as Q2Ext = 0.7268 and RMSEExt = 0.2927 for the external set. Significant descriptors showed correlation with functional substituents, particularly, R1 in governing high potency as aromatase inhibitor. Molecular docking calculations suggest that key residues interacting with the coumarins were predominantly lipophilic or non-polar while a few were polar and positively-charged. Findings illuminated herein serve as the impetus that can be used to rationally guide the design of new aromatase inhibitors. PMID:26417339

  6. The EXOSAT database system. Available databases.

    NASA Astrophysics Data System (ADS)

    Barron, C.

    1991-02-01

    This User's Guide describes the databases that are currently available by remote login to the EXOSAT/ESTEC site of the EXOSAT database system. This includes where ever possible the following: brief descriptions of each observatory, telescope and instrument references to more complete observatory descriptions a list of the contents of each database and how it was generated, parameter descriptions.

  7. Validation of the danish national diabetes register.

    PubMed

    Green, Anders; Sortsø, Camilla; Jensen, Peter Bjødstrup; Emneus, Martha

    2015-01-01

    The Danish National Diabetes Register (NDR) was established in 2006 and builds on data from Danish health registers. We validated the content of NDR, using full information from the Danish National Patient Register and data from the literature. Our study indicates that the completeness in NDR is ≥95% concerning ascertainment from data sources specific for diabetes, ie, prescriptions with antidiabetic drugs and diagnoses of diabetes in the National Patient Register. Since the NDR algorithm ignores diabetes-related hospital contacts terminated before 1990, the establishment of the date of inclusion is systematically delayed for ≥10% of the registrants in general and for ≥30% of the inclusions before 1997 in particular. This bias is enhanced for ascertainment by chiropody services and by frequent measurements of blood glucose because the date of reimbursement of services, rather than the date of encounter, has been taken as the date of inclusion in NDR. We also find that some 20% of the registrations in NDR may represent false positive inclusions of persons with frequent measurements of blood glucose without having diabetes. We conclude that NDR is a novel initiative to support research in the epidemiological and public health aspects of diabetes in Denmark, but we also present a list of recommended changes for improving validity, by reducing the impact of current sources of bias and misclassifications. PMID:25565889

  8. Estimation of the chemical-induced eye injury using a weight-of-evidence (WoE) battery of 21 artificial neural network (ANN) c-QSAR models (QSAR-21): part I: irritation potential.

    PubMed

    Verma, Rajeshwar P; Matthews, Edwin J

    2015-03-01

    Evaluation of potential chemical-induced eye injury through irritation and corrosion is required to ensure occupational and consumer safety for industrial, household and cosmetic ingredient chemicals. The historical method for evaluating eye irritant and corrosion potential of chemicals is the rabbit Draize test. However, the Draize test is controversial and its use is diminishing - the EU 7th Amendment to the Cosmetic Directive (76/768/EEC) and recast Regulation now bans marketing of new cosmetics having animal testing of their ingredients and requires non-animal alternative tests for safety assessments. Thus, in silico and/or in vitro tests are advocated. QSAR models for eye irritation have been reported for several small (congeneric) data sets; however, large global models have not been described. This report describes FDA/CFSAN's development of 21 ANN c-QSAR models (QSAR-21) to predict eye irritation using the ADMET Predictor program and a diverse training data set of 2928 chemicals. The 21 models had external (20% test set) and internal validation and average training/verification/test set statistics were: 88/88/85(%) sensitivity and 82/82/82(%) specificity, respectively. The new method utilized multiple artificial neural network (ANN) molecular descriptor selection functionalities to maximize the applicability domain of the battery. The eye irritation models will be used to provide information to fill the critical data gaps for the safety assessment of cosmetic ingredient chemicals. PMID:25497990

  9. QSAR Study of p56lck Protein Tyrosine Kinase Inhibitory Activity of Flavonoid Derivatives Using MLR and GA-PLS

    PubMed Central

    Fassihi, Afshin; Sabet, Razieh

    2008-01-01

    Quantitative relationships between molecular structure and p56lck protein tyrosine kinase inhibitory activity of 50 flavonoid derivatives are discovered by MLR and GA-PLS methods. Different QSAR models revealed that substituent electronic descriptors (SED) parameters have significant impact on protein tyrosine kinase inhibitory activity of the compounds. Between the two statistical methods employed, GA-PLS gave superior results. The resultant GA-PLS model had a high statistical quality (R2 = 0.74 and Q2 = 0.61) for predicting the activity of the inhibitors. The models proposed in the present work are more useful in describing QSAR of flavonoid derivatives as p56lck protein tyrosine kinase inhibitors than those provided previously. PMID:19325836

  10. Discovery of New Anti-Schistosomal Hits by Integration of QSAR-Based Virtual Screening and High Content Screening.

    PubMed

    Neves, Bruno J; Dantas, Rafael F; Senger, Mario R; Melo-Filho, Cleber C; Valente, Walter C G; de Almeida, Ana C M; Rezende-Neto, João M; Lima, Elid F C; Paveley, Ross; Furnham, Nicholas; Muratov, Eugene; Kamentsky, Lee; Carpenter, Anne E; Braga, Rodolpho C; Silva-Junior, Floriano P; Andrade, Carolina Horta

    2016-08-11

    Schistosomiasis is a debilitating neglected tropical disease, caused by flatworms of Schistosoma genus. The treatment relies on a single drug, praziquantel (PZQ), making the discovery of new compounds extremely urgent. In this work, we integrated QSAR-based virtual screening (VS) of Schistosoma mansoni thioredoxin glutathione reductase (SmTGR) inhibitors and high content screening (HCS) aiming to discover new antischistosomal agents. Initially, binary QSAR models for inhibition of SmTGR were developed and validated using the Organization for Economic Co-operation and Development (OECD) guidance. Using these models, we prioritized 29 compounds for further testing in two HCS platforms based on image analysis of assay plates. Among them, 2-[2-(3-methyl-4-nitro-5-isoxazolyl)vinyl]pyridine and 2-(benzylsulfonyl)-1,3-benzothiazole, two compounds representing new chemical scaffolds have activity against schistosomula and adult worms at low micromolar concentrations and therefore represent promising antischistosomal hits for further hit-to-lead optimization. PMID:27396732

  11. [Application of Kohonen Self-Organizing Feature Maps in QSAR of human ADMET and kinase data sets].

    PubMed

    Hegymegi-Barakonyi, Bálint; Orfi, László; Kéri, György; Kövesdi, István

    2013-01-01

    QSAR predictions have been proven very useful in a large number of studies for drug design, such as kinase inhibitor design as targets for cancer therapy, however the overall predictability often remains unsatisfactory. To improve predictability of ADMET features and kinase inhibitory data, we present a new method using Kohonen's Self-Organizing Feature Map (SOFM) to cluster molecules based on explanatory variables (X) and separate dissimilar ones. We calculated SOFM clusters for a large number of molecules with human ADMET and kinase inhibitory data, and we showed that chemically similar molecules were in the same SOFM cluster, and within such clusters the QSAR models had significantly better predictability. We used also target variables (Y, e.g. ADMET) jointly with X variables to create a novel type of clustering. With our method, cells of loosely coupled XY data could be identified and separated into different model building sets. PMID:24575660

  12. QSAR study of some pyrazolo[3,4-d]pyrimidine derivatives as the c-Src inhibitors

    NASA Astrophysics Data System (ADS)

    Shukla, Bindesh Kumar; Yadava, Umesh

    2016-05-01

    Two dimensional quantitative structure activity relationship (QSAR) studies have been carried out on a series of 42 pyrazolo[3,4-d]pyrimidine derivatives to find out the structural requirements for the inhibition of c-SRC phosphorilation. The best predictions were obtained using Heuristic and Best MLR methods from the model where 33 compounds were considered in the training set and the remaining 9 in the test set. Both Best MLR and Heuristic methods indicate that squared correlation coefficient for training and test sets are very close to observed biological activities which designate the good correlation between the experimental and predicted activity. The results that are obtained from 2D-QSAR studies may provide useful insights into the roles of various substitution patterns on the pyrazolo[3,4-d]pyrimidine core and may also help to design more potent compounds.

  13. Multivariate SAR and QSAR of cucurbitacin derivatives as cytotoxic compounds in a human lung adenocarcinoma cell line.

    PubMed

    Lang, Karen L; Silva, Izabella T; Machado, Vanessa R; Zimmermann, Lara A; Caro, Miguel S B; Simões, Cláudia M O; Schenkel, Eloir P; Durán, Fernando J; Bernardes, Lílian S C; de Melo, Eduardo B

    2014-03-01

    This article describes structure-activity relationship (SAR/QSAR) studies on the cytotoxic activity in a human lung adenocarcinoma cell line (A549) of 43 cucurbitacin derivatives. Modeling was performed using the methods partial least squares with discriminant analysis (PLS-DA) and PLS. For both studies, the variables were selected using the ordered predictor selection (OPS) algorithm. The SAR study demonstrated that the presence or absence of cytotoxic activity of the cucurbitacins could be described using information derived from their chemical structures. The QSAR study displayed suitable internal and external predictivity, and the selected descriptors indicated that the observed activity might be related to electrophilic attack on cellular structures or genetic material. This study provides improves the understanding of the cytotoxic activity of cucurbitacins and could be used to propose new cytotoxic agents. PMID:24378396

  14. Predictive Modeling of Antioxidant Coumarin Derivatives Using Multiple Approaches: Descriptor-Based QSAR, 3D-Pharmacophore Mapping, and HQSAR.

    PubMed

    Mitra, Indrani; Saha, Achintya; Roy, Kunal

    2013-03-01

    The inability of the systemic antioxidants to alleviate the exacerbation of free radical formation from metabolic outputs and environmental pollutants claims an urgent demand for the identification and design of new chemical entities with potent antioxidant activity. In the present work, different QSAR approaches have been utilized for identifying the essential structural attributes imparting a potential antioxidant activity profile of the coumarin derivatives. The descriptor-based QSAR model provides a quantitative outline regarding the structural prerequisites of the molecules, while 3D pharmacophore and HQSAR models emphasize the favourable spatial arrangement of the various chemical features and the crucial molecular fragments, respectively. All the models infer that the fused benzene ring and the oxygen atom of the pyran ring constituting the parent coumarin nucleus capture the prime pharmacophoric features, imparting superior antioxidant activity to the molecules. The developed models may serve as indispensable query tools for screening untested molecules belonging to the class of coumarin derivatives. PMID:23641329

  15. Identification of potential influenza virus endonuclease inhibitors through virtual screening based on the 3D-QSAR model.

    PubMed

    Kim, J; Lee, C; Chong, Y

    2009-01-01

    Influenza endonucleases have appeared as an attractive target of antiviral therapy for influenza infection. With the purpose of designing a novel antiviral agent with enhanced biological activities against influenza endonuclease, a three-dimensional quantitative structure-activity relationships (3D-QSAR) model was generated based on 34 influenza endonuclease inhibitors. The comparative molecular similarity index analysis (CoMSIA) with a steric, electrostatic and hydrophobic (SEH) model showed the best correlative and predictive capability (q(2) = 0.763, r(2) = 0.969 and F = 174.785), which provided a pharmacophore composed of the electronegative moiety as well as the bulky hydrophobic group. The CoMSIA model was used as a pharmacophore query in the UNITY search of the ChemDiv compound library to give virtual active compounds. The 3D-QSAR model was then used to predict the activity of the selected compounds, which identified three compounds as the most likely inhibitor candidates. PMID:19343586

  16. Quality improvement and accountability in the Danish health care system.

    PubMed

    Mainz, Jan; Kristensen, Solvejg; Bartels, Paul

    2015-12-01

    Denmark has unique opportunities for quality measurement and benchmarking since Denmark has well-developed health registries and unique patient identifier that allow all registries to include patient-level data and combine data into sophisticated quality performance monitoring. Over decades, Denmark has developed and implemented national quality and patient safety initiatives in the healthcare system in terms of national clinical guidelines, performance and outcome measurement integrated in clinical databases for important diseases and clinical conditions, measurement of patient experiences, reporting of adverse events, national handling of patient complaints, national accreditation and public disclosure of all data on the quality of care. Over the years, Denmark has worked up a progressive and transparent just culture in quality management; the different actors at the different levels of the healthcare system are mutually attentive and responsive in a coordinated effort for quality of the healthcare services. At national, regional, local and hospital level, it is mandatory to participate in the quality initiatives and to use data and results for quality management, quality improvement, transparency in health care and accountability. To further develop the Danish governance model, it is important to expand the model to the primary care sector. Furthermore, a national quality health programme 2015-18 recently launched by the government supports a new development in health care focusing upon delivering high-quality health care-high quality is defined by results of value to the patients. PMID:26443814

  17. 4D-Fingerprint Categorical QSAR Models for Skin Sensitization Based on Classification Local Lymph Node Assay Measures

    PubMed Central

    Li, Yi; Tseng, Yufeng J.; Pan, Dahua; Liu, Jianzhong; Kern, Petra S.; Gerberick, G. Frank; Hopfinger, Anton J.

    2008-01-01

    Currently, the only validated methods to identify skin sensitization effects are in vivo models, such as the Local Lymph Node Assay (LLNA) and guinea pig studies. There is a tremendous need, in particular due to novel legislation, to develop animal alternatives, eg. Quantitative Structure-Activity Relationship (QSAR) models. Here, QSAR models for skin sensitization using LLNA data have been constructed. The descriptors used to generate these models are derived from the 4D-molecular similarity paradigm and are referred to as universal 4D-fingerprints. A training set of 132 structurally diverse compounds and a test set of 15 structurally diverse compounds were used in this study. The statistical methodologies used to build the models are logistic regression (LR), and partial least square coupled logistic regression (PLS-LR), which prove to be effective tools for studying skin sensitization measures expressed in the two categorical terms of sensitizer and non-sensitizer. QSAR models with low values of the Hosmer-Lemeshow goodness-of-fit statistic, χHL2, are significant and predictive. For the training set, the cross-validated prediction accuracy of the logistic regression models ranges from 77.3% to 78.0%, while that of PLS-logistic regression models ranges from 87.1% to 89.4%. For the test set, the prediction accuracy of logistic regression models ranges from 80.0%-86.7%, while that of PLS-logistic regression models ranges from 73.3%-80.0%. The QSAR models are made up of 4D-fingerprints related to aromatic atoms, hydrogen bond acceptors and negatively partially charged atoms. PMID:17226934

  18. Predicting Toxicities of Diverse Chemical Pesticides in Multiple Avian Species Using Tree-Based QSAR Approaches for Regulatory Purposes.

    PubMed

    Basant, Nikita; Gupta, Shikha; Singh, Kunwar P

    2015-07-27

    A comprehensive safety evaluation of chemicals should require toxicity assessment in both the aquatic and terrestrial test species. Due to the application practices and nature of chemical pesticides, the avian toxicity testing is considered as an essential requirement in the risk assessment process. In this study, tree-based multispecies QSAR (quantitative-structure activity relationship) models were constructed for predicting the avian toxicity of pesticides using a set of nine descriptors derived directly from the chemical structures and following the OECD guidelines. Accordingly, the Bobwhite quail toxicity data was used to construct the QSAR models (SDT, DTF, DTB) and were externally validated using the toxicity data in four other test species (Mallard duck, Ring-necked pheasant, Japanese quail, House sparrow). Prior to the model development, the diversity in the chemical structures and end-point were verified. The external predictive power of the QSAR models was tested through rigorous validation deriving a wide series of statistical checks. Intercorrelation analysis and PCA methods provided information on the association of the molecular descriptors related to MW and topology. The S36 and MW were the most influential descriptors identified by DTF and DTB models. The DTF and DTB performed better than the SDT model and yielded a correlation (R(2)) of 0.945 and 0.966 between the measured and predicted toxicity values in test data array. Both these models also performed well in four other test species (R(2) > 0.918). ChemoTyper was used to identify the substructure alerts responsible for the avian toxicity. The results suggest for the appropriateness of the developed QSAR models to reliably predict the toxicity of pesticides in multiple avian test species and can be useful tools in screening the new chemical pesticides for regulatory purposes. PMID:26158470

  19. A combined 3D-QSAR and docking studies for the In-silico prediction of HIV-protease inhibitors

    PubMed Central

    2013-01-01

    Background Tremendous research from last twenty years has been pursued to cure human life against HIV virus. A large number of HIV protease inhibitors are in clinical trials but still it is an interesting target for researchers due to the viral ability to get mutated. Mutated viral strains led the drug ineffective but still used to increase the life span of HIV patients. Results In the present work, 3D-QSAR and docking studies were performed on a series of Danuravir derivatives, the most potent HIV- protease inhibitor known so far. Combined study of 3D-QSAR was applied for Danuravir derivatives using ligand-based and receptor-based protocols and generated models were compared. The results were in good agreement with the experimental results. Additionally, docking analysis of most active 32 and least active 46 compounds into wild type and mutated protein structures further verified our results. The 3D-QSAR and docking results revealed that compound 32 bind efficiently to the wild and mutated protein whereas, sufficient interactions were lost in compound 46. Conclusion The combination of two computational techniques would helped to make a clear decision that compound 32 with well inhibitory activity bind more efficiently within the binding pocket even in case of mutant virus whereas compound 46 lost its interactions on mutation and marked as least active compound of the series. This is all due to the presence or absence of substituents on core structure, evaluated by 3D-QSAR studies. This set of information could be used to design highly potent drug candidates for both wild and mutated form of viruses. PMID:23683267

  20. Multi-Target QSAR Approaches for Modeling Protein Inhibitors. Simultaneous Prediction of Activities Against Biomacromolecules Present in Gram-Negative Bacteria.

    PubMed

    Speck-Planche, Alejandro; Cordeiro, M N D S

    2015-01-01

    Drug discovery is aimed at finding therapeutic agents for the treatment of many diverse diseases and infections. However, this is a very slow an expensive process, and for this reason, in silico approaches are needed to rationalize the search for new molecular entities with desired biological profiles. Models focused on quantitative structure-activity relationships (QSAR) have constituted useful complementary tools in medicinal chemistry, allowing the virtual predictions of dissimilar pharmacological activities of compounds. In the last 10 years, multi-target (mt) QSAR models have been reported, representing great advances with respect to those models generated from classical approaches. Thus, mt- QSAR models can simultaneously predict activities against different biological targets (proteins, microorganisms, cell lines, etc.) by using large and heterogeneous datasets of chemicals. The present review is devoted to discuss the most promising mt-QSAR models, particularly those developed for the prediction of protein inhibitors. We also report the first multi-tasking QSAR (mtk-QSAR) model for simultaneous prediction of inhibitors against biomacromolecules (specifically proteins) present in Gram-negative bacteria. This model allowed us to consider both different proteins and multiple experimental conditions under which the inhibitory activities of the chemicals were determined. The mtk-QSAR model exhibited accuracies higher than 98% in both training and prediction sets, also displaying a very good performance in the classification of active and inactive cases that depended on the specific elements of the experimental conditions. The physicochemical interpretations of the molecular descriptors were also analyzed, providing important insights regarding the molecular patterns associated with the appearance/enhancement of the inhibitory potency. PMID:25961517

  1. Exploring the ligand recognition properties of the human vasopressin V1a receptor using QSAR and molecular modeling studies.

    PubMed

    Contreras-Romo, Martha C; Martínez-Archundia, Marlet; Deeb, Omar; Slusarz, Magdalena J; Ramírez-Salinas, Gema; Garduño-Juárez, Ramón; Quintanar-Stephano, Andrés; Ramírez-Galicia, Guillermo; Correa-Basurto, José

    2014-02-01

    Vaptans are compounds that act as non-peptide vasopressin receptor antagonists. These compounds have diverse chemical structures. In this study, we used a combined approach of protein folding, molecular dynamics simulations, docking, and quantitative structure-activity relationship (QSAR) to elucidate the detailed interaction of the vasopressin receptor V1a (V1aR) with some of its blockers (134). QSAR studies were performed using MLR analysis and were gathered into one group to perform an artificial neural network (ANN) analysis. For each molecule, 1481 molecular descriptors were calculated. Additionally, 15 quantum chemical descriptors were calculated. The final equation was developed by choosing the optimal combination of descriptors after removing the outliers. Molecular modeling enabled us to obtain a reliable tridimensional model of V1aR. The docking results indicated that the great majority of ligands reach the binding site under π-π, π-cation, and hydrophobic interactions. The QSAR studies demonstrated that the heteroatoms N and O are important for ligand recognition, which could explain the structural diversity of ligands that reach V1aR. PMID:24010681

  2. QSAR Analysis of Some Antagonists for p38 map kinase Using Combination of Principal Component Analysis and Artificial Intelligence.

    PubMed

    Doosti, Elham; Shahlaei, Mohsen

    2015-01-01

    Quantitative relationships between structures of a set of p38 map kinase inhibitors and their activities were investigated by principal component regression (PCR) and principal componentartificial neural network (PC-ANN). Latent variables (called components) generated by principal component analysis procedure were applied as the input of developed Quantitative structure- activity relationships (QSAR) models. An exact study of predictability of PCR and PC-ANN showed that the later model has much higher ability to calculate the biological activity of the investigated molecules. Also, experimental and estimated biological activities of compounds used in model development step have indicated a good correlation. Obtained results show that a non-linear model explaining the relationship between the pIC50s and the calculated principal components (that extract from structural descriptors of the studied molecules) is superior than linear model. Some typical figures of merit for QSAR studies explaining the accuracy and predictability of the suggested models were calculated. Therefore, to design novel inhibitors of p38 map kinase with high potency and low undesired effects the developed QSAR models were used to estimate biological pIC50 of the studied compounds. PMID:26234506

  3. Identification of 3-Nitro-2,4,6-trihydroxybenzamide Derivatives as Photosynthetic Electron Transport Inhibitors by QSAR and Pharmacophore Studies.

    PubMed

    Sharma, Mukesh C

    2016-06-01

    In the present investigation, quantitative structure-activity relationship (QSAR) analysis was performed on a data set consisting of structurally diverse compounds in order to investigate the role of their structural features on their photosynthetic electron transport Inhibitors. The best 2D-QSAR model was selected, having correlation coefficient r (2) = 0.8544 and cross-validated squared correlation coefficient q (2) = 0.7139 with external predictive ability of pred_r (2) = 0.7753. The results obtained in this study indicate that the presence of hydroxy and nitro groups, expressed by the SsOHcount and SddsN (nitro) count, is the most relevant molecular property determining efficiency of photosynthetic inhibitory. Molecular field analysis was used to construct the best k-nearest neighbor (kNN-MFA)-based 3D-QSAR model using SA-PLS method, showing good correlative and predictive capabilities in terms of [Formula: see text] and [Formula: see text]. The pharmacophore model includes three features viz. hydrogen bond donor, hydrogen bond acceptor, and one aromatic feature. The developed model was found to be predictive and can be used to design potent photosynthetic electron transport activities prior to their synthesis for further lead modification. PMID:26245276

  4. U.S. EPA`s use of QSAR for new and existing chemical evaluations: Regulatory aspects

    SciTech Connect

    Zeeman, M.; Clements, R.G.; Nabholz, J.V.; Auer, C.M.

    1994-12-31

    As up front testing is not required, ecotoxicity or fate data are available for only about 5% of the 2,200 new chemicals/year submitted to EPA. The EPA`s Toxic Substances Control Act (TSCA) Inventory of existing chemicals currently lists about 72,000 chemicals. Most of existing chemicals also appear to have little or no ecotoxicity or fate data available. The EPA`s Office of Pollution Prevention and Toxics (OPPT) has developed and relies upon QSARs to estimate the ecotoxicity and fate of most of the new chemicals evaluated for ecological hazard and risk assessment. QSAR methods routinely result in ecotoxicity estimations of acute and sub/chronic toxicity to fish, aquatic invertebrates, and algae, and fate estimations of physical/chemical properties, degradation, and bioconcentration. GSAR methods were also used to screen the TSCA Inventory for the ecotoxicity of specific chemical classes of over 8,000 discrete chemicals. In the latter effort, seven major chemical classes made up almost 95% of these chemicals. From this QSAR analysis, about 10--20% or 15--18% of these chemicals, respectively, are expected to have high acute or high chronic toxicity to aquatic species. Estimates of ecotoxicity for > 8,000 discrete organics enhances prioritization of chemicals on the TSCA Inventory and helps focus EPA/OPPT regulatory efforts upon the potentially most toxic substances.

  5. Combining QSAR Modeling and Text-Mining Techniques to Link Chemical Structures and Carcinogenic Modes of Action.

    PubMed

    Papamokos, George; Silins, Ilona

    2016-01-01

    There is an increasing need for new reliable non-animal based methods to predict and test toxicity of chemicals. Quantitative structure-activity relationship (QSAR), a computer-based method linking chemical structures with biological activities, is used in predictive toxicology. In this study, we tested the approach to combine QSAR data with literature profiles of carcinogenic modes of action automatically generated by a text-mining tool. The aim was to generate data patterns to identify associations between chemical structures and biological mechanisms related to carcinogenesis. Using these two methods, individually and combined, we evaluated 96 rat carcinogens of the hematopoietic system, liver, lung, and skin. We found that skin and lung rat carcinogens were mainly mutagenic, while the group of carcinogens affecting the hematopoietic system and the liver also included a large proportion of non-mutagens. The automatic literature analysis showed that mutagenicity was a frequently reported endpoint in the literature of these carcinogens, however, less common endpoints such as immunosuppression and hormonal receptor-mediated effects were also found in connection with some of the carcinogens, results of potential importance for certain target organs. The combined approach, using QSAR and text-mining techniques, could be useful for identifying more detailed information on biological mechanisms and the relation with chemical structures. The method can be particularly useful in increasing the understanding of structure and activity relationships for non-mutagens. PMID:27625608

  6. Combining QSAR Modeling and Text-Mining Techniques to Link Chemical Structures and Carcinogenic Modes of Action

    PubMed Central

    Papamokos, George; Silins, Ilona

    2016-01-01

    There is an increasing need for new reliable non-animal based methods to predict and test toxicity of chemicals. Quantitative structure-activity relationship (QSAR), a computer-based method linking chemical structures with biological activities, is used in predictive toxicology. In this study, we tested the approach to combine QSAR data with literature profiles of carcinogenic modes of action automatically generated by a text-mining tool. The aim was to generate data patterns to identify associations between chemical structures and biological mechanisms related to carcinogenesis. Using these two methods, individually and combined, we evaluated 96 rat carcinogens of the hematopoietic system, liver, lung, and skin. We found that skin and lung rat carcinogens were mainly mutagenic, while the group of carcinogens affecting the hematopoietic system and the liver also included a large proportion of non-mutagens. The automatic literature analysis showed that mutagenicity was a frequently reported endpoint in the literature of these carcinogens, however, less common endpoints such as immunosuppression and hormonal receptor-mediated effects were also found in connection with some of the carcinogens, results of potential importance for certain target organs. The combined approach, using QSAR and text-mining techniques, could be useful for identifying more detailed information on biological mechanisms and the relation with chemical structures. The method can be particularly useful in increasing the understanding of structure and activity relationships for non-mutagens. PMID:27625608

  7. Docking and 3-D QSAR studies on the binding of tetrahydropyrimid-2-one HIV-1 protease inhibitors

    NASA Astrophysics Data System (ADS)

    Rao, Shashidhar N.; Balaji, Govardhan A.; Balaji, Vitukudi N.

    2013-06-01

    We present molecular docking and 3-D QSAR studies on a series of tetrahydropyrimid-2-one HIV-1 protease inhibitors whose binding affinities to the enzyme span nearly 6 orders of magnitude. The docking investigations have been carried out with Surflex (GEOM, GEOMX) and Glide (SP and XP) methodologies available through Tripos and Schrodinger suite of tools in the context of Sybyl-X and Maestro interfaces, respectively. The alignments for 3-D QSAR studies were obtained by using the automated Surflex-SIM methodology in Sybyl-X and the analyses were performed using the CoMFA and CoMSIA methods. Additionally, the top-ranked poses obtained from various docking protocols were also employed to generate CoMFA and CoMSIA models to evaluate the qualitative consistency of the docked models with experimental data. Our studies demonstrate that while there are a number of common features in the docked models obtained from Surflex-dock and Glide methodologies, the former sets of models are generally better correlated with deduced experimental binding modes based on the X-ray structures of known HIV-1 protease complexes with cyclic ureas. The urea moiety common to all the ligands are much more tightly aligned in Surflex docked structures than in the models obtained from Glide SP and XP dockings. The 3-D QSAR models are qualitatively and quantitatively similar to those previously reported, suggesting the utility of automatically generated alignments from Surflex-SIM methodology.

  8. A data-based exploration of the adverse outcome pathway for skin sensitization points to the necessary requirements for its prediction with alternative methods.

    PubMed

    Benigni, Romualdo; Bossa, Cecilia; Tcheremenskaia, Olga

    2016-07-01

    This paper presents new data-based analyses on the ability of alternative methods to predict the skin sensitization potential of chemicals. It appears that skin sensitization, as shown in humans and rodents, can be predicted with good accuracy both with in vitro assays and QSAR approaches. The accuracy is about the same: 85-90%. Given that every biological measure has inherent uncertainty, this performance is quite remarkable. Overall, there is a good correlation between human data and experimental in vivo systems, except for sensitizers of intermediate potency. This uncertainty/variability is probably the reason why alternative methods are quite efficient in predicting both strong and non-sensitizers, but not the intermediate potency sensitizers. A detailed analysis of the predictivity of the individual approaches shows that the biological in vitro assays have limited added value in respect to the in chemico/QSAR ones, and suggests that the primary interaction with proteins is the rate-limiting step of the entire process. This confirms evidence from other fields (e.g., carcinogenicity, QSAR) indicating that successful predictive models are based on the parameterization of a few mechanistic features/events, whereas the consideration of all events supposedly involved in a toxicity pathway contributes to increase the uncertainty of the predictions. PMID:27090483

  9. Databases: Beyond the Basics.

    ERIC Educational Resources Information Center

    Whittaker, Robert

    This presented paper offers an elementary description of database characteristics and then provides a survey of databases that may be useful to the teacher and researcher in Slavic and East European languages and literatures. The survey focuses on commercial databases that are available, usable, and needed. Individual databases discussed include:…

  10. Reflective Database Access Control

    ERIC Educational Resources Information Center

    Olson, Lars E.

    2009-01-01

    "Reflective Database Access Control" (RDBAC) is a model in which a database privilege is expressed as a database query itself, rather than as a static privilege contained in an access control list. RDBAC aids the management of database access controls by improving the expressiveness of policies. However, such policies introduce new interactions…

  11. The Norwegian Danish Basin: A key to understanding the Cenozoic in the eastern North Sea

    NASA Astrophysics Data System (ADS)

    Rasmussen, Thomas L.; Clausen, Ole R.; Andresen, Katrine J.; Goledowski, Bartosz

    2015-04-01

    The Danish part of Norwegian-Danish Basin, which constitutes the eastern part of the North Sea Basin, has been the key area for sequence stratigraphic subdivision and analysis of the Cenozoic succession since the mid 1990's. Widespread 3D seismic data, in the central parts of the North Sea Basin, as well as more scattered 3D seismic data in the Danish part of the Norwegian-Danish Basin, have given a more detailed understanding of the sequences and indicate that climate is tenable for the origin of Cenozoic sequence boundaries. The previous sequence stratigraphic interpretations have been an integrated part of an ongoing debate concerning vertical movements of the Fennoscandian shield versus the impact of climate and erosion. A newly accessed coherent regional 2D and reprocessed 3D seismic data set, in the Norwegian part of the Norwegian-Danish Basin, constitute the database for a new sequence stratigraphic analysis of the entire area. The objective of the new study is to test previous subdivisions and introduce a coherent 3D sequence stratigraphic analysis and depositional model for the entire Norwegian-Danish Basin. This analysis is necessary to get out of the stalemate with the uplift discussion. The study shows that the original subdivision by Michelsen et al. (1995, 1998) stands. However, revision of few a sequence boundaries may have to be adjusted due to new biostratigraphic information published. Furthermore, high-angle clinoforms and geomorphological transport complexes observed in the Danish North Sea Basin can be traced into the Norwegian sector. This together with the recognition of several other high-angle clinoform complexes, and their associated seismic facies distribution maps and thickness-maps, enhances the level of detail and constrains the previous published paleogeographic reconstructions of the Cenozoic. The geometry of the Cenozoic infill, in the Norwegian part of the Norwegian-Danish Basin, is here interpreted to be controlled by relative sea

  12. Annoying Danish Relatives: Comprehension and Production of Relative Clauses by Danish Children with and without SLI

    ERIC Educational Resources Information Center

    Jensen De Lopez, Kristine; Olsen, Lone Sundahl; Chondrogianni, Vasiliki

    2014-01-01

    This study examines the comprehension and production of subject and object relative clauses (SRCs, ORCs) by children with Specific Language Impairment (SLI) and their typically developing (TD) peers. The purpose is to investigate whether relative clauses are problematic for Danish children with SLI and to compare errors with those produced by TD…

  13. Human Mitochondrial Protein Database

    National Institute of Standards and Technology Data Gateway

    SRD 131 Human Mitochondrial Protein Database (Web, free access)   The Human Mitochondrial Protein Database (HMPDb) provides comprehensive data on mitochondrial and human nuclear encoded proteins involved in mitochondrial biogenesis and function. This database consolidates information from SwissProt, LocusLink, Protein Data Bank (PDB), GenBank, Genome Database (GDB), Online Mendelian Inheritance in Man (OMIM), Human Mitochondrial Genome Database (mtDB), MITOMAP, Neuromuscular Disease Center and Human 2-D PAGE Databases. This database is intended as a tool not only to aid in studying the mitochondrion but in studying the associated diseases.

  14. Multiple receptor conformation docking, dock pose clustering and 3D QSAR studies on human poly(ADP-ribose) polymerase-1 (PARP-1) inhibitors.

    PubMed

    Fatima, Sabiha; Jatavath, Mohan Babu; Bathini, Raju; Sivan, Sree Kanth; Manga, Vijjulatha

    2014-10-01

    Poly(ADP-ribose) polymerase-1 (PARP-1) functions as a DNA damage sensor and signaling molecule. It plays a vital role in the repair of DNA strand breaks induced by radiation and chemotherapeutic drugs; inhibitors of this enzyme have the potential to improve cancer chemotherapy or radiotherapy. Three-dimensional quantitative structure activity relationship (3D QSAR) models were developed using comparative molecular field analysis, comparative molecular similarity indices analysis and docking studies. A set of 88 molecules were docked into the active site of six X-ray crystal structures of poly(ADP-ribose)polymerase-1 (PARP-1), by a procedure called multiple receptor conformation docking (MRCD), in order to improve the 3D QSAR models through the analysis of binding conformations. The docked poses were clustered to obtain the best receptor binding conformation. These dock poses from clustering were used for 3D QSAR analysis. Based on MRCD and QSAR information, some key features have been identified that explain the observed variance in the activity. Two receptor-based QSAR models were generated; these models showed good internal and external statistical reliability that is evident from the [Formula: see text], [Formula: see text] and [Formula: see text]. The identified key features enabled us to design new PARP-1 inhibitors. PMID:25046176

  15. New QSAR prediction models derived from GPCR CB2-antagonistic triaryl bis-sulfone analogues by a combined molecular morphological and pharmacophoric approach.

    PubMed

    Chen, J-Z; Myint, K-Z; Xie, X-Q

    2011-01-01

    In order to build quantitative structure-activity relationship (QSAR) models for virtual screening of novel cannabinoid CB2 ligands and hit ranking selections, a new QSAR algorithm has been developed for the cannabinoid ligands, triaryl bis-sulfones, using a combined molecular morphological and pharmacophoric search approach. Both pharmacophore features and shape complementarity were considered using a number of molecular descriptors, including Surflex-Sim similarity and Unity Query fit, in addition to other molecular properties such as molecular weight, ClogP, molecular volume, molecular area, molecular polar volume, molecular polar surface area and dipole moment. Subsequently, partial least squares regression analyses were carried out to derive QSAR models linking bioactivity and the descriptors mentioned, using a training set of 25 triaryl bis-sulfones. Good prediction capability was confirmed for the best QSAR model by evaluation against a test set of a further 20 triaryl bis-sulfones. The pharmacophore and molecular shape-based QSAR scoring function now established can be used to predict the biological properties of virtual hits or untested compounds obtained from ligand-based virtual screenings. PMID:21714749

  16. Parenting among Wealthy Danish Families: A Concerted Civilising Process

    ERIC Educational Resources Information Center

    Bach, Dil

    2014-01-01

    This article explores the parenting practices of wealthy Danish families and offers insight into the workings of dominant parenting norms within contemporary Danish society. Based on ethnographic fieldwork conducted among 15 families living north of Copenhagen, Denmark, this article identifies the parenting strategies of people with ample…

  17. Statistical Learning in Emerging Lexicons: The Case of Danish

    ERIC Educational Resources Information Center

    Stokes, Stephanie F.; Bleses, Dorthe; Basboll, Hans; Lambertsen, Claus

    2012-01-01

    Purpose: This research explored the impact of neighborhood density (ND), word frequency (WF), and word length (WL) on the vocabulary size of Danish-speaking children. Given the particular phonological properties of Danish, the impact was expected to differ from that reported in studies on English and French. Method: The monosyllabic words in the…

  18. Educational Ambassadors in the Danish Trade Union Movement

    ERIC Educational Resources Information Center

    Keil, Michael

    2008-01-01

    The concept of Educational Ambassadors is embedded within the so-called "Danish model" of industrial relations. The Danish industrial relations system is characterised by strong collective organisations with national coverage, which conclude the collective agreements for various industries or sectors and which are mostly grouped under central…

  19. Screening for celiac disease in Danish adults

    PubMed Central

    Horwitz, Anna; Skaaby, Tea; Kårhus, Line Lund; Schwarz, Peter; Jørgensen, Torben; Rumessen, Jüri J.; Linneberg, Allan

    2015-01-01

    Abstract Objective. The prevalence of celiac disease (CD) as recorded in the Danish National Patient Registry is ∼50/100,000 persons. This is much lower than the reported prevalence of CD in other Nordic countries and underdiagnosis is suspected. Our aim was to estimate the prevalence of CD in a population-based study of Danish adults. Methods. A total of 2297 adults aged 24–76 years living in the southwestern part of Copenhagen were screened for CD by immunoglobulin (Ig)A and IgG antibodies to transglutaminases and deamidated gliadin. IgA/IgG-positive participants were invited to a clinical evaluation, including biopsies, by a gastroenterologist. Results. Of the invited 56 participants, 40 underwent a full clinical evaluation and 8 persons were diagnosed with CD; 2 of the 16 persons, who did not complete the clinical evaluation, were considered by experts to have probable CD. None of the above 56 participants had a known history of CD or a recorded diagnosis of CD in National Patient Registry. By combining cases of biopsy-proven CD (n = 8), probable CD (n = 2), and registry-recorded CD (n = 1), the prevalence of CD was estimated to be 479/100,000 (11/2297) persons (95% CI: 197–761). Conclusion. In this general adult population, the prevalence of CD as estimated by screening and clinical evaluation was 10 times higher than the registry-based prevalence of CD. Of 11 participants diagnosed with CD in our screening study, 10 were unaware of the diagnosis prior to the study. Thus, our study suggests that CD is markedly underdiagnosed in Danish adults. PMID:25687734

  20. Interpersonal violence: patterns in a Danish community.

    PubMed Central

    Hedeboe, J; Charles, A V; Nielsen, J; Grymer, F; Møller, B N; Møller-Madson, B; Jensen, S E

    1985-01-01

    We studied all cases of assault with violence (1,639) in a Danish population of 275,000 over a one-year period. Most victims were young men. The incidence rose during evenings, nights and weekends, and assaults were often seen in or around bars and restaurants. Women accounted for 64 per cent of all victims of assault in the home. Influence of alcohol was identified in 43 per cent of all cases. The fist was the most frequent agent of assault; use of firearms was a very rare act of violence but was associated with death in three out of five cases. There were 10 deaths in all. PMID:4003631

  1. Species Sensitivity Distribution estimation from uncertain (QSAR-based) effects data.

    PubMed

    Aldenberg, Tom; Rorije, Emiel

    2013-03-01

    In environmental risk assessment, Species Sensitivity Distributions (SSDs) can be applied to estimate a PNEC (Predicted No-Effect Concentration) for a chemical substance, when sufficient data on species toxicities are available. The European Chemicals Agency (ECHA) recommendation is 10 biological species. The question addressed in this paper, is whether QSAR-predicted toxicities can be included in SSD based PNEC estimates, and whether any modifications need to be made to account for the uncertainty in the QSAR-model estimates. This problem is addressed from a probabilistic modelling point of view. From classical analysis of variation (ANOVA), we review how the error-in-data SSD problem is similar to separation into between-group and within-group variance. ECHA guidance suggests averaging similar endpoint data for a species, which is consistent with group means, as in ANOVA. This exercise reveals that error-in data reduces the estimation of the between species variation, i.e. the SSD variance, rather than enlarging it. A Bayesian analysis permits the assessment of the uncertainty of the SSD mean and variance parameters for given values of mean species toxicity error. This requires a hierarchical model. Prototyping this model for an artificial five-species data set seems to suggest that the influence of data error is relatively minor. Moreover, when neglecting this data error, a slightly conservative estimate of the SSD results. Hence, we suggest including (model-predicted) data as model point estimates and handling the SSD as usual. The Bayesian simulation of the error-in-data SSD leads to predictive distributions, being an average of posterior spaghetti plot densities or cumulative distributions. We derive new predictive extrapolation constants with several improvements over previous median uncertainty log10HC5 estimates, in that they are easily calculable from spreadsheet Student-t functions and based on a more realistic uniform prior for the SSD standard

  2. QSAR modeling, synthesis and bioassay of diverse leukemia RPMI-8226 cell line active agents.

    PubMed

    Katritzky, Alan R; Girgis, Adel S; Slavov, Svetoslav; Tala, Srinivasa R; Stoyanova-Slavova, Iva

    2010-11-01

    A rigorous QSAR modeling procedure employing CODESSA PRO descriptors has been utilized for the prediction of more efficient anti-leukemia agents. Experimental data concerning the effect on leukemia RPMI-8226 cell line tumor growth of 34 compounds (treated at a dose of 10 μM) was related to their chemical structures by a 4-descriptor QSAR model. Four bis(oxy)bis-urea and bis(sulfanediyl)bis-urea derivatives (4a, 4b, 8, 11a) predicted as active by this model, together with 11b predicted to be of low activity, were synthesized and screened for anti-tumor activity utilizing 55 different tumor cell lines. Compounds 8 and 11a showed anti-tumor properties against most of the adopted cell lines with growth inhibition exceeding 50%. The highly promising preliminary anti-tumor properties of compounds 8 and 11a, were screened at serial dilutions (10(-4)-10(-8) μM) for determination of their GI(50) and TGI against the screened human tumor cell lines. Compound 11a (GI(50) = 1.55, TGI = 8.68 μM) is more effective than compound 8 (GI(50)=58.30, TGI = > 100 μM) against the target leukemia RPMI-8226 cell line. Compound 11a also exhibits highly pronounced anti-tumor properties against NCI-H226, NCI-H23 (non-small cell lung cancer), COLO 205 (colon cancer), SNB-75 (CNS cancer), OVCAR-3, SK-OV-3 (ovarian cancer), A498 (renal cancer) MDA-MB-231/ATCC and MDA-MB-468 (breast cancer) cell lines (GI(50) = 1.95, 1.61, 1.38, 1.56, 1.30, 1.98, 1.18, 1.85, 1.08, TGI = 8.35, 6.01, 2.67, 8.59, 4.01, 7.01, 5.62, 6.38, 5.63 μM, respectively). Thus 11a could be a suitable lead towards the design of broad spectrum anti-tumor active agents targeting various human tumor cell lines. PMID:20843586

  3. Developing and Evaluating a Multimodal Course Format: Danish for Knowledge Workers--Labour Market-Related Danish

    ERIC Educational Resources Information Center

    Frederiksen, Karen-Margrete; Laursen, Katja Årosin

    2015-01-01

    This paper presents our reflections on developing the Computer-Assisted Language Learning (CALL) course "Danish for knowledge workers--labour market-related Danish." As defined by Laursen and Frederiksen (2015), knowledge workers are "highly educated people who typically work at universities, at other institutions of higher…

  4. Risk factors for Campylobacter colonization in Danish broiler flocks, 2010 to 2011.

    PubMed

    Sandberg, M; Sørensen, L L; Steenberg, B; Chowdhury, S; Ersbøll, A K; Alban, L

    2015-03-01

    The objectives of the two studies presented were to estimate the prevalence of Campylobacter-positive farms and flocks and to acquire updated knowledge about risk factors for the introduction of Campylobacter in Danish broiler flocks. In the first study, from September 2010 to September 2011, there were 25 Danish broiler farms visited, and a questionnaire was filled in by a veterinarian/consultant. In the second study, a similar questionnaire was distributed electronically to all Danish broiler farmers (n=164) that were on record with an email address in the Quality Assurance System in the Danish Broiler Production (KIK) database. House- and flock-specific data collected in the surveys were supplemented with information obtained from the KIK database. Data obtained from the two studies were analyzed separately by logistic regression analysis. In both models, the dependent variable was "Campylobacter flock status (positive/negative)," which was based on real-time PCR testing of fecal material from the floor of each broiler house that had been collected preslaughter using a pair of tube gauze "socks." This material was pooled into one sample. Of the 25 farms visited, 17 had delivered Campylobacter-positive flocks during the study period, and eight farms had no Campylobacter-positive flocks. Moreover, the flock prevalence of Campylobacter was 17% (n=418). Data obtained from the electronically distributed survey revealed that 63% (n=71) of the farms were Campylobacter-positive. Further, the flock prevalence of Campylobacter was 14% (n=1,286). The multivariable models from the two sets of data identified the following statistically significant risk factors: summer vs. winter; if the previous flock in the house was positive for Campylobacter vs. if the previous flock in the house was negative; and litter delivered into the house close to the time of arrival of new chickens vs. storing litter on the farm. Furthermore, the data showed that a vertically based ventilation

  5. Existing data sources for clinical epidemiology: The clinical laboratory information system (LABKA) research database at Aarhus University, Denmark

    PubMed Central

    Grann, Anne Fia; Erichsen, Rune; Nielsen, Anders Gunnar; Frøslev, Trine; Thomsen, Reimar W

    2011-01-01

    This paper provides an introduction to the clinical laboratory information system (LABKA) research database in Northern and Central Denmark. The database contains millions of stored laboratory test results for patients living in the two Danish regions, encompassing 1.8 million residents, or one-third of the country’s population. More than 1700 different types of blood test analyses are available. Therefore, the LABKA research database represents an incredible source for studies involving blood test analyses. By record linkage of different Danish registries with the LABKA research database, it is possible to examine a large number of biomarkers as predictors of disease risk and prognosis and as markers of disease severity, and to evaluate medical treatments regarding effectiveness and possible side effects. Large epidemiological studies using routinely stored blood test results for individual patients can be performed because it is possible to link the laboratory data to high-quality individual clinical patient data in Denmark. PMID:21487452

  6. Evaluation of OASIS QSAR Models Using ToxCast™ in Vitro Estrogen and Androgen Receptor Binding Data and Application in an Integrated Endocrine Screening Approach

    PubMed Central

    Bhhatarai, Barun; Wilson, Daniel M.; Price, Paul S.; Marty, Sue; Parks, Amanda K.; Carney, Edward

    2016-01-01

    Background: Integrative testing strategies (ITSs) for potential endocrine activity can use tiered in silico and in vitro models. Each component of an ITS should be thoroughly assessed. Objectives: We used the data from three in vitro ToxCast™ binding assays to assess OASIS, a quantitative structure-activity relationship (QSAR) platform covering both estrogen receptor (ER) and androgen receptor (AR) binding. For stronger binders (described here as AC50 < 1 μM), we also examined the relationship of QSAR predictions of ER or AR binding to the results from 18 ER and 10 AR transactivation assays, 72 ER-binding reference compounds, and the in vivo uterotrophic assay. Methods: NovaScreen binding assay data for ER (human, bovine, and mouse) and AR (human, chimpanzee, and rat) were used to assess the sensitivity, specificity, concordance, and applicability domain of two OASIS QSAR models. The binding strength relative to the QSAR-predicted binding strength was examined for the ER data. The relationship of QSAR predictions of binding to transactivation- and pathway-based assays, as well as to in vivo uterotrophic responses, was examined. Results: The QSAR models had both high sensitivity (> 75%) and specificity (> 86%) for ER as well as both high sensitivity (92–100%) and specificity (70–81%) for AR. For compounds within the domains of the ER and AR QSAR models that bound with AC50 < 1 μM, the QSAR models accurately predicted the binding for the parent compounds. The parent compounds were active in all transactivation assays where metabolism was incorporated and, except for those compounds known to require metabolism to manifest activity, all assay platforms where metabolism was not incorporated. Compounds in-domain and predicted to bind by the ER QSAR model that were positive in ToxCast™ ER binding at AC50 < 1 μM were active in the uterotrophic assay. Conclusions: We used the extensive ToxCast™ HTS binding data set to show that OASIS ER and AR QSAR models had

  7. A QSAR study of radical scavenging antioxidant activity of a series of flavonoids using DFT based quantum chemical descriptors--the importance of group frontier electron density.

    PubMed

    Sarkar, Ananda; Middya, Tapas Ranjan; Jana, Atish Dipnakar

    2012-06-01

    In a pursuit of electronic level understanding of the antioxidant activity of a series of flavonoids, quantitative structure-activity relationship (QSAR) studies have been carried out using density functional theory (DFT) based quantum chemical descriptors. The best QSAR model have been selected for which the computed square correlation coefficient r(2) = 0.937 and cross-validated squared correlation coefficient q(2) =0.916. The QSAR model indicates that hardness (η), group electrophilic frontier electron density (F(E)(A)) and group philicity (ω(B)(+)) of individual molecules are responsible for in vitro biological activity. To the best our knowledge, the group electrophilic frontier electron density (F(E)(A)) has been used for the first time to explain the radical scavenging activity (RSA) of flavonoids. The excellent correlation between the RSA and the above mentioned DFT based descriptors lead us to predict new antioxidants having very good antioxidant activity. PMID:22080306

  8. Danish Ophthalmology - from start to 1865.

    PubMed

    Norn, Mogens

    2016-03-01

    This short paper mentioned the medical treatment using the 'holy' springs, the first 'eye doctor' in Denmark, the first picture of spectacles which was found in Viborg Cathedral of the high priest before he performs circumcisio praeputii on Jesus Christ, further cataract reclination in Denmark from around year zero and cataract extraction in 1667 in Denmark on a goose by Francisco Borri and on humans by the Danish Georg Heuermann in 1755. Epidemic military eye diseases in 1807, 1856 and 1865 are also described in this study. From 1856, a new ophthalmological period started in Denmark with the first eye hospital (lazaret only for eye diseases), and in 1864, patients with eye diseases were transported from the few beds in the surgical departments in the municipal hospital to the first civil eye department in Denmark, the eye hospital Sct. Annae in Copenhagen. The new scientific period started with Jacob Christian Bentz (ophthalmia granulosa, joint editor of the Danish Medical Journal) and Heinrich Lehmann. PMID:26899921

  9. Danish experiences on EIA of livestock projects

    SciTech Connect

    Christensen, Per . E-mail: pc@plan.aau.dk

    2006-07-15

    Since its introduction into Danish planning in 1989, Environmental Impact Assessment (EIA) has been widely discussed. At the centre of the debate has been the question of whether EIA actually offered anything new and there has been a great deal of scepticism about the efficacy of the instrument, especially when it comes to livestock projects. In an evaluation of the Danish EIA experience, we have looked more closely at how the EIA instruments function regarding livestock projects. This article addresses both the EIA process as well as the EIA screening. It is demonstrated that the EIA screening in its own right is a kind of regulatory instrument. Examining the assessments made during screening more closely, we conclude that there is still some way to go in order to make the assessment broader and more holistic in accordance with the ambitions set out in the EIA directive to contribute to a more sustainable development. Although the provisions laid down are the same the praxis related to the field has developed at a considerable speed. In order to understand this development we have closely examined how the decisions made by the Nature Protection Board of Appeal (NPBA) have been changed and conclude that these changes definitely address some of the shortcomings found in the evaluation.

  10. The physician's civil liability under Danish law.

    PubMed

    Fenger, N; Broberg, M

    1991-01-01

    The physician's liability in Danish law is based on negligence, which is assessed by the courts largely on the basis of expert opinions. Such opinions are provided primarily by the Medico-Legal Council rather than by experts selected by the parties. The evaluation of negligence is based on a "reasonable man" standard and the performance expected of a competent colleague; a hospital will be responsible for the negligence of its employees. The burden of proof generally lies with the plaintiff; negligence will not be presumed and the assessment of the evidence of negligence will be adapted to the individual situation, e.g. factors such as the degree of specialization involved, the time which the physician had at his disposal to make his decision and the resources available to him will be taken into consideration. The courts have shown themselves willing to allow for the fact that doctors differ, i.e. recognizing that there must be scope for reasonable discretion. Because the culpa principle is central, the standard applied to medical knowledge will be that which pertained at the time of the treatment. Where a non-specialist is confronted with a problem which may go beyond the knowledge of his limits and experience, he is under an obligation to refer the patient. The principle of informed consent to treatment is accepted in Danish law, but such consent will readily be considered to have been given tacitly. PMID:23511859

  11. Thyroid function in Danish greenhouse workers

    PubMed Central

    Toft, Gunnar; Flyvbjerg, Allan; Bonde, Jens Peter

    2006-01-01

    Background From animal studies it is known that currently used pesticides can disturb thyroid function. Methods In the present study we investigated the thyroid function in 122 Danish greenhouse workers, to evaluate if greenhouse workers classified as highly exposed to pesticides experiences altered thyroid levels compared to greenhouse workers with lower exposure. Serum samples from the greenhouse workers were sampled both in the spring and the fall to evaluate if differences in pesticide use between seasons resulted in altered thyroid hormone levels. Results We found a moderate reduction of free thyroxine (FT4) (10–16%) among the persons working in greenhouses with a high spraying load both in samples collected in the spring and the fall, but none of the other measured thyroid hormones differed significantly between exposure groups in the cross-sectional comparisons. However, in longitudinal analysis of the individual thyroid hormone level between the spring and the fall, more pronounced differences where found with on average 32% higher thyroid stimulating hormone (TSH) level in the spring compared to the fall and at the same time a 5–9% lower total triiodthyroxin (TT3), free triiodthyroxine (FT3) and FT4. The difference between seasons was not consistently more pronounced in the group classified as high exposure compared to the low exposure groups. Conclusion The present study indicates that pesticide exposure among Danish greenhouse workers results in only minor disturbances of thyroid hormone levels. PMID:17147831

  12. Hepatoprotection of sesquiterpenoids: a quantitative structure-activity relationship (QSAR) approach.

    PubMed

    Vinholes, Juliana; Rudnitskaya, Alisa; Gonçalves, Pedro; Martel, Fátima; Coimbra, Manuel A; Rocha, Sílvia M

    2014-03-01

    The relative hepatoprotection effect of fifteen sesquiterpenoids, commonly found in plants and plant-derived foods and beverages was assessed. Endogenous lipid peroxidation (assay A) and induced lipid peroxidation (assay B) were evaluated in liver homogenates from Wistar rats by the thiobarbituric acid reactive species test. Sesquiterpenoids with different chemical structures were tested: trans,trans-farnesol, cis-nerolidol, (-)-α-bisabolol, trans-β-farnesene, germacrene D, α-humulene, β-caryophyllene, isocaryophyllene, (+)-valencene, guaiazulene, (-)-α-cedrene, (+)-aromadendrene, (-)-α-neoclovene, (-)-α-copaene, and (+)-cyclosativene. Ascorbic acid was used as a positive antioxidant control. With the exception of α-humulene, all the sesquiterpenoids under study (1mM) were effective in reducing the malonaldehyde levels in both endogenous and induced lipid peroxidation up to 35% and 70%, respectively. The 3D-QSAR models developed, relating the hepatoprotection activity with molecular properties, showed good fit (Radj(2) 0.819 and 0.972 for the assays A and B, respectively) with good prediction power (Q(2)>0.950 and SDEP<2%, for both models A and B). A network of effects associated with structural and chemical features of sesquiterpenoids such as shape, branching, symmetry, and presence of electronegative fragments, can modulate the hepatoprotective activity observed for these compounds. PMID:24176316

  13. QSARs for photo-induced toxicity of polycyclic aromatic hydrocarbons (PAHs)

    SciTech Connect

    Mekenyan, O.; Call, D.; Ankley, G.; Veith, G.

    1994-12-31

    Photo-induced toxicity of polycyclic aromatic hydrocarbons (PAHs) was found to be a result of competing internal and external factors which interact to produce a complex, multilinear relationship between toxicity and chemical structure. The relationship between molecular electronic structure and photo-dynamic effects was studied in both ground and excited states. A measure of the energy required for an electron to be elevated from the highest occupied molecular orbital (HOMO) to the lowest unoccupied molecular orbital (LUMO), or HOMO-LUMO gap, provided a useful ground state index to explain the persistence, light absorption, and eventual photo-induced toxicity of PAHs to Daphnia magna. The derived QSARs clearly distinguished photo-induced toxicity differences between pairs of structurally similar PAHs, such as phenanthrene and anthracene, benzo[a]anthracene and tetracene, etc. Those PAHs exhibiting photo-induced toxicity were consistently within a specific HOMO-LUMO gap range. The relationship between the excited state electronic parameters and toxicity was also studied. Significant correlations were found with the measured energies of singlet and triplet states from spectroscopic data. An investigation of the effect of substituent additions on photo-induced acute toxicity of parent PAHs revealed that alkyl and hydroxy moieties did not significantly reduce the HOMO-LUMO gap of the parent PAHs. Nitro, alkene and chloro substituents cause gap reductions, whereby certain derivatives of parent chemicals that were close to the ``toxic region`` of the electronic gap could become phototoxic with such additions.

  14. Synthesis, characterization, antifungal evaluation and 3D-QSAR study of phenylhydrazine substituted tetronic acid derivatives.

    PubMed

    Hu, Ying; Wang, Junjun; Lu, Aimin; Yang, Chunlong

    2014-08-15

    A series of 3-(1-(2-(substituted phenyl)hydrazinyl)alkylidene)furan-2,4(3H,5H)-diones were designed and prepared using two synthetic routes. Their structures were confirmed by FT-IR, (1)H NMR, (13)C NMR, MS, elemental analysis and single-crystal X-ray diffraction. Their bioactivity was evaluated against Botrytis cinerea in vitro. Most target compounds exhibited remarkable antifungal activity. Two compounds 7f and 7h were highly effective and their EC50 values were 0.241 μg/mL and 0.167 μg/mL, respectively, close to that of the control drug procymidone. 3D-QSAR studies of CoMFA and CoMSIA were carried out. Models with good predictive ability were generated with the cross validated q(2) values for CoMFA and CoMSIA being 0.565 and 0.823. Conventional r(2) values were 0.983 and 0.945, respectively. The results provided a practical tool for guiding the design and synthesis of novel and more potent tetronic acid derivatives containing substituted phenylhydrazine moiety. PMID:25042337

  15. Mechanistic QSAR models for interpreting degradation rates of sulfonamides in UV-photocatalysis systems.

    PubMed

    Huang, Xiangfeng; Feng, Yi; Hu, Cui; Xiao, Xiaoyu; Yu, Daliang; Zou, Xiaoming

    2015-11-01

    Photocatalysis is one of the most effective methods for treating antibiotic wastewater. Thus, it is of great significance to determine the relationship between degradation rates and structural characteristics of antibiotics in photocatalysis processes. In the present study, the photocatalytic degradation characteristics of 10 sulfonamides (SAs) were studied using two photocatalytic systems composed of nanophase titanium dioxide (nTiO2) plus ultraviolet (UV) and nTiO2/activated carbon fiber (ACF) plus UV. The results indicated that the largest apparent SA degradation rate constant (Kapp) is approximately 5 times as large as that of the smallest one. Based on the degradation mechanism and the partial least squares regression (PLS) method, optimum Quantitative Structure Activity Relationship (QSAR) models were developed for the two systems. Mechanistic models indicated that the degradation rule of SAs in the TiO2 systems strongly relates to their highest occupied molecular orbital (Ehomo), the maximum values of nucleophilic attack (f(+)x), and the minimum values of the most negative partial charge on a main-chain atom (q(C)min), whereas the maximum values of OH radical attack (f(0)x) and the apparent adsorption rate constant values (kad) are key factors affecting the degradation rule of SAs in the TiO2/ACF system. PMID:26070083

  16. Design, synthesis, α-glucosidase inhibitory activity, molecular docking and QSAR studies of benzimidazole derivatives

    NASA Astrophysics Data System (ADS)

    Dinparast, Leila; Valizadeh, Hassan; Bahadori, Mir Babak; Soltani, Somaieh; Asghari, Behvar; Rashidi, Mohammad-Reza

    2016-06-01

    In this study the green, one-pot, solvent-free and selective synthesis of benzimidazole derivatives is reported. The reactions were catalyzed by ZnO/MgO containing ZnO nanoparticles as a highly effective, non-toxic and environmentally friendly catalyst. The structure of synthesized benzimidazoles was characterized using spectroscopic technics (FT-IR, 1HNMR, 13CNMR). Synthesized compounds were evaluated for their α-glucosidase inhibitory potential. Compounds 3c, 3e, 3l and 4n were potent inhibitors with IC50 values ranging from 60.7 to 168.4 μM. In silico studies were performed to explore the binding modes and interactions between enzyme and synthesized benzimidazoles. Developed linear QSAR model based on density and molecular weight could predict bioactivity of newly synthesized compounds well. Molecular docking studies revealed the availability of some hydrophobic interactions. In addition, the bioactivity of most potent compounds had good correlation with estimated free energy of binding (ΔGbinding) which was calculated according to docked best conformations.

  17. Comparison of Cramer classification between Toxtree, the OECD QSAR Toolbox and expert judgment.

    PubMed

    Bhatia, Sneha; Schultz, Terry; Roberts, David; Shen, Jie; Kromidas, Lambros; Marie Api, Anne

    2015-02-01

    The Threshold of Toxicological Concern (TTC) is a pragmatic approach in risk assessment. In the absence of data, it sets up levels of human exposure that are considered to have no appreciable risk to human health. The Cramer decision tree is used extensively to determine these exposure thresholds by categorizing non-carcinogenic chemicals into three different structural classes. Therefore, assigning an accurate Cramer class to a material is a crucial step to preserve the integrity of the risk assessment. In this study the Cramer class of over 1000 fragrance materials across diverse chemical classes were determined by using Toxtree (TT), the OECD QSAR Toolbox (TB), and expert judgment. Disconcordance was observed between TT and the TB. A total of 165 materials (16%) showed different results from the two programs. The overall concordance for Cramer classification between TT and expert judgment is 83%, while the concordance between the TB and expert judgment is 77%. Amines, lactones and heterocycles have the lowest percent agreement with expert judgment for TT and the TB. For amines, the expert judgment agreement is 45% for TT and 55% for the TB. For heterocycles, the expert judgment agreement is 55% for TT and the TB. For lactones, the expert judgment agreement is 56% for TT and 50% for the TB. Additional analyses were conducted to determine the concordance within various chemical classes. Critical checkpoints in the decision tree are identified. Strategies and guidance on determining the Cramer class for various chemical classes are discussed. PMID:25460032

  18. 3D-QSAR studies on chromone derivatives as HIV-1 protease inhibitors

    NASA Astrophysics Data System (ADS)

    Ungwitayatorn, Jiraporn; Samee, Weerasak; Pimthon, Jutarat

    2004-02-01

    The three-dimensional quantitative structure-activity relationship (3D-QSAR) approach using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) was applied to a series of 30 chromone derivatives, a new class of HIV-1 protease inhibitors. The best predictive CoMFA model gives cross-validated r2 ( q2)=0.763, non-cross-validated r2=0.967, standard error of estimate ( S)=5.092, F=90.701. The best CoMSIA model has q2=0.707, non-cross-validated r2=0.943, S=7.018, F=51.734, included steric, electrostatic, hydrophobic, and hydrogen bond donor fields. The predictive ability of these models was validated by a set of five compounds that were not included in the training set. The calculated (predicted) and experimental inhibitory activities were well correlated. The contour maps obtained from CoMFA and CoMSIA models were in agreement with the previous docking study for this chromone series.

  19. Insights into the Interactions between Maleimide Derivates and GSK3β Combining Molecular Docking and QSAR

    PubMed Central

    Quesada-Romero, Luisa; Mena-Ulecia, Karel; Tiznado, William; Caballero, Julio

    2014-01-01

    Many protein kinase (PK) inhibitors have been reported in recent years, but only a few have been approved for clinical use. The understanding of the available molecular information using computational tools is an alternative to contribute to this process. With this in mind, we studied the binding modes of 77 maleimide derivates inside the PK glycogen synthase kinase 3 beta (GSK3β) using docking experiments. We found that the orientations that these compounds adopt inside GSK3β binding site prioritize the formation of hydrogen bond (HB) interactions between the maleimide group and the residues at the hinge region (residues Val135 and Asp133), and adopt propeller-like conformations (where the maleimide is the propeller axis and the heterocyclic substituents are two slanted blades). In addition, quantitative structure–activity relationship (QSAR) models using CoMSIA methodology were constructed to explain the trend of the GSK3β inhibitory activities for the studied compounds. We found a model to explain the structure–activity relationship of non-cyclic maleimide (NCM) derivatives (54 compounds). The best CoMSIA model (training set included 44 compounds) included steric, hydrophobic, and HB donor fields and had a good Q2 value of 0.539. It also predicted adequately the most active compounds contained in the test set. Furthermore, the analysis of the plots of the steric CoMSIA field describes the elements involved in the differential potency of the inhibitors that can be considered for the selection of suitable inhibitors. PMID:25010341

  20. Insights into the interactions between maleimide derivates and GSK3β combining molecular docking and QSAR.

    PubMed

    Quesada-Romero, Luisa; Mena-Ulecia, Karel; Tiznado, William; Caballero, Julio

    2014-01-01

    Many protein kinase (PK) inhibitors have been reported in recent years, but only a few have been approved for clinical use. The understanding of the available molecular information using computational tools is an alternative to contribute to this process. With this in mind, we studied the binding modes of 77 maleimide derivates inside the PK glycogen synthase kinase 3 beta (GSK3β) using docking experiments. We found that the orientations that these compounds adopt inside GSK3β binding site prioritize the formation of hydrogen bond (HB) interactions between the maleimide group and the residues at the hinge region (residues Val135 and Asp133), and adopt propeller-like conformations (where the maleimide is the propeller axis and the heterocyclic substituents are two slanted blades). In addition, quantitative structure-activity relationship (QSAR) models using CoMSIA methodology were constructed to explain the trend of the GSK3β inhibitory activities for the studied compounds. We found a model to explain the structure-activity relationship of non-cyclic maleimide (NCM) derivatives (54 compounds). The best CoMSIA model (training set included 44 compounds) included steric, hydrophobic, and HB donor fields and had a good Q(2) value of 0.539. It also predicted adequately the most active compounds contained in the test set. Furthermore, the analysis of the plots of the steric CoMSIA field describes the elements involved in the differential potency of the inhibitors that can be considered for the selection of suitable inhibitors. PMID:25010341

  1. QSAR studies on triazole derivatives as sglt inhibitors via CoMFA and CoMSIA

    NASA Astrophysics Data System (ADS)

    Zhi, Hui; Zheng, Junxia; Chang, Yiqun; Li, Qingguo; Liao, Guochao; Wang, Qi; Sun, Pinghua

    2015-10-01

    Forty-six sodium-dependent glucose cotransporters-2 (SGLT-2) inhibitors with hypoglycemic activity were selected to develop three-dimensional quantitative structure-activity relationship (3D-QSAR) using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models. A training set of 39 compounds were used to build up the models, which were then evaluated by a series of internal and external cross-validation techniques. A test set of 7 compounds was used for the external validation. The CoMFA model predicted a q2 value of 0.792 and an r2 value of 0.985. The best CoMSIA model predicted a q2 value of 0.633 and an r2 value of 0.895 based on a combination of steric, electrostatic, hydrophobic and hydrogen-bond acceptor effects. The predictive correlation coefficients of CoMFA and CoMSIA models were 0.872 and 0.839, respectively. The analysis of the contour maps from each model provided insight into the structural requirements for the development of more active sglt inhibitors, and on the basis of the models 8 new sglt inhibitors were designed and predicted.

  2. Assessment of bromide-based ionic liquid toxicity toward aquatic organisms and QSAR analysis.

    PubMed

    Wang, Chao; Wei, Zhongbo; Wang, Liansheng; Sun, Ping; Wang, Zunyao

    2015-05-01

    The toxicities of 24 bromide-based ionic liquids (Br-ILs) towards Vibrio fischeri (V. fischeri) and Daphnia magna (D. magna) were determined. These Br-ILs are composed of a bromide ion and a generic cation (i.e., pyrrolidinium, piperidinium, pyridinium or imidazolium) with different alkyl side chains. QSAR models with relatively high correlation coefficients, R(2), of 0.954 and 0.895 were developed for V. fischeri and D. magna. The model for V. fischeri indicated that the Br-IL toxicity towards V. fischeri was negatively correlated with the energy of the lowest unoccupied molecular orbitals (ELUMO) which reflects the electron affinities (EAs) and positively correlated with the volumes of Br-IL cations. For the D. magna model, the Br-IL toxicity was positively correlated with the dipole moment (μ) and negatively correlated with the total energy (TE) that is highly correlated with the molecular volume (V). For Br-ILs with the same cation ring, the toxicity increased as the length of the alkyl chains increased. For the same alkyl chain length, the toxicity order for V. fischeri was pyridinium>imidazolium>piperidinium>pyrrolidinium, except for those containing octyl side chains, while the toxicity ranking for D. magna was imidazolium~pyridinium>piperidinium>pyrrolidinium. PMID:25682588

  3. QSAR study of the toxicity of nitrobenzenes to river bacteria and photobacterium phosphoreum

    SciTech Connect

    Yuan, X.; Lu, G.; Lang, P.

    1997-01-01

    Since nitrobenzenes constitute a class of industrial chemicals that are present in Songhua River and probably in many other industrialized countries as well, it is useful to gain insight into their potential hazard to aquatic organisms. For this reason, it was decided to determine data on the toxicity for bacteria in the Songhua River. Furthermore, the toxicity to Ph. phosphoreum was determined in the Microtox assay, in order to further evaluate the usefulness of this assay for hazard assessment. Quantitative structure-activity relationships (QSARs) have been developed for aromatic nitro compound toxicity to aquatic species, but no data on the toxicity of nitrobenzenes to environmental bacteria were used. In this study, the toxicity of various substituted nitrobenzenes to bacteria in Songhua River and to Ph. phosphoreum has been investigated, establishing quantitative structure-activity relationships with n-octanol-water partition coefficient (log P), the energy of the lowest unoccupied molecular orbital (E{sub LUMO}) and the sum of substituent constant ({Sigma}{sigma}-). 12 refs., 2 tabs.

  4. Combined 3D-QSAR modeling and molecular docking study on azacycles CCR5 antagonists

    NASA Astrophysics Data System (ADS)

    Ji, Yongjun; Shu, Mao; Lin, Yong; Wang, Yuanqiang; Wang, Rui; Hu, Yong; Lin, Zhihua

    2013-08-01

    The beta chemokine receptor 5 (CCR5) is an attractive target for pharmaceutical industry in the HIV-1, inflammation and cancer therapeutic areas. In this study, we have developed quantitative structure activity relationship (QSAR) models for a series of 41 azacycles CCR5 antagonists using comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), and Topomer CoMFA methods. The cross-validated coefficient q2 values of 3D-QASR (CoMFA, CoMSIA, and Topomer CoMFA) methods were 0.630, 0.758, and 0.852, respectively, the non-cross-validated R2 values were 0.979, 0.978, and 0.990, respectively. Docking studies were also employed to determine the most probable binding mode. 3D contour maps and docking results suggested that bulky groups and electron-withdrawing groups on the core part would decrease antiviral activity. Furthermore, docking results indicated that H-bonds and π bonds were favorable for antiviral activities. Finally, a set of novel derivatives with predicted activities were designed.

  5. Enhanced QSAR models for drug-triggered inhibition of the main cardiac ion currents.

    PubMed

    Wiśniowska, Barbara; Mendyk, Aleksander; Szlęk, Jakub; Kołaczkowski, Michał; Polak, Sebastian

    2015-09-01

    The currently changing cardiac safety testing paradigm suggests, among other things, a shift towards using in silico models of cellular electrophysiology and assessment of a concomitant block of multiple ion channels. In this study, a set of four enhanced QSAR models have been developed: for the rapid delayed rectifying potassium current (IKr), slow delayed rectifying potassium current (IKs), peak sodium current (INa) and late calcium current (ICaL), predicting ion currents changes for the specific in vitro experiment from the 2D structure of the compounds. The models are a combination of both in vitro study parameters and physico-chemical descriptors, which is a novel approach in drug-ion channels interactions modeling. Their predictive power assessed in the enhanced, more demanding than standard procedure, 10-fold cross validation was reasonably high. Rough comparison with published pure in silico hERG interaction models shows that the quality of the model predictions does not differ from other models available in the public domain, however, it takes its advantage in accounting for inter-experimental settings variability. Developed models are implemented in the Cardiac Safety Simulator, a commercially available platform enabling the in vitro-in vivo extrapolation of the drugs proarrhythmic effect and ECG simulation. A more comprehensive assessment of the effects of the compounds on ion channels allows for making more informed decisions regarding the risk - and thus avoidance - of exclusion of potentially safe and effective drugs. PMID:25559930

  6. In Silico Model for Developmental Toxicity: How to Use QSAR Models and Interpret Their Results.

    PubMed

    Marzo, Marco; Roncaglioni, Alessandra; Kulkarni, Sunil; Barton-Maclaren, Tara S; Benfenati, Emilio

    2016-01-01

    Modeling developmental toxicity has been a challenge for (Q)SAR model developers due to the complexity of the endpoint. Recently, some new in silico methods have been developed introducing the possibility to evaluate the integration of existing methods by taking advantage of various modeling perspectives. It is important that the model user is aware of the underlying basis of the different models in general, as well as the considerations and assumptions relative to the specific predictions that are obtained from these different models for the same chemical. The evaluation on the predictions needs to be done on a case-by-case basis, checking the analogs (possibly using structural, physicochemical, and toxicological information); for this purpose, the assessment of the applicability domain of the models provides further confidence in the model prediction. In this chapter, we present some examples illustrating an approach to combine human-based rules and statistical methods to support the prediction of developmental toxicity; we also discuss assumptions and uncertainties of the methodology. PMID:27311466

  7. Development of Dual Inhibitors against Alzheimer's Disease Using Fragment-Based QSAR and Molecular Docking

    PubMed Central

    Goyal, Manisha; Dhanjal, Jaspreet Kaur; Goyal, Sukriti; Tyagi, Chetna; Hamid, Rabia; Grover, Abhinav

    2014-01-01

    Alzheimer's (AD) is the leading cause of dementia among elderly people. Considering the complex heterogeneous etiology of AD, there is an urgent need to develop multitargeted drugs for its suppression. β-amyloid cleavage enzyme (BACE-1) and acetylcholinesterase (AChE), being important for AD progression, have been considered as promising drug targets. In this study, a robust and highly predictive group-based QSAR (GQSAR) model has been developed based on the descriptors calculated for the fragments of 20 1,4-dihydropyridine (DHP) derivatives. A large combinatorial library of DHP analogues was created, the activity of each compound was predicted, and the top compounds were analyzed using refined molecular docking. A detailed interaction analysis was carried out for the top two compounds (EDC and FDC) which showed significant binding affinity for BACE-1 and AChE. This study paves way for consideration of these lead molecules as prospective drugs for the effective dual inhibition of BACE-1 and AChE. The GQSAR model provides site-specific clues about the molecules where certain modifications can result in increased biological activity. This information could be of high value for design and development of multifunctional drugs for combating AD. PMID:25019089

  8. Integration of QSAR and SAR methods for the mechanistic interpretation of predictive models for carcinogenicity

    PubMed Central

    Fjodorova, Natalja; Novič, Marjana

    2012-01-01

    The knowledge-based Toxtree expert system (SAR approach) was integrated with the statistically based counter propagation artificial neural network (CP ANN) model (QSAR approach) to contribute to a better mechanistic understanding of a carcinogenicity model for non-congeneric chemicals using Dragon descriptors and carcinogenic potency for rats as a response. The transparency of the CP ANN algorithm was demonstrated using intrinsic mapping technique specifically Kohonen maps. Chemical structures were represented by Dragon descriptors that express the structural and electronic features of molecules such as their shape and electronic surrounding related to reactivity of molecules. It was illustrated how the descriptors are correlated with particular structural alerts (SAs) for carcinogenicity with recognized mechanistic link to carcinogenic activity. Moreover, the Kohonen mapping technique enables one to examine the separation of carcinogens and non-carcinogens (for rats) within a family of chemicals with a particular SA for carcinogenicity. The mechanistic interpretation of models is important for the evaluation of safety of chemicals. PMID:24688639

  9. QSAR studies on 3-(4-biphenylmethyl) 4, 5-dihydro-4-oxo-3H-imidazo [4, 5-c] Pyridine derivatives as angiotensin II (AT1) receptor antagonist.

    PubMed

    Sharma, Mukesh C

    2015-06-01

    QSAR studies were performed for correlating the chemical composition of 3-(4-biphenylmethyl) 4, 5-dihydro-4-oxo-3H-imidazo [4, 5-c] pyridines bearing aryl acetic acid esters and acetamides as angiotensin II AT(1) receptor antagonist. Four different quantitative structure-property relationship (QSAR) methods namely two-dimensional (2D-QSAR), group-based QSAR, k-nearest neighbor and Pharmacophore Modeling were employed to obtain statistically significant models. The statistically significant best 2D-QSAR model having correlation coefficient r(2) = 0:8940 and cross-validated squared correlation coefficient q(2) = 0:7648 with external predictive ability of pred_r(2) = 0:8177,pred_r(2)se = 0.4119 and best group-based QSAR model having r(2) = 0:7392 and q(2) = 0:6710with pred_r(2) = 0:7503was developed by SA-principal component regression. The most predictive k-nearest neighbor model derived from the superposition of conformations has good cross-validated q(2) = 0:7637 and satisfied predictive ability r(2)_pred = 0.7143. Continuing with compounds of substituted 4, 5-dihydro-4-oxo-3H-imidazo [4, 5-c] pyridine derivatives chemical feature-based pharmacophore models with lowest RMSD value (0.3292 Å) consists of two Hac (Hydrogen bond acceptor), negative ionizable, and two AroC (Aromatic) features are important for the activity. The study suggested that substitution of group at R, R 1, R 2 and Ar, and position on 4, 5-dihydro-4-oxo-3H-imidazo [4, 5-c] pyridine ring with more electronegative nature and low bulkiness are favorable for the antihypertensive activity. These theoretical results may provide a useful reference for understanding the action mechanism and designing potential angiotensin II (AT1) receptor antagonist. PMID:26215494

  10. Identification of Potent EGFR Inhibitors from TCM Database@Taiwan

    PubMed Central

    Yang, Shun-Chieh; Chang, Su-Sen; Chen, Hsin-Yi; Chen, Calvin Yu-Chian

    2011-01-01

    Overexpression of epidermal growth factor receptor (EGFR) has been associated with cancer. Targeted inhibition of the EGFR pathway has been shown to limit proliferation of cancerous cells. Hence, we employed Traditional Chinese Medicine Database (TCM Database@Taiwan) (http://tcm.cmu.edu.tw) to identify potential EGFR inhibitor. Multiple Linear Regression (MLR), Support Vector Machine (SVM), Comparative Molecular Field Analysis (CoMFA), and Comparative Molecular Similarities Indices Analysis (CoMSIA) models were generated using a training set of EGFR ligands of known inhibitory activities. The top four TCM candidates based on DockScore were 2-O-caffeoyl tartaric acid, Emitine, Rosmaricine, and 2-O-feruloyl tartaric acid, and all had higher binding affinities than the control Iressa®. The TCM candidates had interactions with Asp855, Lys716, and Lys728, all which are residues of the protein kinase binding site. Validated MLR (r2 = 0.7858) and SVM (r2 = 0.8754) models predicted good bioactivity for the TCM candidates. In addition, the TCM candidates contoured well to the 3D-Quantitative Structure-Activity Relationship (3D-QSAR) map derived from the CoMFA (q2 = 0.721, r2 = 0.986) and CoMSIA (q2 = 0.662, r2 = 0.988) models. The steric field, hydrophobic field, and H-bond of the 3D-QSAR map were well matched by each TCM candidate. Molecular docking indicated that all TCM candidates formed H-bonds within the EGFR protein kinase domain. Based on the different structures, H-bonds were formed at either Asp855 or Lys716/Lys728. The compounds remained stable throughout molecular dynamics (MD) simulation. Based on the results of this study, 2-O-caffeoyl tartaric acid, Emitine, Rosmaricine, and 2-O-feruloyl tartaric acid are suggested to be potential EGFR inhibitors. PMID:22022246

  11. Physiological Information Database (PID)

    EPA Science Inventory

    EPA has developed a physiological information database (created using Microsoft ACCESS) intended to be used in PBPK modeling. The database contains physiological parameter values for humans from early childhood through senescence as well as similar data for laboratory animal spec...

  12. THE ECOTOX DATABASE

    EPA Science Inventory

    The database provides chemical-specific toxicity information for aquatic life, terrestrial plants, and terrestrial wildlife. ECOTOX is a comprehensive ecotoxicology database and is therefore essential for providing and suppoirting high quality models needed to estimate population...

  13. Network II Database

    Energy Science and Technology Software Center (ESTSC)

    1994-11-07

    The Oak Ridge National Laboratory (ORNL) Rail and Barge Network II Database is a representation of the rail and barge system of the United States. The network is derived from the Federal Rail Administration (FRA) rail database.

  14. Household Products Database: Pesticides

    MedlinePlus

    ... Names Types of Products Manufacturers Ingredients About the Database FAQ Product Recalls Help Glossary Contact Us More ... holders. Information is extracted from Consumer Product Information Database ©2001-2015 by DeLima Associates. All rights reserved. ...

  15. Annoying Danish relatives: comprehension and production of relative clauses by Danish children with and without SLI.

    PubMed

    Jensen De López, Kristine; Sundahl Olsen, Lone; Chondrogianni, Vasiliki

    2014-01-01

    This study examines the comprehension and production of subject and object relative clauses (SRCs, ORCs) by children with Specific Language Impairment (SLI) and their typically developing (TD) peers. The purpose is to investigate whether relative clauses are problematic for Danish children with SLI and to compare errors with those produced by TD children. Eighteen children with SLI, eighteen TD age-matched (AM) and nine TD language-matched (LM) Danish-speaking children participated in a comprehension and in a production task. All children performed better on the comprehension compared with the production task, as well as on SRCs compared to ORCs and produced various avoidance strategies. In the ORC context, children with SLI produced more reversal errors than the AM children, who opted for passive ORCs. These results are discussed within current theories of SLI and indicate a deficiency with the assignment of thematic roles rather than with the structural make-up of RCs. PMID:23200200

  16. MPlus Database system

    SciTech Connect

    Not Available

    1989-01-20

    The MPlus Database program was developed to keep track of mail received. This system was developed by TRESP for the Department of Energy/Oak Ridge Operations. The MPlus Database program is a PC application, written in dBase III+'' and compiled with Clipper'' into an executable file. The files you need to run the MPLus Database program can be installed on a Bernoulli, or a hard drive. This paper discusses the use of this database.

  17. Aviation Safety Issues Database

    NASA Technical Reports Server (NTRS)

    Morello, Samuel A.; Ricks, Wendell R.

    2009-01-01

    The aviation safety issues database was instrumental in the refinement and substantiation of the National Aviation Safety Strategic Plan (NASSP). The issues database is a comprehensive set of issues from an extremely broad base of aviation functions, personnel, and vehicle categories, both nationally and internationally. Several aviation safety stakeholders such as the Commercial Aviation Safety Team (CAST) have already used the database. This broader interest was the genesis to making the database publically accessible and writing this report.

  18. Residential radon and lung cancer incidence in a Danish cohort

    SciTech Connect

    Braeuner, Elvira V.; Andersen, Claus E.; Sorensen, Mette; Jovanovic Andersen, Zorana; Gravesen, Peter; Ulbak, Kaare; Hertel, Ole; Pedersen, Camilla; Overvad, Kim; Tjonneland, Anne; Raaschou-Nielsen, Ole

    2012-10-15

    High-level occupational radon exposure is an established risk factor for lung cancer. We assessed the long-term association between residential radon and lung cancer risk using a prospective Danish cohort using 57,053 persons recruited during 1993-1997. We followed each cohort member for cancer occurrence until 27 June 2006, identifying 589 lung cancer cases. We traced residential addresses from 1 January 1971 until 27 June 2006 and calculated radon at each of these addresses using information from central databases regarding geology and house construction. Cox proportional hazards models were used to estimate incidence rate ratios (IRR) and 95% confidence intervals (CI) for lung cancer risk associated with residential radon exposure with and without adjustment for sex, smoking variables, education, socio-economic status, occupation, body mass index, air pollution and consumption of fruit and alcohol. Potential effect modification by sex, traffic-related air pollution and environmental tobacco smoke was assessed. Median estimated radon was 35.8 Bq/m{sup 3}. The adjusted IRR for lung cancer was 1.04 (95% CI: 0.69-1.56) in association with a 100 Bq/m{sup 3} higher radon concentration and 1.67 (95% CI: 0.69-4.04) among non-smokers. We found no evidence of effect modification. We find a positive association between radon and lung cancer risk consistent with previous studies but the role of chance cannot be excluded as these associations were not statistically significant. Our results provide valuable information at the low-level radon dose range.

  19. Residential Radon and Brain Tumour Incidence in a Danish Cohort

    PubMed Central

    Bräuner, Elvira V.; Andersen, Zorana J.; Andersen, Claus E.; Pedersen, Camilla; Gravesen, Peter; Ulbak, Kaare; Hertel, Ole; Loft, Steffen; Raaschou-Nielsen, Ole

    2013-01-01

    Background Increased brain tumour incidence over recent decades may reflect improved diagnostic methods and clinical practice, but remain unexplained. Although estimated doses are low a relationship between radon and brain tumours may exist. Objective To investigate the long-term effect of exposure to residential radon on the risk of primary brain tumour in a prospective Danish cohort. Methods During 1993–1997 we recruited 57,053 persons. We followed each cohort member for cancer occurrence from enrolment until 31 December 2009, identifying 121 primary brain tumour cases. We traced residential addresses from 1 January 1971 until 31 December 2009 and calculated radon concentrations at each address using information from central databases regarding geology and house construction. Cox proportional hazards models were used to estimate incidence rate-ratios (IRR) and 95% confidence intervals (CI) for the risk of primary brain tumours associated with residential radon exposure with adjustment for age, sex, occupation, fruit and vegetable consumption and traffic-related air pollution. Effect modification by air pollution was assessed. Results Median estimated radon was 40.5 Bq/m3. The adjusted IRR for primary brain tumour associated with each 100 Bq/m3 increment in average residential radon levels was 1.96 (95% CI: 1.07; 3.58) and this was exposure-dependently higher over the four radon exposure quartiles. This association was not modified by air pollution. Conclusions We found significant associations and exposure-response patterns between long-term residential radon exposure radon in a general population and risk of primary brain tumours, adding new knowledge to this field. This finding could be chance and needs to be challenged in future studies. PMID:24066143

  20. Mission and Assets Database

    NASA Technical Reports Server (NTRS)

    Baldwin, John; Zendejas, Silvino; Gutheinz, Sandy; Borden, Chester; Wang, Yeou-Fang

    2009-01-01

    Mission and Assets Database (MADB) Version 1.0 is an SQL database system with a Web user interface to centralize information. The database stores flight project support resource requirements, view periods, antenna information, schedule, and forecast results for use in mid-range and long-term planning of Deep Space Network (DSN) assets.

  1. Plant and Crop Databases

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Databases have become an integral part of all aspects of biological research, including basic and applied plant biology. The importance of databases continues to increase as the volume of data from direct and indirect genomics approaches expands. What is not always obvious to users of databases is t...

  2. QSAR modeling of aromatase inhibitory activity of 1-substituted 1,2,3-triazole analogs of letrozole.

    PubMed

    Nantasenamat, Chanin; Worachartcheewan, Apilak; Prachayasittikul, Supaluk; Isarankura-Na-Ayudhya, Chartchalerm; Prachayasittikul, Virapong

    2013-11-01

    Aromatase is an estrogen biosynthesis enzyme belonging to the cytochrome P450 family that catalyzes the rate-limiting step of converting androgens to estrogens. As it is pertinent toward tumor cell growth promotion, aromatase is a lucrative therapeutic target for breast cancer. In the pursuit of robust aromatase inhibitors, a set of fifty-four 1-substituted mono- and bis-benzonitrile or phenyl analogs of 1,2,3-triazole letrozole were employed in quantitative structure-activity relationship (QSAR) study using multiple linear regression (MLR), artificial neural network (ANN) and support vector machine (SVM). Such QSAR models were developed using a set of descriptors providing coverage of the general characteristics of a molecule encompassing molecular size, flexibility, polarity, solubility, charge and electronic properties. Important physicochemical properties giving rise to good aromatase inhibition were obtained by means of exploring its chemical space as a function of the calculated molecular descriptors. The optimal subset of 3 descriptors (i.e. number of rings, ALogP and HOMO-LUMO) was further used for QSAR model construction. The predicted pIC₅₀ values were in strong correlation with their experimental values displaying correlation coefficient values in the range of 0.72-0.83 for the cross-validated set (QCV) while the external test set (Q(Ext)) afforded values in the range of 0.65-0.66. Insights gained from the present study are anticipated to provide pertinent information contributing to the origins of aromatase inhibitory activity and therefore aid in our on-going quest for aromatase inhibitors with robust properties. PMID:24012714

  3. [Method of traditional Chinese medicine formula design based on 3D-database pharmacophore search and patent retrieval].

    PubMed

    He, Yu-su; Sun, Zhi-yi; Zhang, Yan-ling

    2014-11-01

    By using the pharmacophore model of mineralocorticoid receptor antagonists as a starting point, the experiment stud- ies the method of traditional Chinese medicine formula design for anti-hypertensive. Pharmacophore models were generated by 3D-QSAR pharmacophore (Hypogen) program of the DS3.5, based on the training set composed of 33 mineralocorticoid receptor antagonists. The best pharmacophore model consisted of two Hydrogen-bond acceptors, three Hydrophobic and four excluded volumes. Its correlation coefficient of training set and test set, N, and CAI value were 0.9534, 0.6748, 2.878, and 1.119. According to the database screening, 1700 active compounds from 86 source plant were obtained. Because of lacking of available anti-hypertensive medi cation strategy in traditional theory, this article takes advantage of patent retrieval in world traditional medicine patent database, in order to design drug formula. Finally, two formulae was obtained for antihypertensive. PMID:25850277

  4. Identification of phototransformation products of thalidomide and mixture toxicity assessment: an experimental and quantitative structural activity relationships (QSAR) approach.

    PubMed

    Mahmoud, Waleed M M; Toolaram, Anju P; Menz, Jakob; Leder, Christoph; Schneider, Mandy; Kümmerer, Klaus

    2014-02-01

    The fate of thalidomide (TD) was investigated after irradiation with a medium-pressure Hg-lamp. The primary elimination of TD was monitored and structures of phototransformation products (PTPs) were assessed by LC-UV-FL-MS/MS. Environmentally relevant properties of TD and its PTPs as well as hydrolysis products (HTPs) were predicted using in silico QSAR models. Mutagenicity of TD and its PTPs was investigated in the Ames microplate format (MPF) aqua assay (Xenometrix, AG). Furthermore, a modified luminescent bacteria test (kinetic luminescent bacteria test (kinetic LBT)), using the luminescent bacteria species Vibrio fischeri, was applied for the initial screening of environmental toxicity. Additionally, toxicity of phthalimide, one of the identified PTPs, was investigated separately in the kinetic LBT. The UV irradiation eliminated TD itself without complete mineralization and led to the formation of several PTPs. TD and its PTPs did not exhibit mutagenic response in the Salmonella typhimurium strains TA 98, and TA 100 with and without metabolic activation. In contrast, QSAR analysis of PTPs and HTPs provided evidence for mutagenicity, genotoxicity and carcinogenicity using additional endpoints in silico software. QSAR analysis of different ecotoxicological endpoints, such as acute toxicity towards V. fischeri, provided positive alerts for several identified PTPs and HTPs. This was partially confirmed by the results of the kinetic LBT, in which a steady increase of acute and chronic toxicity during the UV-treatment procedure was observed for the photolytic mixtures at the highest tested concentration. Moreover, the number of PTPs within the reaction mixture that might be responsible for the toxification of TD during UV-treatment was successfully narrowed down by correlating the formation kinetics of PTPs with QSAR predictions and experimental toxicity data. Beyond that, further analysis of the commercially available PTP phthalimide indicated that transformation of

  5. T-scale as a novel vector of topological descriptors for amino acids and its application in QSARs of peptides

    NASA Astrophysics Data System (ADS)

    Tian, Feifei; Zhou, Peng; Li, Zhiliang

    2007-03-01

    In this paper, a new topological descriptor T-scale is derived from principal component analysis (PCA) on the collected 67 kinds of structural and topological variables of 135 amino acids. Applying T-scale to three peptide panels as 58 angiotensin-converting enzyme (ACE) inhibitors, 20 thromboplastin inhibitors (TI) and 28 bovine lactoferricin-(17-31)-pentadecapeptides (LFB), the resulting QSAR models, constructed by partial least squares (PLS), are all superior to reference reports, with correlative coefficient r2 and cross-validated q2 of 0.845, 0.786; 0.996, 0.782 (0.988, 0.961); 0.760, 0.627, respectively.

  6. QSAR, docking, dynamic simulation and quantum mechanics studies to explore the recognition properties of cholinesterase binding sites.

    PubMed

    Correa-Basurto, J; Bello, M; Rosales-Hernández, M C; Hernández-Rodríguez, M; Nicolás-Vázquez, I; Rojo-Domínguez, A; Trujillo-Ferrara, J G; Miranda, René; Flores-Sandoval, C A

    2014-02-25

    A set of 84 known N-aryl-monosubstituted derivatives (42 amides: series 1 and 2, and 42 imides: series 3 an 4, from maleic and succinic anhydrides, respectively) that display inhibitory activity toward both acetylcholinesterase and butyrylcholinesterase (ChEs) was considered for Quantitative structure-activity relationship (QSAR) studies. These QSAR studies employed docking data from both ChEs that were previously submitted to molecular dynamics (MD) simulations. Donepezil and galanthamine stereoisomers were included to analyze their quantum mechanics properties and for validating the docking procedure. Quantum parameters such as frontier orbital energies, dipole moment, molecular volume, atomic charges, bond length and reactivity parameters were measured, as well as partition coefficients, molar refractivity and polarizability were also analyzed. In order to evaluate the obtained equations, four compounds: 1a (4-oxo-4-(phenylamino)butanoic acid), 2a ((2Z)-4-oxo-4-(phenylamino)but-2-enoic acid), 3a (2-phenylcyclopentane-1,3-dione) and 4a (2-phenylcyclopent-4-ene-1,3-dione) were employed as independent data set, using only equations with r(m(test))²>0.5. It was observed that residual values gave low value in almost all series, excepting in series 1 for compounds 3a and 4a, and in series 4 for compounds 1a, 2a and 3a, giving a low value for 4a. Consequently, equations seems to be specific according to the structure of the evaluated compound, that means, series 1 fits better for compound 1a, series 3 or 4 fits better for compounds 3a or 4a. Same behavior was observed in the butyrylcholinesterase (BChE). Therefore, obtained equations in this QSAR study could be employed to calculate the inhibition constant (Ki) value for compounds having a similar structure as N-aryl derivatives described here. The QSAR study showed that bond lengths, molecular electrostatic potential and frontier orbital energies are important in both ChE targets. Docking studies revealed that

  7. Visualization of multidimensional database

    NASA Astrophysics Data System (ADS)

    Lee, Chung

    2008-01-01

    The concept of multidimensional databases has been extensively researched and wildly used in actual database application. It plays an important role in contemporary information technology, but due to the complexity of its inner structure, the database design is a complicated process and users are having a hard time fully understanding and using the database. An effective visualization tool for higher dimensional information system helps database designers and users alike. Most visualization techniques focus on displaying dimensional data using spreadsheets and charts. This may be sufficient for the databases having three or fewer dimensions but for higher dimensions, various combinations of projection operations are needed and a full grasp of total database architecture is very difficult. This study reviews existing visualization techniques for multidimensional database and then proposes an alternate approach to visualize a database of any dimension by adopting the tool proposed by Kiviat for software engineering processes. In this diagramming method, each dimension is represented by one branch of concentric spikes. This paper documents a C++ based visualization tool with extensive use of OpenGL graphics library and GUI functions. Detailed examples of actual databases demonstrate the feasibility and effectiveness in visualizing multidimensional databases.

  8. Is the Danish wind energy model replicable for other countries?

    SciTech Connect

    Sovacool, Benjamin K.; Lindboe, Hans H.; Odgaard, Ole

    2008-03-15

    Though aspects of the Danish wind energy model are unique, policymakers might do well to imitate such aspects as a strong political commitment, consistent policy mechanisms, and an incremental, ''hands-on'' approach to R and D. (author)

  9. Explicit Sex--Liberation or Exploitation: Danish "Permissiveness" Revisited

    ERIC Educational Resources Information Center

    Bachy, Victor

    1976-01-01

    Reviews various Danish legislative actions leading up to the lifting of the ban on pornography, and discusses possible consequences of such liberalization by analyzing police statistics from a five year period. (MH)

  10. An Introduction to Database Structure and Database Machines.

    ERIC Educational Resources Information Center

    Detweiler, Karen

    1984-01-01

    Enumerates principal management objectives of database management systems (data independence, quality, security, multiuser access, central control) and criteria for comparison (response time, size, flexibility, other features). Conventional database management systems, relational databases, and database machines used for backend processing are…

  11. Structure based 3D-QSAR studies of Interleukin-2 inhibitors: Comparing the quality and predictivity of 3D-QSAR models obtained from different alignment methods and charge calculations.

    PubMed

    Halim, Sobia Ahsan; Zaheer-ul-Haq

    2015-08-01

    Interleukin-2 is an essential cytokine in an innate immune response, and is a promising drug target for several immunological disorders. In the present study, structure-based 3D-QSAR modeling was carried out via Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Index Analysis (CoMSIA) methods. Six different partial charge calculation methods were used in combination with two different alignment methods to scrutinize their effects on the predictive power of 3D-QSAR models. The best CoMFA and CoMSIA models were obtained with the AM1 charges when used with co-conformer based substructure alignment (CCBSA) method. The obtained models posses excellent correlation coefficient value and also exhibited good predictive power (for CoMFA: q(2)=0.619; r(2)=0.890; r(2)Pred=0.765 and for CoMSIA: q(2)=0.607; r(2)=0.884; r(2)Pred=0.655). The developed models were further validated by using a set of another sixteen compounds as external test set 2 and both models showed strong predictive power with r(2)Pred=>0.8. The contour maps obtained from these models better interpret the structure activity relationship; hence the developed models would help to design and optimize more potent IL-2 inhibitors. The results might have implications for rational design of specific anti-inflammatory compounds with improved affinity and selectivity. PMID:26051521

  12. 4D-QSAR analysis and pharmacophore modeling: electron conformational-genetic algorithm approach for penicillins.

    PubMed

    Yanmaz, Ersin; Sarıpınar, Emin; Şahin, Kader; Geçen, Nazmiye; Çopur, Fatih

    2011-04-01

    4D-QSAR studies were performed on a series of 87 penicillin analogues using the electron conformational-genetic algorithm (EC-GA) method. In this EC-based method, each conformation of the molecular system is described by a matrix (ECMC) with both electron structural parameters and interatomic distances as matrix elements. Multiple comparisons of these matrices within given tolerances for high active and low active penicillin compounds allow one to separate a smaller number of matrix elements (ECSA) which represent the pharmacophore groups. The effect of conformations was investigated building model 1 and 2 based on ensemble of conformers and single conformer, respectively. GA was used to select the most important descriptors and to predict the theoretical activity of the training (74 compounds) and test (13 compounds, commercial penicillins) sets. The model 1 for training and test sets obtained by optimum 12 parameters gave more satisfactory results (R(training)(2)=0.861, SE(training)=0.044, R(test)(2)=0.892, SE(test)=0.099, q(2)=0.702, q(ext1)(2)=0.777 and q(ext2)(2)=0.733) than model 2 (R(training)(2)=0.774, SE(training)=0.056, R(test)(2)=0.840, SE(test)=0.121, q(2)=0.514, q(ext1)(2)=0.641 and q(ext2)(2)=0.570). To estimate the individual influence of each of the molecular descriptors on biological activity, the E statistics technique was applied to the derived EC-GA model. PMID:21419636

  13. CoRILISA: a local similarity based receptor dependent QSAR method.

    PubMed

    Khedkar, Vijay M; Coutinho, Evans C

    2015-01-26

    Molecular similarity methods have played a crucial role in the success of structure-based and computer-assisted drug design. However, with the exception of CoMSIA, the current approaches for estimating molecular similarity yield a global picture thereby providing limited information about the local spatial molecular features responsible for the variation of activity with the 3D structure. Application of molecular similarity measures, each related to the functional "pieces" of a ligand-receptor complex, is advantageous over a composite molecular similarity alone and will provide more insights to rationally interpret the activity based on the receptor and ligand structural features. Building on the ideas of our previously published methodologies-CoRIA and LISA, we present here a local molecular similarity based receptor dependent QSAR method termed CoRILISA which is a hybrid of the two approaches. The method improves on previous techniques by inclusion of receptor attributes for the calculation and comparison of similarity between molecules. For validation studies, the CoRILISA methodology was applied on three large and diverse data sets-glycogen phosphorylase b (GPb), human immunodeficiency virus-1 protease (HIV PR), and cyclin dependent kinase 2 (CDK2) inhibitors. The statistics of the CoRILISA models were benchmarked against the standard CoRIA approach and with other published approaches. The CoRILISA models were found to be significantly better, especially in terms of the predictivity for the test set. CoRILISA is able to identify the thermodynamic properties associated with residues that define the active site and modulate the variation in the activity of the molecules. It is a useful tool in the fragment-based drug discovery approach for ligand activity prediction. PMID:25535645

  14. 3D QSAR and docking studies of various amido and benzyl-substituted 3-amino-4-(2-cyanopyrrolidide)pyrrolidinyl analogs as DPP-IV inhibitors.

    PubMed

    Agrawal, Ritesh; Jain, Pratima; Dikshit, Subodh Narayan; Jain, Sourabh

    2013-09-01

    The article describes the development of a robust pharmacophore model and the investigation of structure activity relationship analysis of 3-amino-4-(2-cyanopyrrolidide)pyrrolidinyl analogs reported for DPP-IV inhibition using PHASE module of Schrodinger software. The present works also encompass molecular interaction study of 3-amino-4-(2- cyanopyrrolidide)pyrrolidinyl analogs on maestro 8.5 workstation. The Phase study module comprises the five points pharmacophore model (AAHPR.617), consisting two hydrogen bond acceptor (A), one Hydrophobic (H), one Positive(P) and one aromatic ring (R) and with discrete geometries as pharmacophoric feature. The developed pharmacophore model was used to derive a predictive atom-based 3D QSAR model. The obtained 3D QSAR model has an excellent correlation coefficient value (r2=0.9926) along with good statistical significance as shown by high Fisher ratio (F=671.7). The model also exhibits good predictive power, which is confirmed by high value of cross validated correlation coefficient (q2 = 0.7311). The QSAR model suggests that hydrophobic and aromatic characters are crucial for the DPP-IV inhibitory activity. The QSAR model also suggests that the inclusion of hydrophobic substituents would enhance the DPP-IV inhibition. In addition to the hydrogen bond acceptor, hydrophobic character, electro withdrawing character positively contributes to the DPP-IV inhibition. This study provides a set of guidelines for designing compounds with better DPP-IV inhibitory potency. PMID:23607811

  15. Cellular Quantitative Structure–Activity Relationship (Cell-QSAR): Conceptual Dissection of Receptor Binding and Intracellular Disposition in Antifilarial Activities of Selwood Antimycins

    PubMed Central

    2012-01-01

    We present the cellular quantitative structure–activity relationship (cell-QSAR) concept that adapts ligand-based and receptor-based 3D-QSAR methods for use with cell-level activities. The unknown intracellular drug disposition is accounted for by the disposition function (DF), a model-based, nonlinear function of a drug’s lipophilicity, acidity, and other properties. We conceptually combined the DF with our multispecies, multimode version of the frequently used ligand-based comparative molecular field analysis (CoMFA) method, forming a single correlation function for fitting the cell-level activities. The resulting cell-QSAR model was applied to the Selwood data on filaricidal activities of antimycin analogues. Their molecules are flexible, ionize under physiologic conditions, form different intramolecular H-bonds for neutral and ionized species, and cross several membranes to reach unknown receptors. The calibrated cell-QSAR model is significantly more predictive than other models lacking the disposition part and provides valuable structure optimization clues by factorizing the cell-level activity of each compound into the contributions of the receptor binding and disposition. PMID:22468611

  16. QSAR Classification of ToxCast and Tox21 Chemicals on the Basis of Estrogen Receptor Assays (FutureToxII)

    EPA Science Inventory

    The ToxCast and Tox21 programs have tested ~8,200 chemicals in a broad screening panel of in vitro high-throughput screening (HTS) assays for estrogen receptor (ER) agonist and antagonist activity. The present work uses this large in vitro data set to develop in silico QSAR model...

  17. The effect of various atomic partial charge schemes to elucidate consensus activity-correlating molecular regions: a test case of diverse QSAR models.

    PubMed

    Kumar, Sivakumar Prasanth; Jha, Prakash C; Jasrai, Yogesh T; Pandya, Himanshu A

    2016-03-01

    The estimation of atomic partial charges of the small molecules to calculate molecular interaction fields (MIFs) is an important process in field-based quantitative structure-activity relationship (QSAR). Several studies showed the influence of partial charge schemes that drastically affects the prediction accuracy of the QSAR model and focused on the selection of appropriate charge models that provide highest cross-validated correlation coefficient ([Formula: see text] or q(2)) to explain the variation in chemical structures against biological endpoints. This study shift this focus in a direction to understand the molecular regions deemed to explain SAR in various charge models and recognize a consensus picture of activity-correlating molecular regions. We selected eleven diverse dataset and developed MIF-based QSAR models using various charge schemes including Gasteiger-Marsili, Del Re, Merck Molecular Force Field, Hückel, Gasteiger-Hückel, and Pullman. The generalized resultant QSAR models were then compared with Open3DQSAR model to interpret the MIF descriptors decisively. We suggest the regions of activity contribution or optimization can be effectively determined by studying various charge-based models to understand SAR precisely. PMID:25997097

  18. Novel 3-Amino-6-chloro-7-(azol-2 or 5-yl)-1,1-dioxo-1,4,2-benzodithiazine Derivatives with Anticancer Activity: Synthesis and QSAR Study.

    PubMed

    Pogorzelska, Aneta; Sławiński, Jarosław; Brożewicz, Kamil; Ulenberg, Szymon; Bączek, Tomasz

    2015-01-01

    A series of new 3-amino-6-chloro-7-(azol-2 or 5-yl)-1,1-dioxo-1,4,2-benzodithiazine derivatives 5a-j have been synthesized and evaluated in vitro for their antiproliferative activity at the U.S. National Cancer Institute. The most active compound 5h showed significant cytotoxic effects against ovarian (OVCAR-3) and breast (MDA-MB-468) cancer (10% and 47% cancer cell death, respectively) as well as a good selectivity toward prostate (DU-145), colon (SW-620) and renal (TK-10) cancer cell lines. To obtain a deeper insight into the structure-activity relationships of the new compounds 5a-j QSAR studies have been applied. Theoretical calculations allowed the identification of molecular descriptors belonging to the RDF (RDF055p and RDF145m in the MOLT-4 and UO-31 QSAR models, respectively) and 3D-MorSE (Mor32m and Mor16e for MOLT-4 and UO-31 QSAR models) descriptor classes. Based on these data, QSAR models with good robustness and predictive ability have been obtained. PMID:26690109

  19. Investigation of antigen-antibody interactions of sulfonamides with a monoclonal antibody in a fluorescence polarization immunoassay using 3D-QSAR models

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A three-dimensional quantitative structure-activity relationship (3D-QSAR) model of sulfonamide analogs binding a monoclonal antibody (MAbSMR) produced against sulfamerazine was carried out by Distance Comparison (DISCOtech), comparative molecular field analysis (CoMFA), and comparative molecular si...

  20. 2D-Qsar for 450 types of amino acid induction peptides with a novel substructure pair descriptor having wider scope

    PubMed Central

    2011-01-01

    Background Quantitative structure-activity relationships (QSAR) analysis of peptides is helpful for designing various types of drugs such as kinase inhibitor or antigen. Capturing various properties of peptides is essential for analyzing two-dimensional QSAR. A descriptor of peptides is an important element for capturing properties. The atom pair holographic (APH) code is designed for the description of peptides and it represents peptides as the combination of thirty-six types of key atoms and their intermediate binding between two key atoms. Results The substructure pair descriptor (SPAD) represents peptides as the combination of forty-nine types of key substructures and the sequence of amino acid residues between two substructures. The size of the key substructures is larger and the length of the sequence is longer than traditional descriptors. Similarity searches on C5a inhibitor data set and kinase inhibitor data set showed that order of inhibitors become three times higher by representing peptides with SPAD, respectively. Comparing scope of each descriptor shows that SPAD captures different properties from APH. Conclusion QSAR/QSPR for peptides is helpful for designing various types of drugs such as kinase inhibitor and antigen. SPAD is a novel and powerful descriptor for various types of peptides. Accuracy of QSAR/QSPR becomes higher by describing peptides with SPAD. PMID:22047717

  1. Computational Study of Quinolone Derivatives to Improve their Therapeutic Index as Anti-malaria Agents: QSAR and QSTR.

    PubMed

    Iman, Maryam; Davood, Asghar; Khamesipour, Ali

    2015-01-01

    Malaria is a parasitic disease caused by five different species of Plasmodium. More than 40% of the world's population is at risk and malaria annual incidence is estimated to be more than two hundred million, malaria is one of the most important public health problems especially in children of the poorest parts of the world, annual mortality is about 1 million. The epidemiological status of the disease justifies to search for control measures, new therapeutic options and development of an effective vaccine. Chemotherapy options in malaria are limited, moreover, drug resistant rate is high. In spite of global efforts to develop an effective vaccine yet there is no vaccine available. In the current study, a series of quinolone derivatives were subjected to quantitative structure activity relationship (QSAR) and quantitative structure toxicity relationship (QSTR) analyses to identify the ideal physicochemical characteristics of potential anti-malaria activity and less cytotoxicity. Quinolone with desirable properties was built using HyperChem program, and conformational studies were performed through the semi-empirical method followed by the PM3 force field. Multi linear regression (MLR) was used as a chemo metric tool for quantitative structure activity relationship modeling and the developed models were shown to be statistically significant according to the validation parameters. The obtained QSAR model reveals that the descriptors PJI2, Mv, PCR, nBM, and VAR mainly affect the anti-malaria activity and descriptors MSD, MAXDP, and X1sol affect the cytotoxicity of the series of ligands. PMID:26330866

  2. Quantitative structure-activity relationship (QSAR) prediction of (eco)toxicity of short aliphatic protic ionic liquids.

    PubMed

    Peric, Brezana; Sierra, Jordi; Martí, Esther; Cruañas, Robert; Garau, Maria Antonia

    2015-05-01

    Ionic liquids (ILs) are considered as a group of very promising compounds due to their excellent properties (practical non-volatility, high thermal stability and very good and diverse solving capacity). The ILs have a good prospect of replacing traditional organic solvents in vast variety of applications. However, the complete information on their environmental impact is still not available. There is also an enormous number of possible combinations of anions and cations which can form ILs, the fact that requires a method allowing the prediction of toxicity of existing and potential ILs. In this study, a group contribution QSAR model has been used in order to predict the (eco)toxicity of protic and aprotic ILs for five tests (Microtox®, Pseudokirchneriella subcapitata and Lemna minor growth inhibition test, and Acetylcholinestherase inhibition and Cell viability assay with IPC-81 cells). The predicted and experimental toxicity are well correlated. A prediction of EC50 for these (eco)toxicity tests has also been made for eight representatives of the new family of short aliphatic protic ILs, whose toxicity has not been determined experimentally to date. The QSAR model applied in this study can allow the selection of potentially less toxic ILs amongst the existing ones (e.g. in the case of aprotic ILs), but it can also be very helpful in directing the synthesis efforts toward developing new "greener" ILs respectful with the environment (e.g. short aliphatic protic ILs). PMID:25728357

  3. Mixed-model QSAR at the human mineralocorticoid receptor: predicting binding mode and affinity of anabolic steroids.

    PubMed

    Peristera, Ourania; Spreafico, Morena; Smiesko, Martin; Ernst, Beat; Vedani, Angelo

    2009-09-28

    We present a computational study on the human mineralocorticoid receptor (hMR) that is based on multi-dimensional quantitative structure-activity relationships (mQSAR). Therein, we identified the binding mode of 48 steroid and non-steroid homologues by flexible docking to the crystal structure (software Yeti) and quantified it using 6D-QSAR (software Quasar). The receptor surrogate, evolved using a genetic algorithm, converged at a cross-validated r2 of 0.810, and yielded a predictive r2 of 0.661. The model was challenged by a series of scramble tests and by consensus scoring (software Raptor: r2=0.844, predictive r(2)=0.620). The model was then employed to predict the binding affinity of 26 anabolic steroids, demonstrating to which extent they might disrupt the endocrine system via binding to the hMR. The model for the hMR was added to the VirtualToxLab, a technology developed by the Biographics Laboratory 3R, allows the identification of the endocrine-disrupting potential of drugs, chemicals and natural products in silico. PMID:19523507

  4. Synthesis, biological evaluation and 3D-QSAR studies of new chalcone derivatives as inhibitors of human P-glycoprotein.

    PubMed

    Parveen, Zahida; Brunhofer, Gerda; Jabeen, Ishrat; Erker, Thomas; Chiba, Peter; Ecker, Gerhard F

    2014-04-01

    P-glycoprotein (P-gp) is an ATP-dependent multidrug resistance efflux transporter that plays an important role in anticancer drug resistance and in pharmacokinetics of medicines. Despite a large number of structurally and functionally diverse compounds, also flavonoids and chalcones have been reported as inhibitors of P-gp. The latter share some similarity with the well studied class of propafenones, but do not contain a basic nitrogen atom. Furthermore, due to their rigidity, they are suitable candidates for 3D-QSAR studies. In this study, a set of 22 new chalcone derivatives were synthesized and evaluated in a daunomycin efflux inhibition assay using the CCRF.CEM.VCR1000 cell line. The compound 10 showed the highest activity (IC50=42nM), which is one order of magnitude higher than the activity for an equilipohillic propafenone analogue. 2D- and 3D-QSAR studies indicate the importance of H-bond acceptors, methoxy groups, hydrophobic groups as well as the number of rotatable bonds as pharmacophoric features influencing P-gp inhibitory activity. PMID:24613626

  5. 5-N-Substituted-2-(substituted benzenesulphonyl) glutamines as antitumor agents. Part II: synthesis, biological activity and QSAR study.

    PubMed

    Samanta, Soma; Srikanth, K; Banerjee, Suchandra; Debnath, Bikash; Gayen, Shovanlal; Jha, Tarun

    2004-03-15

    Cancer is a major killer disease throughout human history. Thus, cancer becomes a major point of interest in life science. It was proved that cancer is a nitrogen trap and tumor cells are avid glutamine consumers. The non-essential amino acid glutamine, which is a glutamic acid derivative, supplies its amide nitrogen to tumor cells in the biosynthesis of purine and pyrimidine bases of nucleic acids as well as takes part in protein synthesis. Based on these and in continuation of our composite programme of development of new potential anticancer agents through rational drug design, 17 new 5-N-Substituted-2-(substituted benzenesulphonyl) glutamines were selected for synthesis. These compounds as well as 36 earlier synthesized glutamine analogues were screened for antitumor activity using percentage inhibition of tumor cell count as the activity parameter. QSAR study was performed with 53 compounds in order to design leads with increased effectiveness for antitumor activity using both physicochemical and topological parameters. QSAR study showed that steric effect on the aromatic ring is conducive to the activity. n-butyl substitution on aliphatic side chain and atom no 12 is important for antitumor activity of glutamine analogues. PMID:15018914

  6. Data Quality in the Human and Environmental Health Sciences: Using Statistical Confidence Scoring to Improve QSAR/QSPR Modeling.

    PubMed

    Steinmetz, Fabian P; Madden, Judith C; Cronin, Mark T D

    2015-08-24

    A greater number of toxicity data are becoming publicly available allowing for in silico modeling. However, questions often arise as to how to incorporate data quality and how to deal with contradicting data if more than a single datum point is available for the same compound. In this study, two well-known and studied QSAR/QSPR models for skin permeability and aquatic toxicology have been investigated in the context of statistical data quality. In particular, the potential benefits of the incorporation of the statistical Confidence Scoring (CS) approach within modeling and validation. As a result, robust QSAR/QSPR models for the skin permeability coefficient and the toxicity of nonpolar narcotics to Aliivibrio fischeri assay were created. CS-weighted linear regression for training and CS-weighted root-mean-square error (RMSE) for validation were statistically superior compared to standard linear regression and standard RMSE. Strategies are proposed as to how to interpret data with high and low CS, as well as how to deal with large data sets containing multiple entries. PMID:26186603

  7. A QSAR model for in silico screening of MAO-A inhibitors. Prediction, synthesis, and biological assay of novel coumarins.

    PubMed

    Santana, Lourdes; Uriarte, Eugenio; González-Díaz, Humberto; Zagotto, Giuseppe; Soto-Otero, Ramón; Méndez-Alvarez, Estefanía

    2006-02-01

    This work explores the potential of the MARCH-INSIDE methodology to seek a QSAR for MAO-A inhibitors from a heterogeneous series of compounds. A Markov model was used to quickly calculate the molecular electron delocalization, polarizability, refractivity, and n-octanol/water partition coefficients for a series of 1406 active/nonactive compounds. LDA was subsequently used to fit a classification function. The model showed 92.8% and 91.8% global accuracy and predictability in training and validation studies. This QSAR model was validated through a virtual screening of a series of coumarin derivatives. The 15 selected compounds were prepared and evaluated as in vitro MAO-A inhibitors. The theoretical prediction was compared with the experimental results and the model correctly predicted 13 compounds with only two mistakes on compounds with activities very close to the cutoff point established for the model. Consequently, this method represents a useful tool for the "in silico" screening of MAO-A inhibitors. PMID:16451079

  8. Towards the chemometric dissection of peptide--HLA-A*0201 binding affinity: comparison of local and global QSAR models.

    PubMed

    Doytchinova, Irini A; Walshe, Valerie; Borrow, Persephone; Flower, Darren R

    2005-03-01

    The affinities of 177 nonameric peptides binding to the HLA-A*0201 molecule were measured using a FACS-based MHC stabilisation assay and analysed using chemometrics. Their structures were described by global and local descriptors, QSAR models were derived by genetic algorithm, stepwise regression and PLS. The global molecular descriptors included molecular connectivity chi indices, kappa shape indices, E-state indices, molecular properties like molecular weight and log P, and three-dimensional descriptors like polarizability, surface area and volume. The local descriptors were of two types. The first used a binary string to indicate the presence of each amino acid type at each position of the peptide. The second was also position-dependent but used five z-scales to describe the main physicochemical properties of the amino acids forming the peptides. The models were developed using a representative training set of 131 peptides and validated using an independent test set of 46 peptides. It was found that the global descriptors could not explain the variance in the training set nor predict the affinities of the test set accurately. Both types of local descriptors gave QSAR models with better explained variance and predictive ability. The results suggest that, in their interactions with the MHC molecule, the peptide acts as a complicated ensemble of multiple amino acids mutually potentiating each other. PMID:16059672

  9. Computational Study of Quinolone Derivatives to Improve their Therapeutic Index as Anti-malaria Agents: QSAR and QSTR

    PubMed Central

    Iman, Maryam; Davood, Asghar; Khamesipour, Ali

    2015-01-01

    Malaria is a parasitic disease caused by five different species of Plasmodium. More than 40% of the world’s population is at risk and malaria annual incidence is estimated to be more than two hundred million, malaria is one of the most important public health problems especially in children of the poorest parts of the world, annual mortality is about 1 million. The epidemiological status of the disease justifies to search for control measures, new therapeutic options and development of an effective vaccine. Chemotherapy options in malaria are limited, moreover, drug resistant rate is high. In spite of global efforts to develop an effective vaccine yet there is no vaccine available. In the current study, a series of quinolone derivatives were subjected to quantitative structure activity relationship (QSAR) and quantitative structure toxicity relationship (QSTR) analyses to identify the ideal physicochemical characteristics of potential anti-malaria activity and less cytotoxicity. Quinolone with desirable properties was built using HyperChem program, and conformational studies were performed through the semi-empirical method followed by the PM3 force field. Multi linear regression (MLR) was used as a chemo metric tool for quantitative structure activity relationship modeling and the developed models were shown to be statistically significant according to the validation parameters. The obtained QSAR model reveals that the descriptors PJI2, Mv, PCR, nBM, and VAR mainly affect the anti-malaria activity and descriptors MSD, MAXDP, and X1sol affect the cytotoxicity of the series of ligands. PMID:26330866

  10. Exploration of Novel Inhibitors for Class I Histone Deacetylase Isoforms by QSAR Modeling and Molecular Dynamics Simulation Assays

    PubMed Central

    Noor, Zainab; Afzal, Noreen; Rashid, Sajid

    2015-01-01

    Histone deacetylases (HDAC) are metal-dependent enzymes and considered as important targets for cell functioning. Particularly, higher expression of class I HDACs is common in the onset of multiple malignancies which results in deregulation of many target genes involved in cell growth, differentiation and survival. Although substantial attempts have been made to control the irregular functioning of HDACs by employing various inhibitors with high sensitivity towards transformed cells, limited success has been achieved in epigenetic cancer therapy. Here in this study, we used ligand-based pharmacophore and 2-dimensional quantitative structure activity relationship (QSAR) modeling approaches for targeting class I HDAC isoforms. Pharmacophore models were generated by taking into account the known IC50 values and experimental energy scores with extensive validations. The QSAR model having an external R2 value of 0.93 was employed for virtual screening of compound libraries. 10 potential lead compounds (C1-C10) were short-listed having strong binding affinities for HDACs, out of which 2 compounds (C8 and C9) were able to interact with all members of class I HDACs. The potential binding modes of HDAC2 and HDAC8 to C8 were explored through molecular dynamics simulations. Overall, bioactivity and ligand efficiency (binding energy/non-hydrogen atoms) profiles suggested that proposed hits may be more effective inhibitors for cancer therapy. PMID:26431201

  11. Synthesis, Molecular Structure, Metabolic Stability and QSAR Studies of a Novel Series of Anticancer N-Acylbenzenesulfonamides.

    PubMed

    Żołnowska, Beata; Sławiński, Jarosław; Belka, Mariusz; Bączek, Tomasz; Kawiak, Anna; Chojnacki, Jarosław; Pogorzelska, Aneta; Szafrański, Krzysztof

    2015-01-01

    A series of novel N-acyl-4-chloro-5-methyl-2-(R¹-methylthio)benzenesulfonamides 18-47 have been synthesized by the reaction of N-[4-chloro-5-methyl-2-(R¹-methylthio) benzenesulfonyl]cyanamide potassium salts with appropriate carboxylic acids. Some of them showed anticancer activity toward the human cancer cell lines MCF-7, HCT-116 and HeLa, with the growth percentages (GPs) in the range from 7% to 46%. Quantitative structure-activity relationship (QSAR) studies on the cytotoxic activity of N-acylsulfonamides toward MCF-7, HCT-116 and HeLa were performed by using topological, ring and charge descriptors based on the stepwise multiple linear regression technique (MLR). The QSAR studies revealed three predictive and statistically significant models for the investigated compounds. The results obtained with these models indicated that the anticancer activity of N-acylsulfonamides depends on topological distances, number of ring system, maximum positive charge and number of atom-centered fragments. The metabolic stability of the selected compounds had been evaluated on pooled human liver microsomes and NADPH, both R¹ and R² substituents of the N-acylsulfonamides simultaneously affected them. PMID:26506328

  12. Design, synthesis and QSAR study of certain isatin-pyridine hybrids as potential anti-proliferative agents.

    PubMed

    Eldehna, Wagdy M; Altoukhy, Ayman; Mahrous, Hoda; Abdel-Aziz, Hatem A

    2015-01-27

    A hybrid pharmacophore approach was adopted to design and synthesize new series of isatin-pyridine hybrids. All the newly prepared hybrids (5a-o, 8 and 11a-d) were in vitro evaluated for their anti-proliferative activity against three human cancer cell lines, namely HepG2 hepatocellular carcinoma, A549 lung cancer and MCF-7 breast cancer. Compound 8 emerged as the most active member against HepG2 cell line (IC50 = 2.5 ± 0.39 μM), with 2.7-fold increased activity than the reference drug, doxorubicin (IC50 = 6.9 ± 2.05 μM). Whilst, compound 11c was found to be the most potent counterpart against A549 and MCF-7 cell lines with IC50 values of 10.8 ± 1.15 and 6.3 ± 0.79, respectively. The weightiness of the utilization of non-cleavable linker, as the chalcone linker, and simplification of the first group, was explored via the SAR study. Furthermore, a QSAR model was built to explore the structural requirements controlling the cytotoxic activities. Notably, the predicted activities by the QSAR model were very close to those experimentally observed, hinting that this model could be safely applied for prediction of more efficacious hits comprising the same skeletal framework. Finally, a theoretical kinetic study was established to predict the ADME of the active hybrids. PMID:25499988

  13. Amino substituted benzimidazo[1,2-a]quinolines: Antiproliferative potency, 3D QSAR study and DNA binding properties.

    PubMed

    Perin, Nataša; Nhili, Raja; Cindrić, Maja; Bertoša, Branimir; Vušak, Darko; Martin-Kleiner, Irena; Laine, William; Karminski-Zamola, Grace; Kralj, Marijeta; David-Cordonnier, Marie-Hélène; Hranjec, Marijana

    2016-10-21

    We describe the synthesis, 3D-derived quantitative structure-activity relationship (QSAR), antiproliferative activity and DNA binding properties of a series of 2-amino, 5-amino and 2,5-diamino substituted benzimidazo[1,2-a]quinolines prepared by environmentally friendly uncatalyzed microwave assisted amination. The antiproliferative activities were assessed in vitro against colon, lung and breast carcinoma cell lines; activities ranged from submicromolar to micromolar. The strongest antiproliferative activity was demonstrated by 2-amino-substituted analogues, whereas 5-amino and or 2,5-diamino substituted derivatives resulted in much less activity. Derivatives bearing 4-methyl- or 3,5-dimethyl-1-piperazinyl substituents emerged as the most active. DNA binding properties and the mode of interaction of chosen substituted benzimidazo[1,2-a]quinolines prepared herein were studied using melting temperature studies, a series of spectroscopic studies (UV/Visible, fluorescence, and circular dichroism), and biochemical experiments (topoisomerase I-mediated DNA relaxation and DNase I footprinting experiments). Both compound 36 and its bis-quaternary iodide salt 37 intercalate between adjacent base pairs of the DNA helix while compound 33 presented a very weak topoisomerase I poisoning activity. A 3D-QSAR analysis was performed to identify hydrogen bonding properties, hydrophobicity, molecular flexibility and distribution of hydrophobic regions as these molecular properties had the highest impact on the antiproliferative activity against the three cell lines. PMID:27448912

  14. 2010 Worldwide Gasification Database

    DOE Data Explorer

    The 2010 Worldwide Gasification Database describes the current world gasification industry and identifies near-term planned capacity additions. The database lists gasification projects and includes information (e.g., plant location, number and type of gasifiers, syngas capacity, feedstock, and products). The database reveals that the worldwide gasification capacity has continued to grow for the past several decades and is now at 70,817 megawatts thermal (MWth) of syngas output at 144 operating plants with a total of 412 gasifiers.

  15. ITS-90 Thermocouple Database

    National Institute of Standards and Technology Data Gateway

    SRD 60 NIST ITS-90 Thermocouple Database (Web, free access)   Web version of Standard Reference Database 60 and NIST Monograph 175. The database gives temperature -- electromotive force (emf) reference functions and tables for the letter-designated thermocouple types B, E, J, K, N, R, S and T. These reference functions have been adopted as standards by the American Society for Testing and Materials (ASTM) and the International Electrotechnical Commission (IEC).

  16. Pharmacophore modeling and atom-based 3D-QSAR studies on amino derivatives of indole as potent isoprenylcysteine carboxyl methyltransferase (Icmt) inhibitors

    NASA Astrophysics Data System (ADS)

    Bhadoriya, Kamlendra Singh; Sharma, Mukesh C.; Jain, Shailesh V.

    2015-02-01

    Icmt enzymes are of particular importance in the post-translational modification of proteins that are involved in the regulation of cell growth. Thus, effective Icmt inhibitors may be of significant therapeutic importance in oncogenesis. To determine the structural requirements responsible for high affinity of previously reported amino derivatives of indole as Icmt inhibitors, a successful pharmacophore generation and atom-based 3D-QSAR analysis have been carried out. The best four-point pharmacophore model with four features HHRR: two hydrophobic groups (H) and two aromatic rings (R) as pharmacophore features was developed by PHASE module of Schrodinger suite. In this study, highly predictive 3D-QSAR models have been developed for Icmt inhibition using HHRR.191 hypothesis. The pharmacophore hypothesis yielded a 3D-QSAR model with good partial least-square (PLS) statistics results. The validation of the PHASE model was done by dividing the dataset into training and test set. The statistically significant the four-point pharmacophore hypothesis yielded a 3D-QSAR model with good PLS statistics results (R2 = 0.9387, Q2 = 0.8132, F = 114.8, SD = 0.1567, RMSE = 0.2682, Pearson-R = 0.9147). The generated model showed excellent predictive power, with a correlation coefficient of Q2 = 0.8132. The results of ligand-based pharmacophore hypothesis and atom-based 3D-QSAR provide detailed structural insights as well as highlights important binding features of novel amino derivatives of indole as Icmt inhibitors which can afford guidance for the rational drug design of novel, potent and promising Icmt inhibitors with enhanced potencies and may prove helpful for further lead optimization and virtual screening.

  17. An integrated QSAR-PBK/D modelling approach for predicting detoxification and DNA adduct formation of 18 acyclic food-borne α,β-unsaturated aldehydes

    SciTech Connect

    Kiwamoto, R. Spenkelink, A.; Rietjens, I.M.C.M.; Punt, A.

    2015-01-01

    Acyclic α,β-unsaturated aldehydes present in food raise a concern because the α,β-unsaturated aldehyde moiety is considered a structural alert for genotoxicity. However, controversy remains on whether in vivo at realistic dietary exposure DNA adduct formation is significant. The aim of the present study was to develop physiologically based kinetic/dynamic (PBK/D) models to examine dose-dependent detoxification and DNA adduct formation of a group of 18 food-borne acyclic α,β-unsaturated aldehydes without 2- or 3-alkylation, and with no more than one conjugated double bond. Parameters for the PBK/D models were obtained using quantitative structure–activity relationships (QSARs) defined with a training set of six selected aldehydes. Using the QSARs, PBK/D models for the other 12 aldehydes were defined. Results revealed that DNA adduct formation in the liver increases with decreasing bulkiness of the molecule especially due to less efficient detoxification. 2-Propenal (acrolein) was identified to induce the highest DNA adduct levels. At realistic dietary intake, the predicted DNA adduct levels for all aldehydes were two orders of magnitude lower than endogenous background levels observed in disease free human liver, suggesting that for all 18 aldehydes DNA adduct formation is negligible at the relevant levels of dietary intake. The present study provides a proof of principle for the use of QSAR-based PBK/D modelling to facilitate group evaluations and read-across in risk assessment. - Highlights: • Physiologically based in silico models were made for 18 α,β-unsaturated aldehydes. • Kinetic parameters were determined by in vitro incubations and a QSAR approach. • DNA adduct formation was negligible at levels relevant for dietary intake. • The use of QSAR-based PBK/D modelling facilitates group evaluations and read-across.

  18. Opening CEM vendor databases

    SciTech Connect

    Long, A.; Patel, D.

    1995-12-31

    CEM database performance requirements (i.e., voluminous data storage, rapid response times) often conflict with the concept of an open, accessible database. Utilities would like to use their CEM data for more purposes than simply submitting environmental reports. But in most cases, other uses are inhibited because today`s sophisticated CEM systems incorporate databases that have forsaken openness and accessibility in favor of performance. Several options are available for CEM vendors wishing to move in the direction of open, accessible CEM databases.

  19. Databases for Microbiologists

    PubMed Central

    2015-01-01

    Databases play an increasingly important role in biology. They archive, store, maintain, and share information on genes, genomes, expression data, protein sequences and structures, metabolites and reactions, interactions, and pathways. All these data are critically important to microbiologists. Furthermore, microbiology has its own databases that deal with model microorganisms, microbial diversity, physiology, and pathogenesis. Thousands of biological databases are currently available, and it becomes increasingly difficult to keep up with their development. The purpose of this minireview is to provide a brief survey of current databases that are of interest to microbiologists. PMID:26013493

  20. Veterans Administration Databases

    Cancer.gov

    The Veterans Administration Information Resource Center provides database and informatics experts, customer service, expert advice, information products, and web technology to VA researchers and others.

  1. Backing up DMF Databases

    NASA Technical Reports Server (NTRS)

    Cardo, Nicholas P.; Woodrow, Thomas (Technical Monitor)

    1994-01-01

    A complete backup of the Cray Data Migration Facility (DMF) databases should include the data migration databases, all media specific process' (MSP's) databases, and the journal file. The backup should be able to accomplished without impacting users or stopping DMF. The High Speed Processors group at the Numerical Aerodynamics Simulation (NAS) Facility at NASA Ames Research Center undertook the task of finding an effective and efficient way to backup all DMF databases. This has been accomplished by taking advantage of new features introduced in DMF 2.0 and adding a minor modification to the dmdaemon. This paper discusses the investigation and the changes necessary to implement these enhancements.

  2. House dust in seven Danish offices

    NASA Astrophysics Data System (ADS)

    Mølhave, L.; Schneider, T.; Kjærgaard, S. K.; Larsen, L.; Norn, S.; Jørgensen, O.

    Floor dust from Danish offices was collected and analyzed. The dust was to be used in an exposure experiment. The dust was analyzed to show the composition of the dust which can be a source of airborne dust indoors. About 11 kg of dust from vacuum cleaner bags from seven Danish office buildings with about 1047 occupants (12 751 m 2) was processed according to a standardized procedure yielding 5.5 kg of processed bulk dust. The bulk dust contained 130.000-160.000 CFU g -1 microorganisms and 71.000-90.000 CFU g -1 microfungi. The content of culturable microfungi was 65-123 CFU 30 g -1 dust. The content of endotoxins ranged from 5.06-7.24 EU g -1 (1.45 ng g -1 to 1.01 ng g -1). Allergens (ng g -1) were from 147-159 (Mite), 395-746 (dog) and 103-330 (cat). The macro molecular organic compounds (the MOD-content) varied from 7.8-9.8 mg g -1. The threshold of release of histamine from basophil leukocytes provoked by the bulk dust was between 0.3 and 1.0 mg ml -1. The water content was 2% (WGT) and the organic fraction 33%. 6.5-5.9% (dry) was water soluble. The fiber content was less than 0.2-1.5% (WGT) and the desorbable VOCs was 176-319 μg g -1. Most of the VOC were aldehydes. However, softeners for plastic (DBP and DEHP) were present. The chemical composition includes human and animal skin fragments, paper fibers, glass wool, wood and textilefibers and inorganic and metal particles. The sizes ranged from 0.001-1 mm and the average specific density was 1.0 g m -3. The bulk dust was resuspended and injected into an exposure chamber. The airborne dust was sampled and analyzed to illustrate the exposures that can result from sedimented dirt and dust. The airborne dust resulting from the bulk dust reached concentrations ranging from 0.26-0.75 mg m -3 in average contained 300-170 CFU m -3. The organic fraction was from 55-70% and the water content about 2.5% (WGT). The content of the dust was compared to the similar results reported in the literature and its toxic potency is

  3. A register-based study of the antimicrobial usage in Danish veal calves and young bulls.

    PubMed

    Fertner, Mette; Toft, Nils; Martin, Henrik Læssøe; Boklund, Anette

    2016-09-01

    High antimicrobial usage and multidrug resistance have been reported in veal calves in Europe. This may be attributed to a high risk of disease as veal calves are often purchased from numerous dairy herds, exposed to stress related to the transport and commingling of new animals, and fed a new ration. In this study, we used national register data to characterize the use of antimicrobials registered for large Danish veal calf and young bull producing herds in 2014. A total of 325 herds with veal calf and potentially young bull production were identified from the Danish Cattle database. According to the national Danish database on drugs for veterinary use (VetStat), a total of 537,399 Animal Daily Doses (ADD200) were registered for these 325 herds during 2014. The amount of antimicrobials registered in 2014 varied throughout the year, with the highest amounts registered in autumn and winter. Antimicrobials were registered for respiratory disorders (79%), joints/limbs/CNS disorders (17%), gastrointestinal disorders (3.7%) and other disorders (0.3%). Of the registered antimicrobials, 15% were for oral and 85% for parenteral administration. Long-acting formulations with a therapeutic effect of more than 48h covered 58% of the drugs for parenteral use. Standardized at the herd-level, as ADD200/100 calves/day, antimicrobial use distributed as median [CI95%] for starter herds (n=22): 2.14 [0.19;7.58], finisher herds (n=24): 0.48 [0.00;1.48], full-line herds (n=183): 0.78 [0.05;2.20] and herds with an inconsistent pattern of movements (n=96): 0.62 [0.00;2.24]. Full-line herds are herds, which purchase calves directly from a dairy herd and raise them to slaughter. Furthermore, we performed a risk factor analysis on the 183 herds with a full-line production. Here, we investigated, whether the number of suppliers, the number of calves purchased, the frequency of purchase, the average age at introduction, the average time in the herd and vaccination influenced the amount of

  4. Occurrence of Ionophores in the Danish Environment

    PubMed Central

    Bak, Søren Alex; Björklund, Erland

    2014-01-01

    Antibiotics in the environment are a potential threat to environmental ecosystems as well as human health and safety. Antibiotics are designed to have a biological effect at low doses, and the low levels detected in the environment have turned focus on the need for more research on environmental occurrence and fate, to assess the risk and requirement for future regulation. This article describes the first occurrence study of the antibiotic polyether ionophores (lasalocid, monensin, narasin, and salinomycin) in the Danish environment. Various environmental matrices (river water, sediment, and soil) have been evaluated during two different sampling campaigns carried out in July 2011 and October 2012 in an agricultural area of Zealand, Denmark. Lasalocid was not detected in any of the samples. Monensin was measured at a concentration up to 20 ng·L−1 in river water and 13 µg·kg−1 dry weight in the sediment as well as being the most frequently detected ionophore in the soil samples with concentrations up to 8 µg·kg−1 dry weight. Narasin was measured in sediment samples at 2 µg·kg−1 dry weight and in soil between 1 and 18 µg·kg−1 dry weight. Salinomycin was detected in a single soil sample at a concentration of 30 µg·kg−1 dry weight.

  5. Atomic Spectra Database (ASD)

    National Institute of Standards and Technology Data Gateway

    SRD 78 NIST Atomic Spectra Database (ASD) (Web, free access)   This database provides access and search capability for NIST critically evaluated data on atomic energy levels, wavelengths, and transition probabilities that are reasonably up-to-date. The NIST Atomic Spectroscopy Data Center has carried out these critical compilations.

  6. CDS - Database Administrator's Guide

    NASA Astrophysics Data System (ADS)

    Day, J. P.

    This guide aims to instruct the CDS database administrator in: o The CDS file system. o The CDS index files. o The procedure for assimilating a new CDS tape into the database. It is assumed that the administrator has read SUN/79.

  7. Ionic Liquids Database- (ILThermo)

    National Institute of Standards and Technology Data Gateway

    SRD 147 Ionic Liquids Database- (ILThermo) (Web, free access)   IUPAC Ionic Liquids Database, ILThermo, is a free web research tool that allows users worldwide to access an up-to-date data collection from the publications on experimental investigations of thermodynamic, and transport properties of ionic liquids as well as binary and ternary mixtures containing ionic liquids.

  8. Database Searching by Managers.

    ERIC Educational Resources Information Center

    Arnold, Stephen E.

    Managers and executives need the easy and quick access to business and management information that online databases can provide, but many have difficulty articulating their search needs to an intermediary. One possible solution would be to encourage managers and their immediate support staff members to search textual databases directly as they now…

  9. Morchella MLST database

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Welcome to the Morchella MLST database. This dedicated database was set up at the CBS-KNAW Biodiversity Center by Vincent Robert in February 2012, using BioloMICS software (Robert et al., 2011), to facilitate DNA sequence-based identifications of Morchella species via the Internet. The current datab...

  10. First Look: TRADEMARKSCAN Database.

    ERIC Educational Resources Information Center

    Fernald, Anne Conway; Davidson, Alan B.

    1984-01-01

    Describes database produced by Thomson and Thomson and available on Dialog which contains over 700,000 records representing all active federal trademark registrations and applications for registrations filed in United States Patent and Trademark Office. A typical record, special features, database applications, learning to use TRADEMARKSCAN, and…

  11. HIV Structural Database

    National Institute of Standards and Technology Data Gateway

    SRD 102 HIV Structural Database (Web, free access)   The HIV Protease Structural Database is an archive of experimentally determined 3-D structures of Human Immunodeficiency Virus 1 (HIV-1), Human Immunodeficiency Virus 2 (HIV-2) and Simian Immunodeficiency Virus (SIV) Proteases and their complexes with inhibitors or products of substrate cleavage.

  12. Biological Macromolecule Crystallization Database

    National Institute of Standards and Technology Data Gateway

    SRD 21 Biological Macromolecule Crystallization Database (Web, free access)   The Biological Macromolecule Crystallization Database and NASA Archive for Protein Crystal Growth Data (BMCD) contains the conditions reported for the crystallization of proteins and nucleic acids used in X-ray structure determinations and archives the results of microgravity macromolecule crystallization studies.

  13. Assignment to database industy

    NASA Astrophysics Data System (ADS)

    Abe, Kohichiroh

    Various kinds of databases are considered to be essential part in future large sized systems. Information provision only by databases is also considered to be growing as the market becomes mature. This paper discusses how such circumstances have been built and will be developed from now on.

  14. Dictionary as Database.

    ERIC Educational Resources Information Center

    Painter, Derrick

    1996-01-01

    Discussion of dictionaries as databases focuses on the digitizing of The Oxford English dictionary (OED) and the use of Standard Generalized Mark-Up Language (SGML). Topics include the creation of a consortium to digitize the OED, document structure, relational databases, text forms, sequence, and discourse. (LRW)

  15. A Quality System Database

    NASA Technical Reports Server (NTRS)

    Snell, William H.; Turner, Anne M.; Gifford, Luther; Stites, William

    2010-01-01

    A quality system database (QSD), and software to administer the database, were developed to support recording of administrative nonconformance activities that involve requirements for documentation of corrective and/or preventive actions, which can include ISO 9000 internal quality audits and customer complaints.

  16. BioImaging Database

    Energy Science and Technology Software Center (ESTSC)

    2006-10-25

    The Biolmaging Database (BID) is a relational database developed to store the data and meta-data for the 3D gene expression in early Drosophila embryo development on a cellular level. The schema was written to be used with the MySQL DBMS but with minor modifications can be used on any SQL compliant relational DBMS.

  17. The intelligent database machine

    NASA Technical Reports Server (NTRS)

    Yancey, K. E.

    1985-01-01

    The IDM data base was compared with the data base crack to determine whether IDM 500 would better serve the needs of the MSFC data base management system than Oracle. The two were compared and the performance of the IDM was studied. Implementations that work best on which database are implicated. The choice is left to the database administrator.

  18. Build Your Own Database.

    ERIC Educational Resources Information Center

    Jacso, Peter; Lancaster, F. W.

    This book is intended to help librarians and others to produce databases of better value and quality, especially if they have had little previous experience in database construction. Drawing upon almost 40 years of experience in the field of information retrieval, this book emphasizes basic principles and approaches rather than in-depth and…

  19. Database Reviews: Legal Information.

    ERIC Educational Resources Information Center

    Seiser, Virginia

    Detailed reviews of two legal information databases--"Laborlaw I" and "Legal Resource Index"--are presented in this paper. Each database review begins with a bibliographic entry listing the title; producer; vendor; cost per hour contact time; offline print cost per citation; time period covered; frequency of updates; and size of file. A detailed…

  20. Database in Artificial Intelligence.

    ERIC Educational Resources Information Center

    Wilkinson, Julia

    1986-01-01

    Describes a specialist bibliographic database of literature in the field of artificial intelligence created by the Turing Institute (Glasgow, Scotland) using the BRS/Search information retrieval software. The subscription method for end-users--i.e., annual fee entitles user to unlimited access to database, document provision, and printed awareness…

  1. Structural Ceramics Database

    National Institute of Standards and Technology Data Gateway

    SRD 30 NIST Structural Ceramics Database (Web, free access)   The NIST Structural Ceramics Database (WebSCD) provides evaluated materials property data for a wide range of advanced ceramics known variously as structural ceramics, engineering ceramics, and fine ceramics.

  2. National Vulnerability Database (NVD)

    National Institute of Standards and Technology Data Gateway

    National Vulnerability Database (NVD) (Web, free access)   NVD is a comprehensive cyber security vulnerability database that integrates all publicly available U.S. Government vulnerability resources and provides references to industry resources. It is based on and synchronized with the CVE vulnerability naming standard.

  3. Knowledge Discovery in Databases.

    ERIC Educational Resources Information Center

    Norton, M. Jay

    1999-01-01

    Knowledge discovery in databases (KDD) revolves around the investigation and creation of knowledge, processes, algorithms, and mechanisms for retrieving knowledge from data collections. The article is an introductory overview of KDD. The rationale and environment of its development and applications are discussed. Issues related to database design…

  4. Online Database Searching Workbook.

    ERIC Educational Resources Information Center

    Littlejohn, Alice C.; Parker, Joan M.

    Designed primarily for use by first-time searchers, this workbook provides an overview of online searching. Following a brief introduction which defines online searching, databases, and database producers, five steps in carrying out a successful search are described: (1) identifying the main concepts of the search statement; (2) selecting a…

  5. CPDB: Carcinogenic Potency Database.

    PubMed

    Fitzpatrick, Roberta Bronson

    2008-01-01

    The Carcinogenic Potency Database reports analyses of animal cancer tests on 1,547 chemicals. These tests are used in support of cancer risk assessments for humans. Results are searchable and are made available via the National Library of Medicine's (NLM) TOXNET system. This column will provide background information on the database, as well as present search basics. PMID:19042710

  6. Probing the origins of human acetylcholinesterase inhibition via QSAR modeling and molecular docking.

    PubMed

    Simeon, Saw; Anuwongcharoen, Nuttapat; Shoombuatong, Watshara; Malik, Aijaz Ahmad; Prachayasittikul, Virapong; Wikberg, Jarl E S; Nantasenamat, Chanin

    2016-01-01

    Alzheimer's disease (AD) is a chronic neurodegenerative disease which leads to the gradual loss of neuronal cells. Several hypotheses for AD exists (e.g., cholinergic, amyloid, tau hypotheses, etc.). As per the cholinergic hypothesis, the deficiency of choline is responsible for AD; therefore, the inhibition of AChE is a lucrative therapeutic strategy for the treatment of AD. Acetylcholinesterase (AChE) is an enzyme that catalyzes the breakdown of the neurotransmitter acetylcholine that is essential for cognition and memory. A large non-redundant data set of 2,570 compounds with reported IC50 values against AChE was obtained from ChEMBL and employed in quantitative structure-activity relationship (QSAR) study so as to gain insights on their origin of bioactivity. AChE inhibitors were described by a set of 12 fingerprint descriptors and predictive models were constructed from 100 different data splits using random forest. Generated models afforded R (2), [Formula: see text] and [Formula: see text] values in ranges of 0.66-0.93, 0.55-0.79 and 0.56-0.81 for the training set, 10-fold cross-validated set and external set, respectively. The best model built using the substructure count was selected according to the OECD guidelines and it afforded R (2), [Formula: see text] and [Formula: see text] values of 0.92 ± 0.01, 0.78 ± 0.06 and 0.78 ± 0.05, respectively. Furthermore, Y-scrambling was applied to evaluate the possibility of chance correlation of the predictive model. Subsequently, a thorough analysis of the substructure fingerprint count was conducted to provide informative insights on the inhibitory activity of AChE inhibitors. Moreover, Kennard-Stone sampling of the actives were applied to select 30 diverse compounds for further molecular docking studies in order to gain structural insights on the origin of AChE inhibition. Site-moiety mapping of compounds from the diversity set revealed three binding anchors encompassing both hydrogen bonding and van der Waals

  7. Cascadia Tsunami Deposit Database

    USGS Publications Warehouse

    Peters, Robert; Jaffe, Bruce; Gelfenbaum, Guy; Peterson, Curt

    2003-01-01

    The Cascadia Tsunami Deposit Database contains data on the location and sedimentological properties of tsunami deposits found along the Cascadia margin. Data have been compiled from 52 studies, documenting 59 sites from northern California to Vancouver Island, British Columbia that contain known or potential tsunami deposits. Bibliographical references are provided for all sites included in the database. Cascadia tsunami deposits are usually seen as anomalous sand layers in coastal marsh or lake sediments. The studies cited in the database use numerous criteria based on sedimentary characteristics to distinguish tsunami deposits from sand layers deposited by other processes, such as river flooding and storm surges. Several studies cited in the database contain evidence for more than one tsunami at a site. Data categories include age, thickness, layering, grainsize, and other sedimentological characteristics of Cascadia tsunami deposits. The database documents the variability observed in tsunami deposits found along the Cascadia margin.

  8. Protein sequence databases.

    PubMed

    Apweiler, Rolf; Bairoch, Amos; Wu, Cathy H

    2004-02-01

    A variety of protein sequence databases exist, ranging from simple sequence repositories, which store data with little or no manual intervention in the creation of the records, to expertly curated universal databases that cover all species and in which the original sequence data are enhanced by the manual addition of further information in each sequence record. As the focus of researchers moves from the genome to the proteins encoded by it, these databases will play an even more important role as central comprehensive resources of protein information. Several the leading protein sequence databases are discussed here, with special emphasis on the databases now provided by the Universal Protein Knowledgebase (UniProt) consortium. PMID:15036160

  9. 3D QSAR and molecular docking studies of benzimidazole derivatives as hepatitis C virus NS5B polymerase inhibitors.

    PubMed

    Patel, Pallav D; Patel, Maulik R; Kaushik-Basu, Neerja; Talele, Tanaji T

    2008-01-01

    The urgent need for novel HCV antiviral agents has provided an impetus for understanding the structural requisites of NS5B polymerase inhibitors at the molecular level. Toward this objective, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) of 67 HCV NS5B polymerase inhibitors were performed using two methods. First, ligand-based 3D QSAR studies were performed based on the lowest energy conformations employing the atom fit alignment method. Second, receptor-based 3D QSAR models were derived from the predicted binding conformations obtained by docking all NS5B inhibitors at the allosteric binding site of NS5B (PDB ID: 2dxs). Results generated from the ligand-based model were found superior (r2cv values of 0.630 for CoMFA and 0.668 for CoMSIA) to those obtained by the receptor-based model (r2cv values of 0.536 and 0.561 for CoMFA and CoMSIA, respectively). The predictive ability of the models was validated using a structurally diversified test set of 22 compounds that had not been included in a preliminary training set of 45 compounds. The predictive r2 values for the ligand-based CoMFA and CoMSIA models were 0.734 and 0.800, respectively, while the corresponding predictive r2 values for the receptor-based CoMFA and CoMSIA models were 0.538 and 0.639, respectively. The greater potency of the tryptophan derivatives over that of the tyrosine derivatives was interpreted based on CoMFA steric and electrostatic contour maps. The CoMSIA results revealed that for a NS5B inhibitor to have appreciable inhibitory activity it requires hydrogen bond donor and acceptor groups at the 5-position of the indole ring and an R substituent at the chiral carbon, respectively. Interpretation of the CoMFA and CoMSIA contour maps in context of the topology of the allosteric binding site of NS5B provided insight into NS5B-inhibitor interactions. Taken together, the present 3D QSAR models were found to accurately predict the HCV NS5B

  10. Electron-correlation based externally predictive QSARs for mutagenicity of nitrated-PAHs in Salmonella typhimurium TA100.

    PubMed

    Reenu; Vikas

    2014-03-01

    In quantitative modeling, there are two major aspects that decide reliability and real external predictivity of a structure-activity relationship (SAR) based on quantum chemical descriptors. First, the information encoded in employed molecular descriptors, computed through a quantum-mechanical method, should be precisely estimated. The accuracy of the quantum-mechanical method, however, is dependent upon the amount of electron-correlation it incorporates. Second, the real external predictivity of a developed quantitative SAR (QSAR) should be validated employing an external prediction set. In this work, to analyze the role of electron-correlation, QSAR models are developed for a set of 51 ubiquitous pollutants, namely, nitrated monocyclic and polycyclic aromatic hydrocarbons (nitrated-AHs and PAHs) having mutagenic activity in TA100 strain of Salmonella typhimurium. The quality of the models, through state-of-the-art external validation procedures employing an external prediction set, is compared to the best models known in the literature for mutagenicity. The molecular descriptors whose electron-correlation contribution is analyzed include total energy, energy of HOMO and LUMO, and commonly employed electron-density based descriptors such as chemical hardness, chemical softness, absolute electronegativity and electrophilicity index. The electron-correlation based QSARs are also compared with those developed using quantum-mechanical descriptors computed with advanced semi-empirical (SE) methods such as PM6, PM7, RM1, and ab initio methods, namely, the Hartree-Fock (HF) and the density functional theory (DFT). The models, developed using electron-correlation contribution of the quantum-mechanical descriptors, are found to be not only reliable but also satisfactorily predictive when compared to the existing robust models. The robustness of the models based on descriptors computed through advanced SE methods, is also observed to be comparable to those developed with

  11. Parameters for pyrethroid insecticide QSAR and PBPK/PD models for human risk assessment.

    PubMed

    Knaak, James B; Dary, Curtis C; Zhang, Xiaofei; Gerlach, Robert W; Tornero-Velez, R; Chang, Daniel T; Goldsmith, Rocky; Blancato, Jerry N

    2012-01-01

    In this review we have examined the status of parameters required by pyrethroid QSAR-PBPK/PD models for assessing health risks. In lieu of the chemical,biological, biochemical, and toxicological information developed on the pyrethroids since 1968, the finding of suitable parameters for QSAR and PBPK/PD model development was a monumental task. The most useful information obtained came from rat toxicokinetic studies (i.e., absorption, distribution, and excretion), metabolism studies with 14C-cyclopropane- and alcohol-labeled pyrethroids, the use of known chiral isomers in the metabolism studies and their relation to commercial products. In this review we identify the individual chiralisomers that have been used in published studies and the chiral HPLC columns available for separating them. Chiral HPLC columns are necessary for isomer identification and for developing kinetic values (Vm,, and Kin) for pyrethroid hydroxylation. Early investigators synthesized analytical standards for key pyrethroid metabolites, and these were used to confirm the identity of urinary etabolites, by using TLC. These analytical standards no longer exist, and muste resynthesized if further studies on the kinetics of the metabolism of pyrethroids are to be undertaken.In an attempt to circumvent the availability of analytical standards, several CYP450 studies were carried out using the substrate depletion method. This approach does not provide information on the products formed downstream, and may be of limited use in developing human environmental exposure PBPK/PD models that require extensive urinary metabolite data. Hydrolytic standards (i.e., alcohols and acids) were available to investigators who studied the carboxylesterase-catalyzed hydrolysis of several pyrethroid insecticides. The data generated in these studies are suitable for use in developing human exposure PBPK/PD models.Tissue:blood partition coefficients were developed for the parent pyrethroids and their metabolites, by using

  12. Hazard Analysis Database Report

    SciTech Connect

    GRAMS, W.H.

    2000-12-28

    The Hazard Analysis Database was developed in conjunction with the hazard analysis activities conducted in accordance with DOE-STD-3009-94, Preparation Guide for U S . Department of Energy Nonreactor Nuclear Facility Safety Analysis Reports, for HNF-SD-WM-SAR-067, Tank Farms Final Safety Analysis Report (FSAR). The FSAR is part of the approved Authorization Basis (AB) for the River Protection Project (RPP). This document describes, identifies, and defines the contents and structure of the Tank Farms FSAR Hazard Analysis Database and documents the configuration control changes made to the database. The Hazard Analysis Database contains the collection of information generated during the initial hazard evaluations and the subsequent hazard and accident analysis activities. The Hazard Analysis Database supports the preparation of Chapters 3 ,4 , and 5 of the Tank Farms FSAR and the Unreviewed Safety Question (USQ) process and consists of two major, interrelated data sets: (1) Hazard Analysis Database: Data from the results of the hazard evaluations, and (2) Hazard Topography Database: Data from the system familiarization and hazard identification.

  13. PADB : Published Association Database

    PubMed Central

    Rhee, Hwanseok; Lee, Jin-Sung

    2007-01-01

    Background Although molecular pathway information and the International HapMap Project data can help biomedical researchers to investigate the aetiology of complex diseases more effectively, such information is missing or insufficient in current genetic association databases. In addition, only a few of the environmental risk factors are included as gene-environment interactions, and the risk measures of associations are not indexed in any association databases. Description We have developed a published association database (PADB; ) that includes both the genetic associations and the environmental risk factors available in PubMed database. Each genetic risk factor is linked to a molecular pathway database and the HapMap database through human gene symbols identified in the abstracts. And the risk measures such as odds ratios or hazard ratios are extracted automatically from the abstracts when available. Thus, users can review the association data sorted by the risk measures, and genetic associations can be grouped by human genes or molecular pathways. The search results can also be saved to tab-delimited text files for further sorting or analysis. Currently, PADB indexes more than 1,500,000 PubMed abstracts that include 3442 human genes, 461 molecular pathways and about 190,000 risk measures ranging from 0.00001 to 4878.9. Conclusion PADB is a unique online database of published associations that will serve as a novel and powerful resource for reviewing and interpreting huge association data of complex human diseases. PMID:17877839

  14. ResPlan Database

    NASA Technical Reports Server (NTRS)

    Zellers, Michael L.

    2003-01-01

    The main project I was involved in was new application development for the existing CIS0 Database (ResPlan). This database application was developed in Microsoft Access. Initial meetings with Greg Follen, Linda McMillen, Griselle LaFontaine and others identified a few key weaknesses with the existing database. The weaknesses centered around that while the database correctly modeled the structure of Programs, Projects and Tasks, once the data was entered, the database did not capture any dynamic status information, and as such was of limited usefulness. After the initial meetings my goals were identified as follows: Enhance the ResPlan Database to include qualitative and quantitative status information about the Programs, Projects and Tasks Train staff members about the ResPlan database from both the user perspective and the developer perspective Give consideration to a Web Interface for reporting. Initially, the thought was that there would not be adequate time to actually develop the Web Interface, Greg wanted it understood that this was an eventual goal and as such should be a consideration throughout the development process.

  15. Hazard Analysis Database Report

    SciTech Connect

    GAULT, G.W.

    1999-10-13

    The Hazard Analysis Database was developed in conjunction with the hazard analysis activities conducted in accordance with DOE-STD-3009-94, Preparation Guide for US Department of Energy Nonreactor Nuclear Facility Safety Analysis Reports, for the Tank Waste Remediation System (TWRS) Final Safety Analysis Report (FSAR). The FSAR is part of the approved TWRS Authorization Basis (AB). This document describes, identifies, and defines the contents and structure of the TWRS FSAR Hazard Analysis Database and documents the configuration control changes made to the database. The TWRS Hazard Analysis Database contains the collection of information generated during the initial hazard evaluations and the subsequent hazard and accident analysis activities. The database supports the preparation of Chapters 3,4, and 5 of the TWRS FSAR and the USQ process and consists of two major, interrelated data sets: (1) Hazard Evaluation Database--Data from the results of the hazard evaluations; and (2) Hazard Topography Database--Data from the system familiarization and hazard identification.

  16. Database for propagation models

    NASA Technical Reports Server (NTRS)

    Kantak, Anil V.

    1991-01-01

    A propagation researcher or a systems engineer who intends to use the results of a propagation experiment is generally faced with various database tasks such as the selection of the computer software, the hardware, and the writing of the programs to pass the data through the models of interest. This task is repeated every time a new experiment is conducted or the same experiment is carried out at a different location generating different data. Thus the users of this data have to spend a considerable portion of their time learning how to implement the computer hardware and the software towards the desired end. This situation may be facilitated considerably if an easily accessible propagation database is created that has all the accepted (standardized) propagation phenomena models approved by the propagation research community. Also, the handling of data will become easier for the user. Such a database construction can only stimulate the growth of the propagation research it if is available to all the researchers, so that the results of the experiment conducted by one researcher can be examined independently by another, without different hardware and software being used. The database may be made flexible so that the researchers need not be confined only to the contents of the database. Another way in which the database may help the researchers is by the fact that they will not have to document the software and hardware tools used in their research since the propagation research community will know the database already. The following sections show a possible database construction, as well as properties of the database for the propagation research.

  17. The Gaia Parameter Database

    NASA Astrophysics Data System (ADS)

    de Bruijne, J. H. J.; Lammers, U.; Perryman, M. A. C.

    2005-01-01

    The parallel development of many aspects of a complex mission like Gaia, which includes numerous participants in ESA, industrial companies, and a large and active scientific collaboration throughout Europe, makes keeping track of the many design changes, instrument and operational complexities, and numerical values for the data analysis a very challenging problem. A comprehensive, easily-accessible, up-to-date, and definitive compilation of a large range of numerical quantities is required, and the Gaia parameter database has been established to satisfy these needs. The database is a centralised repository containing, besides mathematical, physical, and astronomical constants, many satellite and subsystem design parameters. At the end of 2004, more than 1600 parameters had been included. Version control has been implemented, providing, next to a `live' version with the most recent parameters, well-defined reference versions of the full database contents. The database can be queried or browsed using a regular Web browser (http://www.rssd.esa.int/Gaia/paramdb). Query results are formated by default in HTML. Data can also be retrieved as Fortran-77, Fortran-90, Java, ANSIC, C++, or XML structures for direct inclusion into software codes in these languages. The idea is that all collaborating scientists can use the database parameters and values, once retrieved, directly linked to computational routines. An off-line access mode is also available, enabling users to automatically download the contents of the database. The database will be maintained actively, and significant extensions of the contents are planned. Consistent use in the future of the database by the Gaia community at large, including all industrial teams, will ensure correct numerical values throughout the complex software systems being built up as details of the Gaia design develop. The database is already being used for the telemetry simulation chain in ESTEC, and in the data simulations for GDAAS2.

  18. HP-Lattice QSAR for dynein proteins: experimental proteomics (2D-electrophoresis, mass spectrometry) and theoretic study of a Leishmania infantum sequence.

    PubMed

    Dea-Ayuela, María Auxiliadora; Pérez-Castillo, Yunierkis; Meneses-Marcel, Alfredo; Ubeira, Florencio M; Bolas-Fernández, Francisco; Chou, Kuo-Chen; González-Díaz, Humberto

    2008-08-15

    The toxicity and inefficacy of actual organic drugs against Leishmaniosis justify research projects to find new molecular targets in Leishmania species including Leishmania infantum (L. infantum) and Leishmaniamajor (L. major), both important pathogens. In this sense, quantitative structure-activity relationship (QSAR) methods, which are very useful in Bioorganic and Medicinal Chemistry to discover small-sized drugs, may help to identify not only new drugs but also new drug targets, if we apply them to proteins. Dyneins are important proteins of these parasites governing fundamental processes such as cilia and flagella motion, nuclear migration, organization of the mitotic splinde, and chromosome separation during mitosis. However, despite the interest for them as potential drug targets, so far there has been no report whatsoever on dyneins with QSAR techniques. To the best of our knowledge, we report here the first QSAR for dynein proteins. We used as input the Spectral Moments of a Markov matrix associated to the HP-Lattice Network of the protein sequence. The data contain 411 protein sequences of different species selected by ClustalX to develop a QSAR that correctly discriminates on average between 92.75% and 92.51% of dyneins and other proteins in four different train and cross-validation datasets. We also report a combined experimental and theoretic study of a new dynein sequence in order to illustrate the utility of the model to search for potential drug targets with a practical example. First, we carried out a 2D-electrophoresis analysis of L. infantum biological samples. Next, we excised from 2D-E gels one spot of interest belonging to an unknown protein or protein fragment in the region M<20,200 and pI<4. We used MASCOT search engine to find proteins in the L. major data base with the highest similarity score to the MS of the protein isolated from L. infantum. We used the QSAR model to predict the new sequence as dynein with probability of 99.99% without

  19. Human variation databases

    PubMed Central

    Küntzer, Jan; Eggle, Daniela; Klostermann, Stefan; Burtscher, Helmut

    2010-01-01

    More than 100 000 human genetic variations have been described in various genes that are associated with a wide variety of diseases. Such data provides invaluable information for both clinical medicine and basic science. A number of locus-specific databases have been developed to exploit this huge amount of data. However, the scope, format and content of these databases differ strongly and as no standard for variation databases has yet been adopted, the way data is presented varies enormously. This review aims to give an overview of current resources for human variation data in public and commercial resources. PMID:20639550

  20. International Comparisions Database

    National Institute of Standards and Technology Data Gateway

    International Comparisions Database (Web, free access)   The International Comparisons Database (ICDB) serves the U.S. and the Inter-American System of Metrology (SIM) with information based on Appendices B (International Comparisons), C (Calibration and Measurement Capabilities) and D (List of Participating Countries) of the Comit� International des Poids et Mesures (CIPM) Mutual Recognition Arrangement (MRA). The official source of the data is The BIPM key comparison database. The ICDB provides access to results of comparisons of measurements and standards organized by the consultative committees of the CIPM and the Regional Metrology Organizations.

  1. Hybrid Terrain Database

    NASA Technical Reports Server (NTRS)

    Arthur, Trey

    2006-01-01

    A prototype hybrid terrain database is being developed in conjunction with other databases and with hardware and software that constitute subsystems of aerospace cockpit display systems (known in the art as synthetic vision systems) that generate images to increase pilots' situation awareness and eliminate poor visibility as a cause of aviation accidents. The basic idea is to provide a clear view of the world around an aircraft by displaying computer-generated imagery derived from an onboard database of terrain, obstacle, and airport information.

  2. Phase Equilibria Diagrams Database

    National Institute of Standards and Technology Data Gateway

    SRD 31 NIST/ACerS Phase Equilibria Diagrams Database (PC database for purchase)   The Phase Equilibria Diagrams Database contains commentaries and more than 21,000 diagrams for non-organic systems, including those published in all 21 hard-copy volumes produced as part of the ACerS-NIST Phase Equilibria Diagrams Program (formerly titled Phase Diagrams for Ceramists): Volumes I through XIV (blue books); Annuals 91, 92, 93; High Tc Superconductors I & II; Zirconium & Zirconia Systems; and Electronic Ceramics I. Materials covered include oxides as well as non-oxide systems such as chalcogenides and pnictides, phosphates, salt systems, and mixed systems of these classes.

  3. JICST Factual Database(2)

    NASA Astrophysics Data System (ADS)

    Araki, Keisuke

    The computer programme, which builds atom-bond connection tables from nomenclatures, is developed. Chemical substances with their nomenclature and varieties of trivial names or experimental code numbers are inputted. The chemical structures of the database are stereospecifically stored and are able to be searched and displayed according to stereochemistry. Source data are from laws and regulations of Japan, RTECS of US and so on. The database plays a central role within the integrated fact database service of JICST and makes interrelational retrieval possible.

  4. Databases for materials selection

    SciTech Connect

    1996-06-01

    The Cambridge Materials Selector (CMS2.0) materials database was developed by the Engineering Dept. at Cambridge University in the United Kingdom. This database makes it possible to select a material for a specific application from essentially all classes of materials. Genera, Predict, and Socrates software programs from CLI International, Houston, Texas, automate materials selection and corrosion problem-solving tasks. They are said to significantly reduce the time necessary to select a suitable material and/or to assess a corrosion problem and reach cost-effective solutions. This article describes both databases and tells how to use them.

  5. Visual impairment in Danish children 1985.

    PubMed

    Rosenberg, T

    1987-02-01

    In 1985 150 children aged 0-18 were reported to the Danish National Register for Visually Impaired Children. Cross tabulation of the ophthalmological diagnoses by site and type of affection was performed with respect to year of birth, aetiology, visual acuity and birth weight. Finally the relations between aetiology and the presence of additional handicaps are demonstrated. The 'incidence of notification' (IN) was calculated for each birth year as the number of notified children per 100,000 within each birth year group showing variations between 46 in the 1984 birth year group and 3 in the 1970 birth year group with a mean value of 14. The figures stress the impact of congenital and neonatal visual impairment. The significance of IN is discussed with respect to other concepts of incidence. It is concluded that the presented epidemiological method is useful as a tool of analysis in the planning of preventional strategies. From the tables the following main features may be highlighted: Nearly 90% of the blinding causes anatomically are located in the posterior segment of the eye, the optic pathways or in the brain. Isolated visual handicap was notified in 34% of the children, while another 48% presented central nervous system involvement. From an aetiological point of view it is noteworthy that no specific aetiology could be encircled in 38% of the material. In conclusion, it is proposed that future lines of ophthalmological work in the prevention of visual handicap in childhood should concentrate on a higher degree of specificity in diagnostic procedures and an intensified search for specific aetiologies in every single child with visual impairment. PMID:3577699

  6. The Nature of "Udeskole": Outdoor Learning Theory and Practice in Danish Schools

    ERIC Educational Resources Information Center

    Bentsen, Peter; Jensen, Frank Sondergaard

    2012-01-01

    An increasing number of Danish teachers have started introducing school-based outdoor learning as a weekly or biweekly "outdoor school" day for school children--often called "udeskole" in Danish. Although at least 14% of Danish schools practise this form of outdoor teaching with some classes, it is not mentioned in the national curriculum and…

  7. Early Vocabulary Development in Danish and other Languages: A CDI-Based Comparison

    ERIC Educational Resources Information Center

    Bleses, Dorthe; Vach, Werner; Slott, Malene; Wehberg, Sonja; Thomsen, Pia; Madsen, Thomas O.; Basboll, Hans

    2008-01-01

    The main objective of this paper is to describe the trajectory of Danish children's early lexical development relative to other languages, by comparing a Danish study based on the Danish adaptation of "The MacArthur-Bates Communicative Development Inventories" (CDI) to 17 comparable CDI-studies. The second objective is to address the feasibility…

  8. Semantic Categorization of Placement Verbs in L1 and L2 Danish and Spanish

    ERIC Educational Resources Information Center

    Cadierno, Teresa; Ibarretxe-Antuñano, Iraide; Hijazo-Gascón, Alberto

    2016-01-01

    This study investigates semantic categorization of the meaning of placement verbs by Danish and Spanish native speakers and two groups of intermediate second language (L2) learners (Danish learners of L2 Spanish and Spanish learners of L2 Danish). Participants described 31 video clips picturing different types of placement events. Cluster analyses…

  9. Toxicity and QSAR of chlorobenzenes in two species of Benthic flatfish, flounder (Platichthys flesus L.) and sole (Solea solea L.)

    SciTech Connect

    Furay, V.J.; Smith, S.

    1995-01-01

    Chlorinated benzenes were among the first large-scale produced aromatic compounds. They have found broad spectrum of uses in numerous domestic and industrial preparations, ranging from engine - block cleaners, solvents, pharmaceutical intermediates, synthesis of chlorophenols and in disinfectants. Recent investigations have shown that they are present in the major environmental compartments and organisms, including fish tissues, coastal waters, and estuaries. Comparatively little is known about the ecotoxicity of chlorinated benzenes particularly to economically important fish. A number of earlier investigations examined the toxicity of chlorobenzenes and they demonstrated differences in the toxicity values for the same species and isomers of the chemicals investigated. The present investigation has assessed the toxicity and QSARs of selected chlorobenzenes to two ecologically and commercially important flatfish, the flounder (platichthys flesus) and sole (Solea solea). Both have a widespread geographic distribution in coastal and estuarine regions throughout Western Europe and are therefore highly representative test species. 20 refs., 5 tabs.

  10. Elicitation of the most important structural properties of ionic liquids affecting ecotoxicity in limnic green algae; a QSAR approach.

    PubMed

    Izadiyan, Parisa; Fatemi, M H; Izadiyan, Mahsa

    2013-01-01

    Many ionic liquids are soluble in water and their impact on the aquatic environment has to be evaluated. However, due to the large number of ionic liquids and lack of experimental data, it is necessary to develop estimation procedures in order to reduce the materials and time consumption. In this study using multilayer perceptron neural network (MLP), ant colony optimization (ACO) and multiple linear regression (MLR) strategies, good predictive quantitative structure-activity relationships (QSAR) models were introduced and structural parameters affecting ecotoxicity of ionic liquids in limnic green algae (Scenedesmus vacuolatus) were revealed. Moreover, principal component analysis (PCA) and cluster analysis (CA) approaches were also applied to visualize any possible patterns or relationships among ionic liquids data. It was revealed that selected descriptors of the MLR model are also capable of clustering ionic liquids according to their four level of toxicity. PMID:23107477

  11. Building up a QSAR model for toxicity toward Tetrahymena pyriformis by the Monte Carlo method: A case of benzene derivatives.

    PubMed

    Toropova, Alla P; Schultz, Terry W; Toropov, Andrey A

    2016-03-01

    Data on toxicity toward Tetrahymena pyriformis is indicator of applicability of a substance in ecologic and pharmaceutical aspects. Quantitative structure-activity relationships (QSARs) between the molecular structure of benzene derivatives and toxicity toward T. pyriformis (expressed as the negative logarithms of the population growth inhibition dose, mmol/L) are established. The available data were randomly distributed three times into the visible training and calibration sets, and invisible validation sets. The statistical characteristics for the validation set are the following: r(2)=0.8179 and s=0.338 (first distribution); r(2)=0.8682 and s=0.341 (second distribution); r(2)=0.8435 and s=0.323 (third distribution). These models are built up using only information on the molecular structure: no data on physicochemical parameters, 3D features of the molecular structure and quantum mechanics descriptors are involved in the modeling process. PMID:26851376

  12. QSAR modeling of acute toxicity on mammals caused by aromatic compounds: the case study using oral LD50 for rats.

    PubMed

    Rasulev, Bakhtiyor; Kusić, Hrvoje; Leszczynska, Danuta; Leszczynski, Jerzy; Koprivanac, Natalija

    2010-05-01

    The goal of the study was to predict toxicity in vivo caused by aromatic compounds structured with a single benzene ring and the presence or absence of different substituent groups such as hydroxyl-, nitro-, amino-, methyl-, methoxy-, etc., by using QSAR/QSPR tools. A Genetic Algorithm and multiple regression analysis were applied to select the descriptors and to generate the correlation models. The most predictive model is shown to be the 3-variable model which also has a good ratio of the number of descriptors and their predictive ability to avoid overfitting. The main contributions to the toxicity were shown to be the polarizability weighted MATS2p and the number of certain groups C-026 descriptors. The GA-MLRA approach showed good results in this study, which allows the building of a simple, interpretable and transparent model that can be used for future studies of predicting toxicity of organic compounds to mammals. PMID:21491673

  13. Synthesis, bioassay, and QSAR study of bronchodilatory active 4H-pyrano[3,2-c]pyridine-3-carbonitriles.

    PubMed

    Girgis, Adel S; Saleh, Dalia O; George, Riham F; Srour, Aladdin M; Pillai, Girinath G; Panda, Chandramukhi S; Katritzky, Alan R

    2015-01-01

    A statistically significant QSAR model describing the bioactivity of bronchodilatory active 4H-pyrano[3,2-c]pyridine-3-carbonitriles (N = 41, n = 8, R(2) = 0.824, R(2)cv = 0.724, F = 18.749, s(2) = 0.0018) was obtained employing CODESSA-Pro software. The bronchodilatory active 4H-pyrano[3,2-c]pyridine-3-carbonitriles 17-57 were synthesized through a facile approach via reaction of 1-alkyl-4-piperidones 1-4 with ylidenemalononitriles 5-16 in methanol in the presence of sodium. The bronchodilation properties of 17-57 were investigated in vitro using isolated guinea pig tracheal rings pre-contracted with histamine (standard method) and compared with theophylline (standard reference). Most of the compounds synthesized exhibit promising bronchodilation properties especially, compounds 25 and 28. PMID:25462283

  14. 3D-QSAR Studies on a Series of Dihydroorotate Dehydrogenase Inhibitors: Analogues of the Active Metabolite of Leflunomide

    PubMed Central

    Li, Shun-Lai; He, Mao-Yu; Du, Hong-Guang

    2011-01-01

    The active metabolite of the novel immunosuppressive agent leflunomide has been shown to inhibit the enzyme dihydroorotate dehydrogenase (DHODH). This enzyme catalyzes the fourth step in de novo pyrimidine biosynthesis. Self-organizing molecular field analysis (SOMFA), a simple three-dimensional quantitative structure-activity relationship (3D-QSAR) method is used to study the correlation between the molecular properties and the biological activities of a series of analogues of the active metabolite. The statistical results, cross-validated rCV2 (0.664) and non cross-validated r2 (0.687), show a good predictive ability. The final SOMFA model provides a better understanding of DHODH inhibitor-enzyme interactions, and may be useful for further modification and improvement of inhibitors of this important enzyme. PMID:21686163

  15. In Vitro Antioxidant Activity of Selected 4-Hydroxy-chromene-2-one Derivatives—SAR, QSAR and DFT Studies

    PubMed Central

    Mladenović, Milan; Mihailović, Mirjana; Bogojević, Desanka; Matić, Sanja; Nićiforović, Neda; Mihailović, Vladimir; Vuković, Nenad; Sukdolak, Slobodan; Solujić, Slavica

    2011-01-01

    The series of fifteen synthesized 4-hydroxycoumarin derivatives was subjected to antioxidant activity evaluation in vitro, through total antioxidant capacity, 1,1-diphenyl-2-picryl-hydrazyl (DPPH), hydroxyl radical, lipid peroxide scavenging and chelating activity. The highest activity was detected during the radicals scavenging, with 2b, 6b, 2c, and 4c noticed as the most active. The antioxidant activity was further quantified by the quantitative structure-activity relationships (QSAR) studies. For this purpose, the structures were optimized using Paramethric Method 6 (PM6) semi-empirical and Density Functional Theory (DFT) B3LYP methods. Bond dissociation enthalpies of coumarin 4-OH, Natural Bond Orbital (NBO) gained hybridization of the oxygen, acidity of the hydrogen atom and various molecular descriptors obtained, were correlated with biological activity, after which we designed 20 new antioxidant structures, using the most favorable structural motifs, with much improved predicted activity in vitro. PMID:21686153

  16. Regression methods for developing QSAR and QSPR models to predict compounds of specific pharmacodynamic, pharmacokinetic and toxicological properties.

    PubMed

    Yap, C W; Li, H; Ji, Z L; Chen, Y Z

    2007-11-01

    Quantitative structure-activity relationship (QSAR) and quantitative structure-property relationship (QSPR) models have been extensively used for predicting compounds of specific pharmacodynamic, pharmacokinetic, or toxicological property from structure-derived physicochemical and structural features. These models can be developed by using various regression methods including conventional approaches (multiple linear regression and partial least squares) and more recently explored genetic (genetic function approximation) and machine learning (k-nearest neighbour, neural networks, and support vector regression) approaches. This article describes the algorithms of these methods, evaluates their advantages and disadvantages, and discusses the application potential of the recently explored methods. Freely available online and commercial software for these regression methods and the areas of their applications are also presented. PMID:18045213

  17. Semisynthesis and quantitative structure-activity relationship (QSAR) study of some cholesterol-based hydrazone derivatives as insecticidal agents.

    PubMed

    Yang, Chun; Shao, Yonghua; Zhi, Xiaoyan; Huan, Qu; Yu, Xiang; Yao, Xiaojun; Xu, Hui

    2013-09-01

    In continuation of our program aimed at the discovery and development of natural-product-based insecticidal agents, four series of novel cholesterol-based hydrazone derivatives were synthesized, and their insecticidal activity was tested against the pre-third-instar larvae of oriental armyworm, Mythimna separata (Walker) in vivo at 1mg/mL. All the derivatives showed the better insecticidal activity than their precursor cholesterol. Quantitative structure-activity relationship (QSAR) model demonstrated that six descriptors such as RDF085v, Mor06u, Mor11u, Dv, HATS0v and H-046, are likely to influence the insecticidal activity of these compounds. Among them, two important ones are the Mor06u and RDF085v. PMID:23891182

  18. Estimating the persistence of organic contaminants in indirect potable reuse systems using quantitative structure activity relationship (QSAR).

    PubMed

    Lim, Seung Joo; Fox, Peter

    2012-09-01

    Predictions from the quantitative structure activity relationship (QSAR) model EPI Suite were modified to estimate the persistence of organic contaminants in indirect potable reuse systems. The modified prediction included the effects of sorption, biodegradation, and oxidation that may occur during sub-surface transport. A retardation factor was used to simulate the mobility of adsorbed compounds during sub-surface transport to a recovery well. A set of compounds with measured persistent properties during sub-surface transport was used to validate the results of the modifications to the predictions of EPI Suite. A comparison of the predicted values and measured values was done and the residual sum of the squares showed the importance of including oxidation and sorption. Sorption was the most important factor to include in predicting the fates of organic chemicals in the sub-surface environment. PMID:22766422

  19. 3D-QSAR and Docking Studies of Pyrido[2,3-d]pyrimidine Derivatives as Wee1 Inhibitors

    NASA Astrophysics Data System (ADS)

    Zeng, Guo-hua; Wu, Wen-juan; Zhang, Rong; Sun, Jun; Xie, Wen-guo; Shen, Yong

    2012-06-01

    In order to investigate the inhibiting mechanism and obtain some helpful information for designing functional inhibitors against Wee1, three-dimensional quantitative structure-activity relationship (3D-QSAR) and docking studies have been performed on 45 pyrido[2,3-d] pyrimidine derivatives acting as Wee1 inhibitors. Two optimal 3D-QSAR models with significant statistical quality and satisfactory predictive ability were established, including the CoMFA model (q2=0.707, R2=0.964) and CoMSIA model (q2=0.645, R2=0.972). The external validation indicated that both CoMFA and CoMSIA models were quite robust and had high predictive power with the predictive correlation coefficient values of 0.707 and 0.794, essential parameter rm2 values of 0.792 and 0.826, the leave-one-out r2m(LOO) values of 0.781 and 0.809, r2m(overall) values of 0.787 and 0.810, respectively. Moreover, the appropriate binding orientations and conformations of these compounds interacting with Wee1 were revealed by the docking studies. Based on the CoMFA and CoMSIA contour maps and docking analyses, several key structural requirements of these compounds responsible for inhibitory activity were identified as follows: simultaneously introducing high electropositive groups to the substituents R1 and R5 may increase the activity, the substituent R2 should be smaller bulky and higher electronegative, moderate-size and strong electron-withdrawing groups for the substituent R3 is advantageous to the activity, but the substituent X should be medium-size and hydrophilic. These theoretical results help to understand the action mechanism and design novel potential Wee1 inhibitors.

  20. Pharmacophore modeling, virtual screening and 3D-QSAR studies of 5-tetrahydroquinolinylidine aminoguanidine derivatives as sodium hydrogen exchanger inhibitors.

    PubMed

    Bhatt, Hardik G; Patel, Paresh K

    2012-06-01

    Sodium hydrogen exchanger (SHE) inhibitor is one of the most important targets in treatment of myocardial ischemia. In the course of our research into new types of non-acylguanidine, SHE inhibitory activities of 5-tetrahydroquinolinylidine aminoguanidine derivatives were used to build pharmacophore and 3D-QSAR models. Genetic Algorithm Similarity Program (GASP) was used to derive a 3D pharmacophore model which was used in effective alignment of data set. Eight molecules were selected on the basis of structure diversity to build 10 different pharmacophore models. Model 1 was considered as the best model as it has highest fitness score compared to other nine models. The obtained model contained two acceptor sites, two donor atoms and one hydrophobic region. Pharmacophore modeling was followed by substructure searching and virtual screening. The best CoMFA model, representing steric and electrostatic fields, obtained for 30 training set molecules was statistically significant with cross-validated coefficient (q(2)) of 0.673 and conventional coefficient (r(2)) of 0.988. In addition to steric and electrostatic fields observed in CoMFA, CoMSIA also represents hydrophobic, hydrogen bond donor and hydrogen bond acceptor fields. CoMSIA model was also significant with cross-validated coefficient (q(2)) and conventional coefficient (r(2)) of 0.636 and 0.986, respectively. Both models were validated by an external test set of eight compounds and gave satisfactory prediction (r(pred)(2)) of 0.772 and 0.701 for CoMFA and CoMSIA models, respectively. This pharmacophore based 3D-QSAR approach provides significant insights that can be used to design novel, potent and selective SHE inhibitors. PMID:22546667

  1. Synthesis of novel flavone hydrazones: in-vitro evaluation of α-glucosidase inhibition, QSAR analysis and docking studies.

    PubMed

    Imran, Syahrul; Taha, Muhammad; Ismail, Nor Hadiani; Kashif, Syed Muhammad; Rahim, Fazal; Jamil, Waqas; Hariono, Maywan; Yusuf, Muhammad; Wahab, Habibah

    2015-11-13

    Thirty derivatives of flavone hydrazone (5-34) had been synthesized through a five-step reaction and screened for their α-glucosidase inhibition activity. Chalcone 1 was synthesized through aldol condensation then subjected through oxidative cyclization, esterification, and condensation reaction to afford the final products. The result for baker's yeast α-glucosidase (EC 3.2.1.20) inhibition assay showed that all compounds are active with reference to the IC50 value of the acarbose (standard drug) except for compound 3. Increase in activity observed for compounds 2 to 34 clearly highlights the importance of flavone, hydrazide and hydrazone linkage in suppressing the activity of α-glucosidase. Additional functional group on N-benzylidene moiety further enhances the activity significantly. Compound 5 (15.4 ± 0.22 μM), a 2,4,6-trihydroxy substituted compound, is the most active compound in the series. Other compounds which were found to be active are those having chlorine, fluorine, and nitro substituents. Compounds with methoxy, pyridine, and methyl substituents are weakly active. Further studies showed that they are not active in inhibiting histone deacetylase activity and do not possess any cytotoxic properties. QSAR model was being developed to further identify the structural requirements contributing to the activity. Using Discovery Studio (DS) 2.5, various 2D descriptors were being used to develop the model. The QSAR model is able to predict the pIC50 and could be used as a prediction tool for compounds having the same skeletal framework. Molecular docking was done for all compounds using homology model of α-glucosidase to identify important binding modes responsible for inhibition activity. PMID:26491979

  2. Fragment based G-QSAR and molecular dynamics based mechanistic simulations into hydroxamic-based HDAC inhibitors against spinocerebellar ataxia.

    PubMed

    Sinha, Siddharth; Tyagi, Chetna; Goyal, Sukriti; Jamal, Salma; Somvanshi, Pallavi; Grover, Abhinav

    2016-10-01

    Expansion of polyglutamine (CAG) triplets within the coding gene ataxin 2 results in transcriptional repression, forming the molecular basis of the neurodegenerative disorder named spinocerebellar ataxia type-2 (SCA2). HDAC inhibitors (HDACi) have been elements of great interest in polyglutamine disorders such as Huntington's and Ataxia's. In this study, we have selected hydroxamic acid derivatives as HDACi and performed fragment-based G-QSAR, molecular docking studies and molecular dynamics simulations for elucidating the dynamic mode of action of HDACi with His-Asp catalytic dyad of HDAC4. The model was statistically validated to establish its predictive robustness. The model was statistically significant with r(2) value of .6297, cross-validated co-relation coefficient q(2) value of .5905 and pred_r(2) (predicted square co-relation coefficient) value of .85. An F-test value of 56.11 confirms absolute robustness of the model. Two combinatorial libraries comprising of 3180 compounds were created with hydroxamate moiety as the template and their pIC50 activities were predicted based on the G-QSAR model. The combinatorial library created was screened on the basis of predicted activity (pIC50), with two resultant top scoring compounds, HIC and DHC. The interaction of the compounds with His-Asp dyad in terms of H-bond interactions with His802, Asp840, Pro942, and Gly975 residues of HDAC4 was evaluated by docking and 20 ns long molecular dynamics simulations. This study provides valuable leads for structural substitutions required for hydroxamate moiety to exhibit enhanced inhibitory activity against HDAC4. The reported compounds demonstrated good binding and thus can be considered as potent therapeutic leads against ataxia. PMID:26510381

  3. NCCDPHP PUBLICATION DATABASE

    EPA Science Inventory

    This database provides bibliographic citations and abstracts of publications produced by the CDC's National Center for Chronic Disease Prevention and Health Promotion (NCCDPHP) including journal articles, monographs, book chapters, reports, policy documents, and fact sheets. Full...

  4. ARTI Refrigerant Database

    SciTech Connect

    Calm, J.M.

    1994-05-27

    The Refrigerant Database consolidates and facilitates access to information to assist industry in developing equipment using alternative refrigerants. The underlying purpose is to accelerate phase out of chemical compounds of environmental concern.

  5. THE CTEPP DATABASE

    EPA Science Inventory

    The CTEPP (Children's Total Exposure to Persistent Pesticides and Other Persistent Organic Pollutants) database contains a wealth of data on children's aggregate exposures to pollutants in their everyday surroundings. Chemical analysis data for the environmental media and ques...

  6. Hawaii bibliographic database

    USGS Publications Warehouse

    Wright, T.L.; Takahashi, T.J.

    1998-01-01

    The Hawaii bibliographic database has been created to contain all of the literature, from 1779 to the present, pertinent to the volcanological history of the Hawaiian-Emperor volcanic chain. References are entered in a PC- and Macintosh-compatible EndNote Plus bibliographic database with keywords and abstracts or (if no abstract) with annotations as to content. Keywords emphasize location, discipline, process, identification of new chemical data or age determinations, and type of publication. The database is updated approximately three times a year and is available to upload from an ftp site. The bibliography contained 8460 references at the time this paper was submitted for publication. Use of the database greatly enhances the power and completeness of library searches for anyone interested in Hawaiian volcanism.

  7. Chemical Kinetics Database

    National Institute of Standards and Technology Data Gateway

    SRD 17 NIST Chemical Kinetics Database (Web, free access)   The NIST Chemical Kinetics Database includes essentially all reported kinetics results for thermal gas-phase chemical reactions. The database is designed to be searched for kinetics data based on the specific reactants involved, for reactions resulting in specified products, for all the reactions of a particular species, or for various combinations of these. In addition, the bibliography can be searched by author name or combination of names. The database contains in excess of 38,000 separate reaction records for over 11,700 distinct reactant pairs. These data have been abstracted from over 12,000 papers with literature coverage through early 2000.

  8. Requirements Management Database

    Energy Science and Technology Software Center (ESTSC)

    2009-08-13

    This application is a simplified and customized version of the RBA and CTS databases to capture federal, site, and facility requirements, link to actions that must be performed to maintain compliance with their contractual and other requirements.

  9. Navigating Public Microarray Databases

    PubMed Central

    Bähler, Jürg

    2004-01-01

    With the ever-escalating amount of data being produced by genome-wide microarray studies, it is of increasing importance that these data are captured in public databases so that researchers can use this information to complement and enhance their own studies. Many groups have set up databases of expression data, ranging from large repositories, which are designed to comprehensively capture all published data, through to more specialized databases. The public repositories, such as ArrayExpress at the European Bioinformatics Institute contain complete datasets in raw format in addition to processed data, whilst the specialist databases tend to provide downstream analysis of normalized data from more focused studies and data sources. Here we provide a guide to the use of these public microarray resources. PMID:18629145

  10. Nuclear Science References Database

    SciTech Connect

    Pritychenko, B.; Běták, E.; Singh, B.; Totans, J.

    2014-06-15

    The Nuclear Science References (NSR) database together with its associated Web interface, is the world's only comprehensive source of easily accessible low- and intermediate-energy nuclear physics bibliographic information for more than 210,000 articles since the beginning of nuclear science. The weekly-updated NSR database provides essential support for nuclear data evaluation, compilation and research activities. The principles of the database and Web application development and maintenance are described. Examples of nuclear structure, reaction and decay applications are specifically included. The complete NSR database is freely available at the websites of the National Nuclear Data Center (http://www.nndc.bnl.gov/nsr) and the International Atomic Energy Agency (http://www-nds.iaea.org/nsr)

  11. Navigating public microarray databases.

    PubMed

    Penkett, Christopher J; Bähler, Jürg

    2004-01-01

    With the ever-escalating amount of data being produced by genome-wide microarray studies, it is of increasing importance that these data are captured in public databases so that researchers can use this information to complement and enhance their own studies. Many groups have set up databases of expression data, ranging from large repositories, which are designed to comprehensively capture all published data, through to more specialized databases. The public repositories, such as ArrayExpress at the European Bioinformatics Institute contain complete datasets in raw format in addition to processed data, whilst the specialist databases tend to provide downstream analysis of normalized data from more focused studies and data sources. Here we provide a guide to the use of these public microarray resources. PMID:18629145

  12. Household Products Database

    MedlinePlus

    ... Commercial / Institutional Product Names Types of Products Manufacturers Ingredients About the Database FAQ Product Recalls Help Glossary Contact Us More Resources What's under your kitchen sink, in your garage, in your bathroom, and ...

  13. TREATABILITY DATABASE DESCRIPTION

    EPA Science Inventory

    The Drinking Water Treatability Database (TDB) presents referenced information on the control of contaminants in drinking water. It allows drinking water utilities, first responders to spills or emergencies, treatment process designers, research organizations, academics, regulato...

  14. ARTI Refrigerant Database

    SciTech Connect

    Calm, J.M.

    1995-06-01

    The Refrigerant Database consolidates and facilitates access to information to assist industry in developing equipment using alternative refrigerants. The underlying purpose is to accelerate phase out of chemical compounds of environmental concern.

  15. ARTI Refrigerant Database

    SciTech Connect

    Calm, J.M.

    1995-02-01

    The Refrigerant Database consolidates and facilitates access to information to assist industry in developing equipment using alternative refrigerants. The underlying purpose is to accelerate phase-out of chemical compounds of environmental concern.

  16. Querying genomic databases

    SciTech Connect

    Baehr, A.; Hagstrom, R.; Joerg, D.; Overbeek, R.

    1991-09-01

    A natural-language interface has been developed that retrieves genomic information by using a simple subset of English. The interface spares the biologist from the task of learning database-specific query languages and computer programming. Currently, the interface deals with the E. coli genome. It can, however, be readily extended and shows promise as a means of easy access to other sequenced genomic databases as well.

  17. Steam Properties Database

    National Institute of Standards and Technology Data Gateway

    SRD 10 NIST/ASME Steam Properties Database (PC database for purchase)   Based upon the International Association for the Properties of Water and Steam (IAPWS) 1995 formulation for the thermodynamic properties of water and the most recent IAPWS formulations for transport and other properties, this updated version provides water properties over a wide range of conditions according to the accepted international standards.

  18. The ribosomal database project.

    PubMed Central

    Larsen, N; Olsen, G J; Maidak, B L; McCaughey, M J; Overbeek, R; Macke, T J; Marsh, T L; Woese, C R

    1993-01-01

    The Ribosomal Database Project (RDP) is a curated database that offers ribosome data along with related programs and services. The offerings include phylogenetically ordered alignments of ribosomal RNA (rRNA) sequences, derived phylogenetic trees, rRNA secondary structure diagrams and various software packages for handling, analyzing and displaying alignments and trees. The data are available via ftp and electronic mail. Certain analytic services are also provided by the electronic mail server. PMID:8332524

  19. Database computing in HEP

    SciTech Connect

    Day, C.T.; Loken, S.; MacFarlane, J.F. ); May, E.; Lifka, D.; Lusk, E.; Price, L.E. ); Baden, A. . Dept. of Physics); Grossman, R.; Qin, X. . Dept. of Mathematics, Statistics and Computer Science); Cormell, L.; Leibold, P.; Liu, D

    1992-01-01

    The major SSC experiments are expected to produce up to 1 Petabyte of data per year each. Once the primary reconstruction is completed by farms of inexpensive processors. I/O becomes a major factor in further analysis of the data. We believe that the application of database techniques can significantly reduce the I/O performed in these analyses. We present examples of such I/O reductions in prototype based on relational and object-oriented databases of CDF data samples.

  20. Database computing in HEP

    NASA Technical Reports Server (NTRS)

    Day, C. T.; Loken, S.; Macfarlane, J. F.; May, E.; Lifka, D.; Lusk, E.; Price, L. E.; Baden, A.; Grossman, R.; Qin, X.

    1992-01-01

    The major SSC experiments are expected to produce up to 1 Petabyte of data per year each. Once the primary reconstruction is completed by farms of inexpensive processors, I/O becomes a major factor in further analysis of the data. We believe that the application of database techniques can significantly reduce the I/O performed in these analyses. We present examples of such I/O reductions in prototypes based on relational and object-oriented databases of CDF data samples.

  1. Databases: Peter's Picks and Pans.

    ERIC Educational Resources Information Center

    Jacso, Peter

    1995-01-01

    Reviews the best and worst in databases on disk, CD-ROM, and online, and offers judgments and observations on database characteristics. Two databases are praised and three are criticized. (Author/JMV)

  2. Specialist Bibliographic Databases.

    PubMed

    Gasparyan, Armen Yuri; Yessirkepov, Marlen; Voronov, Alexander A; Trukhachev, Vladimir I; Kostyukova, Elena I; Gerasimov, Alexey N; Kitas, George D

    2016-05-01

    Specialist bibliographic databases offer essential online tools for researchers and authors who work on specific subjects and perform comprehensive and systematic syntheses of evidence. This article presents examples of the established specialist databases, which may be of interest to those engaged in multidisciplinary science communication. Access to most specialist databases is through subscription schemes and membership in professional associations. Several aggregators of information and database vendors, such as EBSCOhost and ProQuest, facilitate advanced searches supported by specialist keyword thesauri. Searches of items through specialist databases are complementary to those through multidisciplinary research platforms, such as PubMed, Web of Science, and Google Scholar. Familiarizing with the functional characteristics of biomedical and nonbiomedical bibliographic search tools is mandatory for researchers, authors, editors, and publishers. The database users are offered updates of the indexed journal lists, abstracts, author profiles, and links to other metadata. Editors and publishers may find particularly useful source selection criteria and apply for coverage of their peer-reviewed journals and grey literature sources. These criteria are aimed at accepting relevant sources with established editorial policies and quality controls. PMID:27134485

  3. Crude Oil Analysis Database

    DOE Data Explorer

    Shay, Johanna Y.

    The composition and physical properties of crude oil vary widely from one reservoir to another within an oil field, as well as from one field or region to another. Although all oils consist of hydrocarbons and their derivatives, the proportions of various types of compounds differ greatly. This makes some oils more suitable than others for specific refining processes and uses. To take advantage of this diversity, one needs access to information in a large database of crude oil analyses. The Crude Oil Analysis Database (COADB) currently satisfies this need by offering 9,056 crude oil analyses. Of these, 8,500 are United States domestic oils. The database contains results of analysis of the general properties and chemical composition, as well as the field, formation, and geographic location of the crude oil sample. [Taken from the Introduction to COAMDATA_DESC.pdf, part of the zipped software and database file at http://www.netl.doe.gov/technologies/oil-gas/Software/database.html] Save the zipped file to your PC. When opened, it will contain PDF documents and a large Excel spreadsheet. It will also contain the database in Microsoft Access 2002.

  4. The comprehensive peptaibiotics database.

    PubMed

    Stoppacher, Norbert; Neumann, Nora K N; Burgstaller, Lukas; Zeilinger, Susanne; Degenkolb, Thomas; Brückner, Hans; Schuhmacher, Rainer

    2013-05-01

    Peptaibiotics are nonribosomally biosynthesized peptides, which - according to definition - contain the marker amino acid α-aminoisobutyric acid (Aib) and possess antibiotic properties. Being known since 1958, a constantly increasing number of peptaibiotics have been described and investigated with a particular emphasis on hypocrealean fungi. Starting from the existing online 'Peptaibol Database', first published in 1997, an exhaustive literature survey of all known peptaibiotics was carried out and resulted in a list of 1043 peptaibiotics. The gathered information was compiled and used to create the new 'The Comprehensive Peptaibiotics Database', which is presented here. The database was devised as a software tool based on Microsoft (MS) Access. It is freely available from the internet at http://peptaibiotics-database.boku.ac.at and can easily be installed and operated on any computer offering a Windows XP/7 environment. It provides useful information on characteristic properties of the peptaibiotics included such as peptide category, group name of the microheterogeneous mixture to which the peptide belongs, amino acid sequence, sequence length, producing fungus, peptide subfamily, molecular formula, and monoisotopic mass. All these characteristics can be used and combined for automated search within the database, which makes The Comprehensive Peptaibiotics Database a versatile tool for the retrieval of valuable information about peptaibiotics. Sequence data have been considered as to December 14, 2012. PMID:23681723

  5. Drinking Water Database

    NASA Technical Reports Server (NTRS)

    Murray, ShaTerea R.

    2004-01-01

    This summer I had the opportunity to work in the Environmental Management Office (EMO) under the Chemical Sampling and Analysis Team or CS&AT. This team s mission is to support Glenn Research Center (GRC) and EM0 by providing chemical sampling and analysis services and expert consulting. Services include sampling and chemical analysis of water, soil, fbels, oils, paint, insulation materials, etc. One of this team s major projects is the Drinking Water Project. This is a project that is done on Glenn s water coolers and ten percent of its sink every two years. For the past two summers an intern had been putting together a database for this team to record the test they had perform. She had successfully created a database but hadn't worked out all the quirks. So this summer William Wilder (an intern from Cleveland State University) and I worked together to perfect her database. We began be finding out exactly what every member of the team thought about the database and what they would change if any. After collecting this data we both had to take some courses in Microsoft Access in order to fix the problems. Next we began looking at what exactly how the database worked from the outside inward. Then we began trying to change the database but we quickly found out that this would be virtually impossible.

  6. The Transporter Classification Database

    PubMed Central

    Saier, Milton H.; Reddy, Vamsee S.; Tamang, Dorjee G.; Västermark, Åke

    2014-01-01

    The Transporter Classification Database (TCDB; http://www.tcdb.org) serves as a common reference point for transport protein research. The database contains more than 10 000 non-redundant proteins that represent all currently recognized families of transmembrane molecular transport systems. Proteins in TCDB are organized in a five level hierarchical system, where the first two levels are the class and subclass, the second two are the family and subfamily, and the last one is the transport system. Superfamilies that contain multiple families are included as hyperlinks to the five tier TC hierarchy. TCDB includes proteins from all types of living organisms and is the only transporter classification system that is both universal and recognized by the International Union of Biochemistry and Molecular Biology. It has been expanded by manual curation, contains extensive text descriptions providing structural, functional, mechanistic and evolutionary information, is supported by unique software and is interconnected to many other relevant databases. TCDB is of increasing usefulness to the international scientific community and can serve as a model for the expansion of database technologies. This manuscript describes an update of the database descriptions previously featured in NAR database issues. PMID:24225317

  7. Specialist Bibliographic Databases

    PubMed Central

    2016-01-01

    Specialist bibliographic databases offer essential online tools for researchers and authors who work on specific subjects and perform comprehensive and systematic syntheses of evidence. This article presents examples of the established specialist databases, which may be of interest to those engaged in multidisciplinary science communication. Access to most specialist databases is through subscription schemes and membership in professional associations. Several aggregators of information and database vendors, such as EBSCOhost and ProQuest, facilitate advanced searches supported by specialist keyword thesauri. Searches of items through specialist databases are complementary to those through multidisciplinary research platforms, such as PubMed, Web of Science, and Google Scholar. Familiarizing with the functional characteristics of biomedical and nonbiomedical bibliographic search tools is mandatory for researchers, authors, editors, and publishers. The database users are offered updates of the indexed journal lists, abstracts, author profiles, and links to other metadata. Editors and publishers may find particularly useful source selection criteria and apply for coverage of their peer-reviewed journals and grey literature sources. These criteria are aimed at accepting relevant sources with established editorial policies and quality controls. PMID:27134485

  8. The Center for Integrated Molecular Brain Imaging (Cimbi) database.

    PubMed

    Knudsen, Gitte M; Jensen, Peter S; Erritzoe, David; Baaré, William F C; Ettrup, Anders; Fisher, Patrick M; Gillings, Nic; Hansen, Hanne D; Hansen, Lars Kai; Hasselbalch, Steen G; Henningsson, Susanne; Herth, Matthias M; Holst, Klaus K; Iversen, Pernille; Kessing, Lars V; Macoveanu, Julian; Madsen, Kathrine Skak; Mortensen, Erik L; Nielsen, Finn Årup; Paulson, Olaf B; Siebner, Hartwig R; Stenbæk, Dea S; Svarer, Claus; Jernigan, Terry L; Strother, Stephen C; Frokjaer, Vibe G

    2016-01-01

    We here describe a multimodality neuroimaging containing data from healthy volunteers and patients, acquired within the Lundbeck Foundation Center for Integrated Molecular Brain Imaging (Cimbi) in Copenhagen, Denmark. The data is of particular relevance for neurobiological research questions related to the serotonergic transmitter system with its normative data on the serotonergic subtype receptors 5-HT1A, 5-HT1B, 5-HT2A, and 5-HT4 and the 5-HT transporter (5-HTT), but can easily serve other purposes. The Cimbi database and Cimbi biobank were formally established in 2008 with the purpose to store the wealth of Cimbi-acquired data in a highly structured and standardized manner in accordance with the regulations issued by the Danish Data Protection Agency as well as to provide a quality-controlled resource for future hypothesis-generating and hypothesis-driven studies. The Cimbi database currently comprises a total of 1100 PET and 1000 structural and functional MRI scans and it holds a multitude of additional data, such as genetic and biochemical data, and scores from 17 self-reported questionnaires and from 11 neuropsychological paper/computer tests. The database associated Cimbi biobank currently contains blood and in some instances saliva samples from about 500 healthy volunteers and 300 patients with e.g., major depression, dementia, substance abuse, obesity, and impulsive aggression. Data continue to be added to the Cimbi database and biobank. PMID:25891375

  9. Probing the origins of human acetylcholinesterase inhibition via QSAR modeling and molecular docking

    PubMed Central

    Shoombuatong, Watshara; Malik, Aijaz Ahmad; Prachayasittikul, Virapong; Wikberg, Jarl E.S.

    2016-01-01

    Alzheimer’s disease (AD) is a chronic neurodegenerative disease which leads to the gradual loss of neuronal cells. Several hypotheses for AD exists (e.g., cholinergic, amyloid, tau hypotheses, etc.). As per the cholinergic hypothesis, the deficiency of choline is responsible for AD; therefore, the inhibition of AChE is a lucrative therapeutic strategy for the treatment of AD. Acetylcholinesterase (AChE) is an enzyme that catalyzes the breakdown of the neurotransmitter acetylcholine that is essential for cognition and memory. A large non-redundant data set of 2,570 compounds with reported IC50 values against AChE was obtained from ChEMBL and employed in quantitative structure-activity relationship (QSAR) study so as to gain insights on their origin of bioactivity. AChE inhibitors were described by a set of 12 fingerprint descriptors and predictive models were constructed from 100 different data splits using random forest. Generated models afforded R2, \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}${Q}_{\\mathrm{CV }}^{2}$\\end{document}QCV2 and \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}${Q}_{\\mathrm{Ext}}^{2}$\\end{document}QExt2 values in ranges of 0.66–0.93, 0.55–0.79 and 0.56–0.81 for the training set, 10-fold cross-validated set and external set, respectively. The best model built using the substructure count was selected according to the OECD guidelines and it afforded R2, \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage

  10. Vascular endothelial growth factor receptor-2 (VEGFR-2) inhibitors: development and validation of predictive 3-D QSAR models through extensive ligand- and structure-based approaches.

    PubMed

    Ragno, Rino; Ballante, Flavio; Pirolli, Adele; Wickersham, Richard B; Patsilinakos, Alexandros; Hesse, Stéphanie; Perspicace, Enrico; Kirsch, Gilbert

    2015-08-01

    Vascular endothelial growth factor receptor-2, (VEGFR-2), is a key element in angiogenesis, the process by which new blood vessels are formed, and is thus an important pharmaceutical target. Here, 3-D quantitative structure-activity relationship (3-D QSAR) were used to build a quantitative screening and pharmacophore model of the VEGFR-2 receptors for design of inhibitors with improved activities. Most of available experimental data information has been used as training set to derive optimized and fully cross-validated eight mono-probe and a multi-probe quantitative models. Notable is the use of 262 molecules, aligned following both structure-based and ligand-based protocols, as external test set confirming the 3-D QSAR models' predictive capability and their usefulness in design new VEGFR-2 inhibitors. From a survey on literature, this is the first generation of a wide-ranging computational medicinal chemistry application on VEGFR2 inhibitors. PMID:26194852

  11. The antibacterial activity of some sulfonamides and sulfonyl hydrazones, and 2D-QSAR study of a series of sulfonyl hydrazones

    NASA Astrophysics Data System (ADS)

    Aslan, H. Güzin; Özcan, Servet; Karacan, Nurcan

    2012-12-01

    Benzenesulfonicacid-1-methylhydrazide (1) and its four aromatic sulfonyl hydrazone derivatives (1a-1d), N-(3-amino-2-hydroxypropyl)benzene sulfonamide (2) and N-(2-hydroxyethyl)benzenesulfonamide (3) were synthesized and their structures were determined by IR, 1H NMR, 13C NMR, and LCMS techniques. Antibacterial activities of new synthesized compounds were evaluated against various bacteria strains by microdilution and disk diffusion methods. The experimental results show that presence of OH group on sulfonamides reduces the antimicrobial activity, and antimicrobial activities of the sulfonyl hydrazones (1a-1d) are smaller than that of the parent sulfonamide (1), except Candida albicans. In addition, 2D-QSAR analysis was performed on 28 aromatic sulfonyl hydrazones as antimicrobial agents against Escherichia coli and Staphylococcus aureus. In the QSAR models, the most important descriptor is total point-charge component of the molecular dipole for E. coli, and partial negative surface area (PNSA-1) for S. aureus.

  12. Support vector machine based training of multilayer feedforward neural networks as optimized by particle swarm algorithm: application in QSAR studies of bioactivity of organic compounds.

    PubMed

    Lin, Wei-Qi; Jiang, Jian-Hui; Zhou, Yan-Ping; Wu, Hai-Long; Shen, Guo-Li; Yu, Ru-Qin

    2007-01-30

    Multilayer feedforward neural networks (MLFNNs) are important modeling techniques widely used in QSAR studies for their ability to represent nonlinear relationships between descriptors and activity. However, the problems of overfitting and premature convergence to local optima still pose great challenges in the practice of MLFNNs. To circumvent these problems, a support vector machine (SVM) based training algorithm for MLFNNs has been developed with the incorporation of particle swarm optimization (PSO). The introduction of the SVM based training mechanism imparts the developed algorithm with inherent capacity for combating the overfitting problem. Moreover, with the implementation of PSO for searching the optimal network weights, the SVM based learning algorithm shows relatively high efficiency in converging to the optima. The proposed algorithm has been evaluated using the Hansch data set. Application to QSAR studies of the activity of COX-2 inhibitors is also demonstrated. The results reveal that this technique provides superior performance to backpropagation (BP) and PSO training neural networks. PMID:17186488

  13. Great Basin paleontological database

    USGS Publications Warehouse

    Zhang, N.; Blodgett, R.B.; Hofstra, A.H.

    2008-01-01

    The U.S. Geological Survey has constructed a paleontological database for the Great Basin physiographic province that can be served over the World Wide Web for data entry, queries, displays, and retrievals. It is similar to the web-database solution that we constructed for Alaskan paleontological data (www.alaskafossil.org). The first phase of this effort was to compile a paleontological bibliography for Nevada and portions of adjacent states in the Great Basin that has recently been completed. In addition, we are also compiling paleontological reports (Known as E&R reports) of the U.S. Geological Survey, which are another extensive source of l,egacy data for this region. Initial population of the database benefited from a recently published conodont data set and is otherwise focused on Devonian and Mississippian localities because strata of this age host important sedimentary exhalative (sedex) Au, Zn, and barite resources and enormons Carlin-type An deposits. In addition, these strata are the most important petroleum source rocks in the region, and record the transition from extension to contraction associated with the Antler orogeny, the Alamo meteorite impact, and biotic crises associated with global oceanic anoxic events. The finished product will provide an invaluable tool for future geologic mapping, paleontological research, and mineral resource investigations in the Great Basin, making paleontological data acquired over nearly the past 150 yr readily available over the World Wide Web. A description of the structure of the database and the web interface developed for this effort are provided herein. This database is being used ws a model for a National Paleontological Database (which we am currently developing for the U.S. Geological Survey) as well as for other paleontological databases now being developed in other parts of the globe. ?? 2008 Geological Society of America.

  14. Chemical Explosion Database

    NASA Astrophysics Data System (ADS)

    Johansson, Peder; Brachet, Nicolas

    2010-05-01

    A database containing information on chemical explosions, recorded and located by the International Data Center (IDC) of the CTBTO, should be established in the IDC prior to entry into force of the CTBT. Nearly all of the large chemical explosions occur in connection with mining activity. As a first step towards the establishment of this database, a survey of presumed mining areas where sufficiently large explosions are conducted has been done. This is dominated by the large coal mining areas like the Powder River (U.S.), Kuznetsk (Russia), Bowen (Australia) and Ekibastuz (Kazakhstan) basins. There are also several other smaller mining areas, in e.g. Scandinavia, Poland, Kazakhstan and Australia, with large enough explosions for detection. Events in the Reviewed Event Bulletin (REB) of the IDC that are located in or close to these mining areas, and which therefore are candidates for inclusion in the database, have been investigated. Comparison with a database of infrasound events has been done as many mining blasts generate strong infrasound signals and therefore also are included in the infrasound database. Currently there are 66 such REB events in 18 mining areas in the infrasound database. On a yearly basis several hundreds of events in mining areas have been recorded and included in the REB. Establishment of the database of chemical explosions requires confirmation and ground truth information from the States Parties regarding these events. For an explosion reported in the REB, the appropriate authority in whose country the explosion occurred is encouraged, on a voluntary basis, to seek out information on the explosion and communicate this information to the IDC.

  15. Combined 3D-QSAR, molecular docking and molecular dynamics study on thyroid hormone activity of hydroxylated polybrominated diphenyl ethers to thyroid receptors β

    SciTech Connect

    Li, Xiaolin; Ye, Li; Wang, Xiaoxiang; Wang, Xinzhou; Liu, Hongling; Zhu, Yongliang; Yu, Hongxia

    2012-12-15

    Several recent reports suggested that hydroxylated polybrominated diphenyl ethers (HO-PBDEs) may disturb thyroid hormone homeostasis. To illuminate the structural features for thyroid hormone activity of HO-PBDEs and the binding mode between HO-PBDEs and thyroid hormone receptor (TR), the hormone activity of a series of HO-PBDEs to thyroid receptors β was studied based on the combination of 3D-QSAR, molecular docking, and molecular dynamics (MD) methods. The ligand- and receptor-based 3D-QSAR models were obtained using Comparative Molecular Similarity Index Analysis (CoMSIA) method. The optimum CoMSIA model with region focusing yielded satisfactory statistical results: leave-one-out cross-validation correlation coefficient (q{sup 2}) was 0.571 and non-cross-validation correlation coefficient (r{sup 2}) was 0.951. Furthermore, the results of internal validation such as bootstrapping, leave-many-out cross-validation, and progressive scrambling as well as external validation indicated the rationality and good predictive ability of the best model. In addition, molecular docking elucidated the conformations of compounds and key amino acid residues at the docking pocket, MD simulation further determined the binding process and validated the rationality of docking results. -- Highlights: ► The thyroid hormone activities of HO-PBDEs were studied by 3D-QSAR. ► The binding modes between HO-PBDEs and TRβ were explored. ► 3D-QSAR, molecular docking, and molecular dynamics (MD) methods were performed.

  16. Predicting chemically-induced skin reactions. Part II: QSAR models of skin permeability and the relationships between skin permeability and skin sensitization

    SciTech Connect

    Alves, Vinicius M.; Muratov, Eugene; Fourches, Denis; Strickland, Judy; Kleinstreuer, Nicole; Tropsha, Alexander

    2015-04-15

    Skin permeability is widely considered to be mechanistically implicated in chemically-induced skin sensitization. Although many chemicals have been identified as skin sensitizers, there have been very few reports analyzing the relationships between molecular structure and skin permeability of sensitizers and non-sensitizers. The goals of this study were to: (i) compile, curate, and integrate the largest publicly available dataset of chemicals studied for their skin permeability; (ii) develop and rigorously validate QSAR models to predict skin permeability; and (iii) explore the complex relationships between skin sensitization and skin permeability. Based on the largest publicly available dataset compiled in this study, we found no overall correlation between skin permeability and skin sensitization. In addition, cross-species correlation coefficient between human and rodent permeability data was found to be as low as R{sup 2} = 0.44. Human skin permeability models based on the random forest method have been developed and validated using OECD-compliant QSAR modeling workflow. Their external accuracy was high (Q{sup 2}{sub ext} = 0.73 for 63% of external compounds inside the applicability domain). The extended analysis using both experimentally-measured and QSAR-imputed data still confirmed the absence of any overall concordance between skin permeability and skin sensitization. This observation suggests that chemical modifications that affect skin permeability should not be presumed a priori to modulate the sensitization potential of chemicals. The models reported herein as well as those developed in the companion paper on skin sensitization suggest that it may be possible to rationally design compounds with the desired high skin permeability but low sensitization potential. - Highlights: • It was compiled the largest publicly-available skin permeability dataset. • Predictive QSAR models were developed for skin permeability. • No concordance between skin

  17. Ligand-based 3D QSAR analysis of reactivation potency of mono- and bis-pyridinium aldoximes toward VX-inhibited rat acetylcholinesterase.

    PubMed

    Dolezal, Rafael; Korabecny, Jan; Malinak, David; Honegr, Jan; Musilek, Kamil; Kuca, Kamil

    2015-03-01

    To predict unknown reactivation potencies of 12 mono- and bis-pyridinium aldoximes for VX-inhibited rat acetylcholinesterase (rAChE), three-dimensional quantitative structure-activity relationship (3D QSAR) analysis has been carried out. Utilizing molecular interaction fields (MIFs) calculated by molecular mechanical (MMFF94) and quantum chemical (B3LYP/6-31G*) methods, two satisfactory ligand-based CoMFA models have been developed: 1. R(2)=0.9989, Q(LOO)(2)=0.9090, Q(LTO)(2)=0.8921, Q(LMO(20%))(2)=0.8853, R(ext)(2)=0.9259, SDEP(ext)=6.8938; 2. R(2)=0.9962, Q(LOO)(2)=0.9368, Q(LTO)(2)=0.9298, Q(LMO(20%))(2)=0.9248, R(ext)(2)=0.8905, SDEP(ext)=6.6756. High statistical significance of the 3D QSAR models has been achieved through the application of several data noise reduction techniques (i.e. smart region definition SRD, fractional factor design FFD, uninformative/iterative variable elimination UVE/IVE) on the original MIFs. Besides the ligand-based CoMFA models, an alignment molecular set constructed by flexible molecular docking has been also studied. The contour maps as well as the predicted reactivation potencies resulting from 3D QSAR analyses help better understand which structural features are associated with increased reactivation potency of studied compounds. PMID:25588616

  18. 2 D - QSAR studies on CYP26A1 inhibitory activity of 1-[benzofuran-2-yl-(4-alkyl/aryl-phenyl)-methyl]- 1 H-triazoles.

    PubMed

    Yadav, Madhu

    2011-01-01

    The Quantitative Structure Activity Relationship (QSAR) study is performed over a set of 15, 4-alkyl/aryl-substituted 1- [benzofuran-2-yl-phenylmethyl]-1 H-triazoles derivatives. This study is based on the application of physicochemical parameters in QSAR. The parameters include (MR (molar refractivity), MW (molecular weight), Pc (parachor), St (surface tension), D (density), Ir (index of refraction) and log P (partition coefficient). The parameters describing physiochemical properties are used as independent variables and the biological activity (IC(50)) is considered as dependent variable in multiple regression analysis. Different models were generated with high co-efficient of determination (R(2)). The 2D-QSAR study identified compounds capable of inhibiting the metabolic breakdown of the retinoid (trans-retinoic acid (ATRA)) involved in the activation of specific nuclear Retinoic acid receptors (RARs). This study identifies R115866 as a potential inhibitor of the cytochrome P450 (CYP) mediated metabolism with increased RA levels for retinoid actions. PMID:22347780

  19. QSAR models for oxidation of organic micropollutants in water based on ozone and hydroxyl radical rate constants and their chemical classification.

    PubMed

    Sudhakaran, Sairam; Amy, Gary L

    2013-03-01

    Ozonation is an oxidation process for the removal of organic micropollutants (OMPs) from water and the chemical reaction is governed by second-order kinetics. An advanced oxidation process (AOP), wherein the hydroxyl radicals (OH radicals) are generated, is more effective in removing a wider range of OMPs from water than direct ozonation. Second-order rate constants (k(OH) and k(O3) are good indices to estimate the oxidation efficiency, where higher rate constants indicate more rapid oxidation. In this study, quantitative structure activity relationships (QSAR) models for O(3) and AOP processes were developed, and rate constants, k(OH) and [Formula: see text] , were predicted based on target compound properties. The k(O3) and k(OH) values ranged from 5 * 10(-4) to 10(5) M(-1)s(-1) and 0.04 to 18 * (10(9)) M(-1) s(-1), respectively. Several molecular descriptors which potentially influence O(3) and OH radical oxidation were identified and studied. The QSAR-defining descriptors were double bond equivalence (DBE), ionisation potential (IP), electron-affinity (EA) and weakly-polar component of solvent accessible surface area (WPSA), and the chemical and statistical significance of these descriptors was discussed. Multiple linear regression was used to build the QSAR models, resulting in high goodness-of-fit, r(2) (>0.75). The models were validated by internal and external validation along with residual plots. PMID:23260175

  20. Local intersection volume: a new 3D descriptor applied to develop a 3D-QSAR pharmacophore model for benzodiazepine receptor ligands.

    PubMed

    Verli, Hugo; Albuquerque, Magaly Girão; Bicca de Alencastro, Ricardo; Barreiro, Eliezer J

    2002-03-01

    In this work, we have developed a new descriptor, named local intersection volume (LIV), in order to compose a 3D-QSAR pharmacophore model for benzodiazepine receptor ligands. The LIV can be classified as a 3D local shape descriptor in contraposition to the global shape descriptors. We have selected from the literature 49 non-benzodiazepine compounds as a training data set and the model was obtained and evaluated by genetic algorithms (GA) and partial least-squares (PLS) methods using LIVs as descriptors. The LIV 3D-QSAR model has a good predictive capacity according the cross-validation test by "leave-one-out" procedure (Q(2)=0.72). The developed model was compared to a comprehensive and extensive SAR pharmacophore model, recently proposed by Cook and co-workers, for benzodiazepine receptor ligands [J. Med. Chem. 43 (2000) 71]. It showed a relevant correlation with the pharmacophore groups pointed out in that work. Our LIV 3D-QSAR model was also able to predict affinity values for a series of nine compounds (test data set) that was not included into the training data set. PMID:11900866