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Sample records for danish qsar database

  1. Danish Gynecological Cancer Database

    PubMed Central

    Sørensen, Sarah Mejer; Bjørn, Signe Frahm; Jochumsen, Kirsten Marie; Jensen, Pernille Tine; Thranov, Ingrid Regitze; Hare-Bruun, Helle; Seibæk, Lene; Høgdall, Claus

    2016-01-01

    Aim of database The Danish Gynecological Cancer Database (DGCD) is a nationwide clinical cancer database and its aim is to monitor the treatment quality of Danish gynecological cancer patients, and to generate data for scientific purposes. DGCD also records detailed data on the diagnostic measures for gynecological cancer. Study population DGCD was initiated January 1, 2005, and includes all patients treated at Danish hospitals for cancer of the ovaries, peritoneum, fallopian tubes, cervix, vulva, vagina, and uterus, including rare histological types. Main variables DGCD data are organized within separate data forms as follows: clinical data, surgery, pathology, pre- and postoperative care, complications, follow-up visits, and final quality check. DGCD is linked with additional data from the Danish “Pathology Registry”, the “National Patient Registry”, and the “Cause of Death Registry” using the unique Danish personal identification number (CPR number). Descriptive data Data from DGCD and registers are available online in the Statistical Analysis Software portal. The DGCD forms cover almost all possible clinical variables used to describe gynecological cancer courses. The only limitation is the registration of oncological treatment data, which is incomplete for a large number of patients. Conclusion The very complete collection of available data from more registries form one of the unique strengths of DGCD compared to many other clinical databases, and provides unique possibilities for validation and completeness of data. The success of the DGCD is illustrated through annual reports, high coverage, and several peer-reviewed DGCD-based publications. PMID:27822089

  2. The Danish Melanoma Database

    PubMed Central

    Hölmich, Lisbet Rosenkrantz; Klausen, Siri; Spaun, Eva; Schmidt, Grethe; Gad, Dorte; Svane, Inge Marie; Schmidt, Henrik; Lorentzen, Henrik Frank; Ibfelt, Else Helene

    2016-01-01

    Aim of database The aim of the database is to monitor and improve the treatment and survival of melanoma patients. Study population All Danish patients with cutaneous melanoma and in situ melanomas must be registered in the Danish Melanoma Database (DMD). In 2014, 2,525 patients with invasive melanoma and 780 with in situ tumors were registered. The coverage is currently 93% compared with the Danish Pathology Register. Main variables The main variables include demographic, clinical, and pathological characteristics, including Breslow’s tumor thickness, ± ulceration, mitoses, and tumor–node–metastasis stage. Information about the date of diagnosis, treatment, type of surgery, including safety margins, results of lymphoscintigraphy in patients for whom this was indicated (tumors > T1a), results of sentinel node biopsy, pathological evaluation hereof, and follow-up information, including recurrence, nature, and treatment hereof is registered. In case of death, the cause and date are included. Currently, all data are entered manually; however, data catchment from the existing registries is planned to be included shortly. Descriptive data The DMD is an old research database, but new as a clinical quality register. The coverage is high, and the performance in the five Danish regions is quite similar due to strong adherence to guidelines provided by the Danish Melanoma Group. The list of monitored indicators is constantly expanding, and annual quality reports are issued. Several important scientific studies are based on DMD data. Conclusion DMD holds unique detailed information about tumor characteristics, the surgical treatment, and follow-up of Danish melanoma patients. Registration and monitoring is currently expanding to encompass even more clinical parameters to benefit both patient treatment and research. PMID:27822097

  3. The Danish Sarcoma Database

    PubMed Central

    Jørgensen, Peter Holmberg; Lausten, Gunnar Schwarz; Pedersen, Alma B

    2016-01-01

    Aim The aim of the database is to gather information about sarcomas treated in Denmark in order to continuously monitor and improve the quality of sarcoma treatment in a local, a national, and an international perspective. Study population Patients in Denmark diagnosed with a sarcoma, both skeletal and ekstraskeletal, are to be registered since 2009. Main variables The database contains information about appearance of symptoms; date of receiving referral to a sarcoma center; date of first visit; whether surgery has been performed elsewhere before referral, diagnosis, and treatment; tumor characteristics such as location, size, malignancy grade, and growth pattern; details on treatment (kind of surgery, amount of radiation therapy, type and duration of chemotherapy); complications of treatment; local recurrence and metastases; and comorbidity. In addition, several quality indicators are registered in order to measure the quality of care provided by the hospitals and make comparisons between hospitals and with international standards. Descriptive data Demographic patient-specific data such as age, sex, region of living, comorbidity, World Health Organization’s International Classification of Diseases – tenth edition codes and TNM Classification of Malignant Tumours, and date of death (after yearly coupling to the Danish Civil Registration System). Data quality and completeness are currently secured. Conclusion The Danish Sarcoma Database is population based and includes sarcomas occurring in Denmark since 2009. It is a valuable tool for monitoring sarcoma incidence and quality of treatment and its improvement, postoperative complications, and recurrence within 5 years follow-up. The database is also a valuable research tool to study the impact of technical and medical interventions on prognosis of sarcoma patients. PMID:27822116

  4. Danish Urogynaecological Database

    PubMed Central

    Hansen, Ulla Darling; Gradel, Kim Oren; Larsen, Michael Due

    2016-01-01

    The Danish Urogynaecological Database is established in order to ensure high quality of treatment for patients undergoing urogynecological surgery. The database contains details of all women in Denmark undergoing incontinence surgery or pelvic organ prolapse surgery amounting to ~5,200 procedures per year. The variables are collected along the course of treatment of the patient from the referral to a postoperative control. Main variables are prior obstetrical and gynecological history, symptoms, symptom-related quality of life, objective urogynecological findings, type of operation, complications if relevant, implants used if relevant, 3–6-month postoperative recording of symptoms, if any. A set of clinical quality indicators is being maintained by the steering committee for the database and is published in an annual report which also contains extensive descriptive statistics. The database has a completeness of over 90% of all urogynecological surgeries performed in Denmark. Some of the main variables have been validated using medical records as gold standard. The positive predictive value was above 90%. The data are used as a quality monitoring tool by the hospitals and in a number of scientific studies of specific urogynecological topics, broader epidemiological topics, and the use of patient reported outcome measures. PMID:27826217

  5. Danish Palliative Care Database

    PubMed Central

    Groenvold, Mogens; Adsersen, Mathilde; Hansen, Maiken Bang

    2016-01-01

    Aims The aim of the Danish Palliative Care Database (DPD) is to monitor, evaluate, and improve the clinical quality of specialized palliative care (SPC) (ie, the activity of hospital-based palliative care teams/departments and hospices) in Denmark. Study population The study population is all patients in Denmark referred to and/or in contact with SPC after January 1, 2010. Main variables The main variables in DPD are data about referral for patients admitted and not admitted to SPC, type of the first SPC contact, clinical and sociodemographic factors, multidisciplinary conference, and the patient-reported European Organisation for Research and Treatment of Cancer Quality of Life Questionaire-Core-15-Palliative Care questionnaire, assessing health-related quality of life. The data support the estimation of currently five quality of care indicators, ie, the proportions of 1) referred and eligible patients who were actually admitted to SPC, 2) patients who waited <10 days before admission to SPC, 3) patients who died from cancer and who obtained contact with SPC, 4) patients who were screened with European Organisation for Research and Treatment of Cancer Quality of Life Questionaire-Core-15-Palliative Care at admission to SPC, and 5) patients who were discussed at a multidisciplinary conference. Descriptive data In 2014, all 43 SPC units in Denmark reported their data to DPD, and all 9,434 cancer patients (100%) referred to SPC were registered in DPD. In total, 41,104 unique cancer patients were registered in DPD during the 5 years 2010–2014. Of those registered, 96% had cancer. Conclusion DPD is a national clinical quality database for SPC having clinically relevant variables and high data and patient completeness. PMID:27822111

  6. Danish Colorectal Cancer Group Database

    PubMed Central

    Ingeholm, Peter; Gögenur, Ismail; Iversen, Lene H

    2016-01-01

    Aim of database The aim of the database, which has existed for registration of all patients with colorectal cancer in Denmark since 2001, is to improve the prognosis for this patient group. Study population All Danish patients with newly diagnosed colorectal cancer who are either diagnosed or treated in a surgical department of a public Danish hospital. Main variables The database comprises an array of surgical, radiological, oncological, and pathological variables. The surgeons record data such as diagnostics performed, including type and results of radiological examinations, lifestyle factors, comorbidity and performance, treatment including the surgical procedure, urgency of surgery, and intra- and postoperative complications within 30 days after surgery. The pathologists record data such as tumor type, number of lymph nodes and metastatic lymph nodes, surgical margin status, and other pathological risk factors. Descriptive data The database has had >95% completeness in including patients with colorectal adenocarcinoma with >54,000 patients registered so far with approximately one-third rectal cancers and two-third colon cancers and an overrepresentation of men among rectal cancer patients. The stage distribution has been more or less constant until 2014 with a tendency toward a lower rate of stage IV and higher rate of stage I after introduction of the national screening program in 2014. The 30-day mortality rate after elective surgery has been reduced from >7% in 2001–2003 to <2% since 2013. Conclusion The database is a national population-based clinical database with high patient and data completeness for the perioperative period. The resolution of data is high for description of the patient at the time of diagnosis, including comorbidities, and for characterizing diagnosis, surgical interventions, and short-term outcomes. The database does not have high-resolution oncological data and does not register recurrences after primary surgery. The Danish

  7. The Danish Bladder Cancer Database

    PubMed Central

    Hansen, Erik; Larsson, Heidi; Nørgaard, Mette; Thind, Peter; Jensen, Jørgen Bjerggaard

    2016-01-01

    Aim of database The aim of the Danish Bladder Cancer Database (DaBlaCa-data) is to monitor the treatment of all patients diagnosed with invasive bladder cancer (BC) in Denmark. Study population All patients diagnosed with BC in Denmark from 2012 onward were included in the study. Results presented in this paper are predominantly from the 2013 population. Main variables In 2013, 970 patients were diagnosed with BC in Denmark and were included in a preliminary report from the database. A total of 458 (47%) patients were diagnosed with non-muscle-invasive BC (non-MIBC) and 512 (53%) were diagnosed with muscle-invasive BC (MIBC). A total of 300 (31%) patients underwent cystectomy. Among the 135 patients diagnosed with MIBC, who were 75 years of age or younger, 67 (50%) received neoadjuvent chemotherapy prior to cystectomy. In 2013, a total of 147 patients were treated with curative-intended radiation therapy. Descriptive data One-year mortality was 28% (95% confidence interval [CI]: 15–21). One-year cancer-specific mortality was 25% (95% CI: 22–27%). One-year mortality after cystectomy was 14% (95% CI: 10–18). Ninety-day mortality after cystectomy was 3% (95% CI: 1–5) in 2013. One-year mortality following curative-intended radiation therapy was 32% (95% CI: 24–39) and 1-year cancer-specific mortality was 23% (95% CI: 16–31) in 2013. Conclusion This preliminary DaBlaCa-data report showed that the treatment of MIBC in Denmark overall meet high international academic standards. The database is able to identify Danish BC patients and monitor treatment and mortality. In the future, DaBlaCa-data will be a valuable data source and expansive observational studies on BC will be available. PMID:27822081

  8. The Danish Prostate Cancer Database

    PubMed Central

    Nguyen-Nielsen, Mary; Høyer, Søren; Friis, Søren; Hansen, Steinbjørn; Brasso, Klaus; Jakobsen, Erik Breth; Moe, Mette; Larsson, Heidi; Søgaard, Mette; Nakano, Anne; Borre, Michael

    2016-01-01

    Aim of database The Danish Prostate Cancer Database (DAPROCAdata) is a nationwide clinical cancer database that has prospectively collected data on patients with incident prostate cancer in Denmark since February 2010. The overall aim of the DAPROCAdata is to improve the quality of prostate cancer care in Denmark by systematically collecting key clinical variables for the purposes of health care monitoring, quality improvement, and research. Study population All Danish patients with histologically verified prostate cancer are included in the DAPROCAdata. Main variables The DAPROCAdata registers clinical data and selected characteristics for patients with prostate cancer at diagnosis. Data are collected from the linkage of nationwide health registries and supplemented with online registration of key clinical variables by treating physicians at urological and oncological departments. Main variables include Gleason scores, cancer staging, prostate-specific antigen values, and therapeutic measures (active surveillance, surgery, radiotherapy, endocrine therapy, and chemotherapy). Descriptive data In total, 22,332 patients with prostate cancer were registered in DAPROCAdata as of April 2015. A key feature of DAPROCAdata is the routine collection of patient-reported outcome measures (PROM), including data on quality-of-life (pain levels, physical activity, sexual function, depression, urine and fecal incontinence) and lifestyle factors (smoking, alcohol consumption, and body mass index). PROM data are derived from questionnaires distributed at diagnosis and at 1-year and 3-year follow-up. Hitherto, the PROM data have been limited by low completeness (26% among newly diagnosed patients in 2014). Conclusion DAPROCAdata is a comprehensive, yet still young clinical database. Efforts to improve data collection, data validity, and completeness are ongoing and of high priority. PMID:27843346

  9. The Danish Cardiac Rehabilitation Database

    PubMed Central

    Zwisler, Ann-Dorthe; Rossau, Henriette Knold; Nakano, Anne; Foghmar, Sussie; Eichhorst, Regina; Prescott, Eva; Cerqueira, Charlotte; Soja, Anne Merete Boas; Gislason, Gunnar H; Larsen, Mogens Lytken; Andersen, Ulla Overgaard; Gustafsson, Ida; Thomsen, Kristian K; Boye Hansen, Lene; Hammer, Signe; Viggers, Lone; Christensen, Bo; Kvist, Birgitte; Lindström Egholm, Cecilie; May, Ole

    2016-01-01

    Aim of database The Danish Cardiac Rehabilitation Database (DHRD) aims to improve the quality of cardiac rehabilitation (CR) to the benefit of patients with coronary heart disease (CHD). Study population Hospitalized patients with CHD with stenosis on coronary angiography treated with percutaneous coronary intervention, coronary artery bypass grafting, or medication alone. Reporting is mandatory for all hospitals in Denmark delivering CR. The database was initially implemented in 2013 and was fully running from August 14, 2015, thus comprising data at a patient level from the latter date onward. Main variables Patient-level data are registered by clinicians at the time of entry to CR directly into an online system with simultaneous linkage to other central patient registers. Follow-up data are entered after 6 months. The main variables collected are related to key outcome and performance indicators of CR: referral and adherence, lifestyle, patient-related outcome measures, risk factor control, and medication. Program-level online data are collected every third year. Descriptive data Based on administrative data, approximately 14,000 patients with CHD are hospitalized at 35 hospitals annually, with 75% receiving one or more outpatient rehabilitation services by 2015. The database has not yet been running for a full year, which explains the use of approximations. Conclusion The DHRD is an online, national quality improvement database on CR, aimed at patients with CHD. Mandatory registration of data at both patient level as well as program level is done on the database. DHRD aims to systematically monitor the quality of CR over time, in order to improve the quality of CR throughout Denmark to benefit patients. PMID:27822083

  10. The Danish National Quality Database for Births

    PubMed Central

    Andersson, Charlotte Brix; Flems, Christina; Kesmodel, Ulrik Schiøler

    2016-01-01

    Aim of the database The aim of the Danish National Quality Database for Births (DNQDB) is to measure the quality of the care provided during birth through specific indicators. Study population The database includes all hospital births in Denmark. Main variables Anesthesia/pain relief, continuous support for women in the delivery room, lacerations (third and fourth degree), cesarean section, postpartum hemorrhage, establishment of skin-to-skin contact between the mother and the newborn infant, severe fetal hypoxia (proportion of live-born children with neonatal hypoxia), delivery of a healthy child after an uncomplicated birth, and anesthesia in case of cesarean section. Descriptive data Data have been collected since 2010. As of August 2015, data on women and children representing 269,597 births and 274,153 children have been collected. All data for the DNQDB is collected from the Danish Medical Birth Registry. Registration to the Danish Medical Birth Registry is mandatory for all maternity units in Denmark. During the 5 years, performance has improved in the areas covered by the process indicators and for some of the outcome indicators. Conclusion Measuring quality of care during childbirth has inspired and enabled staff to attend to the quality of the care they provide and has led to improvements in most of the areas covered. PMID:27822105

  11. The Danish Nonmelanoma Skin Cancer Dermatology Database

    PubMed Central

    Lamberg, Anna Lei; Sølvsten, Henrik; Lei, Ulrikke; Vinding, Gabrielle Randskov; Stender, Ida Marie; Jemec, Gregor Borut Ernst; Vestergaard, Tine; Thormann, Henrik; Hædersdal, Merete; Dam, Tomas Norman; Olesen, Anne Braae

    2016-01-01

    Aim of database The Danish Nonmelanoma Skin Cancer Dermatology Database was established in 2008. The aim of this database was to collect data on nonmelanoma skin cancer (NMSC) treatment and improve its treatment in Denmark. NMSC is the most common malignancy in the western countries and represents a significant challenge in terms of public health management and health care costs. However, high-quality epidemiological and treatment data on NMSC are sparse. Study population The NMSC database includes patients with the following skin tumors: basal cell carcinoma (BCC), squamous cell carcinoma, Bowen’s disease, and keratoacanthoma diagnosed by the participating office-based dermatologists in Denmark. Main variables Clinical and histological diagnoses, BCC subtype, localization, size, skin cancer history, skin phototype, and evidence of metastases and treatment modality are the main variables in the NMSC database. Information on recurrence, cosmetic results, and complications are registered at two follow-up visits at 3 months (between 0 and 6 months) and 12 months (between 6 and 15 months) after treatment. Descriptive data In 2014, 11,522 patients with 17,575 tumors were registered in the database. Of tumors with a histological diagnosis, 13,571 were BCCs, 840 squamous cell carcinomas, 504 Bowen’s disease, and 173 keratoakanthomas. Conclusion The NMSC database encompasses detailed information on the type of tumor, a variety of prognostic factors, treatment modalities, and outcomes after treatment. The database has revealed that overall, the quality of care of NMSC in Danish dermatological clinics is high, and the database provides the necessary data for continuous quality assurance. PMID:27822110

  12. The Danish Head and Neck Cancer database

    PubMed Central

    Overgaard, Jens; Jovanovic, Aleksandar; Godballe, Christian; Grau Eriksen, Jesper

    2016-01-01

    Aim of the database The Danish Head and Neck Cancer database is a nationwide clinical quality database that contains prospective data collected since the early 1960s. The overall aim of this study was to describe the outcome of the national strategy for multidisciplinary treatment of head and neck cancer in Denmark and to create a basis for clinical trials. Study population The study population consisted of all Danish patients referred for treatment of squamous cell carcinoma of the larynx, pharynx, oral cavity, or neck nodes from unknown primary or any histopathological type (except lymphoma) of cancer in the nasal sinuses, salivary glands, or thyroid gland (corresponding to the International Classification of Diseases, tenth revision, classifications C.01–C.11, C.30–C.32, C.73, and C.80). Main variables The main variables used in the study were symptoms and the duration of the symptoms; etiological factors; pretreatment and diagnostic evaluation, including tumor–node–metastasis classification, imaging, histopathology, and laboratory tests; primary treatment with semidetailed information of radiotherapy, surgery, and medical treatment; follow-up registration of tumor status and side effects; registration of relapse and treatment thereof; and registration of death and cause of death. Main results Data from >33,000 patients have been recorded during a period of >45 years. In this period, the outcome of treatment improved substantially, partly due to better treatment as a result of a series of continuous clinical trials and subsequent implementation in national guidelines. The database has furthermore been used to describe the effect of reduced waiting time, changed epidemiology, and influence of comorbidity and socioeconomic parameters. Conclusion Half a century of registration of head and neck cancer treatment and outcome has created the basis for understanding and has substantially contributed to improve the treatment of head and neck cancer at both

  13. The Danish National Penile Cancer Quality database

    PubMed Central

    Jakobsen, Jakob Kristian; Öztürk, Buket; Søgaard, Mette

    2016-01-01

    Aim of database The Danish National Penile Cancer Quality database (DaPeCa-data) aims to improve the quality of cancer care and monitor the diagnosis, staging, and treatment of all incident penile cancer cases in Denmark. The aim is to assure referral practice, guideline adherence, and treatment and development of the database in order to enhance research opportunities and increase knowledge and survival outcomes of penile cancer. Study population The DaPeCa-data registers all patients with newly diagnosed invasive squamous cell carcinoma of the penis in Denmark since June 2011. Main variables Data are systematically registered at the time of diagnosis by a combination of automated data-linkage to the central registries as well as online registration by treating clinicians. The main variables registered relate to disease prognosis and treatment morbidity and include the presence of risk factors (phimosis, lichen sclerosus, and human papillomavirus), date of diagnosis, date of treatment decision, date of beginning of treatment, type of treatment, treating hospital, type and time of complications, date of recurrence, date of death, and cause of death. Descriptive data Registration of these variables correlated to the unique Danish ten-digit civil registration number enables characterization of the cohort, individual patients, and patient groups with respect to age; 1-, 3-, and 5-year disease-specific and overall survival; recurrence patterns; and morbidity profile related to treatment modality. As of August 2015, more than 200 patients are registered with ∼65 new entries per year. Conclusion The DaPeCa-data has potential to provide meaningful, timely, and clinically relevant quality data for quality maintenance, development, and research purposes. PMID:27822104

  14. 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.

  15. The Danish Microbiology Database (MiBa) 2010 to 2013.

    PubMed

    Voldstedlund, M; Haarh, M; Mølbak, K

    2014-01-09

    The Danish Microbiology Database (MiBa) is a national database that receives copies of reports from all Danish departments of clinical microbiology. The database was launched in order to provide healthcare personnel with nationwide access to microbiology reports and to enable real-time surveillance of communicable diseases and microorganisms. The establishment and management of MiBa has been a collaborative process among stakeholders, and the present paper summarises lessons learned from this nationwide endeavour which may be relevant to similar projects in the rapidly changing landscape of health informatics.

  16. Towards global QSAR model building for acute toxicity: Munro database case study.

    PubMed

    Chavan, Swapnil; Nicholls, Ian A; Karlsson, Björn C G; Rosengren, Annika M; Ballabio, Davide; Consonni, Viviana; Todeschini, Roberto

    2014-10-09

    A series of 436 Munro database chemicals were studied with respect to their corresponding experimental LD50 values to investigate the possibility of establishing a global QSAR model for acute toxicity. Dragon molecular descriptors were used for the QSAR model development and genetic algorithms were used to select descriptors better correlated with toxicity data. Toxic values were discretized in a qualitative class on the basis of the Globally Harmonized Scheme: the 436 chemicals were divided into 3 classes based on their experimental LD50 values: highly toxic, intermediate toxic and low to non-toxic. The k-nearest neighbor (k-NN) classification method was calibrated on 25 molecular descriptors and gave a non-error rate (NER) equal to 0.66 and 0.57 for internal and external prediction sets, respectively. Even if the classification performances are not optimal, the subsequent analysis of the selected descriptors and their relationship with toxicity levels constitute a step towards the development of a global QSAR model for acute toxicity.

  17. The Danish quality database for prehospital emergency medical services

    PubMed Central

    Frischknecht Christensen, Erika; Berlac, Peter Anthony; Nielsen, Henrik; Christiansen, Christian Fynbo

    2016-01-01

    Aim of database The aim of the Danish quality database for prehospital emergency medical services (QEMS) is to assess, monitor, and improve the quality of prehospital emergency medical service care in the entire prehospital patient pathway. The aim of this review is to describe the design and the implementation of QEMS. Study population The study population consists of all “112 patient contacts” defined as emergency patients, where the entrance to health care is a 112 call forwarded to one of the five regional emergency medical coordination centers in Denmark since January 1, 2014. Estimated annual number of included “112 patients” is 300,000–350,000. Main variables We defined nine quality indicators and the following variables: time stamps for emergency calls received at one of the five regional emergency medical coordination centers, dispatch of prehospital unit(s), arrival of first prehospital unit, arrival of first supplemental prehospital unit, and mission completion. Finally, professional level and type of the prehospital resource dispatched to an incident and end-of-mission status (mission completed by phone, on scene, or admission to hospital) are registered. Descriptive data Descriptive data included age, region, and Danish Index for Emergency Care including urgency level. Conclusion QEMS is a new database under establishment and is expected to provide the basis for quality improvement in the prehospital setting and in the entire patient care pathway, for example, by providing prehospital data for research and other quality databases. PMID:27843347

  18. The Danish National Database for Asthma: establishing clinical quality indicators

    PubMed Central

    Hansen, Susanne; Hoffmann-Petersen, Benjamin; Sverrild, Asger; Bräuner, Elvira V.; Lykkegaard, Jesper; Bodtger, Uffe; Agertoft, Lone; Korshøj, Lene; Backer, Vibeke

    2016-01-01

    Asthma is one of the most common chronic diseases worldwide affecting more than 300 million people. Symptoms are often non-specific and include coughing, wheezing, chest tightness, and shortness of breath. Asthma may be highly variable within the same individual over time. Although asthma results in death only in extreme cases, the disease is associated with significant morbidity, reduced quality of life, increased absenteeism, and large costs for society. Asthma can be diagnosed based on report of characteristic symptoms and/or the use of several different diagnostic tests. However, there is currently no gold standard for making a diagnosis, and some degree of misclassification and inter-observer variation can be expected. This may lead to local and regional differences in the treatment, monitoring, and follow-up of the patients. The Danish National Database for Asthma (DNDA) is slated to be established with the overall aim of collecting data on all patients treated for asthma in Denmark and systematically monitoring the treatment quality and disease management in both primary and secondary care facilities across the country. The DNDA links information from population-based disease registers in Denmark, including the National Patient Register, the National Prescription Registry, and the National Health Insurance Services register, and potentially includes all asthma patients in Denmark. The following quality indicators have been selected to monitor trends: first, conduction of annual asthma control visits, appropriate pharmacological treatment, measurement of lung function, and asthma challenge testing; second, tools used for diagnosis in new cases; and third, annual assessment of smoking status, height, and weight measurements, and the proportion of patients with acute hospital treatment. The DNDA will be launched in 2016 and will initially include patients treated in secondary care facilities in Denmark. In the nearby future, the database aims to include asthma

  19. Validity of data in the Danish Colorectal Cancer Screening Database

    PubMed Central

    Thomsen, Mette Kielsholm; Njor, Sisse Helle; Rasmussen, Morten; Linnemann, Dorte; Andersen, Berit; Baatrup, Gunnar; Friis-Hansen, Lennart Jan; Jørgensen, Jens Christian Riis; Mikkelsen, Ellen Margrethe

    2017-01-01

    Background In Denmark, a nationwide screening program for colorectal cancer was implemented in March 2014. Along with this, a clinical database for program monitoring and research purposes was established. Objective The aim of this study was to estimate the agreement and validity of diagnosis and procedure codes in the Danish Colorectal Cancer Screening Database (DCCSD). Methods All individuals with a positive immunochemical fecal occult blood test (iFOBT) result who were invited to screening in the first 3 months since program initiation were identified. From these, a sample of 150 individuals was selected using stratified random sampling by age, gender and region of residence. Data from the DCCSD were compared with data from hospital records, which were used as the reference. Agreement, sensitivity, specificity and positive and negative predictive values were estimated for categories of codes “clean colon”, “colonoscopy performed”, “overall completeness of colonoscopy”, “incomplete colonoscopy”, “polypectomy”, “tumor tissue left behind”, “number of polyps”, “lost polyps”, “risk group of polyps” and “colorectal cancer and polyps/benign tumor”. Results Hospital records were available for 136 individuals. Agreement was highest for “colorectal cancer” (97.1%) and lowest for “lost polyps” (88.2%). Sensitivity varied between moderate and high, with 60.0% for “incomplete colonoscopy” and 98.5% for “colonoscopy performed”. Specificity was 92.7% or above, except for the categories “colonoscopy performed” and “overall completeness of colonoscopy”, where the specificity was low; however, the estimates were imprecise. Conclusion A high level of agreement between categories of codes in DCCSD and hospital records indicates that DCCSD reflects the hospital records well. Further, the validity of the categories of codes varied from moderate to high. Thus, the DCCSD may be a valuable data source for future research on

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

    PubMed

    Zhu, Xiao; Kruhlak, Naomi L

    2014-07-03

    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.

  1. 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

  2. Quantitative Structure activity Relationship Analysis of Pyridinone HIV-1 Reverse Transcriptase Inhibitors using the k Nearest Neighbor Method and QSAR-based Database Mining

    NASA Astrophysics Data System (ADS)

    Medina-Franco, Jose Luis; Golbraikh, Alexander; Oloff, Scott; Castillo, Rafael; Tropsha, Alexander

    2005-04-01

    We have developed quantitative structure-activity relationship (QSAR) models for 44 non-nucleoside HIV-1 reverse transcriptase inhibitors (NNRTIs) of the pyridinone derivative type. The k nearest neighbor ( kNN) variable selection approach was used. This method utilizes multiple descriptors such as molecular connectivity indices, which are derived from two-dimensional molecular topology. The modeling process entailed extensive validation including the randomization of the target property (Y-randomization) test and the division of the dataset into multiple training and test sets to establish the external predictive power of the training set models. QSAR models with high internal and external accuracy were generated, with leave-one-out cross-validated R 2 ( q 2) values ranging between 0.5 and 0.8 for the training sets and R 2 values exceeding 0.6 for the test sets. The best models with the highest internal and external predictive power were used to search the National Cancer Institute database. Derivatives of the pyrazolo[3,4- d]pyrimidine and phenothiazine type were identified as promising novel NNRTIs leads. Several candidates were docked into the binding pocket of nevirapine with the AutoDock (version 3.0) software. Docking results suggested that these types of compounds could be binding in the NNRTI binding site in a similar mode to a known non-nucleoside inhibitor nevirapine.

  3. Real-time surveillance of laboratory confirmed influenza based on the Danish microbiology database (MiBa).

    PubMed

    Voldstedlund, Marianne; Haahr, Malene; Emborg, Hanne-Dorthe; Bang, Henrik; Krause, Tyra

    2013-01-01

    The Danish microbiology database (MiBa) is a national database that automatically accumulates patient test results from all Danish Departments of Clinical Microbiology. As an example for use of MiBa, we describe the real-time surveillance of laboratory confirmed influenza established in October 2012. It functions without any extra burdens of reporting by laboratories or clinicians. This is an important improvement of the existing surveillance for influenza like illness (ILI) which includes only limited virological testing. The MiBa based surveillance adds complete national virological data which are specific for influenza, in contrast to ILI, and serves as a tool for regional and national preparedness and planning.

  4. Danish Prostate Cancer Registry – methodology and early results from a novel national database

    PubMed Central

    Helgstrand, JT; Klemann, N; Røder, MA; Toft, BG; Brasso, K; Vainer, B; Iversen, P

    2016-01-01

    Background Systematized Nomenclature of Medicine (SNOMED) codes are computer-processable medical terms used to describe histopathological evaluations. SNOMED codes are not readily usable for analysis. We invented an algorithm that converts prostate SNOMED codes into an analyzable format. We present the methodology and early results from a new national Danish prostate database containing clinical data from all males who had evaluation of prostate tissue from 1995 to 2011. Materials and methods SNOMED codes were retrieved from the Danish Pathology Register. A total of 26,295 combinations of SNOMED codes were identified. A computer algorithm was developed to transcode SNOMED codes into an analyzable format including procedure (eg, biopsy, transurethral resection, etc), diagnosis, and date of diagnosis. For validation, ~55,000 pathological reports were manually reviewed. Prostate-specific antigen, vital status, causes of death, and tumor-node-metastasis classification were integrated from national registries. Results Of the 161,525 specimens from 113,801 males identified, 83,379 (51.6%) were sets of prostate biopsies, 56,118 (34.7%) were transurethral/transvesical resections of the prostate (TUR-Ps), and the remaining 22,028 (13.6%) specimens were derived from radical prostatectomies, bladder interventions, etc. A total of 48,078 (42.2%) males had histopathologically verified prostate cancer, and of these, 78.8% and 16.8% were diagnosed on prostate biopsies and TUR-Ps, respectively. Future perspectives A validated algorithm was successfully developed to convert complex prostate SNOMED codes into clinical useful data. A unique database, including males with both normal and cancerous histopathological data, was created to form the most comprehensive national prostate database to date. Potentially, our algorithm can be used for conversion of other SNOMED data and is available upon request. PMID:27729813

  5. Prediction of 222Rn in Danish dwellings using geology and house construction information from central databases.

    PubMed

    Andersen, Claus E; Raaschou-Nielsen, Ole; Andersen, Helle Primdal; Lind, Morten; Gravesen, Peter; Thomsen, Birthe L; Ulbak, Kaare

    2007-01-01

    A linear regression model has been developed for the prediction of indoor (222)Rn in Danish houses. The model provides proxy radon concentrations for about 21,000 houses in a Danish case-control study on the possible association between residential radon and childhood cancer (primarily leukaemia). The model was calibrated against radon measurements in 3116 houses. An independent dataset with 788 house measurements was used for model performance assessment. The model includes nine explanatory variables, of which the most important ones are house type and geology. All explanatory variables are available from central databases. The model was fitted to log-transformed radon concentrations and it has an R(2) of 40%. The uncertainty associated with individual predictions of (untransformed) radon concentrations is about a factor of 2.0 (one standard deviation). The comparison with the independent test data shows that the model makes sound predictions and that errors of radon predictions are only weakly correlated with the estimates themselves (R(2) = 10%).

  6. Fusobacterium necrophorum findings in Denmark from 2010 to 2014 using data from the Danish microbiology database.

    PubMed

    Bank, Steffen; Jensen, Anders; Nielsen, Hanne Merete; Kristensen, Lena Hagelskjaer; Voldstedlund, Marianne; Prag, Jørgen

    2016-12-01

    Fusobacterium necrophorum findings in Denmark and estimation of the incidence of F. necrophorum bacteraemia was described using data from the nationwide Danish microbiology database (MiBa). All microbiological reports on any Fusobacterium species in Denmark were extracted for a period of 5 years from 2010 to 2014 from MiBa and from the local department of clinical microbiology. The overall incidence of F. necrophorum bacteraemia from 2010 to 2014 was 2.8 cases per million/year vs 9.4 in the age group 15-24 years. F. necrophorum was rare in blood cultures from children and middle-aged patients and then raised again. However, 48 of 232 cases of Fusobacterium bacteraemia were not identified to species level, so the incidences of F. necrophorum bacteraemia may be underestimated in our study. F. necrophorum was found in throat swabs in the age group between 13 and 40 years and in otitis media in children below 2 years in those departments which performed anaerobic culture. The incidence of F. necrophorum bacteraemia found was comparable to earlier reported figures for Lemierre's syndrome. Fusobacterium bacteraemia should always be identified to species level.

  7. Incorporation of the CrossFire Beilstein Database into the Organic Chemistry Curriculum at the Royal Danish School of Pharmacy

    NASA Astrophysics Data System (ADS)

    Brøgger Christensen, S.; Franzyk, Henrik; Frølund, Bente; Jaroszewski, Jerzy W.; Stærk, Dan; Vedsø, Per

    2002-06-01

    The CrossFire Beilstein database has been incorporated into the organic chemistry curriculum at the Royal Danish School of Pharmacy as a powerful pedagogic tool. During a laboratory course in organic synthesis the database enables the students to get comprehensive overviews of known synthetic methods for a given compound. During a laboratory course in identification and as a part of an applied course in organic spectroscopy the students use the database for obtaining lists of all recorded isomeric compounds, facilitating an exhaustive identification. The main entrances for identification purposes are molecular formulas deduced either from titrations or from mass spectra combined with partial structures identified by chemical tests, or by interpretation of spectra. Thus, identifications made using the CrossFire Beilstein database will exclude some possibilities and point to correct structures from a selection of existing compounds. This appears to help the learning process considerably.

  8. How can the research potential of the clinical quality databases be maximized? The Danish experience.

    PubMed

    Nørgaard, M; Johnsen, S P

    2016-02-01

    In Denmark, the need for monitoring of clinical quality and patient safety with feedback to the clinical, administrative and political systems has resulted in the establishment of a network of more than 60 publicly financed nationwide clinical quality databases. Although primarily devoted to monitoring and improving quality of care, the potential of these databases as data sources in clinical research is increasingly being recognized. In this review, we describe these databases focusing on their use as data sources for clinical research, including their strengths and weaknesses as well as future concerns and opportunities. The research potential of the clinical quality databases is substantial but has so far only been explored to a limited extent. Efforts related to technical, legal and financial challenges are needed in order to take full advantage of this potential.

  9. Development of an algorithm to identify urgent referrals for suspected cancer from the Danish Primary Care Referral Database

    PubMed Central

    Toftegaard, Berit Skjødeberg; Guldbrandt, Louise Mahncke; Flarup, Kaare Rud; Beyer, Hanne; Bro, Flemming; Vedsted, Peter

    2016-01-01

    Background Accurate identification of specific patient populations is a crucial tool in health care. A prerequisite for exploring the actions taken by general practitioners (GPs) on symptoms of cancer is being able to identify patients urgently referred for suspected cancer. Such system is not available in Denmark; however, all referrals are electronically stored. This study aimed to develop and test an algorithm based on referral text to identify urgent cancer referrals from general practice. Methods Two urgently referred reference populations were extracted from a research database and linked with the Primary Care Referral (PCR) database through the unique Danish civil registration number to identify the corresponding electronic referrals. The PCR database included GP referrals directed to private specialists and hospital departments, and these referrals were scrutinized. The most frequently used words were integrated in the first version of the algorithm, which was further refined by an iterative process involving two population samples from the PCR database. The performance was finally evaluated for two other PCR population samples against manual assessment as the gold standard for urgent cancer referral. Results The final algorithm had a sensitivity of 0.939 (95% confidence intervals [CI]: 0.905–0.963) and a specificity of 0.937 (95% CI: 0.925–0.963) compared to the gold standard. The positive and negative predictive values were 69.8% (95% CI: 65.0–74.3) and 99.0% (95% CI: 98.4–99.4), respectively. When applying the algorithm on referrals for a population without earlier cancer diagnoses, the positive predictive value increased to 83.6% (95% CI: 78.7–87.7) and the specificity to 97.3% (95% CI: 96.4–98.0). Conclusion The final algorithm identified 94% of the patients urgently referred for suspected cancer; less than 3% of the patients were incorrectly identified. It is now possible to identify patients urgently referred on cancer suspicion from

  10. Uncertainty in QSAR predictions.

    PubMed

    Sahlin, Ullrika

    2013-03-01

    It is relevant to consider uncertainty in individual predictions when quantitative structure-activity (or property) relationships (QSARs) are used to support decisions of high societal concern. Successful communication of uncertainty in the integration of QSARs in chemical safety assessment under the EU Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) system can be facilitated by a common understanding of how to define, characterise, assess and evaluate uncertainty in QSAR predictions. A QSAR prediction is, compared to experimental estimates, subject to added uncertainty that comes from the use of a model instead of empirically-based estimates. A framework is provided to aid the distinction between different types of uncertainty in a QSAR prediction: quantitative, i.e. for regressions related to the error in a prediction and characterised by a predictive distribution; and qualitative, by expressing our confidence in the model for predicting a particular compound based on a quantitative measure of predictive reliability. It is possible to assess a quantitative (i.e. probabilistic) predictive distribution, given the supervised learning algorithm, the underlying QSAR data, a probability model for uncertainty and a statistical principle for inference. The integration of QSARs into risk assessment may be facilitated by the inclusion of the assessment of predictive error and predictive reliability into the "unambiguous algorithm", as outlined in the second OECD principle.

  11. 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

  12. The Use of Qsar and Computational Methods in Drug Design

    NASA Astrophysics Data System (ADS)

    Bajot, Fania

    The application of quantitative structure-activity relationships (QSARs) has significantly impacted the paradigm of drug discovery. Following the successful utilization of linear solvation free-energy relationships (LSERs), numerous 2D- and 3D-QSAR methods have been developed, most of them based on descriptors for hydrophobicity, polarizability, ionic interactions, and hydrogen bonding. QSAR models allow for the calculation of physicochemical properties (e.g., lipophilicity), the prediction of biological activity (or toxicity), as well as the evaluation of absorption, distribution, metabolism, and excretion (ADME). In pharmaceutical research, QSAR has a particular interest in the preclinical stages of drug discovery to replace tedious and costly experimentation, to filter large chemical databases, and to select drug candidates. However, to be part of drug discovery and development strategies, QSARs need to meet different criteria (e.g., sufficient predictivity). This chapter describes the foundation of modern QSAR in drug discovery and presents some current challenges and applications for the discovery and optimization of drug candidates

  13. Discrete Derivatives for Atom-Pairs as a Novel Graph-Theoretical Invariant for Generating New Molecular Descriptors: Orthogonality, Interpretation and QSARs/QSPRs on Benchmark Databases.

    PubMed

    Martínez-Santiago, Oscar; Millán-Cabrera, Reisel; Marrero-Ponce, Yovani; Barigye, Stephen J; Martínez-López, Yoan; Torrens, Francisco; Pérez-Giménez, Facundo

    2014-05-01

    indices and other 0-3D MDs is demonstrated by using principal component analysis on a dataset of 41 heterogeneous molecules. It is concluded that the graph derivative indices are independent indices containing important structural information to be used in QSPR/QSAR and drug design studies, and permit obtaining easier, more interpretable and robust mathematical models than the majority of those reported in the literature.

  14. TOXICO-CHEMINFORMATICS AND QSAR MODELING OF ...

    EPA Pesticide Factsheets

    This abstract concludes that QSAR approaches combined with toxico-chemoinformatics descriptors can enhance predictive toxicology models. This abstract concludes that QSAR approaches combined with toxico-chemoinformatics descriptors can enhance predictive toxicology models.

  15. Rational selection of training and test sets for the development of validated QSAR models

    NASA Astrophysics Data System (ADS)

    Golbraikh, Alexander; Shen, Min; Xiao, Zhiyan; Xiao, Yun-De; Lee, Kuo-Hsiung; Tropsha, Alexander

    2003-02-01

    Quantitative Structure-Activity Relationship (QSAR) models are used increasingly to screen chemical databases and/or virtual chemical libraries for potentially bioactive molecules. These developments emphasize the importance of rigorous model validation to ensure that the models have acceptable predictive power. Using k nearest neighbors ( kNN) variable selection QSAR method for the analysis of several datasets, we have demonstrated recently that the widely accepted leave-one-out (LOO) cross-validated R2 (q2) is an inadequate characteristic to assess the predictive ability of the models [Golbraikh, A., Tropsha, A. Beware of q2! J. Mol. Graphics Mod. 20, 269-276, (2002)]. Herein, we provide additional evidence that there exists no correlation between the values of q 2 for the training set and accuracy of prediction ( R 2) for the test set and argue that this observation is a general property of any QSAR model developed with LOO cross-validation. We suggest that external validation using rationally selected training and test sets provides a means to establish a reliable QSAR model. We propose several approaches to the division of experimental datasets into training and test sets and apply them in QSAR studies of 48 functionalized amino acid anticonvulsants and a series of 157 epipodophyllotoxin derivatives with antitumor activity. We formulate a set of general criteria for the evaluation of predictive power of QSAR models.

  16. 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

  17. QSARs in Netherlands water quality management policies.

    PubMed

    van der Gaag, M A

    1991-12-01

    QSARs are a useful tool for predicting the potential toxic effects of compounds for which no data are available. Within strictly defined limits, QSARs can be applied to assess the potential impact of a spill, to evaluate ecotoxicological effects and environmental fate of organics in waste water and to set priorities for water quality criteria. For a wider application, there is a need for 'worst case' SARs providing a 'safer' estimate of toxicity than QSARs with an optimum fit, which might underestimate toxicity.

  18. The Danish Stroke Registry

    PubMed Central

    Johnsen, Søren Paaske; Ingeman, Annette; Hundborg, Heidi Holmager; Schaarup, Susanne Zielke; Gyllenborg, Jesper

    2016-01-01

    Aim of database The aim of the Danish Stroke Registry is to monitor and improve the quality of care among all patients with acute stroke and transient ischemic attack (TIA) treated at Danish hospitals. Study population All patients with acute stroke (from 2003) or TIA (from 2013) treated at Danish hospitals. Reporting is mandatory by law for all hospital departments treating these patients. The registry included >130,000 events by the end of 2014, including 10,822 strokes and 4,227 TIAs registered in 2014. Main variables The registry holds prospectively collected data on key processes of care, mainly covering the early phase after stroke, including data on time of delivery of the processes and the eligibility of the individual patients for each process. The data are used for assessing 18 process indicators reflecting recommendations in the national clinical guidelines for patients with acute stroke and TIA. Patient outcomes are currently monitored using 30-day mortality, unplanned readmission, and for patients receiving revascularization therapy, also functional level at 3 months poststroke. Descriptive data Sociodemographic, clinical, and lifestyle factors with potential prognostic impact are registered. Conclusion The Danish Stroke Registry is a well-established clinical registry which plays a key role for monitoring and improving stroke and TIA care in Denmark. In addition, the registry is increasingly used for research. PMID:27843349

  19. In silico study of in vitro GPCR assays by QSAR modeling ...

    EPA Pesticide Factsheets

    The U.S. EPA is screening thousands of chemicals of environmental interest in hundreds of in vitro high-throughput screening (HTS) assays (the ToxCast program). One goal is to prioritize chemicals for more detailed analyses based on activity in molecular initiating events (MIE) of adverse outcome pathways (AOPs). However, the chemical space of interest for environmental exposure is much wider than this set of chemicals. Thus, there is a need to fill data gaps with in silico methods, and quantitative structure-activity relationships (QSARs) are a proven and cost effective approach to predict biological activity. ToxCast in turn provides relatively large datasets that are ideal for training and testing QSAR models. The overall goal of the study described here was to develop QSAR models to fill the data gaps in a larger environmental database of ~32k structures. The specific aim of the current work was to build QSAR models for 18 G-Protein Coupled Receptor (GPCR) assays, part of the aminergic category. 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 squares d

  20. Development of a general baseline toxicity QSAR model for the fish embryo acute toxicity test.

    PubMed

    Klüver, Nils; Vogs, Carolina; Altenburger, Rolf; Escher, Beate I; Scholz, Stefan

    2016-12-01

    Fish embryos have become a popular model in ecotoxicology and toxicology. The fish embryo acute toxicity test (FET) with the zebrafish embryo was recently adopted by the OECD as technical guideline TG 236 and a large database of concentrations causing 50% lethality (LC50) is available in the literature. Quantitative Structure-Activity Relationships (QSARs) of baseline toxicity (also called narcosis) are helpful to estimate the minimum toxicity of chemicals to be tested and to identify excess toxicity in existing data sets. Here, we analyzed an existing fish embryo toxicity database and established a QSAR for fish embryo LC50 using chemicals that were independently classified to act according to the non-specific mode of action of baseline toxicity. The octanol-water partition coefficient Kow is commonly applied to discriminate between non-polar and polar narcotics. Replacing the Kow by the liposome-water partition coefficient Klipw yielded a common QSAR for polar and non-polar baseline toxicants. This developed baseline toxicity QSAR was applied to compare the final mode of action (MOA) assignment of 132 chemicals. Further, we included the analysis of internal lethal concentration (ILC50) and chemical activity (La50) as complementary approaches to evaluate the robustness of the FET baseline toxicity. The analysis of the FET dataset revealed that specifically acting and reactive chemicals converged towards the baseline toxicity QSAR with increasing hydrophobicity. The developed FET baseline toxicity QSAR can be used to identify specifically acting or reactive compounds by determination of the toxic ratio and in combination with appropriate endpoints to infer the MOA for chemicals.

  1. QSAR and 3D QSAR of inhibitors of the epidermal growth factor receptor

    NASA Astrophysics Data System (ADS)

    Pinto-Bazurco, Mariano; Tsakovska, Ivanka; Pajeva, Ilza

    This article reports quantitative structure-activity relationships (QSAR) and 3D QSAR models of 134 structurally diverse inhibitors of the epidermal growth factor receptor (EGFR) tyrosine kinase. Free-Wilson analysis was used to derive the QSAR model. It identified the substituents in aniline, the polycyclic system, and the substituents at the 6- and 7-positions of the polycyclic system as the most important structural features. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were used in the 3D QSAR modeling. The steric and electrostatic interactions proved the most important for the inhibitory effect. Both QSAR and 3D QSAR models led to consistent results. On the basis of the statistically significant models, new structures were proposed and their inhibitory activities were predicted.

  2. A new computer program for QSAR-analysis: ARTE-QSAR.

    PubMed

    Van Damme, Sofie; Bultinck, Patrick

    2007-08-01

    A new computer program has been designed to build and analyze quantitative-structure activity relationship (QSAR) models through regression analysis. The user is provided with a range of regression and validation techniques. The emphasis of the program lies mainly in the validation of QSAR models in chemical applications. ARTE-QSAR produces an easy interpretable output from which the user can conclude if the obtained model is suitable for prediction and analysis.

  3. Systematic generation of chemical structures for rational drug design based on QSAR models.

    PubMed

    Funatsu, Kimito; Miyao, Tomoyuki; Arakawa, Masamoto

    2011-03-01

    The first step in the process of drug development is to determine those lead compounds that demonstrate significant biological activity with regard to a target protein. Because this process is often costly and time consuming, there is a need to develop efficient methodologies for the generation of lead compounds for practical drug design. One promising approach for determining a potent lead compound is computational virtual screening. The biological activities of candidate structures found in virtual libraries are estimated by using quantitative structure activity relationship (QSAR) models and/or computational docking simulations. In virtual screening studies, databases of existing drugs or natural products are commonly used as a source of lead candidates. However, these databases are not sufficient for the purpose of finding lead candidates having novel scaffolds. Therefore, a method must be developed to generate novel molecular structures to indicate high activity for efficient lead discovery. In this paper, we review current trends in structure generation methods for drug design and discuss future directions. First, we present an overview of lead discovery and drug design, and then, we review structure generation methods. Here, the structure generation methods are classified on the basis of whether or not they employ QSAR models for generating structures. We conclude that the use of QSAR models for structure generation is an effective method for computational lead discovery. Finally, we discuss the problems regarding the applicability domain of QSAR models and future directions in this field.

  4. Developing Enhanced Blood–Brain Barrier Permeability Models: Integrating External Bio-Assay Data in QSAR Modeling

    PubMed Central

    Wang, Wenyi; Kim, Marlene T.; Sedykh, Alexander

    2015-01-01

    Purpose Experimental Blood–Brain Barrier (BBB) permeability models for drug molecules are expensive and time-consuming. As alternative methods, several traditional Quantitative Structure-Activity Relationship (QSAR) models have been developed previously. In this study, we aimed to improve the predictivity of traditional QSAR BBB permeability models by employing relevant public bio-assay data in the modeling process. Methods We compiled a BBB permeability database consisting of 439 unique compounds from various resources. The database was split into a modeling set of 341 compounds and a validation set of 98 compounds. Consensus QSAR modeling workflow was employed on the modeling set to develop various QSAR models. A five-fold cross-validation approach was used to validate the developed models, and the resulting models were used to predict the external validation set compounds. Furthermore, we used previously published membrane transporter models to generate relevant transporter profiles for target compounds. The transporter profiles were used as additional biological descriptors to develop hybrid QSAR BBB models. Results The consensus QSAR models have R2=0.638 for fivefold cross-validation and R2=0.504 for external validation. The consensus model developed by pooling chemical and transporter descriptors showed better predictivity (R2=0.646 for five-fold cross-validation and R2=0.526 for external validation). Moreover, several external bio-assays that correlate with BBB permeability were identified using our automatic profiling tool. Conclusions The BBB permeability models developed in this study can be useful for early evaluation of new compounds (e.g., new drug candidates). The combination of chemical and biological descriptors shows a promising direction to improve the current traditional QSAR models. PMID:25862462

  5. 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

  6. Profile-QSAR: a novel meta-QSAR method that combines activities across the kinase family to accurately predict affinity, selectivity, and cellular activity.

    PubMed

    Martin, Eric; Mukherjee, Prasenjit; Sullivan, David; Jansen, Johanna

    2011-08-22

    Profile-QSAR is a novel 2D predictive model building method for kinases. This "meta-QSAR" method models the activity of each compound against a new kinase target as a linear combination of its predicted activities against a large panel of 92 previously studied kinases comprised from 115 assays. Profile-QSAR starts with a sparse incomplete kinase by compound (KxC) activity matrix, used to generate Bayesian QSAR models for the 92 "basis-set" kinases. These Bayesian QSARs generate a complete "synthetic" KxC activity matrix of predictions. These synthetic activities are used as "chemical descriptors" to train partial-least squares (PLS) models, from modest amounts of medium-throughput screening data, for predicting activity against new kinases. The Profile-QSAR predictions for the 92 kinases (115 assays) gave a median external R²(ext) = 0.59 on 25% held-out test sets. The method has proven accurate enough to predict pairwise kinase selectivities with a median correlation of R²(ext) = 0.61 for 958 kinase pairs with at least 600 common compounds. It has been further expanded by adding a "C(k)XC" cellular activity matrix to the KxC matrix to predict cellular activity for 42 kinase driven cellular assays with median R²(ext) = 0.58 for 24 target modulation assays and R²(ext) = 0.41 for 18 cell proliferation assays. The 2D Profile-QSAR, along with the 3D Surrogate AutoShim, are the foundations of an internally developed iterative medium-throughput screening (IMTS) methodology for virtual screening (VS) of compound archives as an alternative to experimental high-throughput screening (HTS). The method has been applied to 20 actual prospective kinase projects. Biological results have so far been obtained in eight of them. Q² values ranged from 0.3 to 0.7. Hit-rates at 10 uM for experimentally tested compounds varied from 25% to 80%, except in K5, which was a special case aimed specifically at finding "type II" binders, where none of the compounds were predicted to be

  7. 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

  8. A QSAR model for predicting rejection of emerging contaminants (pharmaceuticals, endocrine disruptors) by nanofiltration membranes.

    PubMed

    Yangali-Quintanilla, Victor; Sadmani, Anwar; McConville, Megan; Kennedy, Maria; Amy, Gary

    2010-01-01

    A quantitative structure activity relationship (QSAR) model has been produced for predicting rejection of emerging contaminants (pharmaceuticals, endocrine disruptors, pesticides and other organic compounds) by polyamide nanofiltration (NF) membranes. Principal component analysis, partial least square regression and multiple linear regressions were used to find a general QSAR equation that combines interactions between membrane characteristics, filtration operating conditions and compound properties for predicting rejection. Membrane characteristics related to hydrophobicity (contact angle), salt rejection, and surface charge (zeta potential); compound properties describing hydrophobicity (log K(ow), log D), polarity (dipole moment), and size (molar volume, molecular length, molecular depth, equivalent width, molecular weight); and operating conditions namely flux, pressure, cross flow velocity, back diffusion mass transfer coefficient, hydrodynamic ratio (J(o)/k), and recovery were identified as candidate variables for rejection prediction. An experimental database produced by the authors that accounts for 106 rejection cases of emerging contaminants by NF membranes as result of eight experiments with clean and fouled membranes (NF-90, NF-200) was used to produce the QSAR model. Subsequently, using the QSAR model, rejection predictions were made for external experimental databases. Actual rejections were compared against predicted rejections and acceptable R(2) correlation coefficients were found (0.75 and 0.84) for the best models. Additionally, leave-one-out cross-validation of the models achieved a Q(2) of 0.72 for internal validation. In conclusion, a unified general QSAR equation was able to predict rejections of emerging contaminants during nanofiltration; moreover the present approach is a basis to continue investigation using multivariate analysis techniques for understanding membrane rejection of organic compounds.

  9. 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...

  10. Sensitivity Analysis of QSAR Models for Assessing Novel Military Compounds

    DTIC Science & Technology

    2009-01-01

    erties, such as log P, would aid in estimating a chemical’s environmental fate and toxicology when applied to QSAR modeling. Granted, QSAR mod- els, such...ER D C TR -0 9 -3 Strategic Environmental Research and Development Program Sensitivity Analysis of QSAR Models for Assessing Novel...Environmental Research and Development Program ERDC TR-09-3 January 2009 Sensitivity Analysis of QSAR Models for Assessing Novel Military Compound

  11. Discovery of potent NEK2 inhibitors as potential anticancer agents using structure-based exploration of NEK2 pharmacophoric space coupled with QSAR analyses.

    PubMed

    Khanfar, Mohammad A; Banat, Fahmy; Alabed, Shada; Alqtaishat, Saja

    2017-02-01

    High expression of Nek2 has been detected in several types of cancer and it represents a novel target for human cancer. In the current study, structure-based pharmacophore modeling combined with multiple linear regression (MLR)-based QSAR analyses was applied to disclose the structural requirements for NEK2 inhibition. Generated pharmacophoric models were initially validated with receiver operating characteristic (ROC) curve, and optimum models were subsequently implemented in QSAR modeling with other physiochemical descriptors. QSAR-selected models were implied as 3D search filters to mine the National Cancer Institute (NCI) database for novel NEK2 inhibitors, whereas the associated QSAR model prioritized the bioactivities of captured hits for in vitro evaluation. Experimental validation identified several potent NEK2 inhibitors of novel structural scaffolds. The most potent captured hit exhibited an [Formula: see text] value of 237 nM.

  12. QSARINS-chem: Insubria datasets and new QSAR/QSPR models for environmental pollutants in QSARINS.

    PubMed

    Gramatica, Paola; Cassani, Stefano; Chirico, Nicola

    2014-05-15

    A database of environmentally hazardous chemicals, collected and modeled by QSAR by the Insubria group, is included in the updated version of QSARINS, software recently proposed for the development and validation of QSAR models by the genetic algorithm-ordinary least squares method. In this version, a module, named QSARINS-Chem, includes several datasets of chemical structures and their corresponding endpoints (physicochemical properties and biological activities). The chemicals are accessible in different ways (CAS, SMILES, names and so forth) and their three-dimensional structure can be visualized. Some of the QSAR models, previously published by our group, have been redeveloped using the free online software for molecular descriptor calculation, PaDEL-Descriptor. The new models can be easily applied for future predictions on chemicals without experimental data, also verifying the applicability domain to new chemicals. The QSAR model reporting format (QMRF) of these models is also here downloadable. Additional chemometric analyses can be done by principal component analysis and multicriteria decision making for screening and ranking chemicals to prioritize the most dangerous.

  13. 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.

  14. Identification of novel HIV-1 integrase inhibitors using shape-based screening, QSAR, and docking approach.

    PubMed

    Gupta, Pawan; Garg, Prabha; Roy, Nilanjan

    2012-05-01

    The objective of this study is to identify novel HIV-1 integrase (IN) inhibitors. Here, shape-based screening and QSAR have been successfully implemented to identify the novel inhibitors for HIV-1 IN, and in silico validation is performed by docking studies. The 2D QSAR model of benzodithiazine derivatives was built using genetic function approximation (GFA) method with good internal (cross-validated r(2)  = 0.852) and external prediction (). Best docking pose of highly active molecule of the benzodithiazine derivatives was used as a template for shape-based screening of ZINC database. Toxicity prediction was also performed using Deductive Estimation of Risk from Existing Knowledge (DEREK) program to filter non-toxic molecules. Inhibitory activities of screened non-toxic molecules were predicted using derived QSAR models. Active, non-toxic screened molecules were also docked into the active site of HIV-1 IN using AutoDock and dock program. Some molecules docked similarly as highly active molecule of the benzodithiazine derivatives. These molecules also followed the same docking interactions in both the programs. Finally, four benzodithiazine derivatives were identified as novel HIV-1 integrase inhibitors based on QSAR predictions and docking interactions. ADME properties of these molecules were also computed using Discovery Studio.

  15. Improving confidence in (Q)SAR predictions under Canada's Chemicals Management Plan - a chemical space approach.

    PubMed

    Kulkarni, S A; Benfenati, E; Barton-Maclaren, T S

    2016-10-20

    One of the key challenges of Canada's Chemicals Management Plan (CMP) is assessing chemicals with limited/no empirical hazard data for their risk to human health. In some instances, these chemicals have not been tested broadly for their toxicological potency; as such, limited information exists on their potential to induce human health effects following exposure. Although (quantitative) structure activity relationship ((Q)SAR) models are able to generate predictions to address data gaps for certain toxicological endpoints, the confidence in predictions also needs to be addressed. One way to address this issue is to apply a chemical space approach. This approach uses international toxicological databases, for example, those available in the Organisation for Economic Co-operation and Development (OECD) QSAR Toolbox. The approach,assesses a model's ability to predict the potential hazards of chemicals that have limited hazard data that require assessment under the CMP when compared to a larger, data-rich chemical space that is structurally similar to chemicals of interest. This evaluation of a model's predictive ability makes (Q)SAR analysis more transparent and increases confidence in the application of these predictions in a risk-assessment context. Using this approach, predictions for such chemicals obtained from four (Q)SAR models were successfully classified into high, medium and low confidence levels to better inform their use in decision-making.

  16. Application of topological descriptors in QSAR and drug design: history and new trends.

    PubMed

    Gozalbes, R; Doucet, J P; Derouin, F

    2002-03-01

    Powerful methodologies for drug design and drug database screening and selection are presently available. Studies relating the structure of molecules to a property or a biological activity by means of statistical tools (QSPR and QSAR studies, respectively) are particularly relevant. An important point for this methodology is the use of good structural descriptors that are representative of the molecular features responsible for the relevant activity. Topological indices (TIs) are two-dimensional descriptors which take into account the internal atomic arrangement of compounds, and which encode in numerical form information about molecular size, shape, branching, presence of heteroatoms and multiple bonds. The usefulness of TIs in QSPR and QSAR studies has been extensively demonstrated, and they have also been used as a measure of structural similarity or diversity by their application to databases virtually generated by computer. In this article we will briefly review the history of TIs, their advantages and limitations with respect to other descriptors, and their possibilities in drug design and database selection. These applications rely on new computational techniques such as virtual combinatorial synthesis, virtual computational screening or inverse QSAR.

  17. QNA-based 'Star Track' QSAR approach.

    PubMed

    Filimonov, D A; Zakharov, A V; Lagunin, A A; Poroikov, V V

    2009-10-01

    In the existing quantitative structure-activity relationship (QSAR) methods any molecule is represented as a single point in a many-dimensional space of molecular descriptors. We propose a new QSAR approach based on Quantitative Neighbourhoods of Atoms (QNA) descriptors, which characterize each atom of a molecule and depend on the whole molecule structure. In the 'Star Track' methodology any molecule is represented as a set of points in a two-dimensional space of QNA descriptors. With our new method the estimate of the target property of a chemical compound is calculated as the average value of the function of QNA descriptors in the points of the atoms of a molecule in QNA descriptor space. Substantially, we propose the use of only two descriptors rather than more than 3000 molecular descriptors that apply in the QSAR method. On the basis of this approach we have developed the computer program GUSAR and compared it with several widely used QSAR methods including CoMFA, CoMSIA, Golpe/GRID, HQSAR and others, using ten data sets representing various chemical series and diverse types of biological activity. We show that in the majority of cases the accuracy and predictivity of GUSAR models appears to be better than those for the reference QSAR methods. High predictive ability and robustness of GUSAR are also shown in the leave-20%-out cross-validation procedure.

  18. Metabolic biotransformation half-lives in fish: QSAR modeling and consensus analysis.

    PubMed

    Papa, Ester; van der Wal, Leon; Arnot, Jon A; Gramatica, Paola

    2014-02-01

    Bioaccumulation in fish is a function of competing rates of chemical uptake and elimination. For hydrophobic organic chemicals bioconcentration, bioaccumulation and biomagnification potential are high and the biotransformation rate constant is a key parameter. Few measured biotransformation rate constant data are available compared to the number of chemicals that are being evaluated for bioaccumulation hazard and for exposure and risk assessment. Three new Quantitative Structure-Activity Relationships (QSARs) for predicting whole body biotransformation half-lives (HLN) in fish were developed and validated using theoretical molecular descriptors that seek to capture structural characteristics of the whole molecule and three data set splitting schemes. The new QSARs were developed using a minimal number of theoretical descriptors (n=9) and compared to existing QSARs developed using fragment contribution methods that include up to 59 descriptors. The predictive statistics of the models are similar thus further corroborating the predictive performance of the different QSARs; Q(2)ext ranges from 0.75 to 0.77, CCCext ranges from 0.86 to 0.87, RMSE in prediction ranges from 0.56 to 0.58. The new QSARs provide additional mechanistic insights into the biotransformation capacity of organic chemicals in fish by including whole molecule descriptors and they also include information on the domain of applicability for the chemical of interest. Advantages of consensus modeling for improving overall prediction and minimizing false negative errors in chemical screening assessments, for identifying potential sources of residual error in the empirical HLN database, and for identifying structural features that are not well represented in the HLN dataset to prioritize future testing needs are illustrated.

  19. QSAR modeling of in vitro inhibition of cytochrome P450 3A4.

    PubMed

    Mao, Boryeu; Gozalbes, Rafael; Barbosa, Frédérique; Migeon, Jacques; Merrick, Sandra; Kamm, Kelly; Wong, Eric; Costales, Chester; Shi, Wei; Wu, Cheryl; Froloff, Nicolas

    2006-01-01

    We report the QSAR modeling of cytochrome P450 3A4 (CYP3A4) enzyme inhibition using four large data sets of in vitro data. These data sets consist of marketed drugs and drug-like compounds all tested in four assays measuring the inhibition of the metabolism of four different substrates by the CYP3A4 enzyme. The four probe substrates are benzyloxycoumarin, testosterone, benzyloxyresorufin, and midazolam. We first show that using state-of-the-art QSAR modeling approaches applied to only one of these four data sets does not lead to predictive models that would be useful for in silico filtering of chemical libraries. We then present the development and the testing of a multiple pharmacophore hypothesis (MPH) that is formulated as a conceptual extension of the traditional QSAR approach to modeling the promiscuous binding of a large variety of drugs to CYP3A4. In the simplest form, the MPH approach takes advantage of the multiple substrate data sets and identifies the binding of test compounds as either proximal or distal relative to that of a given substrate. Application of the approach to the in silico filtering of test compounds for potential inhibitors of CYP3A4 is also presented. In addition to an improvement in the QSAR modeling for the inhibition of CYP3A4, the results from this modeling approach provide structural insights into the drug-enzyme interactions. The existence of multiple inhibition data sets in the BioPrint database motivates the original development of the concept of a multiple pharmacophore hypothesis and provides a unique opportunity for formulating alternative strategies of QSAR modeling of the inhibition of the in vitro metabolism of CYP3A4.

  20. Multi-Layer Identification of Highly-Potent ABCA1 Up-Regulators Targeting LXRβ Using Multiple QSAR Modeling, Structural Similarity Analysis, and Molecular Docking.

    PubMed

    Chen, Meimei; Yang, Fafu; Kang, Jie; Yang, Xuemei; Lai, Xinmei; Gao, Yuxing

    2016-11-29

    In this study, in silico approaches, including multiple QSAR modeling, structural similarity analysis, and molecular docking, were applied to develop QSAR classification models as a fast screening tool for identifying highly-potent ABCA1 up-regulators targeting LXRβ based on a series of new flavonoids. Initially, four modeling approaches, including linear discriminant analysis, support vector machine, radial basis function neural network, and classification and regression trees, were applied to construct different QSAR classification models. The statistics results indicated that these four kinds of QSAR models were powerful tools for screening highly potent ABCA1 up-regulators. Then, a consensus QSAR model was developed by combining the predictions from these four models. To discover new ABCA1 up-regulators at maximum accuracy, the compounds in the ZINC database that fulfilled the requirement of structural similarity of 0.7 compared to known potent ABCA1 up-regulator were subjected to the consensus QSAR model, which led to the discovery of 50 compounds. Finally, they were docked into the LXRβ binding site to understand their role in up-regulating ABCA1 expression. The excellent binding modes and docking scores of 10 hit compounds suggested they were highly-potent ABCA1 up-regulators targeting LXRβ. Overall, this study provided an effective strategy to discover highly potent ABCA1 up-regulators.

  1. Quantitative Structure‐activity Relationship (QSAR) Models for Docking Score Correction

    PubMed Central

    Yamasaki, Satoshi; Yasumatsu, Isao; Takeuchi, Koh; Kurosawa, Takashi; Nakamura, Haruki

    2016-01-01

    Abstract In order to improve docking score correction, we developed several structure‐based quantitative structure activity relationship (QSAR) models by protein‐drug docking simulations and applied these models to public affinity data. The prediction models used descriptor‐based regression, and the compound descriptor was a set of docking scores against multiple (∼600) proteins including nontargets. The binding free energy that corresponded to the docking score was approximated by a weighted average of docking scores for multiple proteins, and we tried linear, weighted linear and polynomial regression models considering the compound similarities. In addition, we tried a combination of these regression models for individual data sets such as IC50, Ki, and %inhibition values. The cross‐validation results showed that the weighted linear model was more accurate than the simple linear regression model. Thus, the QSAR approaches based on the affinity data of public databases should improve docking scores. PMID:28001004

  2. 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...

  3. 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.

  4. 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

  5. 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

  6. QSAR trout toxicity models on aromatic pesticides.

    PubMed

    Slavov, Svetoslav; Gini, Giuseppina; Benfenati, Emilio

    2008-11-01

    The pesticides originally designed to kill target organisms are dangerous for many other wild species. Since they are applied directly to the environment, they can easily reach the water basins and the topsoil. A dataset of 125 aromatic pesticides with well-expressed aquatic toxicity towards trout was subjected to quantitative structure activity relationships (QSAR) analysis aimed to establish the relationship between their molecular structure and biological activity. A literature data for LC50 concentration killing 50% of fish was used. In addition to the standard 2D-QSAR analysis, a comparative molecular field analysis (CoMFA) analysis considering the electrostatic and steric properties of the molecules was also performed. The CoMFA analysis helped the recognition of the steric interactions as playing an important role for aquatic toxicity. In addition, the transport properties and the stability of the compounds studied were also identified as important for their biological activity.

  7. 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

  8. Prediction oriented QSAR modelling of EGFR inhibition.

    PubMed

    Szántai-Kis, C; Kövesdi, I; Eros, D; Bánhegyi, P; Ullrich, A; Kéri, G; Orfi, L

    2006-01-01

    Epidermal Growth Factor Receptor (EGFR) is a high priority target in anticancer drug research. Thousands of very effective EGFR inhibitors have been developed in the last decade. The known inhibitors are originated from a very diverse chemical space but--without exception--all of them act at the Adenosine TriPhosphate (ATP) binding site of the enzyme. We have collected all of the diverse inhibitor structures and the relevant biological data obtained from comparable assays and built prediction oriented Quantitative Structure-Activity Relationship (QSAR) which models the ATP binding pocket's interactive surface from the ligand side. We describe a QSAR method with automatic Variable Subset Selection (VSS) by Genetic Algorithm (GA) and goodness-of-prediction driven QSAR model building, resulting an externally validated EGFR inhibitory model built from pIC50 values of a diverse structural set of 623 EGFR inhibitors. Repeated Trainings/Evaluations (RTE) were used to obtain model fitness values and the effectiveness of VSS is amplified by using predictive ability scores of descriptors. Numerous models were generated by different methods and viable models were collected. Then, intensive RTE were applied to identify ultimate models for external validations. Finally, suitable models were validated by statistical tests. Since we use calculated molecular descriptors in the modeling, these models are suitable for virtual screening for obtaining novel potential EGFR inhibitors.

  9. 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...

  10. Unified QSAR approach to antimicrobials. 4. Multi-target QSAR modeling and comparative multi-distance study of the giant components of antiviral drug-drug complex networks.

    PubMed

    Prado-Prado, Francisco J; Martinez de la Vega, Octavio; Uriarte, Eugenio; Ubeira, Florencio M; Chou, Kuo-Chen; González-Díaz, Humberto

    2009-01-15

    One limitation of almost all antiviral Quantitative Structure-Activity Relationships (QSAR) models is that they predict the biological activity of drugs against only one species of virus. Consequently, the development of multi-tasking QSAR models (mt-QSAR) to predict drugs activity against different species of virus is of the major vitally important. These mt-QSARs offer also a good opportunity to construct drug-drug Complex Networks (CNs) that can be used to explore large and complex drug-viral species databases. It is known that in very large CNs we can use the Giant Component (GC) as a representative sub-set of nodes (drugs) and but the drug-drug similarity function selected may strongly determines the final network obtained. In the three previous works of the present series we reported mt-QSAR models to predict the antimicrobial activity against different fungi [Gonzalez-Diaz, H.; Prado-Prado, F. J.; Santana, L.; Uriarte, E. Bioorg.Med.Chem.2006, 14, 5973], bacteria [Prado-Prado, F. J.; Gonzalez-Diaz, H.; Santana, L.; Uriarte E. Bioorg.Med.Chem.2007, 15, 897] or parasite species [Prado-Prado, F.J.; González-Díaz, H.; Martinez de la Vega, O.; Ubeira, F.M.; Chou K.C. Bioorg.Med.Chem.2008, 16, 5871]. However, including these works, we do not found any report of mt-QSAR models for antivirals drug, or a comparative study of the different GC extracted from drug-drug CNs based on different similarity functions. In this work, we used Linear Discriminant Analysis (LDA) to fit a mt-QSAR model that classify 600 drugs as active or non-active against the 41 different tested species of virus. The model correctly classifies 143 of 169 active compounds (specificity=84.62%) and 119 of 139 non-active compounds (sensitivity=85.61%) and presents overall training accuracy of 85.1% (262 of 308 cases). Validation of the model was carried out by means of external predicting series, classifying the model 466 of 514, 90.7% of compounds. In order to illustrate the performance of the

  11. QSAR Modeling is not "Push a Button and Find a Correlation": A Case Study of Toxicity of (Benzo-)triazoles on Algae.

    PubMed

    Gramatica, Paola; Cassani, Stefano; Roy, Partha Pratim; Kovarich, Simona; Yap, Chun Wei; Papa, Ester

    2012-12-01

    A case study of toxicity of (benzo)triazoles ((B)TAZs) to the algae Pseudokirchneriella subcapitata is used to discuss some problems and solutions in QSAR modeling, particularly in the environmental context. The relevance of data curation (not only of experimental data, but also of chemical structures and input formats for the calculation of molecular descriptors), the crucial points of QSAR model validation and the potential application for new chemicals (internal robustness, exclusion of chance correlation, external predictivity, applicability domain) are described, while developing MLR-OLS models based on molecular descriptors, calculated by various QSAR software tools (commercial DRAGON, free PaDEL-Descriptor and QSPR-THESAURUS). Additionally, the utility of consensus models is highlighted. This work summarizes a methodology for a rigorous statistical approach to obtain reliable QSAR predictions, also for a large number of (B)TAZs in the ECHA preregistration list of REACH (even if starting from limited experimental data availability), and has evidenced some ambiguities and discrepancies related to SMILES notations from different databases; furthermore it highlighted some general problems related to QSAR model generation and was useful in the implementation of the PaDEL-Descriptor software.

  12. Danish Breast Cancer Cooperative Group

    PubMed Central

    Christiansen, Peer; Ejlertsen, Bent; Jensen, Maj-Britt; Mouridsen, Henning

    2016-01-01

    Aim of database Danish Breast Cancer Cooperative Group (DBCG), with an associated database, was introduced as a nationwide multidisciplinary group in 1977 with the ultimate aim to improve the prognosis in breast cancer. Since then, the database has registered women diagnosed with primary invasive nonmetastatic breast cancer. The data reported from the departments to the database included details of the characteristics of the primary tumor, of surgery, radiotherapy, and systemic therapies, and of follow-up reported on specific forms from the departments in question. Descriptive data From 1977 through 2014, ~110,000 patients are registered in the nationwide, clinical database. The completeness has gradually improved to more than 95%. DBCG has continuously prepared evidence-based guidelines on diagnosis and treatment of breast cancer and conducted quality control studies to ascertain the degree of adherence to the guidelines in the different departments. Conclusion Utilizing data from the DBCG database, a long array of high-quality DBCG studies of various designs and scope, nationwide or in international collaboration, have contributed to the current updating of the guidelines, and have been an instrumental resource in the improvement of management and prognosis of breast cancer in Denmark. Thus, since the establishment of DBCG, the prognosis in breast cancer has continuously improved with a decrease in 5-year mortality from ~37% to 15%. PMID:27822082

  13. 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.

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

    PubMed Central

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

    1987-01-01

    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 aquatic 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. PMID:3297660

  15. Predicting human plasma protein binding of drugs using plasma protein interaction QSAR analysis (PPI-QSAR).

    PubMed

    Li, Haiyan; Chen, Zhuxi; Xu, Xuejun; Sui, Xiaofan; Guo, Tao; Liu, Wei; Zhang, Jiwen

    2011-09-01

    A novel method, named as the plasma protein-interaction QSAR analysis (PPI-QSAR) was used to construct the QSAR models for human plasma protein binding. The intra-molecular descriptors of drugs and inter-molecular interaction descriptors resulted from the docking simulation between drug molecules and human serum albumin were included as independent variables in this method. A structure-based in silico model for a data set of 65 antibiotic drugs was constructed by the multiple linear regression method and validated by the residual analysis, the normal Probability-Probability plot and Williams plot. The R(2) and Q(2) values of the entire data set were 0.87 and 0.77, respectively, for the training set were 0.86 and 0.72, respectively. The results indicated that the fitted model is robust, stable and satisfies all the prerequisites of the regression models. Combining intra-molecular descriptors with inter-molecular interaction descriptors between drug molecules and human serum albumin, the drug plasma protein binding could be modeled and predicted by the PPI-QSAR method successfully.

  16. The utility of QSARs in predicting acute fish toxicity of pesticide metabolites: A retrospective validation approach.

    PubMed

    Burden, Natalie; Maynard, Samuel K; Weltje, Lennart; Wheeler, James R

    2016-10-01

    The European Plant Protection Products Regulation 1107/2009 requires that registrants establish whether pesticide metabolites pose a risk to the environment. Fish acute toxicity assessments may be carried out to this end. Considering the total number of pesticide (re-) registrations, the number of metabolites can be considerable, and therefore this testing could use many vertebrates. EFSA's recent "Guidance on tiered risk assessment for plant protection products for aquatic organisms in edge-of-field surface waters" outlines opportunities to apply non-testing methods, such as Quantitative Structure Activity Relationship (QSAR) models. However, a scientific evidence base is necessary to support the use of QSARs in predicting acute fish toxicity of pesticide metabolites. Widespread application and subsequent regulatory acceptance of such an approach would reduce the numbers of animals used. The work presented here intends to provide this evidence base, by means of retrospective data analysis. Experimental fish LC50 values for 150 metabolites were extracted from the Pesticide Properties Database (http://sitem.herts.ac.uk/aeru/ppdb/en/atoz.htm). QSAR calculations were performed to predict fish acute toxicity values for these metabolites using the US EPA's ECOSAR software. The most conservative predicted LC50 values generated by ECOSAR were compared with experimental LC50 values. There was a significant correlation between predicted and experimental fish LC50 values (Spearman rs = 0.6304, p < 0.0001). For 62% of metabolites assessed, the QSAR predicted values are equal to or lower than their respective experimental values. Refined analysis, taking into account data quality and experimental variation considerations increases the proportion of sufficiently predictive estimates to 91%. For eight of the nine outliers, there are plausible explanation(s) for the disparity between measured and predicted LC50 values. Following detailed consideration of the robustness of

  17. The importance of molecular structures, endpoints' values, and predictivity parameters in QSAR research: QSAR analysis of a series of estrogen receptor binders.

    PubMed

    Li, Jiazhong; Gramatica, Paola

    2010-11-01

    Quantitative structure-activity relationship (QSAR) methodology aims to explore the relationship between molecular structures and experimental endpoints, producing a model for the prediction of new data; the predictive performance of the model must be checked by external validation. Clearly, the qualities of chemical structure information and experimental endpoints, as well as the statistical parameters used to verify the external predictivity have a strong influence on QSAR model reliability. Here, we emphasize the importance of these three aspects by analyzing our models on estrogen receptor binders (Endocrine disruptor knowledge base (EDKB) database). Endocrine disrupting chemicals, which mimic or antagonize the endogenous hormones such as estrogens, are a hot topic in environmental and toxicological sciences. QSAR shows great values in predicting the estrogenic activity and exploring the interactions between the estrogen receptor and ligands. We have verified our previously published model for additional external validation on new EDKB chemicals. Having found some errors in the used 3D molecular conformations, we redevelop a new model using the same data set with corrected structures, the same method (ordinary least-square regression, OLS) and DRAGON descriptors. The new model, based on some different descriptors, is more predictive on external prediction sets. Three different formulas to calculate correlation coefficient for the external prediction set (Q2 EXT) were compared, and the results indicated that the new proposal of Consonni et al. had more reasonable results, consistent with the conclusions from regression line, Williams plot and root mean square error (RMSE) values. Finally, the importance of reliable endpoints values has been highlighted by comparing the classification assignments of EDKB with those of another estrogen receptor binders database (METI): we found that 16.1% assignments of the common compounds were opposite (20 among 124 common

  18. The Danish Hip Arthroplasty Register

    PubMed Central

    Gundtoft, Per Hviid; Varnum, Claus; Pedersen, Alma Becic; Overgaard, Søren

    2016-01-01

    Aim of database The aim of the Danish Hip Arthroplasty Register (DHR) is to continuously monitor and improve the quality of treatment of primary and revision total hip arthroplasty (THA) in Denmark. Study population The DHR is a Danish nationwide arthroplasty register established in January 1995. All Danish orthopedic departments – both public and private – report to the register, and registration is compulsory. Main variables The main variables in the register include civil registration number, indication for primary and revision surgery, operation date and side, and postoperative complications. Completeness of primary and revision surgery is evaluated annually and validation of a number of variables has been carried out. Descriptive data A total of 139,525 primary THAs and 22,118 revisions have been registered in the DHR between January 1, 1995 and December 31, 2014. Since 1995, completeness of procedure registration has been high, being 97.8% and 92.0% in 2014 for primary THAs and revisions, respectively. Several risk factors, such as comorbidity, age, specific primary diagnosis and fixation types for failure of primary THAs, and postoperative complications, have been identified through the DHR. Approximately 9,000 primary THAs and 1,500 revisions are reported to the register annually. Conclusion The DHR is important for monitoring and improvement of treatment with THA and is a valuable tool for research in THA surgery due to the high quality of prospective collected data with long-term follow-up and high completeness. The register can be used for population-based epidemiology studies of THA surgery and can be linked to a range of other national databases. PMID:27822092

  19. Nanomaterials - the Next Great Challenge for Qsar Modelers

    NASA Astrophysics Data System (ADS)

    Puzyn, Tomasz; Gajewicz, Agnieszka; Leszczynska, Danuta; Leszczynski, Jerzy

    In this final chapter a new perspective for the application of QSAR in the nanosciences is discussed. The role of nanomaterials is rapidly increasing in many aspects of everyday life. This is promoting a wide range of research needs related to both the design of new materials with required properties and performing a comprehensive risk assessment of the manufactured nanoparticles. The development of nanoscience also opens new areas for QSAR modelers. We have begun this contribution with a detailed discussion on the remarkable physical-chemical properties of nanomaterials and their specific toxicities. Both these factors should be considered as potential endpoints for further nano-QSAR studies. Then, we have highlighted the status and research needs in the area of molecular descriptors applicable to nanomaterials. Finally, we have put together currently available nano-QSAR models related to the physico-chemical endpoints of nanoparticles and their activity. Although we have observed many problems (i.e., a lack of experimental data, insufficient and inadequate descriptors), we do believe that application of QSAR methodology will significantly support nanoscience in the near future. Development of reliable nano-QSARs can be considered as the next challenging task for the QSAR community.

  20. 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.

  1. 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.

  2. The Danish National Multiple Myeloma Registry

    PubMed Central

    Gimsing, Peter; Holmström, Morten O; Klausen, Tobias Wirenfelt; Andersen, Niels Frost; Gregersen, Henrik; Pedersen, Robert Schou; Plesner, Torben; Pedersen, Per Trøllund; Frederiksen, Mikael; Frølund, Ulf; Helleberg, Carsten; Vangsted, Annette; de Nully Brown, Peter; Abildgaard, Niels

    2016-01-01

    Aim The Danish National Multiple Myeloma Registry (DMMR) is a population-based clinical quality database established in January 2005. The primary aim of the database is to ensure that diagnosis and treatment of plasma cell dyscrasia are of uniform quality throughout the country. Another aim is to support research. Patients are registered with their unique Danish personal identification number, and the combined use of DMMR, other Danish National registries, and the Danish National Cancer Biobank offers a unique platform for population-based translational research. Study population All newly diagnosed patients with multiple myeloma (MM), smoldering MM, solitary plasmacytomas, and plasma cell leukemia in Denmark are registered annually; ~350 patients. Amyloid light-chain amyloidosis, POEMS syndrome (polyneuropathy, organomegaly, endocrinopathy, monoclonal gammopathy, and skin changes syndrome), monoclonal gammopathy of undetermined significance and monoclonal gammopathy of undetermined significance with polyneuropathy have been registered since 2014. Main variables The main registered variables at diagnosis are patient demographics, baseline disease characteristics, myeloma-defining events, clinical complications, prognostics, first- and second-line treatments, treatment responses, progression free, and overall survival. Descriptive data Up to June 2015, 2,907 newly diagnosed patients with MM, 485 patients with smoldering MM, 64 patients with plasma cell leukemia, and 191 patients with solitary plasmacytomas were registered. Registration completeness of new patients is ~100%. A data validation study performed in 2013–2014 by the Danish Myeloma Study Group showed >95% data correctness. Conclusion The DMMR is a population-based data validated database eligible for clinical, epidemiological, and translational research. PMID:27822103

  3. 3D QSAR studies, pharmacophore modeling and virtual screening on a series of steroidal aromatase inhibitors.

    PubMed

    Xie, Huiding; Qiu, Kaixiong; Xie, Xiaoguang

    2014-11-14

    Aromatase inhibitors are the most important targets in treatment of estrogen-dependent cancers. In order to search for potent steroidal aromatase inhibitors (SAIs) with lower side effects and overcome cellular resistance, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on a series of SAIs to build 3D QSAR models. The reliable and predictive CoMFA and CoMSIA models were obtained with statistical results (CoMFA: q² = 0.636, r²(ncv) = 0.988, r²(pred) = 0.658; CoMSIA: q² = 0.843, r²(ncv) = 0.989, r²(pred) = 0.601). This 3D QSAR approach provides significant insights that can be used to develop novel and potent SAIs. In addition, Genetic algorithm with linear assignment of hypermolecular alignment of database (GALAHAD) was used to derive 3D pharmacophore models. The selected pharmacophore model contains two acceptor atoms and four hydrophobic centers, which was used as a 3D query for virtual screening against NCI2000 database. Six hit compounds were obtained and their biological activities were further predicted by the CoMFA and CoMSIA models, which are expected to design potent and novel SAIs.

  4. National Database of Geriatrics

    PubMed Central

    Kannegaard, Pia Nimann; Vinding, Kirsten L; Hare-Bruun, Helle

    2016-01-01

    Aim of database The aim of the National Database of Geriatrics is to monitor the quality of interdisciplinary diagnostics and treatment of patients admitted to a geriatric hospital unit. Study population The database population consists of patients who were admitted to a geriatric hospital unit. Geriatric patients cannot be defined by specific diagnoses. A geriatric patient is typically a frail multimorbid elderly patient with decreasing functional ability and social challenges. The database includes 14–15,000 admissions per year, and the database completeness has been stable at 90% during the past 5 years. Main variables An important part of the geriatric approach is the interdisciplinary collaboration. Indicators, therefore, reflect the combined efforts directed toward the geriatric patient. The indicators include Barthel index, body mass index, de Morton Mobility Index, Chair Stand, percentage of discharges with a rehabilitation plan, and the part of cases where an interdisciplinary conference has taken place. Data are recorded by doctors, nurses, and therapists in a database and linked to the Danish National Patient Register. Descriptive data Descriptive patient-related data include information about home, mobility aid, need of fall and/or cognitive diagnosing, and categorization of cause (general geriatric, orthogeriatric, or neurogeriatric). Conclusion The National Database of Geriatrics covers ∼90% of geriatric admissions in Danish hospitals and provides valuable information about a large and increasing patient population in the health care system. PMID:27822120

  5. 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...

  6. 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...

  7. The Danish Neuro-Oncology Registry

    PubMed Central

    Hansen, Steinbjørn

    2016-01-01

    Aim of database The Danish Neuro-Oncology Registry (DNOR) was established by the Danish Neuro-Oncology Group as a national clinical database. It was established for the purpose of supporting research and development in adult patients with primary brain tumors in Denmark. Study population DNOR has registered clinical data on diagnostics and treatment of all adult patients diagnosed with glioma since January 1, 2009, which numbers approximately 400 patients each year. Main variables The database contains information about symptoms, presurgical magnetic resonance imaging (MRI) characteristics, performance status, surgical procedures, residual tumor on postsurgical MRI, postsurgical complications, diagnostic and histology codes, radiotherapy, and chemotherapy. Descriptive data DNOR publishes annual reports on descriptive data. During the period of registration, postoperative MRI is performed in a higher proportion of the patients (Indicator II), and a higher proportion of patients have no residual tumor after surgical resection of the primary tumor (Indicator IV). Further data are available in the annual reports. The indicators reflect only minor elements of handling brain tumor patients. Another advantage of reporting indicators is the related multidisciplinary discussions giving a better understanding of what actually is going on, thereby facilitating the work on adjusting the national guidelines in the Danish Neuro-Oncology Group. Conclusion The establishment of DNOR has optimized the quality in handling primary brain tumor patients in Denmark by reporting indicators and facilitating a better multidisciplinary collaboration at a national level. DNOR provides a valuable resource for research. PMID:27822109

  8. 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

  9. Megavariate analysis of hierarchical QSAR data

    NASA Astrophysics Data System (ADS)

    Eriksson, Lennart; Johansson, Erik; Lindgren, Fredrik; Sjöström, Michael; Wold, Svante

    2002-10-01

    Multivariate PCA- and PLS-models involving many variables are often difficult to interpret, because plots and lists of loadings, coefficients, VIPs, etc, rapidly become messy and hard to overview. There may then be a strong temptation to eliminate variables to obtain a smaller data set. Such a reduction of variables, however, often removes information and makes the modelling efforts less reliable. Model interpretation may be misleading and predictive power may deteriorate. A better alternative is usually to partition the variables into blocks of logically related variables and apply hierarchical data analysis. Such blocked data may be analyzed by PCA and PLS. This modelling forms the base-level of the hierarchical modelling set-up. On the base-level in-depth information is extracted for the different blocks. The score vectors formed on the base-level, here called `super variables', may be linked together in new matrices on the top-level. On the top-level superficial relationships between the X- and the Y-data are investigated. In this paper the basic principles of hierarchical modelling by means of PCA and PLS are reviewed. One objective of the paper is to disseminate this concept to a broader QSAR audience. The hierarchical methods are used to analyze a set of 10 haloalkanes for which K = 30 chemical descriptors and M = 255 biological responses have been gathered. Due to the complexity of the biological data, they are sub-divided in four blocks. All the modelling steps on the base-level and the top-level are reported and the final QSAR model is interpreted thoroughly.

  10. 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.

  11. Structure–activity relationships study of mTOR kinase inhibition using QSAR and structure-based drug design approaches

    PubMed Central

    Lakhlili, Wiame; Yasri, Abdelaziz; Ibrahimi, Azeddine

    2016-01-01

    The discovery of clinically relevant inhibitors of mammalian target of rapamycin (mTOR) for anticancer therapy has proved to be a challenging task. The quantitative structure–activity relationship (QSAR) approach is a very useful and widespread technique for ligand-based drug design, which can be used to identify novel and potent mTOR inhibitors. In this study, we performed two-dimensional QSAR tests, and molecular docking validation tests of a series of mTOR ATP-competitive inhibitors to elucidate their structural properties associated with their activity. The QSAR tests were performed using partial least square method with a correlation coefficient of r2=0.799 and a cross-validation of q2=0.714. The chemical library screening was done by associating ligand-based to structure-based approach using the three-dimensional structure of mTOR developed by homology modeling. We were able to select 22 compounds from two databases as inhibitors of the mTOR kinase active site. We believe that the method and applications highlighted in this study will help future efforts toward the design of selective ATP-competitive inhibitors. PMID:27980424

  12. 3D-QSAR and virtual screening studies of thiazolidine-2,4-dione analogs: Validation of experimental inhibitory potencies towards PIM-1 kinase

    NASA Astrophysics Data System (ADS)

    Asati, Vivek; Bharti, Sanjay Kumar; Budhwani, Ashok Kumar

    2017-04-01

    The proviral insertion site in moloney murine leukemia virus (PIM) is a family of serine/threonine kinase of Ca2+-calmodulin-dependent protein kinase (CAMK) group which is responsible for the activation and regulation of cellular transcription and translation. The three isoforms of PIM kinase (PIM-1, PIM-2 and PIM-3) share high homology and functional idleness are widely expressed and involved in a variety of biological processes including cell survival, proliferation, differentiation and apoptosis. Altered expression of PIM-1 kinase correlated with hematologic malignancies and solid tumors. In the present study, atom-based 3D-QSAR, docking and virtual screening studies have been performed on a series of thiazolidine-2,4-dione derivatives as PIM-1 kinase inhibitors. 3D-QSAR and docking approach has shortlisted the most active thiazolidine-2,4-dione derivatives such as 28, 31, 33 and 35 with the incorporation of more than one structural feature in a single molecule. External validations by various parameters and molecular docking studies at the active site of PIM-1 kinase have proved the reliability of the developed 3D-QSAR model. The generated pharmacophore (AADHR.33) from 3D-QSAR study was used for screening of drug like compounds from ZINC database, where ZINC15056464 and ZINC83292944 showed potential binding affinities at the active site amino acid residues (LYS67, GLU171, ASP128 and ASP186) of PIM-1 kinase (PDB ID: "pdb:4DTK").

  13. 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

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

    NASA Astrophysics Data System (ADS)

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

    2017-04-01

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

  15. 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

  16. A QSAR for the hydroxyl radical reaction rate constant: validation, domain of application, and prediction

    NASA Astrophysics Data System (ADS)

    Öberg, Tomas

    A large number of anthropogenic organic chemicals are emitted into the troposphere. Reactions with the hydroxyl radical are a dominant removal pathway for most organic compounds, but experimentally determined gas-phase reaction rate constants are only available for about 750 compounds. The lack of experimental data increases the importance of applying quantitative structure-activity relationships (QSAR) to evaluate and predict reactivities. It is generally acknowledged that these empirical relationships are valid only within the same domain for which they were developed. However, model validation is sometimes neglected and the application domain is not always well defined. The purpose of this paper is to outline how validation and domain definition can facilitate the modeling and prediction of the hydroxyl radical reaction rates for a large database. A substantial number of theoretical descriptors (867) were generated from 2D molecular structures for compounds present in the Syracuse Research Corporation's PhysProp Database. A QSAR model was developed for the hydroxyl radical reaction rate constant using a projection-based regression technique, partial least squares regression (PLSR). The PLSR model was subsequently validated with an external test set. The main factors of variation could be attributed to two reaction pathways, hydrogen atom abstraction and addition to double bonds or aromatic systems. A set of 17 293 compounds, drawn from the PhysProp Database, was projected onto the PLSR model and 74% were inside the applicability domain. The predicted hydroxyl reaction rates for 25% of these compounds were slow or negligible, with atmospheric half-lives in the range from days to years. Finally, the list of persistent organic compounds was matched against the OECD list of high production volume chemicals (HPVC). Together with the experimental data, nearly three hundred compounds were identified as both persistent and in high volume production.

  17. On the development and validation of QSAR models.

    PubMed

    Gramatica, Paola

    2013-01-01

    The fundamental and more critical steps that are necessary for the development and validation of QSAR models are presented in this chapter as best practices in the field. These procedures are discussed in the context of predictive QSAR modelling that is focused on achieving models of the highest statistical quality and with external predictive power. The most important and most used statistical parameters needed to verify the real performances of QSAR models (of both linear regression and classification) are presented. Special emphasis is placed on the validation of models, both internally and externally, as well as on the need to define model applicability domains, which should be done when models are employed for the prediction of new external compounds.

  18. 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

  19. 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.

  20. 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

  1. Robust cross-validation of linear regression QSAR models.

    PubMed

    Konovalov, Dmitry A; Llewellyn, Lyndon E; Vander Heyden, Yvan; Coomans, Danny

    2008-10-01

    A quantitative structure-activity relationship (QSAR) model is typically developed to predict the biochemical activity of untested compounds from the compounds' molecular structures. "The gold standard" of model validation is the blindfold prediction when the model's predictive power is assessed from how well the model predicts the activity values of compounds that were not considered in any way during the model development/calibration. However, during the development of a QSAR model, it is necessary to obtain some indication of the model's predictive power. This is often done by some form of cross-validation (CV). In this study, the concepts of the predictive power and fitting ability of a multiple linear regression (MLR) QSAR model were examined in the CV context allowing for the presence of outliers. Commonly used predictive power and fitting ability statistics were assessed via Monte Carlo cross-validation when applied to percent human intestinal absorption, blood-brain partition coefficient, and toxicity values of saxitoxin QSAR data sets, as well as three known benchmark data sets with known outlier contamination. It was found that (1) a robust version of MLR should always be preferred over the ordinary-least-squares MLR, regardless of the degree of outlier contamination and that (2) the model's predictive power should only be assessed via robust statistics. The Matlab and java source code used in this study is freely available from the QSAR-BENCH section of www.dmitrykonovalov.org for academic use. The Web site also contains the java-based QSAR-BENCH program, which could be run online via java's Web Start technology (supporting Windows, Mac OSX, Linux/Unix) to reproduce most of the reported results or apply the reported procedures to other data sets.

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

    PubMed

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

    2016-01-01

    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.

  3. BioPPSy: An Open-Source Platform for QSAR/QSPR Analysis

    PubMed Central

    Walker, Michael L.

    2016-01-01

    The reliability of quantitative structure-property relationship (QSPR) and quantitative structure-activity relationship (QSAR) models is often difficult to assess due to the problems of accessing the tools and data used to build the models. We present here BioPPSy, which aims to fill this gap by providing an easy-to-use open-source software platform. We demonstrate the program capabilities by calculating three key properties used in drug discovery, aqueous solubility, Caco-2 cell permeability and blood-brain barrier permeability. A comparison is made with a number of previously reported methods, taken from the literature, for each property. The software, including source code, current models and databases, is available from https://sourceforge.net/projects/bioppsy/. PMID:27832156

  4. 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

  5. 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.

  6. The Danish System Revisited.

    ERIC Educational Resources Information Center

    Whitehead, John S.

    The paper is a supplement to an earlier paper in the same series which reviews Danish higher education until 1977. Expansion in higher education in the last 20 years, approaching the scale of mass higher education, culminated in a crisis in 1977. At that time, a trend toward self-government and participatory governing boards was seen as the end of…

  7. 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...

  8. 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...

  9. SAR/QSAR methods in public health practice.

    PubMed

    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.

  10. A Combined Pharmacophore Modeling, 3D QSAR and Virtual Screening Studies on Imidazopyridines as B-Raf Inhibitors.

    PubMed

    Xie, Huiding; Chen, Lijun; Zhang, Jianqiang; Xie, Xiaoguang; Qiu, Kaixiong; Fu, Jijun

    2015-05-29

    B-Raf kinase is an important target in treatment of cancers. In order to design and find potent B-Raf inhibitors (BRIs), 3D pharmacophore models were created using the Genetic Algorithm with Linear Assignment of Hypermolecular Alignment of Database (GALAHAD). The best pharmacophore model obtained which was used in effective alignment of the data set contains two acceptor atoms, three donor atoms and three hydrophobes. In succession, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on 39 imidazopyridine BRIs to build three dimensional quantitative structure-activity relationship (3D QSAR) models based on both pharmacophore and docking alignments. The CoMSIA model based on the pharmacophore alignment shows the best result (q(2) = 0.621, r(2)(pred) = 0.885). This 3D QSAR approach provides significant insights that are useful for designing potent BRIs. In addition, the obtained best pharmacophore model was used for virtual screening against the NCI2000 database. The hit compounds were further filtered with molecular docking, and their biological activities were predicted using the CoMSIA model, and three potential BRIs with new skeletons were obtained.

  11. Chemical domain of QSAR models from atom-centered fragments.

    PubMed

    Kühne, Ralph; Ebert, Ralf-Uwe; Schüürmann, Gerrit

    2009-12-01

    A methodology to characterize the chemical domain of qualitative and quantitative structure-activity relationship (QSAR) models based on the atom-centered fragment (ACF) approach is introduced. ACFs decompose the molecule into structural pieces, with each non-hydrogen atom of the molecule acting as an ACF center. ACFs vary with respect to their size in terms of the path length covered in each bonding direction starting from a given central atom and how comprehensively the neighbor atoms (including hydrogen) are described in terms of element type and bonding environment. In addition to these different levels of ACF definitions, the ACF match mode as degree of strictness of the ACF comparison between a test compound and a given ACF pool (such as from a training set) has to be specified. Analyses of the prediction statistics of three QSAR models with their training sets as well as with external test sets and associated subsets demonstrate a clear relationship between the prediction performance and the levels of ACF definition and match mode. The findings suggest that second-order ACFs combined with a borderline match mode may serve as a generic and at the same time a mechanistically sound tool to define and evaluate the chemical domain of QSAR models. Moreover, four standard categories of the ACF-based membership to a given chemical domain (outside, borderline outside, borderline inside, inside) are introduced that provide more specific information about the expected QSAR prediction performance. As such, the ACF-based characterization of the chemical domain appears to be particularly useful for QSAR applications in the context of REACH and other regulatory schemes addressing the safety evaluation of chemical compounds.

  12. Per- and polyfluoro toxicity (LC(50) inhalation) study in rat and mouse using QSAR modeling.

    PubMed

    Bhhatarai, Barun; Gramatica, Paola

    2010-03-15

    Fully or partially fluorinated compounds, known as per- and polyfluorinated chemicals are widely distributed in the environment and released because of their use in different household and industrial products. Few of these long chain per- and polyfluorinated chemicals are classified as emerging pollutants, and their environmental and toxicological effects are unveiled in the literature. This has diverted the production of long chain compounds, considered as more toxic, to short chains, but concerns regarding the toxicity of both types of per- and polyfluorinated chemicals are alarming. There are few experimental data available on the environmental behavior and toxicity of these compounds, and moreover, toxicity profiles are found to be different for the types of animals and species used. Quantitative structure-activity relationship (QSAR) is applied to a combination of short and long chain per- and polyfluorinated chemicals, for the first time, to model and predict the toxicity on two species of rodents, rat (Rattus) and mouse (Mus), by modeling inhalation (LC(50)) data. Multiple linear regression (MLR) models using the ordinary-least-squares (OLS) method, based on theoretical molecular descriptors selected by genetic algorithm (GA), were used for QSAR studies. Training and prediction sets were prepared a priori, and these sets were used to derive statistically robust and predictive (both internally and externally) models. The structural applicability domain (AD) of the model was verified on a larger set of per- and polyfluorinated chemicals retrieved from different databases and journals. The descriptors involved, the similarities, and the differences observed between models pertaining to the toxicity related to the two species are discussed. Chemometric methods such as principal component analysis (PCA) and multidimensional scaling (MDS) were used to select most toxic compounds from those within the AD of both models, which will be subjected to experimental tests

  13. 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

  14. The Role of Qsar Methodology in the Regulatory Assessment of Chemicals

    NASA Astrophysics Data System (ADS)

    Worth, Andrew Paul

    The aim of this chapter is to outline the different ways in which quantitative structure-activity relationship (QSAR) methods can be used in the regulatory assessment of chemicals. The chapter draws on experience gained in the European Union in the assessment of industrial chemicals, as well as recently developed guidance for the use of QSARs within specific legislative frameworks such as REACH and the Water Framework Directive. This chapter reviews the concepts of QSAR validity, applicability, and acceptability and emphasises that the use of individual QSAR estimates is highly context-dependent, which has implications in terms of the confidence needed in the model validity. In addition to the potential use of QSAR models as stand-alone estimation methods, it is expected that QSARs will be used within the context of broader weight-of-evidence approaches, such as chemical categories and integrated testing strategies; therefore, the role of (Q)SARs within these approaches is explained. This chapter also refers to a range of freely available software tools being developed to facilitate the use of QSARs for regulatory purposes. Finally, some conclusions are drawn concerning current needs for the further development and uptake of QSARs

  15. From QSAR models of drugs to complex networks: state-of-art review and introduction of new Markov-spectral moments indices.

    PubMed

    Riera-Fernández, Pablo; Martín-Romalde, Raquel; Prado-Prado, Francisco J; Escobar, Manuel; Munteanu, Cristian R; Concu, Riccardo; Duardo-Sanchez, Aliuska; González-Díaz, Humberto

    2012-01-01

    Quantitative Structure-Activity/Property Relationships (QSAR/QSPR) models have been largely used for different kind of problems in Medicinal Chemistry and other Biosciences as well. Nevertheless, the applications of QSAR models have been restricted to the study of small molecules in the past. In this context, many authors use molecular graphs, atoms (nodes) connected by chemical bonds (links) to represent and numerically characterize the molecular structure. On the other hand, Complex Networks are useful in solving problems in drug research and industry, developing mathematical representations of different systems. These systems move in a wide range from relatively simple graph representations of drug molecular structures (molecular graphs used in classic QSAR) to large systems. We can cite for instance, drug-target interaction networks, protein structure networks, protein interaction networks (PINs), or drug treatment in large geographical disease spreading networks. In any case, all complex networks have essentially the same components: nodes (atoms, drugs, proteins, microorganisms and/or parasites, geographical areas, drug policy legislations, etc.) and links (chemical bonds, drug-target interactions, drug-parasite treatment, drug use, etc.). Consequently, we can use the same type of numeric parameters called Topological Indices (TIs) to describe the connectivity patterns in all these kinds of Complex Networks irrespective the nature of the object they represent and use these TIs to develop QSAR/QSPR models beyond the classic frontiers of drugs small-sized molecules. The goal of this work, in first instance, is to offer a common background to all the manuscripts presented in this special issue. In so doing, we make a review of the most used software and databases, common types of QSAR/QSPR models, and complex networks involving drugs or their targets. In addition, we review both classic TIs that have been used to describe the molecular structure of drugs and

  16. Danish Cultural Identity and the Teaching of Danish to Foreigners

    ERIC Educational Resources Information Center

    Reuter, Hedwig

    2006-01-01

    Danish as a second language textbooks published over the last 15 years have presented the Danish cultural identity as a homogenous and purely national phenomenon. Research into teaching theory, on the other hand, has been more broad-minded, and is based on interactivity. The aim of this paper is to explain this divergence. (Contains 2 notes.)

  17. 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.

  18. 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.

  19. 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.

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

    USGS Publications Warehouse

    Hickey, James P.; Ostrander, Gary K.

    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.

  1. 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.

  2. 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.

  3. 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

  4. Ranking of aquatic toxicity of esters modelled by QSAR.

    PubMed

    Papa, Ester; Battaini, Francesca; Gramatica, Paola

    2005-02-01

    Alternative methods like predictions based on Quantitative Structure-Activity Relationships (QSARs) are now accepted to fill data gaps and define priority lists for more expensive and time consuming assessments. A heterogeneous data set of 74 esters was studied for their aquatic toxicity, and available experimental toxicity data on algae, Daphnia and fish were used to develop statistically validated QSAR models, obtained using multiple linear regression (MLR) by the OLS (Ordinary Least Squares) method and GA-VSS (Variable Subset Selection by Genetic Algorithms) to predict missing values. An ESter Aquatic Toxicity INdex (ESATIN) was then obtained by combining, by PCA, experimental and predicted toxicity data, from which model outliers and esters highly influential due to their structure had been eliminated. Finally this integrated aquatic toxicity index, defined by the PC1 score, was modelled using only a few theoretical molecular descriptors. This last QSAR model, statistically validated for its predictive power, could be proposed as a preliminary evaluative method for screening/prioritising esters according to their integrated aquatic toxicity, just starting from their molecular structure.

  5. Exhaustive Structure Generation for Inverse-QSPR/QSAR.

    PubMed

    Miyao, Tomoyuki; Arakawa, Masamoto; Funatsu, Kimito

    2010-01-12

    Chemical structure generation based on quantitative structure property relationship (QSPR) or quantitative structure activity relationship (QSAR) models is one of the central themes in the field of computer-aided molecular design. The objective of structure generation is to find promising molecules, which according to statistical models, are considered to have desired properties. In this paper, a new method is proposed for the exhaustive generation of chemical structures based on inverse-QSPR/QSAR. In this method, QSPR/QSAR models are constructed by multiple linear regression method, and then the conditional distribution of explanatory variables given the desired properties is estimated by inverse analysis of the models using the framework of a linear Gaussian model. Finally, chemical structures are exhaustively generated by a sophisticated algorithm that is based on a canonical construction path method. The usefulness of the proposed method is demonstrated using a dataset of the boiling points of acyclic hydrocarbons containing up to 12 carbon atoms. The QSPR model was constructed with 600 hydrocarbons and their boiling points. Using the proposed method, chemical structures which had boiling points of 100, 150, or 200 °C were exhaustively generated.

  6. Comprehensive 3D-QSAR and binding mode of BACE-1 inhibitors using R-group search and molecular docking.

    PubMed

    Huang, Dandan; Liu, Yonglan; Shi, Bozhi; Li, Yueting; Wang, Guixue; Liang, Guizhao

    2013-09-01

    The β-enzyme (BACE), which takes an active part in the processing of amyloid precursor protein, thereby leads to the production of amyloid-β (Aβ) in the brain, is a major therapeutic target against Alzheimer's disease. The present study is aimed at studying 3D-QSAR of BACE-1 inhibitors and their binding mode. We build a 3D-QSAR model involving 99 training BACE-1 inhibitors based on Topomer CoMFA, and 26 molecules are employed to validate the external predictive power of the model obtained. The multiple correlation coefficients of fitting modeling, leave one out cross validation, and external validation are 0.966, 0.767 and 0.784, respectively. Topomer search is used as a tool for virtual screening in lead-like compounds of ZINC databases (2012); as a result, we successfully design 30 new molecules with higher activity than that of all training and test inhibitors. Besides, Surflex-dock is employed to explore binding mode of the inhibitors studied when acting with BACE-1 enzyme. The result shows that the inhibitors closely interact with the key sites related to ASP93, THR133, GLN134, ASP289, GLY291, THR292, THR293, ASN294, ARG296 and SER386 of BACE-1.

  7. The Danish Multiple Sclerosis Treatment Register

    PubMed Central

    Magyari, Melinda; Koch-Henriksen, Nils; Sørensen, Per Soelberg

    2016-01-01

    Aim of the database The Danish Multiple Sclerosis Treatment Register (DMSTR) serves as a clinical quality register, enabling the health authorities to monitor the quality of the disease-modifying treatment, and it is an important data source for epidemiological research. Study population The DMSTR includes all patients with multiple sclerosis who had been treated with disease-modifying drugs since 1996. At present, more than 8,400 patients have been registered in this database. Data are continuously entered online into a central database from all sites in Denmark at start and at regular visits. Main variables Include age, sex, onset year and year of the diagnosis, basic clinical information, and information about treatment, side effects, and relapses. Descriptive data Notification is done at treatment start, and thereafter at every scheduled clinical visit 3 months after treatment start, and thereafter every 6 months. The longitudinally collected information about the disease activity and side effects made it possible to investigate the clinical efficacy and adverse events of different disease-modifying therapies. Conclusion The database contributed to a certain harmonization of treatment procedures in Denmark and will continue to be a major factor in terms of quality in clinical praxis, research and monitoring of adverse events, and plays an important role in research. PMID:27822098

  8. 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...

  9. QSAR modeling for anti-human African trypanosomiasis activity of substituted 2-Phenylimidazopyridines

    NASA Astrophysics Data System (ADS)

    Masand, Vijay H.; El-Sayed, Nahed N. E.; Mahajan, Devidas T.; Mercader, Andrew G.; Alafeefy, Ahmed M.; Shibi, I. G.

    2017-02-01

    In the present work, sixty substituted 2-Phenylimidazopyridines previously reported with potent anti-human African trypanosomiasis (HAT) activity were selected to build genetic algorithm (GA) based QSAR models to determine the structural features that have significant correlation with the activity. Multiple QSAR models were built using easily interpretable descriptors that are directly associated with the presence or the absence of a structural scaffold, or a specific atom. All the QSAR models have been thoroughly validated according to the OECD principles. All the QSAR models are statistically very robust (R2 = 0.80-0.87) with high external predictive ability (CCCex = 0.81-0.92). The QSAR analysis reveals that the HAT activity has good correlation with the presence of five membered rings in the molecule.

  10. Advantages and limitations of classic and 3D QSAR approaches in nano-QSAR studies based on biological activity of fullerene derivatives

    NASA Astrophysics Data System (ADS)

    Jagiello, Karolina; Grzonkowska, Monika; Swirog, Marta; Ahmed, Lucky; Rasulev, Bakhtiyor; Avramopoulos, Aggelos; Papadopoulos, Manthos G.; Leszczynski, Jerzy; Puzyn, Tomasz

    2016-09-01

    In this contribution, the advantages and limitations of two computational techniques that can be used for the investigation of nanoparticles activity and toxicity: classic nano-QSAR (Quantitative Structure-Activity Relationships employed for nanomaterials) and 3D nano-QSAR (three-dimensional Quantitative Structure-Activity Relationships, such us Comparative Molecular Field Analysis, CoMFA/Comparative Molecular Similarity Indices Analysis, CoMSIA analysis employed for nanomaterials) have been briefly summarized. Both approaches were compared according to the selected criteria, including: efficiency, type of experimental data, class of nanomaterials, time required for calculations and computational cost, difficulties in the interpretation. Taking into account the advantages and limitations of each method, we provide the recommendations for nano-QSAR modellers and QSAR model users to be able to determine a proper and efficient methodology to investigate biological activity of nanoparticles in order to describe the underlying interactions in the most reliable and useful manner.

  11. Hierarchical QSAR technology based on the Simplex representation of molecular structure

    NASA Astrophysics Data System (ADS)

    Kuz'min, V. E.; Artemenko, A. G.; Muratov, E. N.

    2008-06-01

    This article is about the hierarchical quantitative structure-activity relationship technology (HiT QSAR) based on the Simplex representation of molecular structure (SiRMS) and its application for different QSAR/QSP(property)R tasks. The essence of this technology is a sequential solution (with the use of the information obtained on the previous steps) to the QSAR problem by the series of enhanced models of molecular structure description [from one dimensional (1D) to four dimensional (4D)]. It is a system of permanently improved solutions. 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 detailing increases consecutively from the 1D to 4D representation of the molecular structure. The advantages of the approach reported here are the absence of "molecular alignment" problems, consideration of different physical-chemical properties of atoms (e.g. charge, lipophilicity, etc.), the high adequacy and good interpretability of obtained models and clear ways for molecular design. The efficiency of the HiT QSAR approach is demonstrated by comparing it 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 predictive virtual screening tools and their ability to serve as the base of directed drug design was validated by subsequent synthetic and biological experiments, among others. The HiT QSAR is realized as a complex of computer programs known as HiT QSAR software that also includes a powerful statistical block and a number of useful utilities.

  12. The Danish Heart Registry

    PubMed Central

    Özcan, Cengiz; Juel, Knud; Flensted Lassen, Jens; von Kappelgaard, Lene Mia; Mortensen, Poul Erik; Gislason, Gunnar

    2016-01-01

    Aim The Danish Heart Registry (DHR) seeks to monitor nationwide activity and quality of invasive diagnostic and treatment strategies in patients with ischemic heart disease as well as valvular heart disease and to provide data for research. Study population All adult (≥15 years) patients undergoing coronary angiography (CAG), percutaneous coronary intervention (PCI), coronary artery bypass grafting, and heart valve surgery performed across all Danish hospitals were included. Main variables The DHR contains a subset of the data stored in the Eastern and Western Denmark Heart Registries (EDHR and WDHR). For each type of procedure, up to 70 variables are registered in the DHR. Since 2010, the data quality protocol encompasses fulfillment of web-based validation rules of daily-submitted records and yearly approval of the data by the EDHR and WDHR. Descriptive data The data collection on procedure has been complete for PCI and surgery since 2000, and for CAG as of 2006. From 2000 to 2014, the number of CAG, PCI, and surgical procedures changed by 231%, 193%, and 99%, respectively. Until the end of 2014, a total of 357,476 CAG, 131,309 PCI, and 60,831 surgical procedures had been performed, corresponding to 249,445, 100,609, and 55,539 first-time patients, respectively. The DHR generally has a high level of completeness (1–missing) of each procedure (>90%) when compared to the National Patient Registry. Variables important for assessing the quality of care have a high level of completeness for surgery since 2000, and for CAG and PCI since 2010. Conclusion The DHR contains valuable data on cardiac invasive procedures, which makes it an important national monitoring and quality system and at the same time serves as a platform for research projects in the cardiovascular field. PMID:27822091

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

    PubMed

    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(SM), 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.

  15. Combinatorial QSAR modeling of chemical toxicants tested against Tetrahymena pyriformis.

    PubMed

    Zhu, Hao; Tropsha, Alexander; Fourches, Denis; Varnek, Alexandre; Papa, Ester; Gramatica, Paola; Oberg, Tomas; Dao, Phuong; Cherkasov, Artem; Tetko, Igor V

    2008-04-01

    Selecting most rigorous quantitative structure-activity relationship (QSAR) approaches is of great importance in the development of robust and predictive models of chemical toxicity. To address this issue in a systematic way, we have formed an international virtual collaboratory consisting of six independent groups with shared interests in computational chemical toxicology. We have compiled an aqueous toxicity data set containing 983 unique compounds tested in the same laboratory over a decade against Tetrahymena pyriformis. A modeling set including 644 compounds was selected randomly from the original set and distributed to all groups that used their own QSAR tools for model development. The remaining 339 compounds in the original set (external set I) as well as 110 additional compounds (external set II) published recently by the same laboratory (after this computational study was already in progress) were used as two independent validation sets to assess the external predictive power of individual models. In total, our virtual collaboratory has developed 15 different types of QSAR models of aquatic toxicity for the training set. The internal prediction accuracy for the modeling set ranged from 0.76 to 0.93 as measured by the leave-one-out cross-validation correlation coefficient ( Q abs2). The prediction accuracy for the external validation sets I and II ranged from 0.71 to 0.85 (linear regression coefficient R absI2) and from 0.38 to 0.83 (linear regression coefficient R absII2), respectively. The use of an applicability domain threshold implemented in most models generally improved the external prediction accuracy but at the same time led to a decrease in chemical space coverage. Finally, several consensus models were developed by averaging the predicted aquatic toxicity for every compound using all 15 models, with or without taking into account their respective applicability domains. We find that consensus models afford higher prediction accuracy for the

  16. QSAR of heterocyclic antifungal agents by flip regression

    NASA Astrophysics Data System (ADS)

    Deeb, Omar; Clare, Brian W.

    2008-12-01

    QSAR analysis of a set of 96 heterocyclics with antifungal activity was performed. The results reveals that a pyridine ring is more favorable than benzene as the 6-membered ring, for high activity, but thiazole is unfavorable as the 5-membered ring relative to imidazole or oxazole. Methylene is the spacer leading to the highest activity. The descriptors used are indicator variables, which account for identity of substituent, lipophilicity and volume of substituent, and total polarizability. Unlike previously reported results for this data set, our fits do not exceed the limitations set by the nature of the data itself.

  17. Receptor-based 3D-QSAR in Drug Design: Methods and Applications in Kinase Studies.

    PubMed

    Fang, Cheng; Xiao, Zhiyan

    2016-01-01

    Receptor-based 3D-QSAR strategy represents a superior integration of structure-based drug design (SBDD) and three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis. It combines the accurate prediction of ligand poses by the SBDD approach with the good predictability and interpretability of statistical models derived from the 3D-QSAR approach. Extensive efforts have been devoted to the development of receptor-based 3D-QSAR methods and two alternative approaches have been exploited. One associates with computing the binding interactions between a receptor and a ligand to generate structure-based descriptors for QSAR analyses. The other concerns the application of various docking protocols to generate optimal ligand poses so as to provide reliable molecular alignments for the conventional 3D-QSAR operations. This review highlights new concepts and methodologies recently developed in the field of receptorbased 3D-QSAR, and in particular, covers its application in kinase studies.

  18. QSAR classification of estrogen receptor binders and pre-screening of potential pleiotropic EDCs.

    PubMed

    Li, J; Gramatica, P

    2010-10-01

    Endocrine disrupting chemicals (EDCs) are suspected of posing serious threats to human and wildlife health through a variety of mechanisms, these being mainly receptor-mediated modes of action. It is reported that some EDCs exhibit dual activities as estrogen receptor (ER) and androgen receptor (AR) binders. Indeed, such compounds can affect the normal endocrine system through a dual complex mechanism, so steps should be taken not only to identify them a priori from their chemical structure, but also to prioritize them for experimental tests in order to reduce and even forbid their usage. To date, very few EDCs with dual activities have been identified. The present research uses QSARs, to investigate what, so far, is the largest and most heterogeneous ER binder data set (combined METI and EDKB databases). New predictive classification models were derived using different modelling methods and a consensus approach, and these were used to virtually screen a large AR binder data set after strict validation. As a result, 46 AR antagonists were predicted from their chemical structure to also have potential ER binding activities, i.e. pleiotropic EDCs. In addition, 48 not yet recognized ER binders were in silico identified, which increases the number of potential EDCs that are substances of very high concern (SVHC) in REACH. Thus, the proposed screening models, based only on structure information, have the main aim to prioritize experimental tests for the highlighted compounds with potential estrogenic activities and also to design safer alternatives.

  19. Application of the modelling power approach to variable subset selection for GA-PLS QSAR models.

    PubMed

    Sagrado, Salvador; Cronin, Mark T D

    2008-02-25

    A previously developed function, the Modelling Power Plot, has been applied to QSARs developed using partial least squares (PLS) following variable selection from a genetic algorithm (GA). Modelling power (Mp) integrates the predictive and descriptive capabilities of a QSAR. With regard to QSARs for narcotic toxic potency, Mp was able to guide the optimal selection of variables using a GA. The results emphasise the importance of Mp to assess the success of the variable selection and that techniques such as PLS are more robust following variable selection.

  20. Compatibility of functional groups in K[sup ow]-based QSARs: Application to nitro compounds

    SciTech Connect

    Banerjee, S.; Williams, C.L. )

    1993-10-01

    Nitro compounds are particular difficult to handle in simple K[sup ow]-based QSARs, owing to differences in their lipid-phase activity coefficients. These differences can be corrected, in part, through inclusion of a term in octanol solubility. A procedure for identifying potentially incompatible groups in a given QSAR is suggested. The quality of a QSAR is best if the interactions of the functional groups involved with octanol fall within a narrow range. These interactions are easily calculated by the UNIFAC method.

  1. Hologram QSAR studies of antiprotozoal activities of sesquiterpene lactones.

    PubMed

    Trossini, Gustavo H G; Maltarollo, Vinícius G; Schmidt, Thomas J

    2014-07-18

    Infectious diseases such as trypanosomiasis and leishmaniasis are considered neglected tropical diseases due the lack for many years of research and development into new drug treatments besides the high incidence of mortality and the lack of current safe and effective drug therapies. Natural products such as sesquiterpene lactones have shown activity against T. brucei and L. donovani, the parasites responsible for these neglected diseases. To evaluate structure activity relationships, HQSAR models were constructed to relate a series of 40 sesquiterpene lactones (STLs) with activity against T. brucei, T. cruzi, L. donovani and P. falciparum and also with their cytotoxicity. All constructed models showed good internal (leave-one-out q2 values ranging from 0.637 to 0.775) and external validation coefficients (r2test values ranging from 0.653 to 0.944). From HQSAR contribution maps, several differences between the most and least potent compounds were found. The fragment contribution of PLS-generated models confirmed the results of previous QSAR studies that the presence of α,β-unsatured carbonyl groups is fundamental to biological activity. QSAR models for the activity of these compounds against T. cruzi, L. donovani and P. falciparum are reported here for the first time. The constructed HQSAR models are suitable to predict the activity of untested STLs.

  2. Correlating metal ionic characteristics with biosorption capacity using QSAR model.

    PubMed

    Can, Chen; Jianlong, Wang

    2007-11-01

    The relationship between metal ionic characteristics and the maximum biosorption capacity (q(max)) was established using QSAR model based on the classification of metal ions (soft, hard and borderline ions). Ten kinds of metal ions (Ag(+), Cs(+), Zn(2+), Pb(2+), N(i2+), Cu(2+), Co(2+), Sr(2+), Cd(2+), Cr(3+)) were selected and the waste biomass of Saccharomyces cerevisiae obtained from a local brewery was used as biosorbent. Eighteen parameters of physiochemical characteristics of metal ions were selected and correlated with q(max). Classification of metal ions could improve the QSAR models and different characteristics were significant in correlating with q(max), such as polarizing power Z(2)/r or the first hydrolysis constant |logK(OH)| or ionization potential IP. X(m)(2)r seemed to be suitable for metal ions including soft ions, and Z(2)/r, |logK(OH)| and IP suitable for only soft ions or metal ions excluding soft ions. It provided a new way to predict the biosorptive capacity of metal ions.

  3. QSAR Modelling of CYP3A4 Inhibition as a Screening Tool in the Context of DrugDrug Interaction Studies.

    PubMed

    Hamon, Véronique; Horvath, Dragos; Gaudin, Cédric; Desrivot, Julie; Junges, Céline; Arrault, Alban; Bertrand, Marc; Vayer, Philippe

    2012-09-01

    Drugdrug interaction potential (DDI), especially cytochrome P450 (CYP) 3A4 inhibition potential, is one of the most important parameters to be optimized before preclinical and clinical pharmaceutical development as regard to the number of marketed drug metabolized mainly by this CYP and potentially co-administered with the future drug. The present study aims to develop in silico models for CYP3A4 inhibition prediction to help medicinal chemists during the discovery phase and even before the synthesis of new chemical entities (NCEs), focusing on NCEs devoid of any inhibitory potential toward this CYP. In order to find a relevant relationship between CYP3A4 inhibition and chemical features of the screened compounds, we applied a genetic-algorithm-based QSAR exploratory tool SQS (Stochastic QSAR Sampler) in combination with different description approaches comprising alignment-independent Volsurf descriptors, ISIDA fragments and Topological Fuzzy Pharmacophore Triplets. The experimental data used to build models were extracted from an in-house database. We derived a model with good prediction ability that was confirmed on both newly synthesized compound and public dataset retrieved from Pubchem database. This model is a promising efficient tool for filtering out potentially problematic compounds.

  4. 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

  5. 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.

  6. 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...

  7. 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...

  8. 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...

  9. 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…

  10. 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.

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

    PubMed

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

    2003-08-01

    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.

  12. 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

  13. 3-D QSAR studies on histone deacetylase inhibitors. A GOLPE/GRID approach on different series of compounds.

    PubMed

    Ragno, Rino; Simeoni, Silvia; Valente, Sergio; Massa, Silvio; Mai, Antonello

    2006-01-01

    Docking simulation and three-dimensional quantitative structure-activity relationships (3D-QSARs) analyses were conducted on four series of HDAC inhibitors. The studies were performed using the GRID/GOLPE combination using structure-based alignment. Twelve 3-D QSAR models were derived and discussed. Compared to previous studies on similar inhibitors, the present 3-D QSAR investigation proved to be of higher statistical value, displaying for the best global model r2, q2, and cross-validated SDEP values of 0.94, 0.83, and 0.41, respectively. A comparison of the 3-D QSAR maps with the structural features of the binding site showed good correlation. The results of 3D-QSAR and docking studies validated each other and provided insight into the structural requirements for anti-HDAC activity. To our knowledge this is the first 3-D QSAR application on a broad molecular diversity training set of HDACIs.

  14. The index of ideality of correlation: A criterion of predictability of QSAR models for skin permeability?

    PubMed

    Toropova, Alla P; Toropov, Andrey A

    2017-02-11

    New criterion of the predictive potential of quantitative structure-property/activity relationships (QSPRs/QSARs) is suggested. This criterion is calculated with utilization of the correlation coefficient between experimental and calculated values of endpoint for the calibration set, with taking into account the positive and negative dispersions between experimental and calculated values. The utilization of this criterion improves the predictive potential of QSAR models of dermal permeability coefficient, logKp (cm/h).

  15. 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

  16. Novel approach to evolutionary neural network based descriptor selection and QSAR model development

    NASA Astrophysics Data System (ADS)

    Debeljak, Željko; Marohnić, Viktor; Srečnik, Goran; Medić-Šarić, Marica

    2005-12-01

    Capability of evolutionary neural network (ENN) based QSAR approach to direct the descriptor selection process towards stable descriptor subset (DS) composition characterized by acceptable generalization, as well as the influence of description stability on QSAR model interpretation have been examined. In order to analyze the DS stability and QSAR model generalization properties multiple random dataset partitions into training and test set were made. Acceptability criteria proposed by Golbraikh et al. [J. Comput.-Aided Mol. Des., 17 (2003) 241] have been chosen for selection of highly predictive QSAR models from a set of all models produced by ENN for each dataset splitting. All QSAR models that pass Golbraikh's filter generated by ENN for each dataset partition were collected. Two final DS forming principles were compared. Standard principle is based on selection of descriptors characterized by highest frequencies among all descriptors that appear in the pool [J. Chem. Inf. Comput. Sci., 43 (2003) 949]. Search across the model pool for DS that are stable against multiple dataset subsampling i.e. universal DS solutions is the basis of novel approach. Based on described principles benzodiazepine QSAR has been proposed and evaluated against results reported by others in terms of final DS composition and model predictive performance.

  17. 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

  18. On various metrics used for validation of predictive QSAR models with applications in virtual screening and focused library design.

    PubMed

    Roy, Kunal; Mitra, Indrani

    2011-07-01

    Quantitative structure-activity relationships (QSARs) have important applications in drug discovery research, environmental fate modeling, property prediction, etc. Validation has been recognized as a very important step for QSAR model development. As one of the important objectives of QSAR modeling is to predict activity/property/toxicity of new chemicals falling within the domain of applicability of the developed models and QSARs are being used for regulatory decisions, checking reliability of the models and confidence of their predictions is a very important aspect, which can be judged during the validation process. One prime application of a statistically significant QSAR model is virtual screening for molecules with improved potency based on the pharmacophoric features and the descriptors appearing in the QSAR model. Validated QSAR models may also be utilized for design of focused libraries which may be subsequently screened for the selection of hits. The present review focuses on various metrics used for validation of predictive QSAR models together with an overview of the application of QSAR models in the fields of virtual screening and focused library design for diverse series of compounds with citation of some recent examples.

  19. 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.

  20. QSID Tool: a new three-dimensional QSAR environmental tool

    NASA Astrophysics Data System (ADS)

    Park, Dong Sun; Kim, Jae Min; Lee, Young Bok; Ahn, Chang Ho

    2008-12-01

    QSID Tool (Quantitative structure-activity relationship tool for Innovative Discovery) was developed to provide an easy-to-use, robust and high quality environmental tool for 3D QSAR. Predictive models developed with QSID Tool can accelerate the discovery of lead compounds by enabling researchers to formulate and test hypotheses for optimizing efficacy and increasing drug safety and bioavailability early in the process of drug discovery. QSID Tool was evaluated by comparison with SYBYL® using two different datasets derived from the inhibitors of Trypsin (Böhm et al., J Med Chem 42:458, 1999) and p38-MAPK (Liverton et al., J Med Chem 42:2180, 1999; Romeiro et al., J Comput Aided Mol Des 19:385, 2005; Romeiro et al., J Mol Model 12:855, 2006). The results suggest that QSID Tool is a useful model for the prediction of new analogue activities.

  1. Molecular design and QSARs/QSPRs with molecular descriptors family.

    PubMed

    Bolboacă, Sorana D; Jäntschi, Lorentz; Diudea, Mircea V

    2013-06-01

    The aim of the present paper is to present the methodology of the molecular descriptors family (MDF) as an integrative tool in molecular modeling and its abilities as a multivariate QSAR/QSPR modeling tool. An algorithm for extracting useful information from the topological and geometrical representation of chemical compounds was developed and integrated to calculate MDF members. The MDF methodology was implemented and the software is available online (http://l.academicdirect.org/Chemistry/SARs/MDF_SARs/). This integrative tool was developed in order to maximize performance, functionality, efficiency and portability. The MDF methodology is able to provide reliable and valid multiple linear regression models. Furthermore, in many cases, the MDF models were better than the published results in the literature in terms of correlation coefficients (statistically significant Steiger's Z test at a significance level of 5%) and/or in terms of values of information criteria and Kubinyi function. The MDF methodology developed and implemented as a platform for investigating and characterizing quantitative relationships between the chemical structure and the activity/property of active compounds was used on more than 50 study cases. In almost all cases, the methodology allowed obtaining of QSAR/QSPR models improved in explanatory power of structure-activity and structure-property relationships. The algorithms applied in the computation of geometric and topological descriptors (useful in modeling physicochemical or biological properties of molecules) and those used in searching for reliable and valid multiple linear regression models certain enrich the pool of low-cost low-time drug design tools.

  2. 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…

  3. A Comparison of QSAR Based Thermo and Water Solvation Property Prediction Tools and Experimental Data for Selected Traditional Chemical Warfare Agents and Simulants

    DTIC Science & Technology

    2014-07-01

    software packages were available, including EPI Suite, ACD Labs, ChemAxon’s Marvin, Vega , and ADF COSMO-RS. EPI Suite’s KOWWIN is a QSAR based model ... QSARs are a well established method of property prediction first demonstrated for petroleum components. QSARs are simple mathematical regression models ...Validation and error assessment of the QSAR model is performed with the remaining laboratory measurements that were not included in the original

  4. Multispecies QSAR modeling for predicting the aquatic toxicity of diverse organic chemicals for regulatory toxicology.

    PubMed

    Singh, Kunwar P; Gupta, Shikha; Kumar, Anuj; Mohan, Dinesh

    2014-05-19

    The research aims to develop multispecies quantitative structure-activity relationships (QSARs) modeling tools capable of predicting the acute toxicity of diverse chemicals in various Organization for Economic Co-operation and Development (OECD) recommended test species of different trophic levels for regulatory toxicology. Accordingly, the ensemble learning (EL) approach based classification and regression QSAR models, such as decision treeboost (DTB) and decision tree forest (DTF) implementing stochastic gradient boosting and bagging algorithms were developed using the algae (P. subcapitata) experimental toxicity data for chemicals. The EL-QSAR models were successfully applied to predict toxicities of wide groups of chemicals in other test species including algae (S. obliguue), daphnia, fish, and bacteria. Structural diversity of the selected chemicals and those of the end-point toxicity data of five different test species were tested using the Tanimoto similarity index and Kruskal-Wallis (K-W) statistics. Predictive and generalization abilities of the constructed QSAR models were compared using statistical parameters. The developed QSAR models (DTB and DTF) yielded a considerably high classification accuracy in complete data of model building (algae) species (97.82%, 99.01%) and ranged between 92.50%-94.26% and 92.14%-94.12% in four test species, respectively, whereas regression QSAR models (DTB and DTF) rendered high correlation (R(2)) between the measured and model predicted toxicity end-point values and low mean-squared error in model building (algae) species (0.918, 0.15; 0.905, 0.21) and ranged between 0.575 and 0.672, 0.18-0.51 and 0.605-0.689 and 0.20-0.45 in four different test species. The developed QSAR models exhibited good predictive and generalization abilities in different test species of varied trophic levels and can be used for predicting the toxicities of new chemicals for screening and prioritization of chemicals for regulation.

  5. 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

  6. Evaluation of the EVA descriptor for QSAR studies: 3. The use of a genetic algorithm to search for models with enhanced predictive properties (EVA_GA)

    NASA Astrophysics Data System (ADS)

    Turner, David B.; Willett, Peter

    2000-01-01

    The EVA structural descriptor, based upon calculated fundamental molecular vibrational frequencies, has proved to be an effective descriptor for both QSAR and database similarity calculations. The descriptor is sensitive to 3D structure but has an advantage over field-based 3D-QSAR methods inasmuch as structural superposition is not required. The original technique involves a standardisation method wherein uniform Gaussians of fixed standard deviation (σ) are used to smear out frequencies projected onto a linear scale. The smearing function permits the overlap of proximal frequencies and thence the extraction of a fixed dimensional descriptor regardless of the number and precise values of the frequencies. It is proposed here that there exist optimal localised values of σ in different spectral regions; that is, the overlap of frequencies using uniform Gaussians may, at certain points in the spectrum, either be insufficient to pick up relationships where they exist or mix up information to such an extent that significant correlations are obscured by noise. A genetic algorithm is used to search for optimal localised σ values using crossvalidated PLS regression scores as the fitness score to be optimised. The resultant models were then validated against a previously unseen test set of compounds and through data scrambling. The performance of EVA_GA is compared to that of EVA and analogous CoMFA studies; in the latter case a brief evaluation is made of the effect of grid resolution upon the stability of CoMFA PLS scores particularly in relation to test set predictions.

  7. Pharmacophore modelling, atom-based 3D-QSAR generation and virtual screening of molecules projected for mPGES-1 inhibitory activity.

    PubMed

    Misra, S; Saini, M; Ojha, H; Sharma, D; Sharma, K

    2017-01-01

    COX-2 inhibitors exhibit anticancer effects in various cancer models but due to the adverse side effects associated with these inhibitors, targeting molecules downstream of COX-2 (such as mPGES-1) has been suggested. Even after calls for mPGES-1 inhibitor design, to date there are only a few published inhibitors targeting the enzyme and displaying anticancer activity. In the present study, we have deployed both ligand and structure-based drug design approaches to hunt novel drug-like candidates as mPGES-1 inhibitors. Fifty-four compounds with tested mPGES-1 inhibitory value were used to develop a model with four pharmacophoric features. 3D-QSAR studies were undertaken to check the robustness of the model. Statistical parameters such as r(2) = 0.9924, q(2) = 0.5761 and F test = 1139.7 indicated significant predictive ability of the proposed model. Our QSAR model exhibits sites where a hydrogen bond donor, hydrophobic group and the aromatic ring can be substituted so as to enhance the efficacy of the inhibitor. Furthermore, we used our validated pharmacophore model as a three-dimensional query to screen the FDA-approved Lopac database. Finally, five compounds were selected as potent mPGES-1 inhibitors on the basis of their docking energy and pharmacokinetic properties such as ADME and Lipinski rule of five.

  8. Searching for anthranilic acid-based thumb pocket 2 HCV NS5B polymerase inhibitors through a combination of molecular docking, 3D-QSAR and virtual screening.

    PubMed

    Vrontaki, Eleni; Melagraki, Georgia; Mavromoustakos, Thomas; Afantitis, Antreas

    2016-01-01

    A combination of the following computational methods: (i) molecular docking, (ii) 3-D Quantitative Structure Activity Relationship Comparative Molecular Field Analysis (3D-QSAR CoMFA), (iii) similarity search and (iv) virtual screening using PubChem database was applied to identify new anthranilic acid-based inhibitors of hepatitis C virus (HCV) replication. A number of known inhibitors were initially docked into the "Thumb Pocket 2" allosteric site of the crystal structure of the enzyme HCV RNA-dependent RNA polymerase (NS5B GT1b). Then, the CoMFA fields were generated through a receptor-based alignment of docking poses to build a validated and stable 3D-QSAR CoMFA model. The proposed model can be first utilized to get insight into the molecular features that promote bioactivity, and then within a virtual screening procedure, it can be used to estimate the activity of novel potential bioactive compounds prior to their synthesis and biological tests.

  9. Image Databases.

    ERIC Educational Resources Information Center

    Pettersson, Rune

    Different kinds of pictorial databases are described with respect to aims, user groups, search possibilities, storage, and distribution. Some specific examples are given for databases used for the following purposes: (1) labor markets for artists; (2) document management; (3) telling a story; (4) preservation (archives and museums); (5) research;…

  10. 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), ...

  11. 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.

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

    NASA Astrophysics Data System (ADS)

    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.

  13. The receptor-dependent LQTA-QSAR: application to a set of trypanothione reductase inhibitors

    NASA Astrophysics Data System (ADS)

    Barbosa, Euzébio G.; Pasqualoto, Kerly Fernanda M.; Ferreira, Márcia M. C.

    2012-09-01

    A new Receptor- Dependent LQTA- QSAR approach, RD- LQTA- QSAR, is proposed as a new 4D-QSAR method. It is an evolution of receptor independent LQTA-QSAR. This approach uses the free GROMACS package to carry out molecular dynamics simulations and generates a conformational ensemble profile for each compound. Such an ensemble is used to build molecular interaction field-based QSAR models, as in CoMFA. To show the potential of this methodology, a set of 38 phenothiazine derivatives that are specific competitive T. cruzi trypanothione reductase inhibitors, was chosen. Using a combination of molecular docking and molecular dynamics simulations, the binding mode of the phenotiazine derivatives was evaluated in a simulated induced fit approach. The ligands alignments were performed using both ligand and binding site atoms, enabling unbiased alignment. The models obtained were extensively validated by leave- N-out cross-validation and y-randomization techniques to test for their robustness and absence of chance correlation. The final model presented Q 2 LOO of 0.87 and R² of 0.92 and a suitable external prediction of Q_{ext}2 = 0.78. The adapted binding site obtained is useful to perform virtual screening and ligand structure-based design and the descriptors in the final model can aid in the design new inhibitors.

  14. Performance of Deep and Shallow Neural Networks, the Universal Approximation Theorem, Activity Cliffs, and QSAR.

    PubMed

    Winkler, David A; Le, Tu C

    2017-01-01

    Neural networks have generated valuable Quantitative Structure-Activity/Property Relationships (QSAR/QSPR) models for a wide variety of small molecules and materials properties. They have grown in sophistication and many of their initial problems have been overcome by modern mathematical techniques. QSAR studies have almost always used so-called "shallow" neural networks in which there is a single hidden layer between the input and output layers. Recently, a new and potentially paradigm-shifting type of neural network based on Deep Learning has appeared. Deep learning methods have generated impressive improvements in image and voice recognition, and are now being applied to QSAR and QSAR modelling. This paper describes the differences in approach between deep and shallow neural networks, compares their abilities to predict the properties of test sets for 15 large drug data sets (the kaggle set), discusses the results in terms of the Universal Approximation theorem for neural networks, and describes how DNN may ameliorate or remove troublesome "activity cliffs" in QSAR data sets.

  15. Monte Carlo method based QSAR modeling of maleimide derivatives as glycogen synthase kinase-3β inhibitors.

    PubMed

    Živković, Jelena V; Trutić, Nataša V; Veselinović, Jovana B; Nikolić, Goran M; Veselinović, Aleksandar M

    2015-09-01

    The Monte Carlo method was used for QSAR modeling of maleimide derivatives as glycogen synthase kinase-3β inhibitors. The first QSAR model was developed for a series of 74 3-anilino-4-arylmaleimide derivatives. The second QSAR model was developed for a series of 177 maleimide derivatives. QSAR models were calculated with the representation of the molecular structure by the simplified molecular input-line entry system. Two splits have been examined: one split into the training and test set for the first QSAR model, and one split into the training, test and validation set for the second. The statistical quality of the developed model is very good. The calculated model for 3-anilino-4-arylmaleimide derivatives had following statistical parameters: r(2)=0.8617 for the training set; r(2)=0.8659, and r(m)(2)=0.7361 for the test set. The calculated model for maleimide derivatives had following statistical parameters: r(2)=0.9435, for the training, r(2)=0.9262 and r(m)(2)=0.8199 for the test and r(2)=0.8418, r(av)(m)(2)=0.7469 and ∆r(m)(2)=0.1476 for the validation set. Structural indicators considered as molecular fragments responsible for the increase and decrease in the inhibition activity have been defined. The computer-aided design of new potential glycogen synthase kinase-3β inhibitors has been presented by using defined structural alerts.

  16. 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.

  17. Free energy force field (FEFF) 3D-QSAR analysis of a set of Plasmodium falciparum dihydrofolate reductase inhibitors

    NASA Astrophysics Data System (ADS)

    Santos-Filho, Osvaldo A.; Mishra, Rama K.; Hopfinger, A. J.

    2001-09-01

    Free energy force field (FEFF) 3D-QSAR analysis was used to construct ligand-receptor binding models for a set of 18 structurally diverse antifolates including pyrimethamine, cycloguanil, methotrexate, aminopterin and trimethoprim, and 13 pyrrolo[2,3-d]pyrimidines. The molecular target (`receptor') used was a 3D-homology model of a specific mutant type of Plasmodium falciparum (Pf) dihydrofolate reductase (DHFR). The dependent variable of the 3D-QSAR models is the IC50 inhibition constant for the specific mutant type of PfDHFR. The independent variables of the 3D-QSAR models (the descriptors) are scaled energy terms of a modified first-generation AMBER force field combined with a hydration shell aqueous solvation model and a collection of 2D-QSAR descriptors often used in QSAR studies. Multiple temperature molecular dynamics simulation (MDS) and the genetic function approximation (GFA) were employed using partial least square (PLS) and multidimensional linear regressions as the fitting functions to develop FEFF 3D-QSAR models for the binding process. The significant FEFF energy terms in the best 3D-QSAR models include energy contributions of the direct ligand-receptor interaction. Some changes in conformational energy terms of the ligand due to binding to the enzyme are also found to be important descriptors. The FEFF 3D-QSAR models indicate some structural features perhaps relevant to the mechanism of resistance of the PfDHFR to current antimalarials. The FEFF 3D-QSAR models are also compared to receptor-independent (RI) 4D-QSAR models developed in an earlier study and subsequently refined using recently developed generalized alignment rules.

  18. 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.

  19. Prediction of PAH mutagenicity in human cells by QSAR classification.

    PubMed

    Papa, E; Pilutti, P; Gramatica, P

    2008-01-01

    Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous pollutants of high environmental concern. The experimental data of a mutagenicity test on human B-lymphoblastoid cells (alternative to the Ames bacterial test) for a set of 70 oxo-, nitro- and unsubstituted PAHs, detected in particulate matter (PM), were modelled by Quantitative Structure-Activity Relationships (QSAR) classification methods (k-NN, k-Nearest Neighbour, and CART, Classification and Regression Tree) based on different theoretical molecular descriptors selected by Genetic Algorithms. The best models were validated for predictivity both externally and internally. For external validation, Self Organizing Maps (SOM) were applied to split the original data set. The best models, developed on the training set alone, show good predictive performance also on the prediction set chemicals (sensitivity 69.2-87.1%, specificity 62.5-87.5%). The classification of PAHs according to their mutagenicity, based only on a few theoretical molecular descriptors, allows a preliminary assessment of the human health risk, and the prioritisation of these compounds.

  20. QSAR Accelerated Discovery of Potent Ice Recrystallization Inhibitors.

    PubMed

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

    2016-05-24

    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.

  1. A new strategy of outlier detection for QSAR/QSPR.

    PubMed

    Cao, Dong-Sheng; Liang, Yi-Zeng; Xu, Qing-Song; Li, Hong-Dong; Chen, Xian

    2010-02-01

    The crucial step of building a high performance QSAR/QSPR model is the detection of outliers in the model. Detecting outliers in a multivariate point cloud is not trivial, especially when several outliers coexist in the model. The classical identification methods do not always identify them, because they are based on the sample mean and covariance matrix influenced by the outliers. Moreover, existing methods only lay stress on some type of outliers but not all the outliers. To avoid these problems and detect all kinds of outliers simultaneously, we provide a new strategy based on Monte-Carlo cross-validation, which was termed as the MC method. The MC method inherently provides a feasible way to detect different kinds of outliers by establishment of many cross-predictive models. With the help of the distribution of predictive residuals such obtained, it seems to be able to reduce the risk caused by the masking effect. In addition, a new display is proposed, in which the absolute values of mean value of predictive residuals are plotted versus standard deviations of predictive residuals. The plot divides the data into normal samples, y direction outliers and X direction outliers. Several examples are used to demonstrate the detection ability of MC method through the comparison of different diagnostic methods.

  2. 3D-QSAR-Assisted Design, Synthesis, and Evaluation of Novobiocin Analogues

    PubMed Central

    2012-01-01

    Hsp90 is an attractive therapeutic target for the treatment of cancer. Extensive structural modifications to novobiocin, the first Hsp90 C-terminal inhibitor discovered, have produced a library of novobiocin analogues and revealed some structure–activity relationships. On the basis of the most potent novobiocin analogues generated from prior studies, a three-dimensional quantitative structure–activity (3D QSAR) model was built. In addition, a new set of novobiocin analogues containing various structural features supported by the 3D QSAR model were synthesized and evaluated against two breast cancer cell lines. Several new inhibitors produced antiproliferative activity at midnanomolar concentrations, which results through Hsp90 inhibition. PMID:23606927

  3. QSAR study and VolSurf characterization of anti-HIV quinolone library

    NASA Astrophysics Data System (ADS)

    Filipponi, Enrica; Cruciani, Gabriele; Tabarrini, Oriana; Cecchetti, Violetta; Fravolini, Arnaldo

    2001-03-01

    Antiviral quinolones are promising compounds in the search for new therapeutically effective agents for the treatment of AIDS. To rationalize the SAR for this new interesting class of anti-HIV derivatives, we performed a 3D-QSAR study on a library of 101 6-fluoro and 6-desfluoroquinolones, taken either from the literature or synthesized by us. The chemometric procedure involved a fully semiempirical minimization of the molecular structures by the AMSOL program, which takes into account the solvatation effect, and their 3D characterization by the VolSurf/GRID program. The QSAR analysis, based on PCA and PLS methods, shows the key structural features responsible for the antiviral activity.

  4. Protonation states and conformational ensemble in ligand-based QSAR modeling.

    PubMed

    De Benedetti, Pier G

    2013-01-01

    Drug affinity and function depend on the different protonation species (present in the biological context) that generate different conformational ensembles with different structural features and, hence, different physico-chemical properties. In the present review article these strongly interdependent structural features will be considered for their crucial role in ligand-based QSAR modeling and drug design by using quantum chemical electronic/reactivity descriptors and molecular shape description. Some selected and relevant examples illustrate the role of these molecular descriptors, computed on the bioactive protonation states and conformers, as determinant factors in mechanistic/causative QSAR analysis.

  5. Computational identification of novel histone deacetylase inhibitors by docking based QSAR.

    PubMed

    Nair, Syam B; Teli, Mahesh Kumar; Pradeep, H; Rajanikant, G K

    2012-06-01

    Histone deacetylases (HDACs) are enzymes that modify chromatin structure and contribute to aberrant gene expression in cancer. A series compounds with well-assigned HDAC inhibitory activity was used for docking based 3D-QSAR analysis. The 3D-QSAR acquired had excellent correlation coefficient value (q2=0.753) and high Fisher ratio (F=300.2). A validated pharmacophore model (AAAPR) was employed for virtual screening. After manual selection, molecular docking and further refinement, six compounds with good absorption, distribution, metabolism, and excretion (ADME) properties were selected as potential HDAC inhibitors. Further, the molecular interactions of these inhibitors with the HDAC active site residues were discussed in detail.

  6. 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.

  7. Reducing abortion: the Danish experience.

    PubMed

    Risor, H

    1989-01-01

    In 1987, 20,830 legal abortions were performed in Denmark. 2,845 involved women below the age of 20, and 532 involved women terminating pregnancy after the 12th week. Danish law permits all of its female citizens to have an abortion free-of-charge before the 12th week of pregnancy. After the 12th week, the abortion must be applied for through a committee of 3 members, and all counties in Denmark have a committee. It is felt in Denmark that a woman has a right to an abortion if she decides to have one. It she makes that choice, doctors and nurses are supportive. Since 1970, sex education has been mandatory in Danish schools. Teachers often collaborate closely with school doctors and nurses in this education. All counties are required to have at least 1 clinic that provides contraceptive counselling. It was recently found that the lowest number of pregnancies among teenaged girls was found in a county in Jutland where all 9th grade students visit the county clinic to learn about contraceptives, pregnancy, and abortion. Within 1 year after Copenhagen had adopted this practice, the number of abortions among teenagers declined by 20%. One fourth of all pharmacies also collaborate with schools to promote sex education, instructing students about contraceptives and pregnancy tests. The Danish Family Planning Association has produced a film on abortion, and plans to produce videos on abortion for use in schools. The organization also holds training programs for health care personnel on contraception, pregnancy, and abortion. By means of the practices described above, it is hoped that the number of abortions and unwanted pregnancies in Denmark will be reduced.

  8. 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.

  9. QSAR analyses of organophosphates for insecticidal activity and its in-silico validation using molecular docking study.

    PubMed

    Niraj, Ravi Ranjan Kumar; Saini, Vandana; Kumar, Ajit

    2015-11-01

    The present work was carried out to design and develop novel QSAR models using 2D-QSAR and 3D-QSAR with CoMFA methodology for prediction of insecticidal activity of organophosphate (OP) molecules. The models were validated on an entirely different external dataset of in-house generated combinatorial library of OPs, by completely different computational approach of molecular docking against the target AChE protein of Musca domestica. The dock scores were observed to be in good correlation with 2D-QSAR and 3D-QSAR with CoMFA predicted activities and had the correlation coefficients (r(2)) of -0.62 and -0.63, respectively. The activities predicted by 2D-QSAR and 3D-QSAR with CoMFA were also observed to be highly correlated with r(2)=0.82. Also, the combinatorial library molecules were screened for toxicity in non-target organisms and degradability using USEPA-EPI Suite. The work was first step towards computer aided design and development of novel OP pesticide candidates with good insecticidal property but lower toxicity in non-targeted organisms and having biodegradation potential.

  10. Statistically validated QSARs, based on theoretical descriptors, for modeling aquatic toxicity of organic chemicals in Pimephales promelas (fathead minnow).

    PubMed

    Papa, Ester; Villa, Fulvio; Gramatica, Paola

    2005-01-01

    The use of Quantitative Structure-Activity Relationships in assessing the potential negative effects of chemicals plays an important role in ecotoxicology. (LC50)(96h) in Pimephales promelas (Duluth database) is widely modeled as an aquatic toxicity end-point. The object of this study was to compare different molecular descriptors in the development of new statistically validated QSAR models to predict the aquatic toxicity of chemicals classified according to their MOA and in a unique general model. The applied multiple linear regression approach (ordinary least squares) is based on theoretical molecular descriptor variety (1D, 2D, and 3D, from DRAGON package, and some calculated logP). The best combination of modeling descriptors was selected by the Genetic Algorithm-Variable Subset Selection procedure. The robustness and the predictive performance of the proposed models was verified using both internal (cross-validation by LOO, bootstrap, Y-scrambling) and external statistical validations (by splitting the original data set into training and validation sets by Kohonen-artificial neural networks (K-ANN)). The model applicability domain (AD) was checked by the leverage approach to verify prediction reliability.

  11. Prediction of biodegradability of aromatics in water using QSAR modeling.

    PubMed

    Cvetnic, Matija; Juretic Perisic, Daria; Kovacic, Marin; Kusic, Hrvoje; Dermadi, Jasna; Horvat, Sanja; Bolanca, Tomislav; Marin, Vedrana; Karamanis, Panaghiotis; Loncaric Bozic, Ana

    2017-05-01

    The study was aimed at developing models for predicting the biodegradability of aromatic water pollutants. For that purpose, 36 single-benzene ring compounds, with different type, number and position of substituents, were used. The biodegradability was estimated according to the ratio of the biochemical (BOD5) and chemical (COD) oxygen demand values determined for parent compounds ((BOD5/COD)0), as well as for their reaction mixtures in half-life achieved by UV-C/H2O2 process ((BOD5/COD)t1/2). The models correlating biodegradability and molecular structure characteristics of studied pollutants were derived using quantitative structure-activity relationship (QSAR) principles and tools. Upon derivation of the models and calibration on the training and subsequent testing on the test set, 3- and 5-variable models were selected as the most predictive for (BOD5/COD)0 and (BOD5/COD)t1/2, respectively, according to the values of statistical parameters R(2) and Q(2). Hence, 3-variable model predicting (BOD5/COD)0 possessed R(2)=0.863 and Q(2)=0.799 for training set, and R(2)=0.710 for test set, while 5-variable model predicting (BOD5/COD)1/2 possessed R(2)=0.886 and Q(2)=0.788 for training set, and R(2)=0.564 for test set. The selected models are interpretable and transparent, reflecting key structural features that influence targeted biodegradability and can be correlated with the degradation mechanisms of studied compounds by UV-C/H2O2.

  12. 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

  13. 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.

  14. QSAR study on the antibacterial activity of some sulfa drugs: building blockers of Mannich bases.

    PubMed

    Mandloi, Dheeraj; Joshi, Sheela; Khadikar, Padmakar V; Khosla, Navita

    2005-01-17

    Sulfa drugs are building blockers of several types of Mannich bases. Consequently, the antibacterial activities of sulfa drugs are reported in this paper, which will help in explaining and understanding antibacterial activities of Mannich bases. Reported QSAR is carried out using distance-based topological indices and discussed critically on the basis of statistical parameters.

  15. QSAR study of selective ligands for the thyroid hormone receptor beta.

    PubMed

    Liu, Huanxiang; Gramatica, Paola

    2007-08-01

    In this paper, an accurate and reliable QSAR model of 87 selective ligands for the thyroid hormone receptor beta 1 (TRbeta1) was developed, based on theoretical molecular descriptors to predict the binding affinity of compounds with receptor. The structural characteristics of compounds were described wholly by a large amount of molecular structural descriptors calculated by DRAGON. Six most relevant structural descriptors to the studied activity were selected as the inputs of QSAR model by a robust optimization algorithm Genetic Algorithm. The built model was fully assessed by various validation methods, including internal and external validation, Y-randomization test, chemical applicability domain, and all the validations indicate that the QSAR model we proposed is robust and satisfactory. Thus, the built QSAR model can be used to fast and accurately predict the binding affinity of compounds (in the defined applicability domain) to TRbeta1. At the same time, the model proposed could also identify and provide some insight into what structural features are related to the biological activity of these compounds and provide some instruction for further designing the new selective ligands for TRbeta1 with high activity.

  16. 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...

  17. The effects of characteristics of substituents on toxicity of the nitroaromatics: HiT QSAR study

    NASA Astrophysics Data System (ADS)

    Kuz'min, Victor E.; Muratov, Eugene N.; Artemenko, Anatoly G.; Gorb, Leonid; Qasim, Mohammad; Leszczynski, Jerzy

    2008-10-01

    The present study applies the Hierarchical Technology for Quantitative Structure-Activity Relationships (HiT QSAR) for (i) evaluation of the influence of the characteristics of 28 nitroaromatic compounds (some of which belong to a widely known class of explosives) as to their toxicity; (ii) prediction of toxicity for new nitroaromatic derivatives; (iii) analysis of the effects of substituents in nitroaromatic compounds on their toxicity in vivo. The 50% lethal dose concentration for rats (LD50) was used to develop the QSAR models based on simplex representation of molecular structure. The preliminary 1D QSAR results show that even the information on the composition of molecules reveals the main tendencies of changes in toxicity. The statistic characteristics for partial least squares 2D QSAR models are quite satisfactory ( R 2 = 0.96-0.98; Q 2 = 0.91-0.93; R 2 test = 0.89-0.92), which allows us to carry out the prediction of activity for 41 novel compounds designed by the application of new combinations of substituents represented in the training set. The comprehensive analysis of toxicity changes as a function of substituent position and nature was carried out. Molecular fragments that promote and interfere with toxicity were defined on the basis of the obtained models. It was shown that the mutual influence of substituents in the benzene ring plays a crucial role regarding toxicity. The influence of different substituents on toxicity can be mediated via different C-H fragments of the aromatic ring.

  18. Molecular docking and QSAR of aplyronine A and analogues: potent inhibitors of actin

    NASA Astrophysics Data System (ADS)

    Hussain, Abrar; Melville, James L.; Hirst, Jonathan D.

    2010-01-01

    Actin-binding natural products have been identified as a potential basis for the design of cancer therapeutic agents. We report flexible docking and QSAR studies on aplyronine A analogues. Our findings show the macrolide `tail' to be fundamental for the depolymerisation effect of actin-binding macrolides and that it is the tail which forms the initial interaction with the actin rather than the macrocycle, as previously believed. Docking energy scores for the compounds were highly correlated with actin depolymerisation activity. The 3D-QSAR models were predictive, with the best model giving a q 2 value of 0.85 and a r 2 of 0.94. Results from the docking simulations and the interpretation from QSAR "coeff*stdev" contour maps provide insight into the binding mechanism of each analogue and highlight key features that influence depolymerisation activity. The results herein may aid the design of a putative set of analogues that can help produce efficacious and tolerable anti-tumour agents. Finally, using the best QSAR model, we have also made genuine predictions for an independent set of recently reported aplyronine analogues.

  19. 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.

  20. 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.

  1. 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.

  2. Synthesis, in vitro antitubercular activity and 3D-QSAR study of 1,4-dihydropyridines.

    PubMed

    Manvar, Atul T; Pissurlenkar, Raghuvir R S; Virsodia, Vijay R; Upadhyay, Kuldip D; Manvar, Dinesh R; Mishra, Arun K; Acharya, Hrishikesh D; Parecha, Alpesh R; Dholakia, Chintan D; Shah, Anamik K; Coutinho, Evans C

    2010-05-01

    In continuation of our research program on new antitubercular agents, this article is a report of the synthesis of 97 various symmetrical, unsymmetrical, and N-substituted 1,4-dihydropyridines. The synthesized molecules were tested for their activity against M. tuberculosis H (37)Rv strain with rifampin as the standard drug. The percentage inhibition was found in the range 3-93%. In an effort to understand the relationship between structure and activity, 3D-QSAR studies were also carried out on a subset that is representative of the molecules synthesized. For the generation of the QSAR models, a training set of 35 diverse molecules representing the synthesized molecules was utilized. The molecules were aligned using the atom-fit technique. The CoMFA and CoMSIA models generated on the molecules aligned by the atom-fit method show a correlation coefficient (r (2)) of 0.98 and 0.95 with cross-validated r (2)(q (2)) of 0.56 and 0.62, respectively. The 3D-QSAR models were externally validated against a test set of 19 molecules (aligned previously with the training set) for which the predictive r(2)(r(r)(pred)) is recorded as 0.74 and 0.69 for the CoMFA and CoMSIA models, respectively. The models were checked for chance correlation through y-scrambling. The QSAR models revealed the importance of the conformational flexibility of the substituents in antitubercular activity.

  3. The Danish Registry of Diabetic Retinopathy

    PubMed Central

    Andersen, Nis; Hjortdal, Jesper Østergaard; Schielke, Katja Christina; Bek, Toke; Grauslund, Jakob; Laugesen, Caroline Schmidt; Lund-Andersen, Henrik; Cerqueira, Charlotte; Andresen, Jens

    2016-01-01

    Aim of database To monitor the development of diabetic eye disease in Denmark and to evaluate the accessibility and effectiveness of diabetic eye screening programs with focus on interregional variations. Target population The target population includes all patients diagnosed with diabetes. Denmark (5.5 million inhabitants) has ~320,000 diabetes patients with an annual increase of 27,000 newly diagnosed patients. The Danish Registry of Diabetic Retinopathy (DiaBase) collects data on all diabetes patients aged ≥18 years who attend screening for diabetic eye disease in hospital eye departments and in private ophthalmological practice. In 2014–2015, DiaBase included data collected from 77,968 diabetes patients. Main variables The main variables provide data for calculation of performance indicators to monitor the quality of diabetic eye screening and development of diabetic retinopathy. Data with respect to age, sex, best corrected visual acuity, screening frequency, grading of diabetic retinopathy and maculopathy at each visit, progression/regression of diabetic eye disease, and prevalence of blindness were obtained. Data analysis from DiaBase’s latest annual report (2014–2015) indicates that the prevalence of no diabetic retinopathy, nonproliferative diabetic retinopathy, and proliferative diabetic retinopathy is 78%, 18%, and 4%, respectively. The percentage of patients without diabetic maculopathy is 97%. The proportion of patients with regression of diabetic retinopathy (20%) is greater than the proportion of patients with progression of diabetic retinopathy (10%). Conclusion The collection of data from diabetic eye screening is still expanding in Denmark. Analysis of the data collected during the period 2014–2015 reveals an overall decrease of diabetic retinopathy compared to the previous year, although the number of patients newly diagnosed with diabetes has been increasing in Denmark. DiaBase is a useful tool to observe the quality of screening

  4. Review of synthesis, biological assay and QSAR studies of β-secretase inhibitors.

    PubMed

    Niño, Helena; García-Pintos, Isela; Rodríguez-Borges, José E; Escobar-Cubiella, Manolo; García-Mera, Xerardo; Prado-Prado, Francisco

    2011-12-01

    Alzheimer's disease (AD) is highly complex. While several pathologies characterize this disease, amyloid plaques, composed of the β-amyloid peptide, are hallmark neuropathological lesions in Alzheimer's disease brain. Indeed, a wealth of evidence suggests that β-amyloid is central to the pathophysiology of AD and is likely to play an early role in this intractable neurodegenerative disorder. The BACE-1 enzyme is essential for the generation of β-amyloid. BACE-1 knockout mice do not produce β-amyloid and are free from Alzheimer's associated pathologies, including neuronal loss and certain memory deficits. The fact that BACE-1 initiates the formation of β-amyloid, and the observation that BACE-1 levels are elevated in this disease provide direct and compelling reasons to develop therapies directed at BACE-1 inhibition, thus reducing β-amyloid and its associated toxicities. In this sense, quantitative structure-activity relationships (QSAR) could play an important role in studying these β-secretase inhibitors. QSAR models are necessary in order to guide the β-secretase synthesis. This work is aimed at reviewing different design and synthesis and computational studies for a very large and heterogeneous series of β-secretase inhibitors. First, we review design, synthesis, and Biological assay of β-secretase inhibitors. Next, we review 2D QSAR, 3D QSAR, CoMFA, CoMSIA and Docking with different compounds to find out the structural requirements. Next, we review QSAR studies using the method of Linear Discriminant Analysis (LDA) in order to understand the essential structural requirement for receptor binding for β- secretase inhibitors.

  5. QSAR models for predicting in vivo aquatic toxicity of chlorinated alkanes to fish.

    PubMed

    Zvinavashe, Elton; van den Berg, Hans; Soffers, Ans E M F; Vervoort, Jacques; Freidig, Andreas; Murk, Albertinka J; Rietjens, Ivonne M C M

    2008-03-01

    Quantitative structure-activity relationship (QSAR) models are expected to play a crucial role in reducing the number of animals to be used for toxicity testing resulting from the adoption of the new European Union chemical control system called Registration, Evaluation, and Authorization of Chemicals (REACH). The objective of the present study was to generate in vitro acute toxicity data that could be used to develop a QSAR model to describe acute in vivo toxicity of chlorinated alkanes. Cytotoxicity of a series of chlorinated alkanes to Chinese hamster ovary (CHO) cells was observed at concentrations similar to those that have been shown previously to be toxic to fish. Strong correlations exist between the acute in vitro toxicity of the chlorinated alkanes and (i) hydrophobicity [modeled by the calculated log K ow (octanol-water partition coefficient); r (2) = 0.883 and r int (2) = 0.854] and (ii) in vivo acute toxicity to fish ( r (2) = 0.758). A QSAR model has been developed to predict in vivo acute toxicity to fish, based on the in vitro data and even on in silico log K ow data only. The developed QSAR model is applicable to chlorinated alkanes with up to 10 carbon atoms, up to eight chlorine atoms, and log K ow values lying within the range from 1.71 to 5.70. Out of the 100204 compounds on the European Inventory of Existing Chemicals (EINECS), our QSAR model covers 77 (0.1%) of them. Our findings demonstrate that in vitro experiments and even in silico calculations can replace animal experiments in the prediction of the acute toxicity of chlorinated alkanes.

  6. Summary of a workshop on regulatory acceptance of (Q)SARs for human health and environmental endpoints.

    PubMed Central

    Jaworska, Joanna S; Comber, M; Auer, C; Van Leeuwen, C J

    2003-01-01

    The "Workshop on Regulatory Use of (Q)SARs for Human Health and Environmental Endpoints," organized by the European Chemical Industry Council and the International Council of Chemical Associations, gathered more than 60 human health and environmental experts from industry, academia, and regulatory agencies from around the world. They agreed, especially industry and regulatory authorities, that the workshop initiated great potential for the further development and use of predictive models, that is, quantitative structure-activity relationships [(Q)SARs], for chemicals management in a much broader scope than is currently the case. To increase confidence in (Q)SAR predictions and minimization of their misuse, the workshop aimed to develop proposals for guidance and acceptability criteria. The workshop also described the broad outline of a system that would apply that guidance and acceptability criteria to a (Q)SAR when used for chemical management purposes, including priority setting, risk assessment, and classification and labeling. PMID:12896859

  7. Quantitative structure-activity relationship (QSAR) study of a series of benzimidazole derivatives as inhibitors of Saccharomyces cerevisiae.

    PubMed

    Podunavac-Kuzmanović, Sonja O; Cvetković, Dragoljub D; Jevrić, Lidija R; Uzelac, Natasa J

    2013-01-01

    A quantitative structure activity relationship (QSAR) has been carried out on a series of benzimidazole derivatives to identify the structural requirements for their inhibitory activity against yeast Saccharomyces cerevisiae. A multiple linear regression (MLR) procedure was used to model the relationships between various physicochemical, steric, electronic, and structural molecular descriptors and antifungal activity of benzimidazole derivatives. The QSAR expressions were generated using a training set of 16 compounds and the predictive ability of the resulting models was evaluated against a test set of 8 compounds. The best QSAR models were further validated by leave one out technique as well as by the calculation of statistical parameters for the established theoretical models. Therefore, satisfactory relationships between antifungal activity and molecular descriptors were found. QSAR analysis reveals that lipophilicity descriptor (logP), dipole moment (DM) and surface area grid (SAG) govern the inhibitory activity of compounds studied against Saccharomyces cerevisiae.

  8. 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...

  9. 3-D QSAutogrid/R: an alternative procedure to build 3-D QSAR models. Methodologies and applications.

    PubMed

    Ballante, Flavio; Ragno, Rino

    2012-06-25

    Since it first appeared in 1988 3-D QSAR has proved its potential in the field of drug design and activity prediction. Although thousands of citations now exist in 3-D QSAR, its development was rather slow with the majority of new 3-D QSAR applications just extensions of CoMFA. An alternative way to build 3-D QSAR models, based on an evolution of software, has been named 3-D QSAutogrid/R and has been developed to use only software freely available to academics. 3-D QSAutogrid/R covers all the main features of CoMFA and GRID/GOLPE with implementation by multiprobe/multiregion variable selection (MPGRS) that improves the simplification of interpretation of the 3-D QSAR map. The methodology is based on the integration of the molecular interaction fields as calculated by AutoGrid and the R statistical environment that can be easily coupled with many free graphical molecular interfaces such as UCSF-Chimera, AutoDock Tools, JMol, and others. The description of each R package is reported in detail, and, to assess its validity, 3-D QSAutogrid/R has been applied to three molecular data sets of which either CoMFA or GRID/GOLPE models were reported in order to compare the results. 3-D QSAutogrid/R has been used as the core engine to prepare more that 240 3-D QSAR models forming the very first 3-D QSAR server ( www.3d-qsar.com ) with its code freely available through R-Cran distribution.

  10. QSAR of anticancer compounds. Bis(11-oxo-11H-indeno[1,2-b]quinoline-6-carboxamides), bis(phenazine-1-carboxamides), and bis(naphthalimides).

    PubMed

    Mekapati, S B; Denny, W A; Kurup, A; Hansch, C

    2001-11-01

    QSAR have been developed for the anticancer activity (growth inhibition) of various tumor cells by bis(11-oxo-11H-indeno[1,2-b]quinoline-6-carboxamides), bis(phenazine-1-carboxamides), and bis(naphthalimides). Of the seven QSAR, positive hydrophobic interactions are found in only two examples: bis(naphthalimides) versus human colon cancer cells. This is consistent with other QSAR of anticancer compounds where hydrophobic interactions are found to be unimportant.

  11. 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.

  12. A review of QSAR studies to discover new drug-like compounds actives against leishmaniasis and trypanosomiasis.

    PubMed

    Castillo-Garit, Juan Alberto; Abad, Concepción; Rodríguez-Borges, J Enrique; Marrero-Ponce, Yovani; Torrens, Francisco

    2012-01-01

    The neglected tropical diseases (NTDs) affect more than one billion people (one-sixth of the world's population) and occur primarily in undeveloped countries in sub-Saharan Africa, Asia, and Latin America. Available drugs for these diseases are decades old and present an important number of limitations, especially high toxicity and, more recently, the emergence of drug resistance. In the last decade several Quantitative Structure-Activity Relationship (QSAR) studies have been developed in order to identify new organic compounds with activity against the parasites responsible for these diseases, which are reviewed in this paper. The topics summarized in this work are: 1) QSAR studies to identify new organic compounds actives against Chaga's disease; 2) Development of QSAR studies to discover new antileishmanial drusg; 3) Computational studies to identify new drug-like compounds against human African trypanosomiasis. Each topic include the general characteristics, epidemiology and chemotherapy of the disease as well as the main QSAR approaches to discovery/identification of new actives compounds for the corresponding neglected disease. The last section is devoted to a new approach know as multi-target QSAR models developed for antiparasitic drugs specifically those actives against trypanosomatid parasites. At present, as a result of these QSAR studies several promising compounds, active against these parasites, are been indentify. However, more efforts will be required in the future to develop more selective (specific) useful drugs.

  13. 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

  14. The Future of the Danish Army

    DTIC Science & Technology

    2013-03-01

    as a natural consequence of being a co-founder of the United Nations, focused on promoting peace and stability in the world, as a relatively large...Soviet invasion to a more expeditionary course of deploying forces to promote peace and stability around the globe. As a result, Danish defense policy...Danish government including the armed forces. As a consequence Defense Agreement 2010 – 2014 was replaced by Defense Agreement 2013 – 2017 including

  15. Atomic Databases

    NASA Astrophysics Data System (ADS)

    Mendoza, Claudio

    2000-10-01

    Atomic and molecular data are required in a variety of fields ranging from the traditional astronomy, atmospherics and fusion research to fast growing technologies such as lasers, lighting, low-temperature plasmas, plasma assisted etching and radiotherapy. In this context, there are some research groups, both theoretical and experimental, scattered round the world that attend to most of this data demand, but the implementation of atomic databases has grown independently out of sheer necessity. In some cases the latter has been associated with the data production process or with data centers involved in data collection and evaluation; but sometimes it has been the result of individual initiatives that have been quite successful. In any case, the development and maintenance of atomic databases call for a number of skills and an entrepreneurial spirit that are not usually associated with most physics researchers. In the present report we present some of the highlights in this area in the past five years and discuss what we think are some of the main issues that have to be addressed.

  16. 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.

  17. The Danish National Registry for Biological Therapy in Inflammatory Bowel Disease

    PubMed Central

    Larsen, Lone; Jensen, Michael Dam; Larsen, Michael Due; Nielsen, Rasmus Gaardskær; Thorsgaard, Niels; Vind, Ida; Wildt, Signe; Kjeldsen, Jens

    2016-01-01

    Aim The aims of The Danish National Registry for Biological Therapy in Inflammatory Bowel Disease are to ensure that biological therapy and the clinical management of patients with inflammatory bowel disease (IBD) receiving biological treatment are in accordance with the national clinical guidelines and, second, the database allows register-based clinical epidemiological research. Study population The study population comprises all Danish patients with IBD (both children and adults) with ulcerative colitis, Crohn’s disease, and IBD unclassified who receive biological therapy. Patients will be enrolled consecutively when biological treatment is initiated. Main variables The variables in the database are: diagnosis, time of diagnosis, disease manifestation, indication for biological therapy, previous biological and nonbiological therapy, date of visit, clinical indices, physician’s global assessment, pregnancy and breastfeeding (women), height (children), weight, dosage (current biological agent), adverse events, surgery, endoscopic procedures, and radiology. Descriptive data Eleven clinical indicators have been selected to monitor the quality of biological treatment. For each indicator, a standard has been defined based on the available evidence. National results will be published in an annual report and local results on a quarterly basis. The indicators will be reported as department-specific proportions with 95% confidence intervals, and the national average will be provided for comparison. An estimated 1,200–1,300 new biological therapies are initiated each year in Danish patients with IBD. Conclusion The database will be available for research during 2016. Data will be made available by The Danish Clinical Registries (www.rkkp.dk). PMID:27822107

  18. Assessment of the probability of introducing Mycobacterium tuberculosis into Danish cattle herds.

    PubMed

    Foddai, Alessandro; Nielsen, Liza Rosenbaum; Krogh, Kaspar; Alban, Lis

    2015-11-01

    Tuberculosis is a zoonosis caused by Mycobacterium spp. International trade in cattle is regulated with respect to Mycobacterium bovis (M. bovis) but not Mycobacterium tuberculosis (M. tuberculosis), despite that cattle can become infected with both species. In this study we estimated the annual probability (PIntro) of introducing M. tuberculosis into the Danish cattle population, by the import of cattle and/or by immigrants working in Danish cattle herds. Data from 2013 with date, number, and origin of imported live cattle were obtained from the Danish cattle database. Information on immigrants working in Danish cattle herds was obtained through a questionnaire sent to Danish cattle farmers. The gained inputs were fed into three stochastic scenario trees to assess the PIntro for the current and alternative test-and-manage strategies, such as testing of imported animals and/or testing immigrant workers with the tuberculin skin test. We considered the population of Danish farmers and practitioners free of tuberculosis, because in Denmark, the incidence of the disease in humans is low and primarily related to immigrants and socially disadvantaged people. The median annual probability of introducing M. tuberculosis into the Danish cattle population due to imported live cattle was 0.008% (90% P.I.: 0.0007%; 0.03%), while the probability due to immigrant workers was 4.1% (90% P.I.: 0.8%; 12.1%). The median combined probability (PIntro) due to imported cattle plus workers was 4.1% (90% P.I.: 0.8%; 12.6%). Hence, on average at least one introduction each 24 (90% P.I.: 8; 125) years could be expected. Imported live cattle appeared to play a marginal role on the overall annual PIntro, because they represented only approximately 0.2% of the median annual probability. By testing immigrant workers the overall annual PIntro could be reduced to 0.2% (90% P.I.: 0.04%; 0.7%). Thus, testing of immigrant workers could be considered as a risk mitigation strategy to markedly reduce

  19. 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.

  20. The Danish Centre for Strategic Research in Type 2 Diabetes (DD2): organization of diabetes care in Denmark and supplementary data sources for data collection among DD2 study participants.

    PubMed

    Thomsen, Reimar Wernich; Friborg, Søren; Nielsen, Jens Steen; Schroll, Henrik; Johnsen, Søren Paaske

    2012-01-01

    This paper provides a short overview of the Danish health care system and the organization of care for type 2 diabetes patients in Denmark. It also describes the supplementary data sources that are used for collection of baseline data in the nationwide Danish Centre for Strategic Research in Type 2 Diabetes (DD2) Project. The Danish National Health Service provides tax-funded medical care for all 5.6 million Danish residents. The health care system is characterized by extensive individual-level registration of data used for planning, administration, quality improvement, and research. It is estimated that there are currently at least 250,000 individuals with known diabetes in Denmark (approximately 4.5% of the Danish population), of which an estimated 80% are followed and treated by their general practitioners and approximately 20% are followed at hospital specialist outpatient clinics. These health care providers form the basis for recruiting diabetes patients in the DD2 project, and the data sources that these providers use in clinical practice give access to important supplementary patient data. The DD2's patient-enrollment system is designed to be fast and simple, and thus only collects primary interview data that cannot be extracted from already existing data sources. Thus, in addition to an online DD2 questionnaire filled out by general practitioners and hospital physicians at the time of patient enrollment, supplementary data are obtained from the Danish Diabetes Database for Adults, a nationwide clinical quality improvement registry. Both hospital physicians and a growing number of general practitioners routinely report data to this database. For general practitioners, the Danish General Practice Database acts as an important feeder database for the Danish Diabetes Database for Adults and thereby also for the DD2 project.

  1. Monitoring of equine health in Denmark: the importance, purpose, research areas and content of a future database.

    PubMed

    Hartig, Wendy; Houe, Hans; Andersen, Pia Haubro

    2013-04-01

    The plentiful data on Danish horses are currently neither organized nor easily accessible, impeding register-based epidemiological studies on Danish horses. A common database could be beneficial. In principle, databases can contain a wealth of information, but no single database can serve every purpose. Hence the establishment of a Danish equine health database should be preceded by careful consideration of its purpose and content, and stakeholder attitudes should be investigated. The objectives of the present study were to identify stakeholder attitudes to the importance, purpose, research areas and content of a health database for horses in Denmark. A cross-sectional study was conducted with 13 horse-related stakeholder groups in Denmark. The groups surveyed included equine veterinarians, researchers, veterinary students, representatives from animal welfare organizations, horse owners, trainers, farriers, authority representatives, ordinary citizens, and representatives from laboratories, insurance companies, medical equipment companies and pharmaceutical companies. Supplementary attitudes were inferred from qualitative responses. The overall response rate for all stakeholder groups was 45%. Stakeholder group-specific response rates were 27-80%. Sixty-eight percent of questionnaire respondents thought a national equine health database was important. Most respondents wanted the database to contribute to improved horse health and welfare, to be used for research into durability and disease heritability, and to serve as a basis for health declarations for individual horses. The generally preferred purpose of the database was thus that it should focus on horse health and welfare rather than on performance or food safety, and that it should be able to function both at a population and an individual horse level. In conclusion, there is a positive attitude to the establishment of a health database for Danish horses. These results could enrich further reflection on the

  2. 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

  3. Differentiation of AmpC beta-lactamase binders vs. decoys using classification kNN QSAR modeling and application of the QSAR classifier to virtual screening

    NASA Astrophysics Data System (ADS)

    Hsieh, Jui-Hua; Wang, Xiang S.; Teotico, Denise; Golbraikh, Alexander; Tropsha, Alexander

    2008-09-01

    The use of inaccurate scoring functions in docking algorithms may result in the selection of compounds with high predicted binding affinity that nevertheless are known experimentally not to bind to the target receptor. Such falsely predicted binders have been termed `binding decoys'. We posed a question as to whether true binders and decoys could be distinguished based only on their structural chemical descriptors using approaches commonly used in ligand based drug design. We have applied the k-Nearest Neighbor ( kNN) classification QSAR approach to a dataset of compounds characterized as binders or binding decoys of AmpC beta-lactamase. Models were subjected to rigorous internal and external validation as part of our standard workflow and a special QSAR modeling scheme was employed that took into account the imbalanced ratio of inhibitors to non-binders (1:4) in this dataset. 342 predictive models were obtained with correct classification rate (CCR) for both training and test sets as high as 0.90 or higher. The prediction accuracy was as high as 100% (CCR = 1.00) for the external validation set composed of 10 compounds (5 true binders and 5 decoys) selected randomly from the original dataset. For an additional external set of 50 known non-binders, we have achieved the CCR of 0.87 using very conservative model applicability domain threshold. The validated binary kNN QSAR models were further employed for mining the NCGC AmpC screening dataset (69653 compounds). The consensus prediction of 64 compounds identified as screening hits in the AmpC PubChem assay disagreed with their annotation in PubChem but was in agreement with the results of secondary assays. At the same time, 15 compounds were identified as potential binders contrary to their annotation in PubChem. Five of them were tested experimentally and showed inhibitory activities in millimolar range with the highest binding constant Ki of 135 μM. Our studies suggest that validated QSAR models could complement

  4. Approaches for externally validated QSAR modelling of Nitrated Polycyclic Aromatic Hydrocarbon mutagenicity.

    PubMed

    Gramatica, P; Pilutti, P; Papa, E

    2007-01-01

    Nitrated Polycyclic Aromatic Hydrocarbons (nitro-PAHs), ubiquitous environmental pollutants, are recognized mutagens and carcinogens. A set of mutagenicity data (TA100) for 48 nitro-PAHs was modeled by the Quantitative Structure-Activity Relationships (QSAR) regression method, and OECD principles for QSAR model validation were applied. The proposed Multiple Linear Regression (MLR) models are based on two topological molecular descriptors. The models were validated for predictivity by both internal and external validation. For the external validation, three different splitting approaches, D-optimal Experimental Design, Self Organizing Maps (SOM) and Random Selection by activity sampling, were applied to the original data set in order to compare these methodologies and to select the best descriptors able to model each prediction set chemicals independently of the splitting method applied. The applicability domain was verified by the leverage approach.

  5. Towards understanding mechanisms governing cytotoxicity of metal oxides nanoparticles: hints from nano-QSAR studies.

    PubMed

    Gajewicz, Agnieszka; Schaeublin, Nicole; Rasulev, Bakhtiyor; Hussain, Saber; Leszczynska, Danuta; Puzyn, Tomasz; Leszczynski, Jerzy

    2015-05-01

    The production of nanomaterials increases every year exponentially and therefore the probability these novel materials that they could cause adverse outcomes for human health and the environment also expands rapidly. We proposed two types of mechanisms of toxic action that are collectively applied in a nano-QSAR model, which provides governance over the toxicity of metal oxide nanoparticles to the human keratinocyte cell line (HaCaT). The combined experimental-theoretical studies allowed the development of an interpretative nano-QSAR model describing the toxicity of 18 nano-metal oxides to the HaCaT cell line, which is a common in vitro model for keratinocyte response during toxic dermal exposure. The comparison of the toxicity of metal oxide nanoparticles to bacteria Escherichia coli (prokaryotic system) and a human keratinocyte cell line (eukaryotic system), resulted in the hypothesis that different modes of toxic action occur between prokaryotic and eukaryotic systems.

  6. Systemic QSAR and phenotypic virtual screening: chasing butterflies in drug discovery.

    PubMed

    Cruz-Monteagudo, Maykel; Schürer, Stephan; Tejera, Eduardo; Pérez-Castillo, Yunierkis; Medina-Franco, José L; Sánchez-Rodríguez, Aminael; Borges, Fernanda

    2017-03-06

    Current advances in systems biology suggest a new change of paradigm reinforcing the holistic nature of the drug discovery process. According to the principles of systems biology, a simple drug perturbing a network of targets can trigger complex reactions. Therefore, it is possible to connect initial events with final outcomes and consequently prioritize those events, leading to a desired effect. Here, we introduce a new concept, 'Systemic Chemogenomics/Quantitative Structure-Activity Relationship (QSAR)'. To elaborate on the concept, relevant information surrounding it is addressed. The concept is challenged by implementing a systemic QSAR approach for phenotypic virtual screening (VS) of candidate ligands acting as neuroprotective agents in Parkinson's disease (PD). The results support the suitability of the approach for the phenotypic prioritization of drug candidates.

  7. Automatic QSAR modeling of ADME properties: blood-brain barrier penetration and aqueous solubility.

    PubMed

    Obrezanova, Olga; Gola, Joelle M R; Champness, Edmund J; Segall, Matthew D

    2008-01-01

    In this article, we present an automatic model generation process for building QSAR models using Gaussian Processes, a powerful machine learning modeling method. We describe the stages of the process that ensure models are built and validated within a rigorous framework: descriptor calculation, splitting data into training, validation and test sets, descriptor filtering, application of modeling techniques and selection of the best model. We apply this automatic process to data sets of blood-brain barrier penetration and aqueous solubility and compare the resulting automatically generated models with 'manually' built models using external test sets. The results demonstrate the effectiveness of the automatic model generation process for two types of data sets commonly encountered in building ADME QSAR models, a small set of in vivo data and a large set of physico-chemical data.

  8. Three-dimensional QSAR analysis and design of new 1,2,4-oxadiazole antibacterials.

    PubMed

    Leemans, Erika; Mahasenan, Kiran V; Kumarasiri, Malika; Spink, Edward; Ding, Derong; O'Daniel, Peter I; Boudreau, Marc A; Lastochkin, Elena; Testero, Sebastian A; Yamaguchi, Takao; Lee, Mijoon; Hesek, Dusan; Fisher, Jed F; Chang, Mayland; Mobashery, Shahriar

    2016-02-01

    The oxadiazole antibacterials, a class of newly discovered compounds that are active against Gram-positive bacteria, target bacterial cell-wall biosynthesis by inhibition of a family of essential enzymes, the penicillin-binding proteins. Ligand-based 3D-QSAR analyses by comparative molecular field analysis (CoMFA), comparative molecular shape indices analysis (CoMSIA) and Field-Based 3D-QSAR evaluated a series of 102 members of this class. This series included inactive compounds as well as compounds that were moderately to strongly antibacterial against Staphylococcus aureus. Multiple models were constructed using different types of energy minimization and charge calculations. CoMFA derived contour maps successfully defined favored and disfavored regions of the molecules in terms of steric and electrostatic properties for substitution.

  9. Automatic QSAR modeling of ADME properties: blood brain barrier penetration and aqueous solubility

    NASA Astrophysics Data System (ADS)

    Obrezanova, Olga; Gola, Joelle M. R.; Champness, Edmund J.; Segall, Matthew D.

    2008-06-01

    In this article, we present an automatic model generation process for building QSAR models using Gaussian Processes, a powerful machine learning modeling method. We describe the stages of the process that ensure models are built and validated within a rigorous framework: descriptor calculation, splitting data into training, validation and test sets, descriptor filtering, application of modeling techniques and selection of the best model. We apply this automatic process to data sets of blood-brain barrier penetration and aqueous solubility and compare the resulting automatically generated models with `manually' built models using external test sets. The results demonstrate the effectiveness of the automatic model generation process for two types of data sets commonly encountered in building ADME QSAR models, a small set of in vivo data and a large set of physico-chemical data.

  10. 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.

  11. Does rational selection of training and test sets improve the outcome of QSAR modeling?

    PubMed

    Martin, Todd M; Harten, Paul; Young, Douglas M; Muratov, Eugene N; Golbraikh, Alexander; Zhu, Hao; Tropsha, Alexander

    2012-10-22

    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 data set, the best way to validate the predictive ability of a model is to perform its statistical external validation. In statistical external validation, the overall data set is divided into training and test sets. Commonly, this splitting is performed using random division. Rational splitting methods can divide data sets into training and test sets in an intelligent fashion. The purpose of this study was to determine whether rational division methods lead to more predictive models compared to random division. A special data splitting procedure was used to facilitate the comparison between random and rational division methods. For each toxicity end point, the overall data set was divided into a modeling set (80% of the overall set) and an external evaluation set (20% of the overall set) using random division. The modeling set was then subdivided into a training set (80% of the modeling set) and a test set (20% of the modeling set) using rational division methods and by using random division. The Kennard-Stone, minimal test set dissimilarity, and sphere exclusion algorithms were used as the rational division methods. The hierarchical clustering, random forest, and k-nearest neighbor (kNN) methods were used to develop QSAR models based on the training sets. For kNN QSAR, multiple training and test sets were generated, and multiple QSAR models were built. The results of this study indicate that models based on rational division methods generate better statistical results for the test sets than models based on random division, but the predictive power of both types of models are comparable.

  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.

  13. 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.

  14. 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.

  15. Molecular modeling of histamine H3 receptor and QSAR studies on arylbenzofuran derived H3 antagonists.

    PubMed

    Dastmalchi, Siavoush; Hamzeh-Mivehroud, Maryam; Ghafourian, Taravat; Hamzeiy, Hossain

    2008-01-01

    Histamine H3 receptors are presynaptic autoreceptors found in both central and peripheral nervous systems of many species. The central effects of these receptors suggest a potential therapeutic role for their antagonists in treatment of several neurological disorders such as epilepsy, schizophrenia, Alzheimer's and Parkinson's diseases. The purpose of this study was to identify the structural requirements for H3 antagonistic activity via quantitative structure-activity relationship (QSAR) studies and receptor modeling/docking techniques. A combination of partial least squares (PLS) and genetic algorithm (GA) was used in the QSAR approach to select the structural descriptors relevant to the receptor binding affinity of a series of 58 H3 antagonists. The descriptors were selected out of a pool of >1000 descriptors calculated by DRAGON, Hyperchem and ACD labs suite of programs. The resulting QSAR models for rat and human H3 binding affinities were validated using different strategies. QSAR models generated in the current work suggested the role of charge transfer interactions in the ligand-receptor interaction verified using the molecular modeling of the receptor and docking two antagonists to the binding site. The 3D model of human H3 receptor was built based on bovine rhodopsin structure and evaluated by molecular dynamics (MD) simulation in a mixed water-vacuum-water environment. The results were indicative of the stability of the model relating the observed structural changes during the MD simulation to the suggested ligand-receptor interactions. The results of this investigation are expected to be useful in the process of design and development of new potent H3 receptor antagonists.

  16. Validation of Quantitative Structure-Activity Relationship (QSAR) Model for Photosensitizer Activity Prediction

    PubMed Central

    Frimayanti, Neni; Yam, Mun Li; Lee, Hong Boon; Othman, Rozana; Zain, Sharifuddin M.; Rahman, Noorsaadah Abd.

    2011-01-01

    Photodynamic therapy is a relatively new treatment method for cancer which utilizes a combination of oxygen, a photosensitizer and light to generate reactive singlet oxygen that eradicates tumors via direct cell-killing, vasculature damage and engagement of the immune system. Most of photosensitizers that are in clinical and pre-clinical assessments, or those that are already approved for clinical use, are mainly based on cyclic tetrapyrroles. In an attempt to discover new effective photosensitizers, we report the use of the quantitative structure-activity relationship (QSAR) method to develop a model that could correlate the structural features of cyclic tetrapyrrole-based compounds with their photodynamic therapy (PDT) activity. In this study, a set of 36 porphyrin derivatives was used in the model development where 24 of these compounds were in the training set and the remaining 12 compounds were in the test set. The development of the QSAR model involved the use of the multiple linear regression analysis (MLRA) method. Based on the method, r2 value, r2 (CV) value and r2 prediction value of 0.87, 0.71 and 0.70 were obtained. The QSAR model was also employed to predict the experimental compounds in an external test set. This external test set comprises 20 porphyrin-based compounds with experimental IC50 values ranging from 0.39 μM to 7.04 μM. Thus the model showed good correlative and predictive ability, with a predictive correlation coefficient (r2 prediction for external test set) of 0.52. The developed QSAR model was used to discover some compounds as new lead photosensitizers from this external test set. PMID:22272096

  17. 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

  18. 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

  19. QSAR-assisted virtual screening of lead-like molecules from marine and microbial natural sources for antitumor and antibiotic drug discovery.

    PubMed

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

    2015-03-17

    A Quantitative Structure-Activity Relationship (QSAR) approach for classification was used for the prediction of compounds as active/inactive relatively to overall biological activity, antitumor and antibiotic activities using a data set of 1746 compounds from PubChem with empirical CDK descriptors and semi-empirical quantum-chemical descriptors. A data set of 183 active pharmaceutical ingredients was additionally used for the external validation of the best models. The best classification models for antibiotic and antitumor activities were used to screen a data set of marine and microbial natural products from the AntiMarin database-25 and four lead compounds for antibiotic and antitumor drug design were proposed, respectively. The present work enables the presentation of a new set of possible lead like bioactive compounds and corroborates the results of our previous investigations. By other side it is shown the usefulness of quantum-chemical descriptors in the discrimination of biologically active and inactive compounds. None of the compounds suggested by our approach have assigned non-antibiotic and non-antitumor activities in the AntiMarin database and almost all were lately reported as being active in the literature.

  20. Understanding hERG inhibition with QSAR models based on a one-dimensional molecular representation

    NASA Astrophysics Data System (ADS)

    Diller, David J.; Hobbs, Doug W.

    2007-07-01

    Blockage of the potassium channel encoded by the human ether-a-go-go related gene (hERG) is well understood to be the root cause of the cardio-toxicity of numerous approved and investigational drugs. As such, a cascade of in vitro and in vivo assays have been developed to filter compounds with hERG inhibitory activity. Quantitative structure activity relationship (QSAR) models are used at the very earliest part of this cascade to eliminate compounds that are likely to have this undesirable activity prior to synthesis. Here a new QSAR technique based on the one-dimensional representation is described in the context of the development of a model to predict hERG inhibition. The model is shown to perform close to the limits of the quality of the data used for model building. In order to make optimal use of the available data, a general robust mathematical scheme was developed and is described to simultaneously incorporate quantitative data, such as IC50 = 50 nM, and qualitative data, such as inactive or IC50 > 30 μM into QSAR models without discarding any experimental information.

  1. QSAR: an in silico approach for predicting the partitioning of pesticides into breast milk.

    PubMed

    Agatonovic-Kustrin, Suezana; Morton, David W; Celebic, D

    2013-03-01

    The aim of this study was to develop an in silico Quantitative Structure Activity Relationship (QSAR) model capable of predicting partitioning of pesticides into breast milk from their respective chemical structures. A large data set of 190 diverse compounds, including drugs and their active metabolites (87%), and pesticides (13%) with experimentally derived milk/plasma (M/P) ratios taken from the literature, was used to train, test and validate a predictive model. Each compound was encoded with 65 calculated chemical structure descriptors. Sensitivity analysis was then used to select a subset of the descriptors that best describe the transfer of pesticides into breast milk and Artificial neural networks modeling was applied to correlate selected descriptors (inputs) with the M/P ratio (output) in order to develop a predictive QSAR. The developed QSAR model included 26 molecular descriptors related to the molecular size, polarity and hydrogen binding capacity. Together with aromatic rings, these descriptors account for molecule's size and hydrophobic interaction capabilities. The average correlation for the final model (incorporating training, testing, and validation) was 0.85. The developed model provides a useful method for predicting the M/P ratios of pesticides from just a sketch of their respective molecular structures. However, these predictions should only be used to assist in the evaluation of risk in conjunction with an assessment of the infant's response to a given drug/pesticide.

  2. QSAR prediction of the competitive interaction of emerging halogenated pollutants with human transthyretin.

    PubMed

    Papa, E; Kovarich, S; Gramatica, P

    2013-01-01

    The determination of the potential endocrine disruption (ED) activity of chemicals such as poly/perfluorinated compounds (PFCs) and brominated flame retardants (BFRs) is still hindered by a limited availability of experimental data. Quantitative structure-activity relationship (QSAR) strategies can be applied to fill this data gap, help in the characterization of the ED potential, and screen PFCs and BFRs with a hazardous toxicological profile. This paper proposes the modelling of T4-TTR (thyroxin-transthyretin) competing potency and relative binding potency toward T4 (logT4-REP) of PFCs and BFRs by regression and classification QSAR models. This study is a follow up of a former work, which analysed separately the interaction of BFRs and PFCs with the carrier TTR. The new results demonstrate the possibility of developing robust and predictive QSARs, which include both BFRs and PFCs in the training set, obtaining larger applicability domains than the existing models developed separately for BFRs and PFCs. The selection of modelling molecular descriptors confirms the importance of structural features, such as the aromatic OH or the molecular length, to increase the binding of the studied chemicals to TTR. Additionally, the need of experimental tests for some chemicals, and in particular for some of the BFRs, is highlighted.

  3. QSAR modeling and prediction of the endocrine-disrupting potencies of brominated flame retardants.

    PubMed

    Papa, Ester; Kovarich, Simona; Gramatica, Paola

    2010-05-17

    In the European Union REACH regulation, the chemicals with particularly harmful behaviors, such as endocrine disruptors (EDs), are subject to authorization, and the identification of safer alternatives to these chemicals is required. In this context, the use of quantitative structure-activity relationships (QSAR) becomes particularly useful to fill the data gap due to the very small number of experimental data available to characterize the environmental and toxicological profiles of new and emerging pollutants with ED behavior such as brominated flame retardants (BFRs). In this study, different QSAR models were developed on different responses of endocrine disruption measured for several BFRs. The multiple linear regression approach was applied to a variety of theoretical molecular descriptors, and the best models, which were identified from all of the possible combinations of the structural variables, were internally validated for their performance using the leave-one-out (Q(LOO)(2) = 73-91%) procedure and scrambling of the responses. External validation was provided, when possible, by splitting the data sets in training and test sets (range of Q(EXT)(2) = 76-90%), which confirmed the predictive ability of the proposed equations. These models, which were developed according to the principles defined by the Organization for Economic Co-operation and Development to improve the regulatory acceptance of QSARs, represent a simple tool for the screening and characterization of BFRs.

  4. QSAR classification models for the prediction of endocrine disrupting activity of brominated flame retardants.

    PubMed

    Kovarich, Simona; Papa, Ester; Gramatica, Paola

    2011-06-15

    The identification of potential endocrine disrupting (ED) chemicals is an important task for the scientific community due to their diffusion in the environment; the production and use of such compounds will be strictly regulated through the authorization process of the REACH regulation. To overcome the problem of insufficient experimental data, the quantitative structure-activity relationship (QSAR) approach is applied to predict the ED activity of new chemicals. In the present study QSAR classification models are developed, according to the OECD principles, to predict the ED potency for a class of emerging ubiquitary pollutants, viz. brominated flame retardants (BFRs). Different endpoints related to ED activity (i.e. aryl hydrocarbon receptor agonism and antagonism, estrogen receptor agonism and antagonism, androgen and progesterone receptor antagonism, T4-TTR competition, E2SULT inhibition) are modeled using the k-NN classification method. The best models are selected by maximizing the sensitivity and external predictive ability. We propose simple QSARs (based on few descriptors) characterized by internal stability, good predictive power and with a verified applicability domain. These models are simple tools that are applicable to screen BFRs in relation to their ED activity, and also to design safer alternatives, in agreement with the requirements of REACH regulation at the authorization step.

  5. QSAR model as a random event: A case of rat toxicity.

    PubMed

    Toropova, Alla P; Toropov, Andrey A; Benfenati, Emilio; Leszczynska, Danuta; Leszczynski, Jerzy

    2015-03-15

    Quantitative structure-property/activity relationships (QSPRs/QSARs) can be used to predict physicochemical and/or biochemical behavior of substances which were not studied experimentally. Typically predicted values for chemicals in the training set are accurate since they were used to build the model. QSPR/QSAR models must be validated before they are used in practice. Unfortunately, the majority of the suggested approaches of the validation of QSPR/QSAR models are based on consideration of geometrical features of clusters of data points in the plot of experimental versus calculated values of an endpoint. We believe these geometrical criteria can be more useful if they are analyzed for several splits into the training and test sets. In this way, one can estimate the reproducibility of the model with various splits and better evaluate model reliability. The probability of the correct prediction of an endpoint for external validation set (in the series of the above-mentioned splits) can provide an useful way to evaluate the domain of applicability of the model.

  6. 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

  7. Development of biologically active compounds by combining 3D QSAR and structure-based design methods

    NASA Astrophysics Data System (ADS)

    Sippl, Wolfgang

    2002-11-01

    One of the major challenges in computational approaches to drug design is the accurate prediction of the binding affinity of novel biomolecules. In the present study an automated procedure which combines docking and 3D-QSAR methods was applied to several drug targets. The developed receptor-based 3D-QSAR methodology was tested on several sets of ligands for which the three-dimensional structure of the target protein has been solved - namely estrogen receptor, acetylcholine esterase and protein-tyrosine-phosphatase 1B. The molecular alignments of the studied ligands were determined using the docking program AutoDock and were compared with the X-ray structures of the corresponding protein-ligand complexes. The automatically generated protein-based ligand alignment obtained was subsequently taken as basis for a comparative field analysis applying the GRID/GOLPE approach. Using GRID interaction fields and applying variable selection procedures, highly predictive models were obtained. It is expected that concepts from receptor-based 3D QSAR will be valuable tools for the analysis of high-throughput screening as well as virtual screening data

  8. Blood-brain barrier permeability mechanisms in view of quantitative structure-activity relationships (QSAR).

    PubMed

    Bujak, Renata; Struck-Lewicka, Wiktoria; Kaliszan, Michał; Kaliszan, Roman; Markuszewski, Michał J

    2015-04-10

    The goal of the present paper was to develop a quantitative structure-activity relationship (QSAR) method using a simple statistical approach, such as multiple linear regression (MLR) for predicting the blood-brain barrier (BBB) permeability of chemical compounds. The "best" MLR models, comprised logP and either molecular mass (M) or isolated atomic energy (E(isol)), tested on a structurally diverse set of 66 compounds, is characterized the by correlation coefficients (R) around 0.8. The obtained models were validated using leave-one-out (LOO) cross-validation technique and the correlation coefficient of leave-one-out- R(LOO)(2) (Q(2)) was at least 0.6. Analysis of a case from legal medicine demonstrated informative value of our QSAR model. To best authors' knowledge the present study is a first application of the developed QSAR models of BBB permeability to case from the legal medicine. Our data indicate that molecular energy-related descriptors, in combination with the well-known descriptors of lipophilicity may have a supportive value in predicting blood-brain distribution, which is of utmost importance in drug development and toxicological studies.

  9. Fragment-based strategy for structural optimization in combination with 3D-QSAR.

    PubMed

    Yuan, Haoliang; Tai, Wenting; Hu, Shihe; Liu, Haichun; Zhang, Yanmin; Yao, Sihui; Ran, Ting; Lu, Shuai; Ke, Zhipeng; Xiong, Xiao; Xu, Jinxing; Chen, Yadong; Lu, Tao

    2013-10-01

    Fragment-based drug design has emerged as an important methodology for lead discovery and drug design. Different with other studies focused on fragment library design and active fragment identification, a fragment-based strategy was developed in combination with three-dimensional quantitative structure-activity relationship (3D-QSAR) for structural optimization in this study. Based on a validated scaffold or fragment hit, a series of structural optimization was conducted to convert it to lead compounds, including 3D-QSAR modelling, active site analysis, fragment-based structural optimization and evaluation of new molecules. 3D-QSAR models and active site analysis provided sufficient information for confirming the SAR and pharmacophoric features for fragments. This strategy was evaluated through the structural optimization on a c-Met inhibitor scaffold 5H-benzo[4,5]cyclohepta[1,2-b]pyridin-5-one, which resulted in an c-Met inhibitor with high inhibitory activity. Our study suggested the effectiveness of this fragment-based strategy and the druggability of our newly explored active region. The reliability of this strategy indicated it could also be applied to facilitate lead optimization of other targets.

  10. 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.

  11. QSAR modeling of a set of pyrazinoate esters as antituberculosis prodrugs.

    PubMed

    Fernandes, João P S; Pasqualoto, Kerly F M; Felli, Veni M A; Ferreira, Elizabeth I; Brandt, Carlos A

    2010-02-01

    Tuberculosis is an infection caused mainly by Mycobacterium tuberculosis. A first-line antimycobacterial drug is pyrazinamide (PZA), which acts partially as a prodrug activated by a pyrazinamidase releasing the active agent, pyrazinoic acid (POA). As pyrazinoic acid presents some difficulty to cross the mycobacterial cell wall, and also the pyrazinamide-resistant strains do not express the pyrazinamidase, a set of pyrazinoic acid esters have been evaluated as antimycobacterial agents. In this work, a QSAR approach was applied to a set of forty-three pyrazinoates against M. tuberculosis ATCC 27294, using genetic algorithm function and partial least squares regression (WOLF 5.5 program). The independent variables selected were the Balaban index (J), calculated n-octanol/water partition coefficient (ClogP), van-der-Waals surface area, dipole moment, and stretching-energy contribution. The final QSAR model (N = 32, r(2) = 0.68, q(2) = 0.59, LOF = 0.25, and LSE = 0.19) was fully validated employing leave-N-out cross-validation and y-scrambling techniques. The test set (N = 11) presented an external prediction power of 73%. In conclusion, the QSAR model generated can be used as a valuable tool to optimize the activity of future pyrazinoic acid esters in the designing of new antituberculosis agents.

  12. 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

  13. QSAR studies, synthesis and antibacterial assessment of new inhibitors against multidrug-resistant Mycobacterium tuberculosis.

    PubMed

    Kovalishyn, Vasyl; Brovarets, Volodymyr; Blagodatnyi, Volodymyr; Kopernyk, Iryna; Hodyna, Diana; Chumachenko, Svitlana; Shablykin, Oleg; Kozachenko, Oleksandr; Vovk, Myhailo; Barus, Marianna; Bratenko, Myhailo; Metelytsia, Larysa

    2016-11-08

    This paper describes Quantitative Structure-Activity Relationships (QSAR) studies using Artificial Neural Networks (ANN), synthesis and in vitro antitubercular activity of several potent compounds against H37Rv and resistant Mycobacterium tuberculosis (Mtb) strains. Eight QSAR models were built using various types of descriptors with four publicly available structurally diverse datasets, including recent data from PubChem and ChEMBL. The predictive power of the obtained QSAR models was evaluated with a cross-validation procedure, giving a q2=0.74-0.78 for regression models and overall accuracy 78.9-94.4% for classification models. The external test sets were predicted with accuracies in the range of 84.1-95.0% (for the active/inactive classifications) and q2=0.80-0.83 for regressions. The 15 synthesized compounds showed inhibitory activity against H37Rv strain whereas the compounds 1-7 were also active against resistant Mtb strain (resistant to isoniazid and rifampicin). The results indicated that compounds 1-7 could serve as promising leads for further optimization as novel antibacterial inhibitors, in particular, for the treatment of drug resistance of Mtb forms.

  14. 3D-QSAR and molecular docking studies on HIV protease inhibitors

    NASA Astrophysics Data System (ADS)

    Tong, Jianbo; Wu, Yingji; Bai, Min; Zhan, Pei

    2017-02-01

    In order to well understand the chemical-biological interactions governing their activities toward HIV protease activity, QSAR models of 34 cyclic-urea derivatives with inhibitory HIV were developed. The quantitative structure activity relationship (QSAR) model was built by using comparative molecular similarity indices analysis (CoMSIA) technique. And the best CoMSIA model has rcv2, rncv2 values of 0.586 and 0.931 for cross-validated and non-cross-validated. The predictive ability of CoMSIA model was further validated by a test set of 7 compounds, giving rpred2 value of 0.973. Docking studies were used to find the actual conformations of chemicals in active site of HIV protease, as well as the binding mode pattern to the binding site in protease enzyme. The information provided by 3D-QSAR model and molecular docking may lead to a better understanding of the structural requirements of 34 cyclic-urea derivatives and help to design potential anti-HIV protease molecules.

  15. Application of quantitative structure activity relationship (QSAR) models to predict ozone toxicity in the lung.

    PubMed

    Kafoury, Ramzi M; Huang, Ming-Ju

    2005-08-01

    The sequence of events leading to ozone-induced airway inflammation is not well known. To elucidate the molecular and cellular events underlying ozone toxicity in the lung, we hypothesized that lipid ozonation products (LOPs) generated by the reaction of ozone with unsaturated fatty acids in the epithelial lining fluid and cell membranes play a key role in mediating ozone-induced airway inflammation. To test our hypothesis, we ozonized 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylcholine (POPC) and generated LOPs. Confluent human bronchial epithelial cells were exposed to the derivatives of ozonized POPC-9-oxononanoyl, 9-hydroxy-9-hydroperoxynonanoyl, and 8-(5-octyl-1,2,4-trioxolan-3-yl-)octanoyl-at a concentration of 10 muM, and the activity of phospholipases A2 (PLA2), C (PLC), and D (PLD) was measured (1, 0.5, and 1 h, respectively). Quantitative structure-activity relationship (QSAR) models were utilized to predict the biological activity of LOPs in airway epithelial cells. The QSAR results showed a strong correlation between experimental and computed activity (r = 0.97, 0.98, 0.99, for PLA2, PLC, and PLD, respectively). The results indicate that QSAR models can be utilized to predict the biological activity of the various ozone-derived LOP species in the lung.

  16. Fragment-based strategy for structural optimization in combination with 3D-QSAR

    NASA Astrophysics Data System (ADS)

    Yuan, Haoliang; Tai, Wenting; Hu, Shihe; Liu, Haichun; Zhang, Yanmin; Yao, Sihui; Ran, Ting; Lu, Shuai; Ke, Zhipeng; Xiong, Xiao; Xu, Jinxing; Chen, Yadong; Lu, Tao

    2013-10-01

    Fragment-based drug design has emerged as an important methodology for lead discovery and drug design. Different with other studies focused on fragment library design and active fragment identification, a fragment-based strategy was developed in combination with three-dimensional quantitative structure-activity relationship (3D-QSAR) for structural optimization in this study. Based on a validated scaffold or fragment hit, a series of structural optimization was conducted to convert it to lead compounds, including 3D-QSAR modelling, active site analysis, fragment-based structural optimization and evaluation of new molecules. 3D-QSAR models and active site analysis provided sufficient information for confirming the SAR and pharmacophoric features for fragments. This strategy was evaluated through the structural optimization on a c-Met inhibitor scaffold 5H-benzo[4,5]cyclohepta[1,2-b]pyridin-5-one, which resulted in an c-Met inhibitor with high inhibitory activity. Our study suggested the effectiveness of this fragment-based strategy and the druggability of our newly explored active region. The reliability of this strategy indicated it could also be applied to facilitate lead optimization of other targets.

  17. QSAR modeling and chemical space analysis of antimalarial compounds.

    PubMed

    Sidorov, Pavel; Viira, Birgit; Davioud-Charvet, Elisabeth; Maran, Uko; Marcou, Gilles; Horvath, Dragos; Varnek, Alexandre

    2017-04-03

    Generative topographic mapping (GTM) has been used to visualize and analyze the chemical space of antimalarial compounds as well as to build predictive models linking structure of molecules with their antimalarial activity. For this, a database, including ~3000 molecules tested in one or several of 17 anti-Plasmodium activity assessment protocols, has been compiled by assembling experimental data from in-house and ChEMBL databases. GTM classification models built on subsets corresponding to individual bioassays perform similarly to the earlier reported SVM models. Zones preferentially populated by active and inactive molecules, respectively, clearly emerge in the class landscapes supported by the GTM model. Their analysis resulted in identification of privileged structural motifs of potential antimalarial compounds. Projection of marketed antimalarial drugs on this map allowed us to delineate several areas in the chemical space corresponding to different mechanisms of antimalarial activity. This helped us to make a suggestion about the mode of action of the molecules populating these zones.

  18. 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…

  19. Integrated QSAR study for inhibitors of hedgehog signal pathway against multiple cell lines:a collaborative filtering method

    PubMed Central

    2012-01-01

    Background The Hedgehog Signaling Pathway is one of signaling pathways that are very important to embryonic development. The participation of inhibitors in the Hedgehog Signal Pathway can control cell growth and death, and searching novel inhibitors to the functioning of the pathway are in a great demand. As the matter of fact, effective inhibitors could provide efficient therapies for a wide range of malignancies, and targeting such pathway in cells represents a promising new paradigm for cell growth and death control. Current research mainly focuses on the syntheses of the inhibitors of cyclopamine derivatives, which bind specifically to the Smo protein, and can be used for cancer therapy. While quantitatively structure-activity relationship (QSAR) studies have been performed for these compounds among different cell lines, none of them have achieved acceptable results in the prediction of activity values of new compounds. In this study, we proposed a novel collaborative QSAR model for inhibitors of the Hedgehog Signaling Pathway by integration the information from multiple cell lines. Such a model is expected to substantially improve the QSAR ability from single cell lines, and provide useful clues in developing clinically effective inhibitors and modifications of parent lead compounds for target on the Hedgehog Signaling Pathway. Results In this study, we have presented: (1) a collaborative QSAR model, which is used to integrate information among multiple cell lines to boost the QSAR results, rather than only a single cell line QSAR modeling. Our experiments have shown that the performance of our model is significantly better than single cell line QSAR methods; and (2) an efficient feature selection strategy under such collaborative environment, which can derive the commonly important features related to the entire given cell lines, while simultaneously showing their specific contributions to a specific cell-line. Based on feature selection results, we have

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

    PubMed

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

    2016-04-07

    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.

  1. Comprehension of drug toxicity: software and databases.

    PubMed

    Toropov, Andrey A; Toropova, Alla P; Raska, Ivan; Leszczynska, Danuta; Leszczynski, Jerzy

    2014-02-01

    Quantitative structure-property/activity relationships (QSPRs/QSARs) are a tool (in silico) to rapidly predict various endpoints in general, and drug toxicity in particular. However, this dynamic evolution of experimental data (expansion of existing experimental data on drugs toxicity) leads to the problem of critical estimation of the data. The carcinogenicity, mutagenicity, liver effects and cardiac toxicity should be evaluated as the most important aspects of the drug toxicity. The toxicity is a multidimensional phenomenon. It is apparent that the main reasons for the increase in applications of in silico prediction of toxicity include the following: (i) the need to reduce animal testing; (ii) computational models provide reliable toxicity prediction; (iii) development of legislation that is related to use of new substances; (iv) filling data gaps; (v) reduction of cost and time; (vi) designing of new compounds; (vii) advancement of understanding of biology and chemistry. This mini-review provides analysis of existing databases and software which are necessary for use of robust computational assessments and robust prediction of potential drug toxicities by means of in silico methods.

  2. 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.

  3. Aldose reductase inhibitors for diabetic complications: Receptor induced atom-based 3D-QSAR analysis, synthesis and biological evaluation.

    PubMed

    Vyas, Bhawna; Singh, Manjinder; Kaur, Maninder; Bahia, Malkeet Singh; Jaggi, Amteshwar Singh; Silakari, Om; Singh, Baldev

    2015-06-01

    Herein, atom-based 3D-QSAR analysis was performed using receptor-guided alignment of 46 flavonoid inhibitors of aldose reductase (ALR2) enzyme. 3D-QSAR models were generated in PHASE programme, and the best model corresponding to PLS factor four (QSAR4), was selected based on different statistical parameters (i.e., Rtrain(2), 0.96; Qtest(2) 0.81; SD, 0.26). The contour plots of different structural properties generated from the selected model were utilized for the designing of five new congener molecules. These designed molecules were duly synthesized, and evaluated for their in vitro ALR2 inhibitory activity that resulted in the micromolar (IC50<22μM) activity of all molecules. Thus, the newly designed molecules having ALR inhibitory potential could be employed for the management of diabetic complications.

  4. A quantitative structure-activity relationship (QSAR) study of some diaryl urea derivatives of B-RAF inhibitors

    PubMed Central

    Sadeghian-Rizi, Sedighe; Sakhteman, Amirhossein; Hassanzadeh, Farshid

    2016-01-01

    In the current study, both ligand-based molecular docking and receptor-based quantitative structure activity relationships (QSAR) modeling were performed on 35 diaryl urea derivative inhibitors of V600EB-RAF. In this QSAR study, a linear (multiple linear regressions) and a nonlinear (partial least squares least squares support vector machine (PLS-LS-SVM)) were used and compared. The predictive quality of the QSAR models was tested for an external set of 31 compounds, randomly chosen out of 35 compounds. The results revealed the more predictive ability of PLS-LS-SVM in analysis of compounds with urea structure. The selected descriptors indicated that size, degree of branching, aromaticity, and polarizability affected the inhibition activity of these inhibitors. Furthermore, molecular docking was carried out to study the binding mode of the compounds. Docking analysis indicated some essential H-bonding and orientations of the molecules in the active site. PMID:28003837

  5. Consistency of QSAR models: Correct split of training and test sets, ranking of models and performance parameters.

    PubMed

    Rácz, A; Bajusz, D; Héberger, K

    2015-01-01

    Recent implementations of QSAR modelling software provide the user with numerous models and a wealth of information. In this work, we provide some guidance on how one should interpret the results of QSAR modelling, compare and assess the resulting models, and select the best and most consistent ones. Two QSAR datasets are applied as case studies for the comparison of model performance parameters and model selection methods. We demonstrate the capabilities of sum of ranking differences (SRD) in model selection and ranking, and identify the best performance indicators and models. While the exchange of the original training and (external) test sets does not affect the ranking of performance parameters, it provides improved models in certain cases (despite the lower number of molecules in the training set). Performance parameters for external validation are substantially separated from the other merits in SRD analyses, highlighting their value in data fusion.

  6. Synthesis and 3D-QSAR study of 1,4-dihydropyridine derivatives as MDR cancer reverters.

    PubMed

    Radadiya, Ashish; Khedkar, Vijay; Bavishi, Abhay; Vala, Hardevsinh; Thakrar, Shailesh; Bhavsar, Dhairya; Shah, Anamik; Coutinho, Evans

    2014-03-03

    A series of symmetrical and unsymmetrical 1,4-dihydropyridines were synthesized by a rapid, single pot microwave irradiation (MWI) based protocol along with conventional approach and characterized by NMR, IR and mass spectroscopic techniques. The compounds were evaluated for their tumor cell cytotoxicity in HL-60 tumor cells. A 3D-QSAR study using CoMFA and CoMSIA was carried out to decipher the factors governing MDR reversing ability in cancer. The resulting contour maps derived by the best 3D-QSAR models provide a good insight into the molecular features relevant to the biological activity in this series of analogs. 3D contour maps as a result of 3D-QSAR were utilized to identify some novel features that can be incorporated into the 1,4-dihydropyridine framework to enhance the activity.

  7. JICST Factual Database JICST DNA Database

    NASA Astrophysics Data System (ADS)

    Shirokizawa, Yoshiko; Abe, Atsushi

    Japan Information Center of Science and Technology (JICST) has started the on-line service of DNA database in October 1988. This database is composed of EMBL Nucleotide Sequence Library and Genetic Sequence Data Bank. The authors outline the database system, data items and search commands. Examples of retrieval session are presented.

  8. Increasing Staff Mobility--A Danish Initiative.

    ERIC Educational Resources Information Center

    Sorensen, Henning

    1985-01-01

    Recent Danish government proposals to increase the national and international mobility of scientists are reviewed, including a formalized sabbatical system in the universities, new rules for obtaining leaves of absence with or without salary, and plans for increased mobility between public and private sectors. (MSE)

  9. 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?

  10. 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…

  11. 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…

  12. 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.

  13. 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

  14. 3D QSAR studies, pharmacophore modeling, and virtual screening of diarylpyrazole-benzenesulfonamide derivatives as a template to obtain new inhibitors, using human carbonic anhydrase II as a model protein.

    PubMed

    Entezari Heravi, Yeganeh; Sereshti, Hassan; Saboury, Ali Akbar; Ghasemi, Jahan; Amirmostofian, Marzieh; Supuran, Claudiu T

    2017-12-01

    A 3D-QSAR modeling was performed on a series of diarylpyrazole-benzenesulfonamide derivatives acting as inhibitors of the metalloenzyme carbonic anhydrase (CA, EC 4.2.1.1). The compounds were collected from two datasets with the same scaffold, and utilized as a template for a new pharmacophore model to screen the ZINC database of commercially available derivatives. The datasets were divided into training, test, and validation sets. As the first step, comparative molecular field analysis (CoMFA), CoMFA region focusing and comparative molecular similarity indices analysis (CoMSIA) in parallel with docking studies were applied to a set of 41 human (h) CA II inhibitors. The validity and the prediction capacity of the resulting models were evaluated by leave-one-out (LOO) cross-validation approach. The reliability of the model for the prediction of possibly new CA inhibitors was also tested.

  15. The air quality in Danish urban areas.

    PubMed Central

    Jensen, F P; Fenger, J

    1994-01-01

    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

  16. Finding new scaffolds of JAK3 inhibitors in public database: 3D-QSAR models & shape-based screening.

    PubMed

    Gadhe, Changdev G; Lee, Eunhee; Kim, Mi-Hyun

    2015-11-01

    The STAT/JAK3 pathway is a well-known therapeutic target in various diseases (ex. rheumatoid arthritis and psoriasis). The therapeutic advantage of JAK3 inhibition motivated to find new scaffolds with desired DMPK. For the purpose, in silico high-throughput sieves method is developed consisting of a receptor-guided three-dimensional quantitative structure-activity relationship study and shape-based virtual screening. We developed robust and predictive comparative molecular field analysis (q (2) = 0.760, r (2) = 0.915) and comparative molecular similarity index analysis (q (2) = 0.817, r (2) = 0.981) models and validated these using a test set, which produced satisfactory predictions of 0.925 and 0.838, respectively.

  17. Quantitative structure-activity relationships (QSARs) for estrogen binding to the estrogen receptor: predictions across species.

    PubMed Central

    Tong, W; Perkins, R; Strelitz, R; Collantes, E R; Keenan, S; Welsh, W J; Branham, W S; Sheehan, D M

    1997-01-01

    The recognition of adverse effects due to environmental endocrine disruptors in humans and wildlife has focused attention on the need for predictive tools to select the most likely estrogenic chemicals from a very large number of chemicals for subsequent screening and/or testing for potential environmental toxicity. A three-dimensional quantitative structure-activity relationship (QSAR) model using comparative molecular field analysis (CoMFA) was constructed based on relative binding affinity (RBA) data from an estrogen receptor (ER) binding assay using calf uterine cytosol. The model demonstrated significant correlation of the calculated steric and electrostatic fields with RBA and yielded predictions that agreed well with experimental values over the entire range of RBA values. Analysis of the CoMFA three-dimensional contour plots revealed a consistent picture of the structural features that are largely responsible for the observed variations in RBA. Importantly, we established a correlation between the predicted RBA values for calf ER and their actual RBA values for human ER. These findings suggest a means to begin to construct a more comprehensive estrogen knowledge base by combining RBA assay data from multiple species in 3D-QSAR based predictive models, which could then be used to screen untested chemicals for their potential to bind to the ER. Another QSAR model was developed based on classical physicochemical descriptors generated using the CODESSA (Comprehensive Descriptors for Structural and Statistical Analysis) program. The predictive ability of the CoMFA model was superior to the corresponding CODESSA model. Images Figure 2. Figure 3. Figure 4. Figure 5. PMID:9353176

  18. 3D QSAR models built on structure-based alignments of Abl tyrosine kinase inhibitors.

    PubMed

    Falchi, Federico; Manetti, Fabrizio; Carraro, Fabio; Naldini, Antonella; Maga, Giovanni; Crespan, Emmanuele; Schenone, Silvia; Bruno, Olga; Brullo, Chiara; Botta, Maurizio

    2009-06-01

    Quality QSAR: A combination of docking calculations and a statistical approach toward Abl inhibitors resulted in a 3D QSAR model, the analysis of which led to the identification of ligand portions important for affinity. New compounds designed on the basis of the model were found to have very good affinity for the target, providing further validation of the model itself.The X-ray crystallographic coordinates of the Abl tyrosine kinase domain in its active, inactive, and Src-like inactive conformations were used as targets to simulate the binding mode of a large series of pyrazolo[3,4-d]pyrimidines (known Abl inhibitors) by means of GOLD software. Receptor-based alignments provided by molecular docking calculations were submitted to a GRID-GOLPE protocol to generate 3D QSAR models. Analysis of the results showed that the models based on the inactive and Src-like inactive conformations had very poor statistical parameters, whereas the sole model based on the active conformation of Abl was characterized by significant internal and external predictive ability. Subsequent analysis of GOLPE PLS pseudo-coefficient contour plots of this model gave us a better understanding of the relationships between structure and affinity, providing suggestions for the next optimization process. On the basis of these results, new compounds were designed according to the hydrophobic and hydrogen bond donor and acceptor contours, and were found to have improved enzymatic and cellular activity with respect to parent compounds. Additional biological assays confirmed the important role of the selected compounds as inhibitors of cell proliferation in leukemia cells.

  19. 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

  20. QSAR models for prediction of chromatographic behavior of homologous Fab variants.

    PubMed

    Robinson, Julie R; Karkov, Hanne S; Woo, James A; Krogh, Berit O; Cramer, Steven M

    2016-12-12

    While quantitative structure activity relationship (QSAR) models have been employed successfully for the prediction of small model protein chromatographic behavior, there have been few reports to date on the use of this methodology for larger, more complex proteins. Recently our group generated focused libraries of antibody Fab fragment variants with different combinations of surface hydrophobicities and electrostatic potentials, and demonstrated that the unique selectivities of multimodal resins can be exploited to separate these Fab variants. In this work, results from linear salt gradient experiments with these Fabs were employed to develop QSAR models for six chromatographic systems, including multimodal (Capto MMC, Nuvia cPrime, and two novel ligand prototypes), hydrophobic interaction chromatography (HIC; Capto Phenyl), and cation exchange (CEX; CM Sepharose FF) resins. The models utilized newly developed "local descriptors" to quantify changes around point mutations in the Fab libraries as well as novel cluster descriptors recently introduced by our group. Subsequent rounds of feature selection and linearized machine learning algorithms were used to generate robust, well-validated models with high training set correlations (R(2)  > 0.70) that were well suited for predicting elution salt concentrations in the various systems. The developed models then were used to predict the retention of a deamidated Fab and isotype variants, with varying success. The results represent the first successful utilization of QSAR for the prediction of chromatographic behavior of complex proteins such as Fab fragments in multimodal chromatographic systems. The framework presented here can be employed to facilitate process development for the purification of biological products from product-related impurities by in silico screening of resin alternatives. Biotechnol. Bioeng. 2016;9999: 1-10. © 2016 Wiley Periodicals, Inc.

  1. 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.

  2. 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.

  3. Toxicity on the luminescent bacterium Vibrio fischeri (Beijerinck). I: QSAR equation for narcotics and polar narcotics.

    PubMed

    Vighi, Marco; Migliorati, Sonia; Monti, Gianna Serafina

    2009-01-01

    Toxicity data on chemicals, supposed to have a narcotic or polar narcotic toxicological mode of action, have been produced on the luminescent bacterium Vibrio fischeri using the Microtox test procedure. Advanced statistical methods have been used to calculate statistically sound values for ecotoxicological endpoints. Simple quantitative structure activity relationship (QSAR) equations were developed for narcotics and polar narcotics. These equations were compared with those proposed by the European Technical Guidance Document on Risk Assessment for other aquatic organisms (algae, Daphnia, and fish). Similarities and differences are discussed. The need for including the bacterial component in the ecotoxicological risk assessment for aquatic ecosystems is highlighted.

  4. Predicting mitochondrial targeting by small molecule xenobiotics within living cells using QSAR models.

    PubMed

    Horobin, Richard W

    2015-01-01

    Whether small molecule xenobiotics (biocides, drugs, probes, toxins) will target mitochondria in living cells can be predicted using an algorithm derived from QSAR modeling. Application of the algorithm requires the chemical structures of all ionic species of the xenobiotic compound in question to be defined, and for certain numerical structure parameters (AI, CBN, log P, pKa, and Z) to be obtained for all such species. How the chemical structures are specified, how the structure parameters are obtained or estimated, and how the algorithm is used are described in an explicit protocol.

  5. Design, synthesis and 3D-QSAR study of cytotoxic flavonoid derivatives.

    PubMed

    Ou, Lili; Han, Shuang; Ding, Wenbo; Chen, Zhe; Ye, Ziqi; Yang, Hongyu; Zhang, Goulin; Lou, Yijia; Chen, Jian-Zhong; Yu, Yongping

    2011-08-01

    Three series of flavonoid derivatives were designed and synthesized. All synthesized compounds were evaluated for cytotoxic activities against five human cancer cell lines, including K562, PC-3, MCF-7, A549, and HO8910. Among the compounds tested, compound 9 d exhibited the most potent cytotoxic activity with IC(50) values of 2.76-6.98 μM. Further comparative molecular field analysis was performed to conduct a 3D quantitative structure-activity relationship study. The generated 3D-QSAR model could be used for further rational design of novel flavonoid analogs as highly potent cytotoxic agents.

  6. 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

  7. 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.

  8. 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…

  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. 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.

  11. 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...

  12. 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

    2016-05-05

    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.

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

    PubMed

    Tripuraneni, Naga Srinivas; Azam, Mohammed Afzal

    2016-04-07

    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.

  14. 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...

  15. 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.

  16. QSAR prediction of estrogen activity for a large set of diverse chemicals under the guidance of OECD principles.

    PubMed

    Liu, Huanxiang; Papa, Ester; Gramatica, Paola

    2006-11-01

    A large number of environmental chemicals, known as endocrine-disrupting chemicals, are suspected of disrupting endocrine functions by mimicking or antagonizing natural hormones, and such chemicals may pose a serious threat to the health of humans and wildlife. They are thought to act through a variety of mechanisms, mainly estrogen-receptor-mediated mechanisms of toxicity. However, it is practically impossible to perform thorough toxicological tests on all potential xenoestrogens, and thus, the quantitative structure--activity relationship (QSAR) provides a promising method for the estimation of a compound's estrogenic activity. Here, QSAR models of the estrogen receptor binding affinity of a large data set of heterogeneous chemicals have been built using theoretical molecular descriptors, giving full consideration to the new OECD principles in regulation for QSAR acceptability, during model construction and assessment. An unambiguous multiple linear regression (MLR) algorithm was used to build the models, and model predictive ability was validated by both internal and external validation. The applicability domain was checked by the leverage approach to verify prediction reliability. The results obtained using several validation paths indicate that the proposed QSAR model is robust and satisfactory, and can provide a feasible and practical tool for the rapid screening of the estrogen activity of organic compounds.

  17. Quantitative studies on structure-ORAC relationships of anthocyanins from eggplant and radish using 3D-QSAR.

    PubMed

    Jing, Pu; Zhao, Shujuan; Ruan, Siyu; Sui, Zhongquan; Chen, Lihong; Jiang, Linlei; Qian, Bingjun

    2014-02-15

    The 3-dimensional quantitative structure activity relationship (3D-QSAR) models were established from 21 anthocyanins based on their oxygen radical absorbing capacity (ORAC) and were applied to predict anthocyanins in eggplant and radish for their ORAC values. The cross-validated q(2)=0.857/0.729, non-cross-validated r(2) = 0.958/0.856, standard error of estimate = 0.153/0.134, and F = 73.267/19.247 were for the best QSAR (CoMFA/CoMSIA) models, where the correlation coefficient r(2)pred = 0.998/0.997 (>0.6) indicated a high predictive ability for each. Additionally, the contour map results suggested that structural characteristics of anthocyanins favourable for the high ORAC. Four anthocyanins from eggplant and radish have been screened based on the QSAR models. Pelargonidin-3-[(6''-p-coumaroyl)-glucosyl(2 → 1)glucoside]-5-(6''-malonyl)-glucoside, delphinidin-3-rutinoside-5-glucoside, and delphinidin-3-[(4''-p-coumaroyl)-rhamnosyl(1 → 6)glucoside]-5-glucoside potential with high ORAC based the QSAR models were isolated and also confirmed for their relative high antioxidant ability, which might attribute to the bulky and/or electron-donating substituent at the 3-position in the C ring or/and hydrogen bond donor group/electron donating group on the R1 position in the B ring.

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

    NASA Astrophysics Data System (ADS)

    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.

  19. 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...

  20. 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 ...

  1. 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.

  2. Local indices for similarity analysis (LISA)-a 3D-QSAR formalism based on local molecular similarity.

    PubMed

    Verma, Jitender; Malde, Alpeshkumar; Khedkar, Santosh; Iyer, Radhakrishnan; Coutinho, Evans

    2009-12-01

    A simple quantitative structure activity relationship (QSAR) approach termed local indices for similarity analysis (LISA) has been developed. In this technique, the global molecular similarity is broken up as local similarity at each grid point surrounding the molecules and is used as a QSAR descriptor. In this way, a view of the molecular sites permitting favorable and rational changes to enhance activity is obtained. The local similarity index, calculated on the basis of Petke's formula, segregates the regions into "equivalent", "favored similar", and "disfavored similar" (alternatively "favored dissimilar") potentials with respect to a reference molecule in the data set. The method has been tested on three large and diverse data sets-thrombin, glycogen phosphorylase b, and thermolysin inhibitors. The QSAR models derived using genetic algorithm incorporated partial least square analysis statistics are found to be comparable to the ones obtained by the standard three-dimensional (3D)-QSAR methods, such as comparative molecular field analysis and comparative molecular similarity indices analysis. The graphical interpretation of the LISA models is straightforward, and the outcome of the models corroborates well with literature data. The LISA models give insight into the binding mechanisms of the ligand with the enzyme and allow fine-tuning of the molecules at the local level to improve their activity.

  3. 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.

  4. Living Kinship Trouble: Danish Sperm Donors' Narratives of Relatedness.

    PubMed

    Mohr, Sebastian

    2015-01-01

    Danish sperm donors face a particular kind of kinship trouble: they find themselves in a cultural and organizational context that offers different and contrary ways of how to make connections to donor-conceived individuals meaningful. Whereas Danish sperm banks and Danish law want sperm donors to regard these connections as contractual issues, the dominant kinship narrative in Denmark asks sperm donors to also consider them as family and kinship relations. Based on interviews with Danish sperm donors and participant observation at Danish sperm banks, I argue that Danish sperm donors make sense of connections to donor-conceived individuals as a particular kind of relatedness that cannot be reduced to either contractual or kinship relations. Making sense of these connections, sperm donors negotiate their social significance and thereby participate in opening a space which offers avenues for new kinds of sociality.

  5. Combined QSAR and molecule docking studies on predicting P-glycoprotein inhibitors

    NASA Astrophysics Data System (ADS)

    Tan, Wen; Mei, Hu; Chao, Li; Liu, Tengfei; Pan, Xianchao; Shu, Mao; Yang, Li

    2013-12-01

    P-glycoprotein (P-gp) is an ATP-binding cassette multidrug transporter. The over expression of P-gp leads to the development of multidrug resistance (MDR), which is a major obstacle to effective treatment of cancer. Thus, designing effective P-gp inhibitors has an extremely important role in the overcoming MDR. In this paper, both ligand-based quantitative structure-activity relationship (QSAR) and receptor-based molecular docking are used to predict P-gp inhibitors. The results show that each method achieves good prediction performance. According to the results of tenfold cross-validation, an optimal linear SVM model with only three descriptors is established on 857 training samples, of which the overall accuracy (Acc), sensitivity, specificity, and Matthews correlation coefficient are 0.840, 0.873, 0.813, and 0.683, respectively. The SVM model is further validated by 418 test samples with the overall Acc of 0.868. Based on a homology model of human P-gp established, Surflex-dock is also performed to give binding free energy-based evaluations with the overall accuracies of 0.823 for the test set. Furthermore, a consensus evaluation is also performed by using these two methods. Both QSAR and molecular docking studies indicate that molecular volume, hydrophobicity and aromaticity are three dominant factors influencing the inhibitory activities.

  6. Pharmacophore modeling, comprehensive 3D-QSAR, and binding mode analysis of TGR5 agonists.

    PubMed

    Sindhu, Thangaraj; Srinivasan, Pappu

    2017-04-01

    Takeda G-protein-coupled receptor 5 (TGR5) is emerging as an important and promising target for the development of anti-diabetic drugs. Pharmacophore modeling and atom-based 3D-QSAR studies were carried out on a new series of 5-phenoxy-1,3-dimethyl-1H-pyrazole-4-carboxamides as highly potent agonists of TGR5. The generated best six featured pharmacophore model AAHHRR consists of two hydrogen bond acceptors (A): two hydrophobic groups (H) and two aromatic rings (R). The constructed 3D-QSAR model acquired excellent correlation coefficient value (R(2 )=( )0.9018), exhibited good predictive power (Q(2 )=( )0.8494) and high Fisher ratio (F = 61.2). The pharmacophore model was validated through Guner-Henry (GH) scoring method. The GH value of 0.5743 indicated that the AAHHRR model was statistically valuable and reliable in the identification of TGR5 agonists. Furthermore, the combined approach of molecular docking and binding free energy calculations were carried out for the 5-phenoxy-1,3-dimethyl-1H-pyrazole-4-carboxamides to explore the binding mode and interaction pattern. The generated contour maps revealed the important structural insights for the activity of the compounds. The results obtained from this study could be helpful in the development of novel and more potent agonists of TGR5.

  7. The use of Hasse diagrams as a potential approach for inverse QSAR.

    PubMed

    Brüggemann, R; Pudenz, S; Carlsen, L; Sørensen, P B; Thomsen, M; Mishra, R K

    2001-02-01

    Quantitative structure-activity relationships are often based on standard multidimensional statistical analyses and sophisticated local and global molecular descriptors. Here, the aim is to develop a tool helpful to define a molecule or a class of molecules which fulfills pre-described properties, i.e., an Inverse QSAR approach. If highly sophisticated descriptors are used in QSAR, the structure and then the synthesis recipe may be hard to derive. Thus, descriptors, from which the synthesis recipe can be easily derived, seem appropriate to be included within this study. However, if descriptors simple enough to be useful for defining syntheses recipes of chemicals were used, the accuracy of a numeric expression may fail. This paper suggests a method, based on very simple elements of the theory of partially ordered sets, to find a qualitative basis for the relationship between such fairly simple descriptors on the one side and a series of ecotoxicological properties, on the other side. The partial order ranking method assumes neither linearity nor certain statistical distribution properties. Therefore the method may be more general compared to many standard statistical techniques. A series of chlorinated aliphatic compounds has been used as an illustrative example and a comparison with more sophisticated descriptors derived from quantum chemistry and graph theory is given. Among the results, it was disclosed that only for algae lethal concentration, as one of the four ecotoxicological properties, the synthesis specific predictors seem to be good estimators. For all other ecotoxicological properties quantum chemical descriptors appear as the more suitable estimators.

  8. 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.

  9. 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

  10. QSAR, molecular docking studies of thiophene and imidazopyridine derivatives as polo-like kinase 1 inhibitors

    NASA Astrophysics Data System (ADS)

    Cao, Shandong

    2012-08-01

    The purpose of the present study was to develop in silico models allowing for a reliable prediction of polo-like kinase inhibitors based on a large diverse dataset of 136 compounds. As an effective method, quantitative structure activity relationship (QSAR) was applied using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The proposed QSAR models showed reasonable predictivity of thiophene analogs (Rcv2=0.533, Rpred2=0.845) and included four molecular descriptors, namely IC3, RDF075m, Mor02m and R4e+. The optimal model for imidazopyridine derivatives (Rcv2=0.776, Rpred2=0.876) was shown to perform good in prediction accuracy, using GATS2m and BEHe1 descriptors. Analysis of the contour maps helped to identify structural requirements for the inhibitors and served as a basis for the design of the next generation of the inhibitor analogues. Docking studies were also employed to position the inhibitors into the polo-like kinase active site to determine the most probable binding mode. These studies may help to understand the factors influencing the binding affinity of chemicals and to develop alternative methods for prescreening and designing of polo-like kinase inhibitors.

  11. 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

  12. Diagnostic tools to determine the quality of "transparent" regression-based QSARs: the "modelling power" plot.

    PubMed

    Sagrado, Salvador; Cronin, Mark T D

    2006-01-01

    A bivariate plot is presented for comparing two or more QSAR models. It is based on two new statistics associated with a regression model, the "descriptive power" (Dp), which is estimated through the relative uncertainty of model coefficients, and the "predictive power" (Pp), which is estimated through both the fitted and cross-validated explained variance of the response variable (i.e., biological activity). An algorithm was developed for performing equivalent multiple linear regression and partial-least-squares calculations. The results were validated by comparison with widely accepted commercial software. Dp and Pp statistics are defined to vary from 0 to 100%, so the modeler has a intuitive impression of the descriptive (i.e., global importance of the selected descriptors) and predictive (i.e., possibility of performing QSAR or just SAR estimations) power. These statistics represent a point in the Dp versus Pp "modelling power" plot, which facilitates visual multiple models comparison, but also could be used to substitute classical statistics and could even be combined to obtain a unique parameter to define (or compare) the model's quality.

  13. Combined QSAR and molecule docking studies on predicting P-glycoprotein inhibitors.

    PubMed

    Tan, Wen; Mei, Hu; Chao, Li; Liu, Tengfei; Pan, Xianchao; Shu, Mao; Yang, Li

    2013-12-01

    P-glycoprotein (P-gp) is an ATP-binding cassette multidrug transporter. The over expression of P-gp leads to the development of multidrug resistance (MDR), which is a major obstacle to effective treatment of cancer. Thus, designing effective P-gp inhibitors has an extremely important role in the overcoming MDR. In this paper, both ligand-based quantitative structure-activity relationship (QSAR) and receptor-based molecular docking are used to predict P-gp inhibitors. The results show that each method achieves good prediction performance. According to the results of tenfold cross-validation, an optimal linear SVM model with only three descriptors is established on 857 training samples, of which the overall accuracy (Acc), sensitivity, specificity, and Matthews correlation coefficient are 0.840, 0.873, 0.813, and 0.683, respectively. The SVM model is further validated by 418 test samples with the overall Acc of 0.868. Based on a homology model of human P-gp established, Surflex-dock is also performed to give binding free energy-based evaluations with the overall accuracies of 0.823 for the test set. Furthermore, a consensus evaluation is also performed by using these two methods. Both QSAR and molecular docking studies indicate that molecular volume, hydrophobicity and aromaticity are three dominant factors influencing the inhibitory activities.

  14. The Use of Pseudo-equilibrium Constant Affords Improved QSAR Models of Human Plasma Protein Binding

    PubMed Central

    Zhu, Xiangwei; Sedykh, Alexander; Zhu, Hao; Liu, Shushen; Tropsha, Alexander

    2015-01-01

    Purpose To develop accurate in silico predictors of Plasma Protein Binding (PPB). Methods Experimental PPB data were compiled for over 1,200 compounds. Two endpoints have been considered: (1) fraction bound (%PPB); and (2) the logarithm of a pseudo binding constant (lnKa) derived from %PPB. The latter metric was employed because it reflects the PPB thermodynamics and the distribution of the transformed data is closer to normal. Quantitative Structure-Activity Relationship (QSAR) models were built with Dragon descriptors and three statistical methods. Results Five-fold external validation procedure resulted in models with the prediction accuracy (R2) of 0.67±0.04 and 0.66±0.04, respectively, and the mean absolute error (MAE) of 15.3±0.2% and 13.6±0.2%, respectively. Models were validated with two external datasets: 173 compounds from DrugBank, and 236 chemicals from the US EPA ToxCast project. Models built with lnKa were significantly more accurate (MAE of 6.2–10.7%) than those built with %PPB (MAE of 11.9–17.6%) for highly bound compounds both for the training and the external sets. Conclusion The pseudo binding constant (lnKa) is more appropriate for characterizing PPB binding than conventional %PPB. Validated QSAR models developed herein can be applied as reliable tools in early drug development and in chemical risk assessment. PMID:23568522

  15. QSAR Study for Carcinogenic Potency of Aromatic Amines Based on GEP and MLPs

    PubMed Central

    Song, Fucheng; Zhang, Anling; Liang, Hui; Cui, Lianhua; Li, Wenlian; Si, Hongzong; Duan, Yunbo; Zhai, Honglin

    2016-01-01

    A new analysis strategy was used to classify the carcinogenicity of aromatic amines. The physical-chemical parameters are closely related to the carcinogenicity of compounds. Quantitative structure activity relationship (QSAR) is a method of predicting the carcinogenicity of aromatic amine, which can reveal the relationship between carcinogenicity and physical-chemical parameters. This study accessed gene expression programming by APS software, the multilayer perceptrons by Weka software to predict the carcinogenicity of aromatic amines, respectively. All these methods relied on molecular descriptors calculated by CODESSA software and eight molecular descriptors were selected to build function equations. As a remarkable result, the accuracy of gene expression programming in training and test sets are 0.92 and 0.82, the accuracy of multilayer perceptrons in training and test sets are 0.84 and 0.74 respectively. The precision of the gene expression programming is obviously superior to multilayer perceptrons both in training set and test set. The QSAR application in the identification of carcinogenic compounds is a high efficiency method. PMID:27854309

  16. Monte Carlo method based QSAR modelling of natural lipase inhibitors using hybrid optimal descriptors.

    PubMed

    Kumar, A; Chauhan, S

    2017-03-08

    Obesity is one of the most provoking health burdens in the developed countries. One of the strategies to prevent obesity is the inhibition of pancreatic lipase enzyme. The aim of this study was to build QSAR models for natural lipase inhibitors by using the Monte Carlo method. The molecular structures were represented by the simplified molecular input line entry system (SMILES) notation and molecular graphs. Three sets - training, calibration and test set of three splits - were examined and validated. Statistical quality of all the described models was very good. The best QSAR model showed the following statistical parameters: r(2) = 0.864 and Q(2) = 0.836 for the test set and r(2) = 0.824 and Q(2) = 0.819 for the validation set. Structural attributes for increasing and decreasing the activity (expressed as pIC50) were also defined. Using defined structural attributes, the design of new potential lipase inhibitors is also presented. Additionally, a molecular docking study was performed for the determination of binding modes of designed molecules.

  17. Monte carlo method-based QSAR modeling of penicillins binding to human serum proteins.

    PubMed

    Veselinović, Jovana B; Toropov, Andrey A; Toropova, Alla P; Nikolić, Goran M; Veselinović, Aleksandar M

    2015-01-01

    The binding of penicillins to human serum proteins was modeled with optimal descriptors based on the Simplified Molecular Input-Line Entry System (SMILES). The concentrations of protein-bound drug for 87 penicillins expressed as percentage of the total plasma concentration were used as experimental data. The Monte Carlo method was used as a computational tool to build up the quantitative structure-activity relationship (QSAR) model for penicillins binding to plasma proteins. One random data split into training, test and validation set was examined. The calculated QSAR model had the following statistical parameters: r(2)  = 0.8760, q(2)  = 0.8665, s = 8.94 for the training set and r(2)  = 0.9812, q(2)  = 0.9753, s = 7.31 for the test set. For the validation set, the statistical parameters were r(2)  = 0.727 and s = 12.52, but after removing the three worst outliers, the statistical parameters improved to r(2)  = 0.921 and s = 7.18. SMILES-based molecular fragments (structural indicators) responsible for the increase and decrease of penicillins binding to plasma proteins were identified. The possibility of using these results for the computer-aided design of new penicillins with desired binding properties is presented.

  18. 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.

  19. Quantification of contributions of molecular fragments for eye irritation of organic chemicals using QSAR study.

    PubMed

    Kar, Supratik; Roy, Kunal

    2014-05-01

    The eye irritation potential of chemicals has largely been evaluated using the Draize rabbit-eye test for a very long time. The Draize eye-irritation data on 38 compounds established by the European Center for Ecotoxicology and Toxicology of Chemicals (ECETOC) has been used in the present quantitative structure-activity relationship (QSAR) analysis in order to predict molar-adjusted eye scores (MES) and determine possible structural requisites and attributes that are primarily responsible for the eye irritation caused by the studied solutes. The developed model was rigorously validated internally as well as externally by applying principles of the Organization for Economic Cooperation and Development (OECD). The test for applicability domain was also carried out in order to check the reliability of the predictions. Important fragments contributing to higher MES values of the solutes were identified through critical analysis and interpretation of the developed model. Considering all the identified structural attributes, one can choose or design safe solutes with low eye irritant properties. The presented approach suggests a model for use in the context of virtual screening of relevant solute libraries. The developed QSAR model can be used to predict existing as well as future chemicals falling within the applicability domain of the model in order to reduce the use of animals.

  20. 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.

  1. Structure-hepatoprotective activity relationship study of sesquiterpene lactones: A QSAR analysis

    NASA Astrophysics Data System (ADS)

    Paukku, Yuliya; Rasulev, Bakhtiyor; Syrov, Vladimir; Khushbaktova, Zainab; Leszczynski, Jerzy

    This study has been carried out using quantitative structure-activity relationship analysis (QSAR) for 22 sesquiterpene lactones to correlate and predict their hepatoprotective activity. Sesquiterpenoids, the largest class of terpenoids, are a widespread group of substances occurring in various plant organisms. QSAR analysis was carried out using methods such as genetic algorithm for variables selection among generated and calculated descriptors and multiple linear regression analysis. Quantum-chemical calculations have been performed by density functional theory at B3LYP/6-311G(d, p) level for evaluation of electronic properties using reference geometries optimized by semi-empirical AM1 approach. Three models describing hepatoprotective activity values for series of sesquiterpene lactones are proposed. The obtained models are useful for description of sesquiterpene lactones hepatoprotective activity and can be used to estimate the hepatoprotective activity of new substituted sesquiterpene lactones. The models obtained in our study show not only statistical significance, but also good predictive ability. The estimated predictive ability (rtest2) of these models lies within 0.942-0.969.

  2. In vitro investigations for the QSAR mechanism of lymphocytes apoptosis induced by substituted aromatic toxicants.

    PubMed

    Zhang, Hangjun; Zhang, Jianying; Zhu, Yinmei

    2008-12-01

    The objective of this study was to assess the chemicals-induced apoptosis effects on fish lymphocytes and to use the QSAR model to interpret the relationships between apoptotic effects and chemical structures to identify the immune toxicology mechanism. By the use of a simple in vitro toxicological assay, the measured apoptotic parameter (EC50) is used in a QSAR to interpret the apoptotic effects of 25 substituted benzenes at low exposure levels. The apoptotic effects of all tested substituted aromatic chemicals with Carassius auratus lymphocytes were confirmed by DNA ladder and nucleus condensation. For both chlorobenzenes and PCBs, the EC50 values increase with increasing Cl number in the molecule, a result reflecting probably the increased p-pi conjugation of the C-Cl bonds that lowers the molecular reactivity. Furthermore, the apoptotic EC50 data were best correlated with the dipole moment (mu) and the energy of the lowest unoccupied molecular orbital (ELUMO) such that: log(1/EC50)=0.325+0.222 micro-0.163(ELUMO) (with R(2)=0.879). The dependence on the electronic ELUMO factor of the established correlation suggests that during the apoptotic process the ROS (reactive oxygen substance) produced by cells acts as a Lewis base in substituted nucleophilic reactions with toxic chemicals behaving as an electron acceptor. On the basis of the test results, the present toxicological assay offers a rapid tool for assessing the toxic effects of chemicals at low exposure levels.

  3. In silico study combining docking and QSAR methods on a series of matrix metalloproteinase 13 inhibitors.

    PubMed

    Xi, Lili; Li, Shuyan; Yao, Xiaojun; Wei, Yuhui; Li, Jiazhong; Liu, Huanxiang; Wu, Xin'an

    2014-11-01

    Matrix metalloproteinase 13 (MMP-13) plays an important role in the degradation of articular cartilage and has been considered as an attractive target for the treatment of osteoarthritis; hence, the development of efficient inhibitors of MMP-13 has become a hot study field. Taking a series of carboxylic acid-based MMP-13 inhibitors as research object, this work utilized an extended QSAR method to analyze the structure-activity relationships. We focused on two important topics in QSAR: bioactive conformation and descriptors. Firstly, molecular docking was carried out to dock all molecules into the MMP-13 active site in order to obtain the bioactive conformation. Secondly, based on the docked complex, descriptors characterizing receptor-ligand interactions and the ligand structure were calculated. Thirdly, a genetic algorithm (GA) and multiple linear regression (MLR) were employed to select important descriptors related to inhibitory activities, simultaneously, to build the predictive model. The built model gave satisfactory results with highly accurate fitting and strong external predictive abilities for chemicals not used in model development. Furthermore, the selected descriptors were explored to elucidate important factors influencing the inhibition activities. This study demonstrates that the selection strategy of the docking-guided bioactive conformation is rational and useful in predicting MMP-13 inhibitor activities, and receptor-ligand complex descriptors have an advantage over directly reflecting receptor-ligand interactions.

  4. 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.

  5. The interplay between QSAR/QSPR studies and partial order ranking and formal concept analyses.

    PubMed

    Carlsen, Lars

    2009-04-17

    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.

  6. 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

  7. [COMMODE] a large-scale database of molecular descriptors using compounds from PubChem

    PubMed Central

    2013-01-01

    Background Molecular descriptors have been extensively used in the field of structure-oriented drug design and structural chemistry. They have been applied in QSPR and QSAR models to predict ADME-Tox properties, which specify essential features for drugs. Molecular descriptors capture chemical and structural information, but investigating their interpretation and meaning remains very challenging. Results This paper introduces a large-scale database of molecular descriptors called COMMODE containing more than 25 million compounds originated from PubChem. About 2500 DRAGON-descriptors have been calculated for all compounds and integrated into this database, which is accessible through a web interface at http://commode.i-med.ac.at. PMID:24225386

  8. 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.

  9. Development of predictive pharmacophore model for in silico screening, and 3D QSAR CoMFA and CoMSIA studies for lead optimization, for designing of potent tumor necrosis factor alpha converting enzyme inhibitors

    NASA Astrophysics Data System (ADS)

    Murumkar, Prashant Revan; Zambre, Vishal Prakash; Yadav, Mange Ram

    2010-02-01

    A chemical feature-based pharmacophore model was developed for Tumor Necrosis Factor-α converting enzyme (TACE) inhibitors. A five point pharmacophore model having two hydrogen bond acceptors (A), one hydrogen bond donor (D) and two aromatic rings (R) with discrete geometries as pharmacophoric features was developed. The pharmacophore model so generated was then utilized for in silico screening of a database. The pharmacophore model so developed was validated by using four compounds having proven TACE inhibitory activity which were grafted into the database. These compounds mapped well onto the five listed pharmacophoric features. This validated pharmacophore model was also used for alignment of molecules in CoMFA and CoMSIA analysis. The contour maps of the CoMFA/CoMSIA models were utilized to provide structural insight for activity improvement of potential novel TACE inhibitors. The pharmacophore model so developed could be used for in silico screening of any commercial/in house database for identification of TACE inhibiting lead compounds, and the leads so identified could be optimized using the developed CoMSIA model. The present work highlights the tremendous potential of the two mutually complementary ligand-based drug designing techniques (i.e. pharmacophore mapping and 3D-QSAR analysis) using TACE inhibitors as prototype biologically active molecules.

  10. 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.

  11. The aquatic toxicity of anionic surfactants to Daphnia magna--a comparative QSAR study of linear alkylbenzene sulphonates and ester sulphonates.

    PubMed

    Hodges, Geoff; Roberts, David W; Marshall, Stuart J; Dearden, John C

    2006-06-01

    This paper develops quantitative structure activity relationships (QSARs) for the acute aquatic toxicity of the anionic surfactants linear alkylbenzene sulphonates (LAS) and ester sulphonates (ES) to Daphnia magna, the aim being to investigate the modes of action by comparing the QSARs for the two types of surfactant. The generated data for ES have been used to develop a QSAR correlating toxicity with calculated log P values: log(1/EC50)= 0.78 log P+1.37. This equation has an intercept 1.1 log units lower than a QSAR for linear alkylbenzene sulphonates (LAS). The findings suggest that either ES surfactants act by a different mode of action to LAS and other anionic surfactants or the log P calculation method introduces a systematic overestimate when applied to ES.

  12. 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.

  13. Rationalizing fragment based drug discovery for BACE1: insights from FB-QSAR, FB-QSSR, multi objective (MO-QSPR) and MIF studies

    NASA Astrophysics Data System (ADS)

    Manoharan, Prabu; Vijayan, R. S. K.; Ghoshal, Nanda

    2010-10-01

    The ability to identify fragments that interact with a biological target is a key step in FBDD. To date, the concept of fragment based drug design (FBDD) is increasingly driven by bio-physical methods. To expand the boundaries of QSAR paradigm, and to rationalize FBDD using In silico approach, we propose a fragment based QSAR methodology referred here in as FB-QSAR. The FB-QSAR methodology was validated on a dataset consisting of 52 Hydroxy ethylamine (HEA) inhibitors, disclosed by GlaxoSmithKline Pharmaceuticals as potential anti-Alzheimer agents. To address the issue of target selectivity, a major confounding factor in the development of selective BACE1 inhibitors, FB-QSSR models were developed using the reported off target activity values. A heat map constructed, based on the activity and selectivity profile of the individual R-group fragments, and was in turn used to identify superior R-group fragments. Further, simultaneous optimization of multiple properties, an issue encountered in real-world drug discovery scenario, and often overlooked in QSAR approaches, was addressed using a Multi Objective (MO-QSPR) method that balances properties, based on the defined objectives. MO-QSPR was implemented using Derringer and Suich desirability algorithm to identify the optimal level of independent variables ( X) that could confer a trade-off between selectivity and activity. The results obtained from FB-QSAR were further substantiated using MIF (Molecular Interaction Fields) studies. To exemplify the potentials of FB-QSAR and MO-QSPR in a pragmatic fashion, the insights gleaned from the MO-QSPR study was reverse engineered using Inverse-QSAR in a combinatorial fashion to enumerate some prospective novel, potent and selective BACE1 inhibitors.

  14. 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...

  15. 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...

  16. 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.

  17. Scopus database: a review.

    PubMed

    Burnham, Judy F

    2006-03-08

    The Scopus database provides access to STM journal articles and the references included in those articles, allowing the searcher to search both forward and backward in time. The database can be used for collection development as well as for research. This review provides information on the key points of the database and compares it to Web of Science. Neither database is inclusive, but complements each other. If a library can only afford one, choice must be based in institutional needs.

  18. 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

  19. 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.

  20. Biomacromolecular quantitative structure-activity relationship (BioQSAR): a proof-of-concept study on the modeling, prediction and interpretation of protein-protein binding affinity

    NASA Astrophysics Data System (ADS)

    Zhou, Peng; Wang, Congcong; Tian, Feifei; Ren, Yanrong; Yang, Chao; Huang, Jian

    2013-01-01

    Quantitative structure-activity relationship (QSAR), a regression modeling methodology that establishes statistical correlation between structure feature and apparent behavior for a series of congeneric molecules quantitatively, has been widely used to evaluate the activity, toxicity and property of various small-molecule compounds such as drugs, toxicants and surfactants. However, it is surprising to see that such useful technique has only very limited applications to biomacromolecules, albeit the solved 3D atom-resolution structures of proteins, nucleic acids and their complexes have accumulated rapidly in past decades. Here, we present a proof-of-concept paradigm for the modeling, prediction and interpretation of the binding affinity of 144 sequence-nonredundant, structure-available and affinity-known protein complexes (Kastritis et al. Protein Sci 20:482-491, 2011) using a biomacromolecular QSAR (BioQSAR) scheme. We demonstrate that the modeling performance and predictive power of BioQSAR are comparable to or even better than that of traditional knowledge-based strategies, mechanism-type methods and empirical scoring algorithms, while BioQSAR possesses certain additional features compared to the traditional methods, such as adaptability, interpretability, deep-validation and high-efficiency. The BioQSAR scheme could be readily modified to infer the biological behavior and functions of other biomacromolecules, if their X-ray crystal structures, NMR conformation assemblies or computationally modeled structures are available.

  1. JICST Factual Database

    NASA Astrophysics Data System (ADS)

    Hayase, Shuichi; Okano, Keiko

    Japan Information Center of Science and Technology (JICST) has started the on-line service of JICST Crystal Structure Database (JICST CR) in this January (1990). This database provides the information of atomic positions in a crystal and related informations of the crystal. The database system and the crystal data in JICST CR are outlined in this manuscript.

  2. 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…

  3. 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…

  4. 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…

  5. 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…

  6. Development of Novel Repellents Using Structure - Activity Modeling of Compounds in the USDA Archival Database

    DTIC Science & Technology

    2011-01-01

    used in efforts to develop QSAR models. Measurement of Repellent Efficacy Screening for Repellency of Compounds with Unknown Toxicology In screening...CPT) were used to develop Quantitative Structure Activity Relationship ( QSAR ) models to predict repellency. Successful prediction of novel...acylpiperidine QSAR models employed 4 descriptors to describe the relationship between structure and repellent duration. The ANN model of the carboxamides did not

  7. Prediction of air to liver partition coefficient for volatile organic compounds using QSAR approaches.

    PubMed

    Dashtbozorgi, Zahra; Golmohammadi, Hassan

    2010-06-01

    In this work a quantitative structure-activity relationship (QSAR) technique was developed to investigate the air to liver partition coefficient (log Kliver) for volatile organic compounds (VOCs). Suitable set of molecular descriptors was calculated and the important descriptors were selected by GA-PLS methods. These variables were served as inputs to generate neural networks. After optimization and training of the networks, they were used for the calculation of log Kliver for the validation set. The root mean square errors for the neural network calculated log Kliver of training, test, and validation sets are 0.100, 0.091, and 0.112, respectively. Results obtained reveal the reliability and good predictivity of neural network for the prediction of air to liver partition coefficient for volatile organic compounds.

  8. EVA: A new theoretically based molecular descriptor for use in QSAR/QSPR analysis

    NASA Astrophysics Data System (ADS)

    Ferguson, A. M.; Heritage, T.; Jonathon, P.; Pack, S. E.; Phillips, L.; Rogan, J.; Snaith, P. J.

    1997-03-01

    A new descriptor of molecular structure, EVA, for use in the derivation of robustly predictive QSAR relationships is described. It is based on theoretically derived normal coordinate frequencies, and has been used extensively and successfully in proprietary chemical discovery programmes within Shell Research. As a result of informal dissemination of the methodology, it is now being used successfully in related areas such as pharmaceutical drug discovery. Much of the experimental data used in development remain proprietary, and are not available for publication. This paper describes the method and illustrates its application to the calculation of nonproprietary data, log Pow, in both explanatory and predictive modes. It will be followed by other publications illustrating its application to a range of data derived from biological systems.

  9. Pharmacophore identification and bioactivity prediction for triaminotriazine derivatives by electron conformational-genetic algorithm QSAR method.

    PubMed

    Saripinar, Emin; Geçen, Nazmiye; Sahin, Kader; Yanmaz, Ersin

    2010-09-01

    The electron conformational-genetic algorithm (EC-GA) method has been employed as a 4D-QSAR approach to reveal the pharmacophore (Pha) and to predict anticancer activity in the N-morpholino triaminotriazine derivatives. The electron conformational matrices of congruity (ECMCs) identified by electronic and structural parameters are constructed from data of conformational analysis and electronic structure calculation of molecules. Comparing the matrices, electron conformational submatrix of activity (ECSA, Pha) are revealed that are common for these compounds within a minimum tolerance. To predict the theoretical activity of training and test set and to select important variables for describing the activities, genetic algorithm and non-linear least square regression methods were applied. Regression coefficients were found 0.9708 for training and 0.9520 for test set.

  10. QSAR studies of bioconcentration factors of polychlorinated biphenyls (PCBs) using DFT, PCS and CoMFA.

    PubMed

    Liu, Hui; Liu, Hongxia; Sun, Ping; Wang, Zunyao

    2014-11-01

    The bioconcentration factors (BCFs) of 58 polychlorinated biphenyls (PCBs) were modeled by quantitative structure-activity relationship (QSAR) using density functional theory (DFT), the position of Cl substitution (PCS) and comparative molecular field analysis (CoMFA) methods. All the models were robust and predictive, and especially, the best CoMFA model was significant with a correlation coefficient (R(2)) of 0.926, a cross-validation correlation coefficient (Q(2)) of 0.821 and a root mean square error estimated (RMSE) of 0.235. The results indicate that the electrostatic descriptors play a more significant role in BCFs of PCBs. Additionally, a test set was used to compare the predictive ability of our models to others, and results show that our CoMFA model present the lowest RMSE. Thus, the models obtain in this work can be used to predict the BCFs of remaining 152 PCBs without available experimental values.

  11. A DFT-based QSAR study on inhibition of human dihydrofolate reductase.

    PubMed

    Karabulut, Sedat; Sizochenko, Natalia; Orhan, Adnan; Leszczynski, Jerzy

    2016-11-01

    Diaminopyrimidine derivatives are frequently used as inhibitors of human dihydrofolate reductase, for example in treatment of patients whose immune system are affected by human immunodeficiency virus. Forty-seven dicyclic and tricyclic potential inhibitors of human dihydrofolate reductase were analyzed using the quantitative structure-activity analysis supported by DFT-based and DRAGON-based descriptors. The developed model yielded an RMSE deviation of 1.1 a correlation coefficient of 0.81. The prediction set was characterized by R(2)=0.60 and RMSE=3.59. Factors responsible for inhibition process were identified and discussed. The resulting model was validated via cross validation and Y-scrambling procedure. From the best model, we found several mass-related descriptors and Sanderson electronegativity-related descriptors that have the best correlations with the investigated inhibitory concentration. These descriptors reflect results from QSAR studies based on characteristics of human dihydrofolate reductase inhibitors.

  12. Design, synthesis, and 3D QSAR of novel potent and selective aromatase inhibitors.

    PubMed

    Leonetti, Francesco; Favia, Angelo; Rao, Angela; Aliano, Rosaria; Paluszcak, Anja; Hartmann, Rolf W; Carotti, Angelo

    2004-12-30

    The design, synthesis, and biological evaluation of a series of new aromatase inhibitors bearing an imidazole or triazole ring linked to a fluorene (A), indenodiazine (B), or coumarin scaffold (C) are reported. Properly substituted coumarin derivatives displayed the highest aromatase inhibitory potency and selectivity over 17-alpha-hydroxylase/17-20 lyase. The modeling of the aromatase inhibition data by Comparative Molecular Field Analysis (CoMFA/GOLPE 3D QSAR approach) led to the development of a PLS model with good fitting and predictive powers (n = 22, ONC = 3, r(2) = 0.949, s = 0.216, and q(2) = 0.715). The relationship between aromatase inhibition and the steric and electrostatic fields generated by the examined azole inhibitors enables a clear understanding of the nature and spatial location of the main interactions modulating the aromatase inhibitory potency.

  13. QSAR Study and Molecular Design of Open-Chain Enaminones as Anticonvulsant Agents

    PubMed Central

    Garro Martinez, Juan C.; Duchowicz, Pablo R.; Estrada, Mario R.; Zamarbide, Graciela N.; Castro, Eduardo A.

    2011-01-01

    Present work employs the QSAR formalism to predict the ED50 anticonvulsant activity of ringed-enaminones, in order to apply these relationships for the prediction of unknown open-chain compounds containing the same types of functional groups in their molecular structure. Two different modeling approaches are applied with the purpose of comparing the consistency of our results: (a) the search of molecular descriptors via multivariable linear regressions; and (b) the calculation of flexible descriptors with the CORAL (CORrelation And Logic) program. Among the results found, we propose some potent candidate open-chain enaminones having ED50 values lower than 10 mg·kg−1 for corresponding pharmacological studies. These compounds are classified as Class 1 and Class 2 according to the Anticonvulsant Selection Project. PMID:22272137

  14. Boosting support vector regression in QSAR studies of bioactivities of chemical compounds.

    PubMed

    Zhou, Yan-Ping; Jiang, Jian-Hui; Lin, Wei-Qi; Zou, Hong-Yan; Wu, Hai-Long; Shen, Guo-Li; Yu, Ru-Qin

    2006-07-01

    In this paper, boosting has been coupled with SVR to develop a new method, boosting support vector regression (BSVR). BSVR is implemented by firstly constructing a series of SVR models on the various weighted versions of the original training set and then combining the predictions from the constructed SVR models to obtain integrative results by weighted median. The proposed BSVR algorithm has been used to predict toxicities of nitrobenzenes and inhibitory potency of 1-phenyl[2H]-tetrahydro-triazine-3-one analogues as inhibitors of 5-lipoxygenase. As comparisons to this method, the multiple linear regression (MLR) and conventional support vector regression (SVR) have also been investigated. Experimental results have shown that the introduction of boosting drastically enhances the generalization performance of individual SVR model and BSVR is a well-performing technique in QSAR studies superior to multiple linear regression.

  15. Design, synthesis and 3D-QSAR of beta-carboline derivatives as potent antitumor agents.

    PubMed

    Cao, Rihui; Guan, Xiangdong; Shi, Buxi; Chen, Zhiyong; Ren, Zhenhua; Peng, Wenlie; Song, Huacan

    2010-06-01

    In a continuing effort to develop novel beta-carbolines endowed with better pharmacological profiles, a series of beta-carboline derivatives were designed and synthesized based on the previously developed SARs. Cytotoxicities in vitro of these compounds against a panel of human tumor cell lines were also investigated. The results demonstrated that the N2-benzylated beta-carbolinium bromides 56-60 represented the most potent compounds with IC50 values lower than 10 microM. The application of 3D-QSAR to these compounds explored the structural basis for their biological activities. CoMFA (q2=0.513, r2=0.862) and CoMSIA (q2=0.503, r2=0.831) models were developed for a set of 47 beta-carbolines. The results indicated that the antitumor pharmacophore of these molecules were marked at position-1, -2, -3, -7 and -9 of beta-carboline ring.

  16. QSAR Differential Model for Prediction of SIRT1 Modulation using Monte Carlo Method.

    PubMed

    Kumar, Ashwani; Chauhan, Shilpi

    2017-03-01

    Silent information regulator 2 homologue one (SIRT1) modulators have therapeutic potential for a number of diseases like cardiovascular, metabolic, inflammatory and age related disorders. Here, we have studied both activators and inhibitors of SIRT1 and constructed differential quantitative structure activity relationship (QSAR) models using CORAL software by Monte Carlo optimization method and SMILES notation. 3 splits divided into 3 subsets: sub-training, calibration and test sets, were examined and validated with a prediction set. All the described models were statistically significant models. The values of sensitivity, specificity, accuracy and Matthews' correlation coefficient for the validation set of best model were 1.0000, 0.8889, 0.9524 and 0.9058, respectively. In mechanistic interpretation, structural features important for SIRT1 activation and inhibition have been defined.

  17. The NCBI Taxonomy database.

    PubMed

    Federhen, Scott

    2012-01-01

    The NCBI Taxonomy database (http://www.ncbi.nlm.nih.gov/taxonomy) is the standard nomenclature and classification repository for the International Nucleotide Sequence Database Collaboration (INSDC), comprising the GenBank, ENA (EMBL) and DDBJ databases. It includes organism names and taxonomic lineages for each of the sequences represented in the INSDC's nucleotide and protein sequence databases. The taxonomy database is manually curated by a small group of scientists at the NCBI who use the current taxonomic literature to maintain a phylogenetic taxonomy for the source organisms represented in the sequence databases. The taxonomy database is a central organizing hub for many of the resources at the NCBI, and provides a means for clustering elements within other domains of NCBI web site, for internal linking between domains of the Entrez system and for linking out to taxon-specific external resources on the web. Our primary purpose is to index the domain of sequences as conveniently as possible for our user community.

  18. 3D-QSAR and molecular modeling of HIV-1 integrase inhibitors

    NASA Astrophysics Data System (ADS)

    Makhija, Mahindra T.; Kulkarni, Vithal M.

    2002-03-01

    Three-dimensional quantitative structure-activity relationship (3D QSAR) methods were applied on a series of inhibitors of HIV-1 integrase with respect to their inhibition of 3'-processing and 3'-end joining steps in vitro.The training set consisted of 27 compounds belonging to the class of thiazolothiazepines. The predictive ability of each model was evaluated using test set I consisting of four thiazolothiazepines and test set II comprised of seven compounds belonging to an entirely different structural class of coumarins. Maximum Common Substructure (MCS) based method was used to align the molecules and this was compared with other known methods of alignment. Two methods of 3D QSAR: comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were analyzed in terms of their predictive abilities. CoMSIA produced significantly better results for all correlations. The results indicate a strong correlation between the inhibitory activity of these compounds and the steric and electrostatic fields around them. CoMSIA models with considerable internal as well as external predictive ability were obtained. A poor correlation obtained with hydrophobic field indicates that the binding of thiazolothiazepines to HIV-1 integrase is mainly enthalpic in nature. Further the most active compound of the series was docked into the active site using the crystal structure of integrase. The binding site was formed by the amino acid residues 64-67, 116, 148, 151-152, 155-156, and 159. The comparison of coefficient contour maps with the steric and electrostatic properties of the receptor shows high level of compatibility.

  19. 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

  20. 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.

  1. Development and validation of a robust QSAR model for prediction of carcinogenicity of drugs.

    PubMed

    Kar, Supratik; Roy, Kunal

    2011-04-01

    Carcinogenicity is one of the toxicological endpoints causing the highest concern. Also, the standard bioassays in rodents used to assess the carcinogenic potential of chemicals and drugs are extremely long, costly and require the sacrifice of large numbers of animals. For these reasons, we have attempted development of a global quantitative structure-activity relationship (QSAR) model using a data set of 1464 compounds (the Galvez data set available from http://www.uv.es/-galvez/tablevi.pdf), including many marketed drugs for their carcinogenesis potential. Though experimental toxicity testing using animal models is unavoidable for new drug candidates at an advanced stage of drug development, yet the developed global QSAR model can in silico predict the carcinogenicity of new drug compounds to provide a tool for initial screening of new drug candidate molecules with reduced number of animal testing, money and time. Considering large number of data points with diverse structural features used for model development (n(training) = 732) and model validation (n(test) = 732), the model developed in this study has an encouraging statistical quality (leave-one-out Q2 = 0.731, R2pred = 0.716). Our developed model suggests that higher lipophilicity values and conjugated ring systems, thioketo and nitro groups contribute positively towards drug carcinogenicity. On the contrary, tertiary and secondary nitrogens, phenolic, enolic and carboxylic OH fragments and presence of three-membered rings reduce the carcinogenicity. Branching, size and shape are found to be crucial factors for drug-induced carcinogenicity. One may consider all these points to reduce carcinogenic potential of the molecules.

  2. Are Mechanistic and Statistical QSAR Approaches Really Different? MLR Studies on 158 Cycloalkyl-Pyranones.

    PubMed

    Bhhatarai, Barun; Garg, Rajni; Gramatica, Paola

    2010-07-12

    Two parallel approaches for quantitative structure-activity relationships (QSAR) are predominant in literature, one guided by mechanistic methods (including read-across) and another by the use of statistical methods. To bridge the gap between these two approaches and to verify their main differences, a comparative study of mechanistically relevant and statistically relevant QSAR models, developed on a case study of 158 cycloalkyl-pyranones, biologically active on inhibition (Ki ) of HIV protease, was performed. Firstly, Multiple Linear Regression (MLR) based models were developed starting from a limited amount of molecular descriptors which were widely proven to have mechanistic interpretation. Then robust and predictive MLR models were developed on the same set using two different statistical approaches unbiased of input descriptors. Development of models based on Statistical I method was guided by stepwise addition of descriptors while Genetic Algorithm based selection of descriptors was used for the Statistical II. Internal validation, the standard error of the estimate, and Fisher's significance test were performed for both the statistical models. In addition, external validation was performed for Statistical II model, and Applicability Domain was verified as normally practiced in this approach. The relationships between the activity and the important descriptors selected in all the models were analyzed and compared. It is concluded that, despite the different type and number of input descriptors, and the applied descriptor selection tools or the algorithms used for developing the final model, the mechanistical and statistical approach are comparable to each other in terms of quality and also for mechanistic interpretability of modelling descriptors. Agreement can be observed between these two approaches and the better result could be a consensus prediction from both the models.

  3. Structure-based 3D QSAR and design of novel acetylcholinesterase inhibitors

    NASA Astrophysics Data System (ADS)

    Sippl, Wolfgang; Contreras, Jean-Marie; Parrot, Isabelle; Rival, Yveline M.; Wermuth, Camille G.

    2001-05-01

    The paper describes the construction, validation and application of a structure-based 3D QSAR model of novel acetylcholinesterase (AChE) inhibitors. Initial use was made of four X-ray structures of AChE complexed with small, non-specific inhibitors to create a model of the binding of recently developed aminopyridazine derivatives. Combined automated and manual docking methods were applied to dock the co-crystallized inhibitors into the binding pocket. Validation of the modelling process was achieved by comparing the predicted enzyme-bound conformation with the known conformation in the X-ray structure. The successful prediction of the binding conformation of the known inhibitors gave confidence that we could use our model to evaluate the binding conformation of the aminopyridazine compounds. The alignment of 42 aminopyridazine compounds derived by the docking procedure was taken as the basis for a 3D QSAR analysis applying the GRID/GOLPE method. A model of high quality was obtained using the GRID water probe, as confirmed by the cross-validation method (q2 LOO=0.937, q2 L50% O=0.910). The validated model, together with the information obtained from the calculated AChE-inhibitor complexes, were considered for the design of novel compounds. Seven designed inhibitors which were synthesized and tested were shown to be highly active. After performing our modelling study the X-ray structure of AChE complexed with donepezil, an inhibitor structurally related to the developed aminopyirdazines, has been made available. The good agreement found between the predicted binding conformation of the aminopyridazines and the one observed for donepezil in the crystal structure further supports our developed model.

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

    NASA Astrophysics Data System (ADS)

    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.

  5. Molecular modeling studies of phenoxypyrimidinyl imidazoles as p38 kinase inhibitors using QSAR and docking.

    PubMed

    Ravindra, G K; Achaiah, G; Sastry, G N

    2008-04-01

    p38 Kinase plays a vital role in inflammation mediated by tumor necrosis factor-alpha (TNFalpha) and interleukin-1beta (IL-1beta) pathways and inhibitors of p38 kinase provide effective approach for the treatment of inflammatory diseases. Pyridinyl and pyrimidinyl imidazoles, selectively inhibit p38alpha MAP kinase, are useful in the treatment of inflammatory diseases like rheumatoid arthritis. Three dimensional quantitative structure-activity relationship studies (3D-QSAR) involving comparative molecular field analysis (CoMFA) and comparative similarity indices analysis (CoMSIA) and molecular docking were performed on 44 phenoxypyrimidinyl imidazole p38 kinase inhibitors to find out the structural relationship with the activity. The best predictive CoMFA model with atom fit alignment resulted in cross-validated r(2) value of 0.553, noncross-validated r(2) value of 0.908 and standard error of estimate 0.187. Similarly the best predictive CoMSIA model was derived with q(2) of 0.508, noncross-validated r(2) of 0.894 and standard error of estimate of 0.197, comprising steric, electrostatic, hydrophobic and hydrogen bond donor fields. These models were able to predict the activity of test set molecules efficiently within an acceptable error range. GOLD and FlexX were employed to dock the inhibitors into the active site of the p38 kinase and these docking studies revealed the vital interactions and binding conformation of the inhibitors. The information rendered by 3D-QSAR models and the docking interactions may afford valuable clues to optimize the lead and design new potential inhibitors.

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

    PubMed

    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: R (2) Tr = 0.9576 and RMSETr = 0.0958 for the training set; Q (2) CV = 0.9239 and RMSECV = 0.1304 for the LOO-CV set as well as Q (2) Ext = 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.

  7. 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…

  8. Inhibition of immune complex-mediated neutrophil oxidative metabolism: a pharmacophore model for 3-phenylcoumarin derivatives using GRIND-based 3D-QSAR and 2D-QSAR procedures.

    PubMed

    Kabeya, Luciana M; da Silva, Carlos H T P; Kanashiro, Alexandre; Campos, Joaquín M; Azzolini, Ana Elisa C S; Polizello, Ana Cristina M; Pupo, Mônica T; Lucisano-Valim, Yara M

    2008-05-01

    In this study, twenty hydroxylated and acetoxylated 3-phenylcoumarin derivatives were evaluated as inhibitors of immune complex-stimulated neutrophil oxidative metabolism and possible modulators of the inflammatory tissue damage found in type III hypersensitivity reactions. By using lucigenin- and luminol-enhanced chemiluminescence assays (CL-luc and CL-lum, respectively), we found that the 6,7-dihydroxylated and 6,7-diacetoxylated 3-phenylcoumarin derivatives were the most effective inhibitors. Different structural features of the other compounds determined CL-luc and/or CL-lum inhibition. The 2D-QSAR analysis suggested the importance of hydrophobic contributions to explain these effects. In addition, a statistically significant 3D-QSAR model built applying GRIND descriptors allowed us to propose a virtual receptor site considering pharmacophoric regions and mutual distances. Furthermore, the 3-phenylcoumarins studied were not toxic to neutrophils under the assessed conditions.

  9. 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

  10. IDPredictor: predict database links in biomedical database.

    PubMed

    Mehlhorn, Hendrik; Lange, Matthias; Scholz, Uwe; Schreiber, Falk

    2012-06-26

    Knowledge found in biomedical databases, in particular in Web information systems, is a major bioinformatics resource. In general, this biological knowledge is worldwide represented in a network of databases. These data is spread among thousands of databases, which overlap in content, but differ substantially with respect to content detail, interface, formats and data structure. To support a functional annotation of lab data, such as protein sequences, metabolites or DNA sequences as well as a semi-automated data exploration in information retrieval environments, an integrated view to databases is essential. Search engines have the potential of assisting in data retrieval from these structured sources, but fall short of providing a comprehensive knowledge except out of the interlinked databases. A prerequisite of supporting the concept of an integrated data view is to acquire insights into cross-references among database entities. This issue is being hampered by the fact, that only a fraction of all possible cross-references are explicitely tagged in the particular biomedical informations systems. In this work, we investigate to what extend an automated construction of an integrated data network is possible. We propose a method that predicts and extracts cross-references from multiple life science databases and possible referenced data targets. We study the retrieval quality of our method and report on first, promising results. The method is implemented as the tool IDPredictor, which is published under the DOI 10.5447/IPK/2012/4 and is freely available using the URL: http://dx.doi.org/10.5447/IPK/2012/4.

  11. 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…

  12. 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.

  13. 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

  14. 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.

  15. Comparison of fate profiles of PAHs in soil, sediments and mangrove leaves after oil spills by QSAR and QSPR.

    PubMed

    Tansel, Berrin; Lee, Mengshan; Tansel, Derya Z

    2013-08-15

    First order removal rates for 15 polyaromatic hydrocarbons (PAHs) in soil, sediments and mangrove leaves were compared in relation to the parameters used in fate transport analyses (i.e., octanol-water partition coefficient, organic carbon-water partition coefficient, solubility, diffusivity in water, HOMO-LUMO gap, molecular size, molecular aspect ratio). The quantitative structure activity relationships (QSAR) and quantitative structure property relationships (QSPR) showed that the rate of disappearance of PAHs is correlated with their diffusivities in water as well as molecular volumes in different media. Strong correlations for the rate of disappearance of PAHs in sediments could not be obtained in relation to most of the parameters evaluated. The analyses showed that the QSAR and QSPR correlations developed for removal rates of PAHs in soils would not be adequate for sediments and plant tissues.

  16. Validated QSAR prediction of OH tropospheric degradation of VOCs: splitting into training-test sets and consensus modeling.

    PubMed

    Gramatica, Paola; Pilutti, Pamela; Papa, Ester

    2004-01-01

    The rate constant for hydroxyl radical tropospheric degradation of 460 heterogeneous organic compounds is predicted by QSAR modeling. The applied Multiple Linear Regression is based on a variety of theoretical molecular descriptors, selected by the Genetic Algorithms-Variable Subset Selection (GA-VSS) procedure. The models were validated for predictivity by both internal and external validation. For the external validation two splitting approaches, D-optimal Experimental Design and Kohonen Artificial Neural Networks (K-ANN), were applied to the original data set to compare the two methodologies. We emphasize that external validation is the only way to establish a reliable QSAR model for predictive purposes. Predicted data by consensus modeling from different models are also proposed.

  17. 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.

  18. 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.

  19. Exploring QSAR, pharmacophore mapping and docking studies and virtual library generation for cycloguanil derivatives as PfDHFR-TS inhibitors.

    PubMed

    Ojha, Probir Kumar; Roy, Kunal

    2011-05-01

    Resistance of available antimalarial drugs against Plasmodium species is one of the major problems of malaria control in the developing world. In the present study, we have performed QSAR, pharmacophore mapping and molecular docking studies of cycloguanil derivatives as Plasmodium falciparum dihydrofolate reductase thymidylate synthase (PfDHFR-TS) inhibitors to explore essential features required for the antimalarial activity and important interaction patterns between the enzyme and ligands for the design of new potent PfDHFR-TS inhibitors. The QSAR studies have been carried out using topological parameters along with thermodynamic and structural descriptors. Acceptable values of internal and external validation parameters for the developed QSAR models confirm acceptability of the models. Pharmacophore mapping revealed that two hydrogen bond donor (HBD) features and a hydrophobic feature (HYD) are important parameters for PfDHFR-TS inhibitory activity. The docking studies suggest that the PfDHFR-TS inhibitors interact with Asp54, Ile14, Ile164, ser108, Ser111, Tyr170, Met55, Ala16, Thr185, Leu46, Cys15, Phe58, Ile112, Trp48, Tyr57 and Leu119 amino acid residues. The QSAR, pharmacophore and docking studies inferred that i) branching of the substituents at R1 and R2 positions should be less (small alkyl chain substituents are favored); ii) the electronegativity of the molecules should be high but within some limit; iii) the size and volume of the molecules should be high; iv) molecules should be flexible enough; v) R configuration at C6 position of the triazine ring favors the inhibitory binding affinity; vi) the substituents of the phenyl ring at 3, 4 and 5 position of the phenyl ring should be small hydrophobic groups. Based on these studies, we have designed a library of cycloguanil derivatives with good in silico predicted PfDHFR-TS inhibitory activity.

  20. 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.

  1. Synthesis and quantitative structure activity relationship (QSAR) of arylidene (benzimidazol-1-yl)acetohydrazones as potential antibacterial agents.

    PubMed

    El-Kilany, Yeldez; Nahas, Nariman M; Al-Ghamdi, Mariam A; Badawy, Mohamed E I; El Ashry, El Sayed H

    2015-01-01

    Ethyl (benzimidazol-1-yl)acetate was subjected to hydrazinolysis with hydrazine hydrate to give (benzimidazol-1-yl)acetohydrazide. The latter was reacted with various aromatic aldehydes to give the respective arylidene (1H-benzimidazol-1-yl)acetohydrazones. Solutions of the prepared hydrazones were found to contain two geometric isomers. Similarly (2-methyl-benzimidazol-1-yl)acetohydrazide was reacted with various aldehydes to give the corresponding hydrazones. The antibacterial activity was evaluated in vitro by minimum inhibitory concentration (MIC) against Agrobacterium tumefaciens (A. tumefaciens), Erwinia carotovora (E. carotovora), Corynebacterium fascians (C. fascians) and Pseudomonas solanacearum (P. solanacearum). MIC result demonstrated that salicylaldehyde(1H-benzimidazol-1-yl)acetohydrazone (4) was the most active compound (MIC = 20, 35, 25 and 30 mg/L against A. tumefaciens, C. fascians, E. carotovora and P. solanacearum, respectively). Quantitative structure activity relationship (QSAR) investigation using Hansch analysis was applied to find out the correlation between antibacterial activity and physicochemical properties. Various physicochemical descriptors and experimentally determined MIC values for different microorganisms were used as independent and dependent variables, respectively. pMICs of the compounds exhibited good correlation (r = 0.983, 0.914, 0.960 and 0.958 for A. tumefaciens, C. fascians, E. carotovora and P. solanacearum, respectively) with the prediction made by the model. QSAR study revealed that the hydrophobic parameter (ClogP), the aqueous solubility (LogS), calculated molar refractivity, topological polar surface area and hydrogen bond acceptor were found to have overall significant correlation with antibacterial activity. The statistical results of training set, correlation coefficient (r and r (2)), the ratio between regression and residual variances (f, Fisher's statistic), the standard error of estimates and

  2. 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.

  3. 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).

  4. 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.

  5. 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

  6. Anabolic and androgenic activities of 19-nor-testosterone steroids: QSAR study using quantum and physicochemical molecular descriptors.

    PubMed

    Alvarez-Ginarte, Yoanna María; Montero-Cabrera, Luis Alberto; de la Vega, José Manuel García; Noheda-Marín, Pedro; Marrero-Ponce, Yovani; Ruíz-García, José Alberto

    2011-08-01

    Quantitative structure-activity relationship (QSAR) study of 19-nor-testosterone steroids family was performed using quantum and physicochemical molecular descriptors. The quantum-chemical descriptors were calculated using semiempirical calculations. The descriptor values were statistically correlated using multi-linear regression analysis. The QSAR study indicated that the electronic properties of these derivatives have significant relationship with observed biological activities. The found QSAR equations explain that the energy difference between the LUMO and HOMO, the total dipole moment, the chemical potential and the value of the net charge of different carbon atoms in the steroid nucleus showed key interaction of these steroids with their anabolic-androgenic receptor binding site. The calculated values predict that the 17α-cyclopropyl-17β, 3β-hydroxy-4-estrene compound presents the highest anabolic-androgenic ratio (AAR) and the 7α-methyl-17β-acetoxy-estr-4-en-3-one compound the lowest AAR. This study might be helpful in the future successful identification of "real" or "virtual" anabolic-androgenic steroids.

  7. Pharmacophore modeling, 3D-QSAR and molecular docking studies of benzimidazole derivatives as potential FXR agonists.

    PubMed

    Sindhu, Thangaraj; Srinivasan, Pappu

    2014-08-01

    Farnesoid X receptor (FXR) is a potential therapeutic target for the treatment of diabetes mellitus. Atom-based three-dimensional quantitative structure activity relationship (3D-QSAR) models were developed for a series of 48 benzimidazole-based agonists of FXR. A total of five pharmacophore hypotheses were generated based on the survival score to build QSAR models. HHHRR was considered as a best model that consisted of three hydrophobic features (H) and two aromatic rings (R). The best hypothesis, HHHRR yielded a 3D-QSAR model with good statistical value (R(2)) of 0.8974 for a training set of 39 compounds and also showed good predictive power with correlation coefficient (Q(2)) of 0.7559 for a test set of nine compounds. Furthermore, molecular docking simulation was performed to understand the binding affinity of 48 benzimidazole-based compounds against the active site of human FXR protein. Docking results revealed that both the most active and least active compounds showed similar binding mode to the experimentally observed binding mode of co-crystallized ligand. The generated 3D contour maps revealed the structure activity relationship of the compounds. Substitution effects at different positions of benzimidazole derivatives would lead to the discovery of new agonists against human FXR protein.

  8. 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.

  9. Evaluation of CADASTER QSAR models for the aquatic toxicity of (benzo)triazoles and prioritisation by consensus prediction.

    PubMed

    Cassani, Stefano; Kovarich, Simona; Papa, Ester; Roy, Partha Pratim; Rahmberg, Magnus; Nilsson, Sara; Sahlin, Ullrika; Jeliazkova, Nina; Kochev, Nikolay; Pukalov, Ognyan; Tetko, Igor; Brandmaier, Stefan; Durjava, Mojca Kos; Kolar, Boris; Peijnenburg, Willie; Gramatica, Paola

    2013-03-01

    QSAR regression models of the toxicity of triazoles and benzotriazoles ([B]TAZs) to an alga (Pseudokirchneriella subcapitata), Daphnia magna and a fish (Onchorhynchus mykiss), were developed by five partners in the FP7-EU Project, CADASTER. The models were developed by different methods - Ordinary Least Squares (OLS), Partial Least Squares (PLS), Bayesian regularised regression and Associative Neural Network (ASNN) - by using various molecular descriptors (DRAGON, PaDEL-Descriptor and QSPR-THESAURUS web). In addition, different procedures were used for variable selection, validation and applicability domain inspection. The predictions of the models developed, as well as those obtained in a consensus approach by averaging the data predicted from each model, were compared with the results of experimental tests that were performed by two CADASTER partners. The individual and consensus models were able to correctly predict the toxicity classes of the chemicals tested in the CADASTER project, confirming the utility of the QSAR approach. The models were also used for the prediction of aquatic toxicity of over 300 (B)TAZs, many of which are included in the REACH pre-registration list, and were without experimental data. This highlights the importance of QSAR models for the screening and prioritisation of untested chemicals, in order to reduce and focus experimental testing.

  10. Application of 3D-QSAR techniques in anti-HIV-1 drug design--an overview.

    PubMed

    Debnath, Asim Kumar

    2005-01-01

    Despite the availability of several classes of drugs against acquired immunodeficiency syndrome (AIDS) caused by human immunodeficiency virus type 1(HIV-1), this deadly disease showing very little sign of containment, especially in Sub-Saharan Africa and South-East Asia. More than 20 million people died since the first diagnosis of AIDS more than twenty years ago and almost 40 million people are currently living with HIV/AIDS. Structure-based drug design effort was immensely successful in identifying several drugs that are currently available for the treatment of HIV-1. Many applications have been reported on the use of quantitative structure-activity relationship (QSAR) studies to understand the drug-receptor interactions and help in the design of more effective analogs. Extensive application was also reported on the application of 3D-QSAR techniques, such as, Comparative Molecular Field Analysis (CoMFA), Comparative Molecular Similarity Analysis (CoMSIA), pharmacophore generation using Catalyst/HypoGen, free-energy binding analysis, GRID/GOLPE, HINT-based techniques, etc. in anti-HIV-1 drug discovery programs in academia and industry. We have attempted to put together a comprehensive overview on the 3D-QSAR applications in anti-HIV-1 drug design reported in the literature during the last decade.

  11. 3-Heterocycle-phenyl N-alkylcarbamates as FAAH inhibitors: design, synthesis and 3D-QSAR studies.

    PubMed

    Käsnänen, Heikki; Myllymäki, Mikko J; Minkkilä, Anna; Kataja, Antti O; Saario, Susanna M; Nevalainen, Tapio; Koskinen, Ari M P; Poso, Antti

    2010-02-01

    Carbamates are a well-established class of fatty acid amide hydrolase (FAAH) inhibitors. Here we describe the synthesis of meta-substituted phenolic N-alkyl/aryl carbamates and their in vitro FAAH inhibitory activities. The most potent compound, 3-(oxazol-2yl)phenyl cyclohexylcarbamate (2 a), inhibited FAAH with a sub-nanomolar IC(50) value (IC(50)=0.74 nM). Additionally, we developed and validated three-dimensional quantitative structure-activity relationships (QSAR) models of FAAH inhibition combining the newly disclosed carbamates with our previously published inhibitors to give a total set of 99 compounds. Prior to 3D-QSAR modeling, the degree of correlation between FAAH inhibition and in silico reactivity was also established. Both 3D-QSAR methods used, CoMSIA and GRID/GOLPE, produced statistically significant models with coefficient of correlation for external prediction (R(2) (PRED)) values of 0.732 and 0.760, respectively. These models could be of high value in further FAAH inhibitor design.

  12. Inhibitory mode of indole-2-carboxamide derivatives against HLGPa: molecular docking and 3D-QSAR analyses.

    PubMed

    Liu, Guixia; Zhang, Zhenshan; Luo, Xiaomin; Shen, Jianhua; Liu, Hong; Shen, Xu; Chen, Kaixian; Jiang, Hualiang

    2004-08-01

    The interaction of a series of indole-2-carboxamide compounds with human liver glycogen phosphorylase a (HLGPa) have been studied employing molecular docking and 3D-QSAR approaches. The Lamarckian Genetic Algorithm (LGA) of AutoDock 3.0 was employed to locate the binding orientations and conformations of the inhibitors interacting with HLGPa. The binding models were demonstrated in the aspects of inhibitor's conformation, subsite interaction, and hydrogen bonding. The very similar binding conformations of these inhibitors show that they interact with HLGPa in a very similar way. Good correlations between the calculated interaction free energies and experimental inhibitory activities suggest that the binding conformations of these inhibitors are reasonable. The structural and energetic differences in inhibitory potencies of indole-2-carboxamide compounds were reasonably explored. Using the binding conformations of indole-2-carboxamides, consistent and highly predictive 3D-QSAR models were developed by CoMFA and CoMSIA analyses. The q2 values are 0.697 and 0.622 for CoMFA and CoMSIA models, respectively. The predictive ability of these models was validated by four compounds that were not included in the training set. Mapping these models back to the topology of the active site of HLGPa leads to a better understanding of the vital indole-2-carboxamide-HLGPa interactions. Structure-based investigations and the final 3D-QSAR results provide clear guidelines and accurate activity predictions for novel inhibitor design.

  13. A QSAR model of benzoxazole derivatives as potential inhibitors for inosine 5`-monophosphate dehydrogenase from Cryptosporidium parvum

    PubMed Central

    Teotia, Pratibha; Prakash Dwivedi, Surya; Dwivedi, Neeraja

    2016-01-01

    Cryptosporidium parvum is the common enteric protozoan pathogen causing cryptosporidiosis in human. Available drugs to treat cryptosporidiosis are ineffective and there is yet no vaccine against C. parvum. Therefore, it is of interest to design an improved yet effective drug against C. parvum. Here, we docked benzoxazole derivatives (collected from literature) with inosine 5`- monophosphate dehydrogenase (IMPDH) from Cryptosporidium parvum using the program AutoDock 4.2. The docked protein - inhibitor complex structure was optimized using molecular dynamics simulation for 5 ps with the CHARMM-22 force field using NAMD (NAnoscale Molecular Dynamics program) incorporated in visual molecular dynamics (VMD 1.9.2) and then evaluating the stability of complex structure by calculating RMSD values. NAMD is a parallel, object-oriented molecular dynamics code designed for high-performance simulation of large biomolecular systems. A quantitative structure activity relationship (QSAR) model was built using energy-based descriptors as independent variable and pIC50 value as dependent variable of fifteen known benzoxazole derivatives with C. parvum IMPDH protein, yielding correlation coefficient r2 of 0.7948. The predictive performance of QSAR model was assessed using different cross-validation procedures. Our results suggest that a ligand-receptor binding interaction for inosine 5`-monophosphate dehydrogenase using a QSAR model is promising approach to design more potent inosine 5`-monophosphate dehydrogenase inhibitors prior to their synthesis. PMID:28149045

  14. Elaborate ligand-based modeling coupled with QSAR analysis and in silico screening reveal new potent acetylcholinesterase inhibitors

    NASA Astrophysics Data System (ADS)

    Abuhamdah, Sawsan; Habash, Maha; Taha, Mutasem O.

    2013-12-01

    Inhibition of the enzyme acetylcholinesterase (AChE) has been shown to alleviate neurodegenerative diseases prompting several attempts to discover and optimize new AChE inhibitors. In this direction, we explored the pharmacophoric space of 85 AChE inhibitors to identify high quality pharmacophores. Subsequently, we implemented genetic algorithm-based quantitative structure-activity relationship (QSAR) modeling to select optimal combination of pharmacophoric models and 2D physicochemical descriptors capable of explaining bioactivity variation among training compounds ( {{r}}^{ 2}_{ 6 8} = 0. 9 4 , F-statistic = 125.8, {{r}}^{ 2}_{{LOO}} { = 0} . 9 2 , {{r}}^{ 2}_{{PRESS}} against 17 external test inhibitors = 0.84). Two orthogonal pharmacophores emerged in the QSAR equation suggesting the existence of at least two binding modes accessible to ligands within AChE binding pocket. The successful pharmacophores were comparable with crystallographically resolved AChE binding pocket. We employed the pharmacophoric models and associated QSAR equation to screen the national cancer institute list of compounds. Twenty-four low micromolar AChE inhibitors were identified. The most potent gave IC50 value of 1.0 μM.

  15. Quantitative structure-activity relationships (QSAR) of some 2,2-diphenyl propionate (DPP) derivatives of muscarinic antagonists

    SciTech Connect

    Gordon, R.K.; Breuer, E.; Padilla, F.N.; Chiang, P.K.

    1987-05-01

    QSAR between biological activities and molecular-chemical properties were investigated to aid in designing more effective and potent antimuscarinic pharmacophores. A molecular modeling program was used to calculate geometrical and topological values of a series of DPP pharmacophores. The newly synthesized pharmacophores were tested for their antagonist activities by: (1) inhibition of (N-methyl-/sup 3/H)scopolamine binding assay to the muscarinic receptors of N4TG1 neuroblastoma cells; (2) blocking of acetylcholine-induced contraction of guinea pig ileum; and (3) inhibition of carbachol-induced ..cap alpha..-amylase release from rat pancreas. The differences in the log of these biological activities were directly and significantly related to the distances between the carbonyl oxygen of the DPP and the quaternary nitrogen of the modified pharmacophores. The biological activities, while depending on each particular assay, varied between three and four logs of activity. The charge remained the same in all the pharmacophores. There were no QSAR correlations between molecular volume, molecular connectivity, or principle moments and their antagonistic activities, although multivariate QSAR was not employed. Thus, based on distance geometry, potent muscarinic pharmacophores can be predicted.

  16. Genotoxicity of quinolones: substituents contribution and transformation products QSAR evaluation using 2D and 3D models.

    PubMed

    Li, Min; Wei, Dongbin; Zhao, Huimin; Du, Yuguo

    2014-01-01

    The genotoxicity of 21 quinolones antibiotics was determined using SOS/umu assay. Some quinolones exhibited high genotoxicity, and the chemical substituent on quinolone ring significantly affected genotoxicity. To establish the relationship between genotoxicity and substituent, a 2D-QSAR model based on quantum chemical parameters was developed. Calculation suggested that both steric and electrostatic properties were correlated well with genotoxicity. Furthermore, the specific effect on three key active sites (1-, 7- and 8-positions) of quinolone ring was investigated using a 3D-QSAR (comparative molecular field analysis, CoMFA) method. From our modeling, the genotoxicity increased when substituents had: (1) big volume and/or positive charge at 1-position; (2) negative charge at 7-position; and (3) small volume and/or negative charge at 8-position. The developed QSAR models were applicable to estimate genotoxicity of quinolones antibiotics and their transformation products. It is noted that some of the transformation products exhibited higher genotoxicity comparing to their precursor (e.g., ciprofloxacin). This study provided an alternative way to understand the molecule genotoxicity of quinolones derivatives, as well as to evaluate their potential environmental risks.

  17. 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.

  18. Mugshot Identification Database (MID)

    National Institute of Standards and Technology Data Gateway

    NIST Mugshot Identification Database (MID) (PC database for purchase)   NIST Special Database 18 is being distributed for use in development and testing of automated mugshot identification systems. The database consists of three CD-ROMs, containing a total of 3248 images of variable size using lossless compression. A newer version of the compression/decompression software on the CDROM can be found at the website http://www.nist.gov/itl/iad/ig/nigos.cfm as part of the NBIS package.

  19. Databases for Microbiologists

    DOE PAGES

    Zhulin, Igor B.

    2015-05-26

    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. Finally, the purpose of this minireview is to provide a brief survey of current databases that are of interest to microbiologists.

  20. 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

  1. HIV Sequence Databases

    PubMed Central

    Kuiken, Carla; Korber, Bette; Shafer, Robert W.

    2008-01-01

    Two important databases are often used in HIV genetic research, the HIV Sequence Database in Los Alamos, which collects all sequences and focuses on annotation and data analysis, and the HIV RT/Protease Sequence Database in Stanford, which collects sequences associated with the development of viral resistance against anti-retroviral drugs and focuses on analysis of those sequences. The types of data and services these two databases offer, the tools they provide, and the way they are set up and operated are described in detail. PMID:12875108

  2. 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.

  3. 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

  4. ALS and the Military: A Population-Based Study in the Danish Registries

    PubMed Central

    Seals, Ryan M.; Kioumourtzoglou, Marianthi-Anna; Gredal, Ole; Hansen, Johnni; Weisskopf, Marc G.

    2016-01-01

    Background Prior studies have suggested that military service may be associated with the development of amyotrophic lateral sclerosis. We conducted a population-based case-control study in Denmark to assess whether occupation in the Danish military is associated with an increased risk of developing amyotrophic lateral sclerosis. Methods There were 3,650 incident cases of amyotrophic lateral sclerosis recorded in the Danish National Patient Registry between 1982 and 2009. Each case was matched to 100 age- and sex-matched population controls alive and free of amyotrophic lateral sclerosis on the date of the case diagnosis. Comprehensive occupational history was obtained from the Danish Pension Fund database, which began in 1964. Results 2.4% (n=8,922) of controls had a history of employment in the military prior to the index date. Military employees overall had an elevated rate of ALS (OR=1.3; 95% CI: 1.1-1.6). A ten-year increase in years employed by the military was associated with an odds ratio of 1.2 (95% CI: 1.0-1.4), and all quartiles of time employed were elevated. There was little suggestion of a pattern across calendar year of first employment, but there was some evidence that increasing age at first employment was associated with increased ALS rates. Rates were highest in the decade immediately following the end of employment (OR=1.6; 95% CI: 1.2-2.2). Conclusions In this large population-based case-control study, employment by the military is associated with increased rates of ALS. These findings are consistent with earlier findings that military service or employment may entail exposure to risk factors for ALS. PMID:26583610

  5. Psychological defenses of Danish medical students.

    PubMed

    la Cour, Peter

    2002-01-01

    Patterns in the psychological defenses of medical students may have implications for the way they handle and respond to the pressures and developmental issues they encounter in medical school and beyond. Using the Defense Style Questionnaire (DSQ40) to assess psychological defenses, a sample of first-year Danish medical students was compared with a sample of students at a short-term boarding school for general education. The medical students scored significantly higher on items connected with pseudo-altruism, denial, and undoing. Trends in the data furthermore suggest a greater use of sublimation, rationalization, and dissociation among medical students. When defense mechanisms were labeled into mature, neurotic, and immature categories, there were no differences between the groups or in the total defense scores.

  6. Consumer Product Category Database

    EPA Pesticide Factsheets

    The Chemical and Product Categories database (CPCat) catalogs the use of over 40,000 chemicals and their presence in different consumer products. The chemical use information is compiled from multiple sources while product information is gathered from publicly available Material Safety Data Sheets (MSDS). EPA researchers are evaluating the possibility of expanding the database with additional product and use information.

  7. BioImaging Database

    SciTech Connect

    David Nix, Lisa Simirenko

    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.

  8. 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.

  9. 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…

  10. 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.

  11. 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.

  12. 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.

  13. 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...

  14. 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.

  15. 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…

  16. 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.

  17. 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…

  18. Importance of Kier-Hall topological indices in the QSAR of anticancer drug design.

    PubMed

    Nandi, Sisir; Bagchi, Manish C

    2012-06-01

    An important area of theoretical drug design research is quantitative structure activity relationship (QSAR) using structural invariants. The impetus for this research trend comes from various directions. Researchers in chemical documentation have searched for a set of invariants which will be more convenient than the adjacency matrix (or connection table) for the storage and comparison of chemical structures. Molecular structure can be looked upon as the representation of the relationship among its various constituents. The term molecular structure represents a set of nonequivalent and probably disjoint concepts. There is no reason to believe that when we discuss diverse topics (e.g. chemical synthesis, reaction rates, spectroscopic transitions, reaction mechanisms, and ab initio calculations) using the notion of molecular structure, the different meanings we attach to the single term molecular structure originate from the same fundamental concept. On the contrary, there is a theoretical and philosophical basis for the non-homogeneity of concepts covered by the term molecular structure. In the context of molecular science, the various concepts of molecular structure (e.g. classical valence bond representations, various chemical graph-theoretic representations, ball and spoke model of a molecule, representation of a molecule by minimum energy conformation, semi symbolic contour map of a molecule, or symbolic representation of chemical species by Hamiltonian operators) are model objects derived through different abstractions of the same chemical reality. In each instance, the equivalence class (concept or model of molecular structure) is generated by selecting certain aspects while ignoring some unique properties of those actual events. This explains the plurality of the concept of molecular structure and their autonomous nature, the word autonomous being used in the same sense that one concept is not logically derived from the other. At the most fundamental level

  19. A Structure-Activity Relationship Study of Imidazole-5-Carboxylic Acid Derivatives as Angiotensin II Receptor Antagonists Combining 2D and 3D QSAR Methods.

    PubMed

    Sharma, Mukesh C

    2016-03-01

    Two-dimensional (2D) and three-dimensional (3D) quantitative structure-activity relationship (QSAR) studies were performed for correlating the chemical composition of imidazole-5-carboxylic acid analogs and their angiotensin II [Formula: see text] receptor antagonist activity using partial least squares and k-nearest neighbor, respectively. For comparing the three different feature selection methods of 2D-QSAR, k-nearest neighbor models were used in conjunction with simulated annealing (SA), genetic algorithm and stepwise coupled with partial least square (PLS) showed variation in biological activity. The statistically significant best 2D-QSAR model having good predictive ability with statistical values of [Formula: see text] and [Formula: see text] was developed by SA-partial least square with the descriptors like [Formula: see text]count, 5Chain count, SdsCHE-index, and H-acceptor count, showing that increase in the values of these descriptors is beneficial to the activity. The 3D-QSAR studies were performed using the SA-PLS. A leave-one-out cross-validated correlation coefficient [Formula: see text] and predicate activity [Formula: see text] = 0.7226 were obtained. The information rendered by QSAR models may lead to a better understanding of structural requirements of substituted imidazole-5-carboxylic acid derivatives and also aid in designing novel potent antihypertensive molecules.

  20. The Immigrant Worker and the Danish Public Library System

    ERIC Educational Resources Information Center

    UNESCO Bulletin for Libraries, 1978

    1978-01-01

    A summary of a survey conducted in 1973 of Danish library services available to immigrant workers and their families, especially those speaking Arabic, Turkish, Urdu, and the languages used in Yugoslavia. (Author/KP)

  1. 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.

  2. Glycoproteomic and glycomic databases.

    PubMed

    Baycin Hizal, Deniz; Wolozny, Daniel; Colao, Joseph; Jacobson, Elena; Tian, Yuan; Krag, Sharon S; Betenbaugh, Michael J; Zhang, Hui

    2014-01-01

    Protein glycosylation serves critical roles in the cellular and biological processes of many organisms. Aberrant glycosylation has been associated with many illnesses such as hereditary and chronic diseases like cancer, cardiovascular diseases, neurological disorders, and immunological disorders. Emerging mass spectrometry (MS) technologies that enable the high-throughput identification of glycoproteins and glycans have accelerated the analysis and made possible the creation of dynamic and expanding databases. Although glycosylation-related databases have been established by many laboratories and institutions, they are not yet widely known in the community. Our study reviews 15 different publicly available databases and identifies their key elements so that users can identify the most applicable platform for their analytical needs. These databases include biological information on the experimentally identified glycans and glycopeptides from various cells and organisms such as human, rat, mouse, fly and zebrafish. The features of these databases - 7 for glycoproteomic data, 6 for glycomic data, and 2 for glycan binding proteins are summarized including the enrichment techniques that are used for glycoproteome and glycan identification. Furthermore databases such as Unipep, GlycoFly, GlycoFish recently established by our group are introduced. The unique features of each database, such as the analytical methods used and bioinformatical tools available are summarized. This information will be a valuable resource for the glycobiology community as it presents the analytical methods and glycosylation related databases together in one compendium. It will also represent a step towards the desired long term goal of integrating the different databases of glycosylation in order to characterize and categorize glycoproteins and glycans better for biomedical research.

  3. 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.

  4. JICST Factual Database

    NASA Astrophysics Data System (ADS)

    Suzuki, Kazuaki; Shimura, Kazuki; Monma, Yoshio; Sakamoto, Masao; Morishita, Hiroshi; Kanazawa, Kenji

    The Japan Information Center of Science and Technology (JICST) has started the on-line service of JICST/NRIM Materials Strength Database for Engineering Steels and Alloys (JICST ME) in this March (1990). This database has been developed under the joint research between JICST and the National Research Institute for Metals (NRIM). It provides material strength data (creep, fatigue, etc.) of engineering steels and alloys. It is able to search and display on-line, and to analyze the searched data statistically and plot the result on graphic display. The database system and the data in JICST ME are described.

  5. Plant Genome Duplication Database.

    PubMed

    Lee, Tae-Ho; Kim, Junah; Robertson, Jon S; Paterson, Andrew H

    2017-01-01

    Genome duplication, widespread in flowering plants, is a driving force in evolution. Genome alignments between/within genomes facilitate identification of homologous regions and individual genes to investigate evolutionary consequences of genome duplication. PGDD (the Plant Genome Duplication Database), a public web service database, provides intra- or interplant genome alignment information. At present, PGDD contains information for 47 plants whose genome sequences have been released. Here, we describe methods for identification and estimation of dates of genome duplication and speciation by functions of PGDD.The database is freely available at http://chibba.agtec.uga.edu/duplication/.

  6. Analysis of matches and partial-matches in a Danish STR data set.

    PubMed

    Tvedebrink, Torben; Eriksen, Poul Svante; Curran, James Michael; Mogensen, Helle Smidt; Morling, Niels

    2012-05-01

    Over the recent years, the national databases of STR profiles have grown in size due to the success of forensic DNA analysis in solving crimes. The accumulation of DNA profiles implies that the probability of a random match or near match of two randomly selected DNA profiles in the database increases. We analysed 53,295 STR profiles from individuals investigated in relation to crime case investigations at the Department of Forensic Medicine, Faculty of Health Sciences, University of Copenhagen, Denmark. Incomplete STR profiles (437 circa 0.8% of the total), 48 redundant STR profiles from monozygotic twins (0.09%), 6 redundant STR profiles of unknown cause and 1283 STR profiles from repeated testing of individuals were removed leaving 51,517 complete 10 locus STR profiles for analysis. The number corresponds to approximately 1% of the Danish population. We compared all STR profiles to each other, i.e. 1.3×10(9) comparisons. With these large number of comparisons, it is likely to observe DNA profiles that coincide on many loci, which has concerned some commentators and raised questions about "overstating" the power of DNA evidence. We used the method of Weir [11,12] and Curran et al. [3] to compare the observed and expected number of matches and near matches in the data set. We extended the methods by computing the covariance matrix of the summary statistic and used it for the estimation of the identical-by-descent parameter, θ. The analysis demonstrated a number of close relatives in the Danish data set and substructure. The main contribution to the substructure comes from close relatives. An overall θ-value of 1% compensated for the observed substructure, when close familial relationships were accounted for.

  7. Numeric Databases in the Sciences.

    ERIC Educational Resources Information Center

    Meschel, S. V.

    1984-01-01

    Provides exploration into types of numeric databases available (also known as source databases, nonbibliographic databases, data-files, data-banks, fact banks); examines differences and similarities between bibliographic and numeric databases; identifies disciplines that utilize numeric databases; and surveys representative examples in the…

  8. 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.

  9. 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

  10. 3D-QSAR Design of New Escitalopram Derivatives for the Treatment of Major Depressive Disorders

    PubMed Central

    Avram, Speranta; Buiu, Catalin; Duda-Seiman, Daniel M.; Duda-Seiman, Corina; Mihailescu, Dan

    2010-01-01

    Antidepressants are psychiatric agents used for the treatment of different types of depression being at present amongst the most commonly prescribed drug, while their effectiveness and adverse effects are the subject of many studies and competing claims. Having studied five QSAR models predicting the biological activities of 18 antidepressants, already approved for clinical treatment, in interaction with the serotonin transporter (SERT), we attempted to establish the membrane ions’ contributions (sodium, potassium, chlorine and calcium) supplied by donor/acceptor hydrogen bond character and electrostatic field to the antidepressant activity. Significant cross-validated correlation q2 (0.5–0.6) and the fitted correlation r2 (0.7–0.82) coefficients were obtained indicating that the models can predict the antidepressant activity of compounds. Moreover, considering the contribution of membrane ions (sodium, potassium and calcium) and hydrogen bond donor character, we have proposed a library of 24 new escitalopram structures, some of them probably with significantly improved antidepressant activity in comparison with the parent compound. PMID:21179345

  11. Evaluation and QSAR modeling on multiple endpoints of estrogen activity based on different bioassays.

    PubMed

    Liu, Huanxiang; Papa, Ester; Gramatica, Paola

    2008-02-01

    There is a great need for an effective means of rapidly assessing endocrine-disrupting activity, especially estrogen-simulating activity, due to the large number of chemicals that have serious adverse effects on the environment. Many approaches using a variety of biological screening assays are used to identify endocrine disrupting chemicals. The present investigation analyzes the consistency and peculiarity of information from different experimental assays collected from a literature survey, by studying the correlation of the different endpoints. In addition, the activity values of more widely used selected bioassays have been combined by principle components analysis (PCA) to build one cumulative endpoint, the estrogen activity index (EAI), for priority setting to identify chemicals most likely possessing estrogen activity for early entry into screening. This index was then modeled using only a few theoretical molecular descriptors. The constructed MLR-QSAR model has been statistically validated for its predictive power, and can be proposed as a preliminary evaluative method to screen/prioritize estrogens according to their integrated estrogen activity, just starting from molecular structure.

  12. Beware of R2: simple, unambiguous assessment of the prediction accuracy of QSAR and QSPR models

    PubMed Central

    Alexander, D. L. J.; Tropsha, A.; Winkler, David A.

    2015-01-01

    The statistical metrics used to characterize the external predictivity of a model, i.e., how well it predicts the properties of an independent test set, have proliferated over the past decade. This paper clarifies some apparent confusion over the use of the coefficient of determination, R2, as a measure of model fit and predictive power in QSAR and QSPR modelling. R2 (or R2) has been used in various contexts in the literature in conjunction with training and test data, for both ordinary linear regression and regression through the origin as well as with linear and nonlinear regression models. We analyze the widely adopted model fit criteria suggested by Golbraikh and Tropsha1 in a strict statistical manner. Shortcomings in these criteria are identified and a clearer and simpler alternative method to characterize model predictivity is provided. The intent is not to repeat the well-documented arguments for model validation using test data, but to guide the application of R2 as a model fit statistic. Examples are used to illustrate both correct and incorrect use of R2. Reporting the root mean squared error or equivalent measures of dispersion, typically of more practical importance than R2, is also encouraged and important challenges in addressing the needs of different categories of users such as computational chemists, experimental scientists, and regulatory decision support specialists are outlined. PMID:26099013

  13. QSAR classification models for the screening of the endocrine-disrupting activity of perfluorinated compounds.

    PubMed

    Kovarich, S; Papa, E; Li, J; Gramatica, P

    2012-01-01

    Perfluorinated compounds (PFCs) are a class of emerging pollutants still widely used in different materials as non-adhesives, waterproof fabrics, fire-fighting foams, etc. Their toxic effects include potential for endocrine-disrupting activity, but the amount of experimental data available for these pollutants is limited. The use of predictive strategies such as quantitative structure-activity relationships (QSARs) is recommended under the REACH regulation, to fill data gaps and to screen and prioritize chemicals for further experimentation, with a consequent reduction of costs and number of tested animals. In this study, local classification models for PFCs were developed to predict their T4-TTR (thyroxin-transthyretin) competing potency. The best models were selected by maximizing the sensitivity and external predictive ability. These models, characterized by robustness, good predictive power and a defined applicability domain, were applied to predict the activity of 33 other PFCs of environmental concern. Finally, classification models recently published by our research group for T4-TTR binding of brominated flame retardants and for estrogenic and anti-androgenic activity were applied to the studied perfluorinated chemicals to compare results and to further evaluate the potential for these PFCs to cause endocrine disruption.

  14. 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.

  15. On an aspect of calculated molecular descriptors in QSAR studies of quinolone antibacterials.

    PubMed

    Ghosh, Payel; Thanadath, Megha; Bagchi, Manish C

    2006-08-01

    The re-emergence of tuberculosis infections, which are resistant to conventional drug therapy, has steadily risen in the last decade and as a result of that, fluoroquinolone drugs are being used as the second line of action. But there is hardly any study to examine specific structure activity relationships of quinolone antibacterials against mycobacteria. In this paper, an attempt has been made to establish a quantitative structure activity relationship modeling for a series of quinolone compounds against Mycobacterium fortuitum and Mycobacterium smegmatis. Due to lack of sufficient physicochemical data for the anti-mycobacterial compounds, it becomes very difficult to develop predictive methods based on experimental data. The present paper is an effort for the development of QSARs from the standpoint of physicochemical, constitutional, geometrical, electrostatic and topological indices. Molecular descriptors have been calculated solely from the chemical structure of N-1, C-7 and 8 substituted quinolone compounds and ridge regression models have been developed which can explain a better structure-activity relationship. Consideration of an intermolecular similarity analysis approach that led to a successful computer program development in PERL language has been used for comparing the influence of various molecular descriptors in different data subsets. The comparison of relative effectiveness of the calculated descriptors in our ridge regression model gives rise to some interesting results.

  16. 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

  17. Development, interpretation and temporal evaluation of a global QSAR of hERG electrophysiology screening data

    NASA Astrophysics Data System (ADS)

    Gavaghan, Claire L.; Arnby, Catrin Hasselgren; Blomberg, Niklas; Strandlund, Gert; Boyer, Scott

    2007-04-01

    A `global' model of hERG K+ channel was built to satisfy three basic criteria for QSAR models in drug discovery: (1) assessment of the applicability domain, (2) assuring that model decisions can be interpreted by medicinal chemists and (3) assessment of model performance after the model was built. A combination of D-optimal onion design and hierarchical partial least squares modelling was applied to construct a global model of hERG blockade in order to maximize the applicability domain of the model and to enhance its interpretability. Additionally, easily interpretable hERG specific fragment-based descriptors were developed. Model performance was monitored, throughout a time period of 15 months, after model implementation. It was found that after this time duration a greater proportion of molecules were outside the model's applicability domain and that these compounds had a markedly higher average prediction error than those from molecules within the model's applicability domain. The model's predictive performance deteriorated within 4 months after building, illustrating the necessity of regular updating of global models within a drug discovery environment.

  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. Development of QSAR model to predict the ecotoxicity of Vibrio fischeri using COSMO-RS descriptors.

    PubMed

    Ghanem, Ouahid Ben; Mutalib, M I Abdul; Lévêque, Jean-Marc; El-Harbawi, Mohanad

    2017-03-01

    Ionic liquids (ILs) are class of solvent whose properties can be modified and tuned to meet industrial requirements. However, a high number of potentially available cations and anions leads to an even increasing members of newly-synthesized ionic liquids, adding to the complexity of understanding on their impact on aquatic organisms. Quantitative structure activity∖property relationship (QSAR∖QSPR) technique has been proven to be a useful method for toxicity prediction. In this work,σ-profile descriptors were used to build linear and non-linear QSAR models to predict the ecotoxicities of a wide variety of ILs towards bioluminescent bacterium Vibrio fischeri. Linear model was constructed using five descriptors resulting in high accuracy prediction of 0.906. The model performance and stability were ascertained using k-fold cross validation method. The selected descriptors set from the linear model was then used in multilayer perceptron (MLP) technique to develop the non-linear model, the accuracy of the model was further enhanced achieving high correlation coefficient with the lowest value being 0.961 with the highest mean square error of 0.157.

  20. Assessing bioaccumulation of polybrominated diphenyl ethers for aquatic species by QSAR modeling.

    PubMed

    Mansouri, Kamel; Consonni, Viviana; Durjava, Mojca Kos; Kolar, Boris; Öberg, Tomas; Todeschini, Roberto

    2012-10-01

    Polybrominated diphenyl ethers (PBDEs) are used as flame retardants in textiles, foams and plastics. Highly bioaccumulative with toxic effects including developmental neurotoxicity estrogen and thyroid hormones disruption, they are considered as persistent organic pollutants (POPs) and have been found in human tissues, wildlife and biota worldwide. But only some of them are banned from EU market. For the environmental fate studies of these compounds the bioconcentration factor (BCF) is one of the most important endpoints to start with. We applied quantitative structure-activity relationships techniques to overcome the limited experimental data and avoid more animal testing. The aim of this work was to assess the bioaccumulation of PBDEs by means of QSAR. First, a BCF dataset of specifically conducted experiments was modeled. Then the study was extended by predicting the bioaccumulation and biomagnification factors using some experimental values from the literature. Molecular descriptors were calculated using DRAGON 6. The most relevant ones were selected and resulting models were compared paying attention to the applicability domain.

  1. 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.

  2. 3D-QSAR and docking studies of pentacycloundecylamines at the sigma-1 (σ1) receptor.

    PubMed

    Geldenhuys, Werner J; Novotny, Nicholas; Malan, Sarel F; Van der Schyf, Cornelis J

    2013-03-15

    Pentacycloundecylamine (PCU) derived compounds have been shown to be promising lead structures for the development of novel drug candidates aimed at a variety of neurodegenerative and psychiatric diseases. Here we show for the first time a 3D quantitative structure-activity relationship (3D-QSAR) for a series of aza-PCU-derived compounds with activity at the sigma-1 (σ1) receptor. A comparative molecular field analysis (CoMFA) model was developed with a partial least squares cross validated (q(2)) regression value of 0.6, and a non-cross validated r(2) of 0.9. The CoMFA model was effective at predicting the sigma-1 activities of a test set with an r(2) >0.7. We also describe here the docking of the PCU-derived compounds into a homology model of the sigma-1 (σ1) receptor, which was developed to gain insight into binding of these cage compounds to the receptor. Based on docking studies we evaluated in a [(3)H]pentazocine binding assay an oxa-PCU, NGP1-01 (IC50=1.78μM) and its phenethyl derivative (IC50=1.54μM). Results from these studies can be used to develop new compounds with specific affinity for the sigma-1(σ1) receptor.

  3. 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.

  4. Pyridones as NNRTIs against HIV-1 mutants: 3D-QSAR and protein informatics

    NASA Astrophysics Data System (ADS)

    Debnath, Utsab; Verma, Saroj; Jain, Surabhi; Katti, Setu B.; Prabhakar, Yenamandra S.

    2013-07-01

    CoMFA and CoMSIA based 3D-QSAR of HIV-1 RT wild and mutant (K103, Y181C, and Y188L) inhibitory activities of 4-benzyl/benzoyl pyridin-2-ones followed by protein informatics of corresponding non-nucleoside inhibitors' binding pockets from pdbs 2BAN, 3MED, 1JKH, and 2YNF were analysed to discover consensus features of the compounds for broad-spectrum activity. The CoMFA/CoMSIA models indicated that compounds with groups which lend steric-cum-electropositive fields in the vicinity of C5, hydrophobic field in the vicinity of C3 of pyridone region and steric field in aryl region produce broad-spectrum anti-HIV-1 RT activity. Also, a linker rendering electronegative field between pyridone and aryl moieties is common requirement for the activities. The protein informatics showed considerable alteration in residues 181 and 188 characteristics on mutation. Also, mutants' isoelectric points shifted in acidic direction. The study offered fresh avenues for broad-spectrum anti-HIV-1 agents through designing new molecules seeded with groups satisfying common molecular fields and concerns of mutating residues.

  5. Hydrophobicity-dependent QSARs to predict the toxicity of perfluorinated carboxylic acids and their mixtures.

    PubMed

    Wang, Ting; Lin, Zhifen; Yin, Daqiang; Tian, Dayong; Zhang, Yalei; Kong, Deyang

    2011-09-01

    Perfluorinated carboxylic acids (PFCAs) have wide industrial applications because of their unique physicochemical characteristics. However, data on the toxicity of much of this chemical class is lacking, particularly with regard to mixture toxicity. In this study, the toxicity of individual PFCAs and their mixtures to Photobacterium phosphoreum were observed. There was a tendency of increasing toxicity from C3 to C14 PFCA and a tendency of decreasing toxicity from C14 to C18 PFCA because of "the maximum tolerance of the cell membrane". Using the equivalent logK(OW) (octanol-water partition coefficient) and logK(SD) (C(18)-Empore™ disks/water partition coefficient), two linear quantitative structure-activity relationship (QSAR) models were formulated. This indicated both K(SD) and K(OW) can describe the hydrophobicity of a single chemical. However, for the PFCA mixtures, K(MD) is the more reasonable parameter than K(owmix) to describe the hydrophobicity because only the equivalent logK(MD) could be used to predict the mixture toxicity.

  6. QSAR analysis of blood-brain distribution: the influence of plasma and brain tissue binding.

    PubMed

    Lanevskij, Kiril; Dapkunas, Justas; Juska, Liutauras; Japertas, Pranas; Didziapetris, Remigijus

    2011-06-01

    The extent of brain delivery expressed as steady-state brain/blood distribution ratio (log BB) is the most frequently used parameter for characterizing central nervous system exposure of drugs and drug candidates. The aim of the current study was to propose a physicochemical QSAR model for log BB prediction. Model development involved the following steps: (i) A data set consisting of 470 experimental log BB values determined in rodents was compiled and verified to ensure that selected data represented drug disposition governed by passive diffusion across blood-brain barrier. (ii) Available log BB values were corrected for unbound fraction in plasma to separate the influence of drug binding to brain and plasma constituents. (iii) The resulting ratios of total brain to unbound plasma concentrations reflecting brain tissue binding were described by a nonlinear ionization-specific model in terms of octanol/water log P and pK(a). The results of internal and external validation demonstrated good predictive power of the obtained model as both log BB and brain tissue binding strength were predicted with residual mean square error of 0.4 log units. The statistical parameters were similar among training and validation sets, indicating that the model is not likely to be overfitted.

  7. 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.

  8. 3D-QSAR study of hallucinogenic phenylalkylamines by using CoMFA approach

    NASA Astrophysics Data System (ADS)

    Zhang, Zhuoyong; An, Liying; Hu, Wenxiang; Xiang, Yuhong

    2007-04-01

    The three-dimensional quantitative structure-activity relationship (3D-QSAR) has been studied on 90 hallucinogenic phenylalkylamines by the comparative molecular field analysis (CoMFA). Two conformations were compared during the modeling. Conformation I referred to the amino group close to ring position 6 and conformation II related to the amino group trans to the phenyl ring. Satisfactory results were obtained by using both conformations. There were still differences between the two models. The model based on conformation I got better statistical results than the one about conformation II. And this may suggest that conformation I be preponderant when the hallucinogenic phenylalkylamines interact with the receptor. To further confirm the predictive capability of the CoMFA model, 18 compounds with conformation I were randomly selected as a test set and the remaining ones as training set. The best CoMFA model based on the training set had a cross-validation coefficient q 2 of 0.549 at five components and non cross-validation coefficient R 2 of 0.835, the standard error of estimation was 0.219. The model showed good predictive ability in the external test with a coefficient R pre 2 of 0.611. The CoMFA coefficient contour maps suggested that both steric and electrostatic interactions play an important role. The contributions from the steric and electrostatic fields were 0.450 and 0.550, respectively.

  9. 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.

  10. 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.

  11. 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

  12. 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...

  13. 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.

  14. Hawaii bibliographic database

    NASA Astrophysics Data System (ADS)

    Wright, Thomas L.; Takahashi, Taeko Jane

    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 s or (if no ) 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.

  15. Enhancing medical database security.

    PubMed

    Pangalos, G; Khair, M; Bozios, L

    1994-08-01

    A methodology for the enhancement of database security in a hospital environment is presented in this paper which is based on both the discretionary and the mandatory database security policies. In this way the advantages of both approaches are combined to enhance medical database security. An appropriate classification of the different types of users according to their different needs and roles and a User Role Definition Hierarchy has been used. The experience obtained from the experimental implementation of the proposed methodology in a major general hospital is briefly discussed. The implementation has shown that the combined discretionary and mandatory security enforcement effectively limits the unauthorized access to the medical database, without severely restricting the capabilities of the system.

  16. Uranium Location Database Compilation

    EPA Pesticide Factsheets

    EPA has compiled mine location information from federal, state, and Tribal agencies into a single database as part of its investigation into the potential environmental hazards of wastes from abandoned uranium mines in the western United States.

  17. Livestock Anaerobic Digester Database

    EPA Pesticide Factsheets

    The Anaerobic Digester Database provides basic information about anaerobic digesters on livestock farms in the United States, organized in Excel spreadsheets. It includes projects that are under construction, operating, or shut down.

  18. 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.

  19. 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)

  20. 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.

  1. The prospects for using (Q)SARs in a changing political environment--high expectations and a key role for the European Commission's joint research centre.

    PubMed

    Worth, A P; Van Leeuwen, C J; Hartung, T

    2004-01-01

    Recent policy developments in the European union (EU) and within the Organisation for Economic Cooperation and Development (OECD) have placed increased emphasis on the use of structure-activity relationships (SARs) and quantitative structure-activity relationships (QSARs), collectively referred to as (Q)SARs, within various regulatory programmes for the assessment of chemicals and products. The most significant example within the EU is the European commission's proposal (of 29 October 2003) to introduce a new system for managing chemicals (called REACH), which calls for an increased use of (Q)SARs and other non-animal methods, especially for the assessment of low production volume chemicals. Another development within the EU is the Seventh Amendment to the Cosmetics Directive, which foresees the phasing out of animal testing on cosmetics, combined with the imposition of marketing bans on cosmetics that have been tested on animals after certain deadlines. At the same time, the Existing Chemicals programme within the OECD is investigating ways of increasing the use of chemical category approaches, which depend heavily on the use of (Q)SARs, activity-activity relationships and read-across. Such developments are placing an enormous challenge on industry, regulatory bodies, and on the European commission's Joint Research Centre (JRC), which is responsible for providing independent scientific advice to policy makers in the European Commission and the Member States. This paper reviews the different scientific and regulatory purposes for which reliable (Q)SARs could be used, and describes the current work of the JRC in providing scientific support for the development, validation and implementation of (Q)SARs.

  2. 3D-QSAR and docking studies on 4-anilinoquinazoline and 4-anilinoquinoline epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors

    NASA Astrophysics Data System (ADS)

    Assefa, Haregewein; Kamath, Shantaram; Buolamwini, John K.

    2003-08-01

    The overexpression and/or mutation of the epidermal growth factor receptor (EGFR) tyrosine kinase has been observed in many human solid tumors, and is under intense investigation as a novel anticancer molecular target. Comparative 3D-QSAR analyses using different alignments were undertaken employing comparative molecular field analysis (CoMFA) and comparative molecular similarity analysis (CoMSIA) for 122 anilinoquinazoline and 50 anilinoquinoline inhibitors of EGFR kinase. The SYBYL multifit alignment rule was applied to three different conformational templates, two obtained from a MacroModel Monte Carlo conformational search, and one from the bound conformation of erlotinib in complex with EGFR in the X-ray crystal structure. In addition, a flexible ligand docking alignment obtained with the GOLD docking program, and a novel flexible receptor-guided consensus dynamics alignment obtained with the DISCOVER program in the INSIGHTII modeling package were also investigated. 3D-QSAR models with q2 values up to 0.70 and r2 values up to 0.97 were obtained. Among the 4-anilinoquinazoline set, the q2 values were similar, but the ability of the different conformational models to predict the activities of an external test set varied considerably. In this regard, the model derived using the X-ray crystallographically determined bioactive conformation of erlotinib afforded the best predictive model. Electrostatic, hydrophobic and H-bond donor descriptors contributed the most to the QSAR models of the 4-anilinoquinazolines, whereas electrostatic, hydrophobic and H-bond acceptor descriptors contributed the most to the 4-anilinoquinoline QSAR, particularly the H-bond acceptor descriptor. A novel receptor-guided consensus dynamics alignment has also been introduced for 3D-QSAR studies. This new alignment method may incorporate to some extent ligand-receptor induced fit effects into 3D-QSAR models.

  3. 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.

  4. 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.

  5. Human mapping databases.

    PubMed

    Talbot, C; Cuticchia, A J

    2001-05-01

    This unit concentrates on the data contained within two human genome databasesGDB (Genome Database) and OMIM (Online Mendelian Inheritance in Man)and includes discussion of different methods for submitting and accessing data. An understanding of electronic mail, FTP, and the use of a World Wide Web (WWW) navigational tool such as Netscape or Internet Explorer is a prerequisite for utilizing the information in this unit.

  6. 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.

  7. 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

  8. 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.

  9. 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.

  10. 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

  11. 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.

  12. 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

  13. 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.

  14. Structural insights of JAK2 inhibitors: pharmacophore modeling and ligand-based 3D-QSAR studies of pyrido-indole derivatives.

    PubMed

    Gade, Deepak Reddy; Kunala, Pavan; Raavi, Divya; Reddy, Pavan Kumar K; Prasad, Rajendra V V S

    2015-04-01

    In this study we have performed pharmacophore modeling and built a 3D QSAR model for pyrido-indole derivatives as Janus Kinase 2 inhibitors. An efficient pharmacophore has been identified from a data set of 51 molecules and the identified pharmacophore hypothesis consisted of one hydrogen bond acceptor, two hydrogen bond donors and three aromatic rings, i.e. ADDRRR. A powerful 3D-QSAR model has also been constructed by employing Partial Least Square regression analysis with a regression coefficient of 0.97 (R(2)) and Q(2) of 0.95, and Pearson-R of 0.98.

  15. 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)

  16. 2D QSAR Study for Gemfibrozil Glucuronide as the Mechanism-based Inhibitor of CYP2C8

    PubMed Central

    Taxak, N.; Bharatam, P. V.

    2013-01-01

    Mechanism-based inhibition of cytochrome P450 involves the bioactivation of the drug to a reactive metabolite, which leads to cytochrome inhibition via various mechanisms. This is generally seen in the Phase I of drug metabolism. However, gemfibrozil (hypolipidemic drug) leads to mechanism-based inhibition after generating glucuronide conjugate (gemfibrozil acyl-β-glucuronide) in the Phase II metabolism reaction. The mechanism involves the covalent binding of the benzyl radical (generated from the oxidation of aromatic methyl group in conjugate) to the heme of CYP2C8. This article deals with the development of a 2D QSAR model based on the inhibitory potential of gemfibrozil, its analogues and corresponding glucuronide conjugates in inhibiting the CYP2C8-catalysed amodiaquine N-deethylation. The 2D QSAR model was developed using multiple linear regression analysis in Accelrys Discovery Studio 2.5 and helps in identifying the descriptors, which are actually contributing to the inhibitory potency of the molecules studied. The built model was further validated using leave one out method. The best quantitative structure activity relationship model was selected having a correlation coefficient (r) of 0.814 and cross-validated correlation coefficient (q2) of 0.799. 2D QSAR revealed the importance of volume descriptor (Mor15v), shape descriptor (SP09) and 3D matrix-based descriptor (SpMax_RG) in defining the activity for this series of molecules. It was observed that volume and 3D matrix-based descriptors were crucial in imparting higher potency to gemfibrozil glucuronide conjugate, as compared with other molecules. The results obtained from the present study may be useful in predicting the inhibitory potential (IC50 for CYP2C8 inhibition) of the glucuronide conjugates of new molecules and compare with the standard gemfibrozil acyl-β-glucuronide (in terms of pIC50 values) in early stages of drug discovery and development. PMID:24591743

  17. Molecular docking and 3D-QSAR studies on gag peptide analogue inhibitors interacting with human cyclophilin A.

    PubMed

    Cui, Meng; Huang, Xiaoqin; Luo, Xiaomin; Briggs, James M; Ji, Ruyun; Chen, Kaixian; Shen, Jianhua; Jiang, Hualiang

    2002-11-21

    The interaction of a series gag peptide analogues with human cyclophilin A (hCypA) have been studied employing molecular docking and 3D-QSAR approaches. The Lamarckian Genetic Algorithm (LGA) and divide-and-conquer methods were applied to locate the binding orientations and conformations of the inhibitors interacting with hCypA. Good correlations between the calculated interaction free energies and experimental inhibitory activities suggest that the binding conformations of these inhibitors are reasonable. A novel interaction model was identified for inhibitors 11, 15, and 17 whose N-termini were modified by addition of the deaminovaline (Dav) group and the C-termini of 15 and 17 were modified by addition of a benzyl group. Accordingly, two new binding sites (sites A and D in Figure 1) were revealed, which show a strong correlation with inhibitor potency and thus can be used as a starting point for new inhibitor design. In addition, two predictive 3D-QSAR models were obtained by CoMFA and CoMSIA analyses based on the binding conformations derived from the molecular docking calculations. The reasonable r(cross)(2) (cross-validated) values 0.738 and 0.762 were obtained for CoMFA and CoMSIA models, respectively. The predictive ability of these models was validated by four peptide analogues test set. The CoMFA and CoMSIA field distributions are in general agreement with the structural characteristics of the binding groove of hCypA. This indicates the reasonableness of the binding model of the inhibitors with hCypA. Considering all these results together with the valuable clues of binding from references published recently, reasonable pharmacophore elements have been suggested, demonstrating that the 3D-QSAR models about peptide analogue inhibitors are expected to be further employed in predicting activities of the novel compounds for inhibiting hCypA.

  18. 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.

  19. Attitudes towards abortion in the Danish population.

    PubMed

    Norup, Michael

    1997-10-01

    This article reports the results of a survey, by mailed questionnaire, of the attitudes among a sample of the Danish population towards abortion for social and genetic reasons. Of 1080 questionnaires sent to a random sample of persons between 18 and 45 years, 731 (68%) were completed and returned. A great majority of the respondents were liberal towards early abortion both for social reasons and in case of minor disease. In contrast, there was controversy about late abortions for social reasons and in the case of Down syndrome. Further there was strong reluctance to accept late abortion in case of minor disease. An analysis of the response patterns showed that most of the respondents had gradualist views on abortion, i.e. they would allow all early abortions, but only abortions for some reasons later in pregnancy. It was also found that the number who would find an early abortion acceptable in general was much higher than the number who would accept it in their own case. These findings suggest that a great part of the resistance towards abortion does not rest on a concern for the rights and interests for the fetus. Instead it may be explained on a view according to which fetal life is ascribed intrinsic moral value.

  20. 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.

  1. 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.

  2. Synthesis, insecticidal activity, and QSAR of novel nitromethylene neonicotinoids with tetrahydropyridine fixed cis configuration and exo-ring ether modification.

    PubMed

    Tian, Zhongzhen; Shao, Xusheng; Li, Zhong; Qian, Xuhong; Huang, Qingchun

    2007-03-21

    To keep the nitro group in the cis position, a series of nitromethylene neonicotinoids containing a tetrahydropyridine ring with exo-ring ether modifications were designed and synthesized. All of the compounds were characterized and confirmed by 1H NMR, high-resolution mass spectroscopy, elemental analysis, and IR. The bioassay tests showed that some of them exhibited good insecticidal activities against pea aphids. On the basis of 10 nitromethylene derivatives, the quantitative structure-bioactivity relationship (QSAR) was analyzed and established. The results suggested that AlogP98 and Dipole_Mopac might be the important parameters related with biological activities.

  3. 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

  4. Debunking the Idea that Ligand Efficiency Indices Are Superior to pIC50 as QSAR Activities.

    PubMed

    Sheridan, Robert P

    2016-11-28

    Several papers have appeared in which a ligand efficiency index instead of pIC50 is used as the activity in QSAR. The claim is that better fits and predictions are obtained with ligand efficiency. We show on both public-domain and in-house data sets that the apparent superiority is a statistical artifact that occurs when ligand efficiency indices are correlated with the physical property included in their definition (number of non-hydrogens, ALOGP, TPSA, etc.) and when the property is easier to predict than the original pIC50.

  5. 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.

  6. NASA Records Database

    NASA Technical Reports Server (NTRS)

    Callac, Christopher; Lunsford, Michelle

    2005-01-01

    The NASA Records Database, comprising a Web-based application program and a database, is used to administer an archive of paper records at Stennis Space Center. The system begins with an electronic form, into which a user enters information about records that the user is sending to the archive. The form is smart : it provides instructions for entering information correctly and prompts the user to enter all required information. Once complete, the form is digitally signed and submitted to the database. The system determines which storage locations are not in use, assigns the user s boxes of records to some of them, and enters these assignments in the database. Thereafter, the software tracks the boxes and can be used to locate them. By use of search capabilities of the software, specific records can be sought by box storage locations, accession numbers, record dates, submitting organizations, or details of the records themselves. Boxes can be marked with such statuses as checked out, lost, transferred, and destroyed. The system can generate reports showing boxes awaiting destruction or transfer. When boxes are transferred to the National Archives and Records Administration (NARA), the system can automatically fill out NARA records-transfer forms. Currently, several other NASA Centers are considering deploying the NASA Records Database to help automate their records archives.

  7. ADANS database specification

    SciTech Connect

    1997-01-16

    The purpose of the Air Mobility Command (AMC) Deployment Analysis System (ADANS) Database Specification (DS) is to describe the database organization and storage allocation and to provide the detailed data model of the physical design and information necessary for the construction of the parts of the database (e.g., tables, indexes, rules, defaults). The DS includes entity relationship diagrams, table and field definitions, reports on other database objects, and a description of the ADANS data dictionary. ADANS is the automated system used by Headquarters AMC and the Tanker Airlift Control Center (TACC) for airlift planning and scheduling of peacetime and contingency operations as well as for deliberate planning. ADANS also supports planning and scheduling of Air Refueling Events by the TACC and the unit-level tanker schedulers. ADANS receives input in the form of movement requirements and air refueling requests. It provides a suite of tools for planners to manipulate these requirements/requests against mobility assets and to develop, analyze, and distribute schedules. Analysis tools are provided for assessing the products of the scheduling subsystems, and editing capabilities support the refinement of schedules. A reporting capability provides formatted screen, print, and/or file outputs of various standard reports. An interface subsystem handles message traffic to and from external systems. The database is an integral part of the functionality summarized above.

  8. The Chandra Bibliography Database

    NASA Astrophysics Data System (ADS)

    Rots, A. H.; Winkelman, S. L.; Paltani, S.; Blecksmith, S. E.; Bright, J. D.

    2004-07-01

    Early in the mission, the Chandra Data Archive started the development of a bibliography database, tracking publications in refereed journals and on-line conference proceedings that are based on Chandra observations, allowing our users to link directly to articles in the ADS from our archive, and to link to the relevant data in the archive from the ADS entries. Subsequently, we have been working closely with the ADS and other data centers, in the context of the ADEC-ITWG, on standardizing the literature-data linking. We have also extended our bibliography database to include all Chandra-related articles and we are also keeping track of the number of citations of each paper. Obviously, in addition to providing valuable services to our users, this database allows us to extract a wide variety of statistical information. The project comprises five components: the bibliography database-proper, a maintenance database, an interactive maintenance tool, a user browsing interface, and a web services component for exchanging information with the ADS. All of these elements are nearly mission-independent and we intend make the package as a whole available for use by other data centers. The capabilities thus provided represent support for an essential component of the Virtual Observatory.

  9. FishTraits Database

    USGS Publications Warehouse

    Angermeier, Paul L.; Frimpong, Emmanuel A.

    2009-01-01

    The need for integrated and widely accessible sources of species traits data to facilitate studies of ecology, conservation, and management has motivated development of traits databases for various taxa. In spite of the increasing number of traits-based analyses of freshwater fishes in the United States, no consolidated database of traits of this group exists publicly, and much useful information on these species is documented only in obscure sources. The largely inaccessible and unconsolidated traits information makes large-scale analysis involving many fishes and/or traits particularly challenging. FishTraits is a database of >100 traits for 809 (731 native and 78 exotic) fish species found in freshwaters of the conterminous United States, including 37 native families and 145 native genera. The database contains information on four major categories of traits: (1) trophic ecology, (2) body size and reproductive ecology (life history), (3) habitat associations, and (4) salinity and temperature tolerances. Information on geographic distribution and conservation status is also included. Together, we refer to the traits, distribution, and conservation status information as attributes. Descriptions of attributes are available here. Many sources were consulted to compile attributes, including state and regional species accounts and other databases.

  10. Shuttle Hypervelocity Impact Database

    NASA Technical Reports Server (NTRS)

    Hyde, James L.; Christiansen, Eric L.; Lear, Dana M.

    2011-01-01

    With three missions outstanding, the Shuttle Hypervelocity Impact Database has nearly 3000 entries. The data is divided into tables for crew module windows, payload bay door radiators and thermal protection system regions, with window impacts compromising just over half the records. In general, the database provides dimensions of hypervelocity impact damage, a component level location (i.e., window number or radiator panel number) and the orbiter mission when the impact occurred. Additional detail on the type of particle that produced the damage site is provided when sampling data and definitive analysis results are available. Details and insights on the contents of the database including examples of descriptive statistics will be provided. Post flight impact damage inspection and sampling techniques that were employed during the different observation campaigns will also be discussed. Potential enhancements to the database structure and availability of the data for other researchers will be addressed in the Future Work section. A related database of returned surfaces from the International Space Station will also be introduced.

  11. Shuttle Hypervelocity Impact Database

    NASA Technical Reports Server (NTRS)

    Hyde, James I.; Christiansen, Eric I.; Lear, Dana M.

    2011-01-01

    With three flights remaining on the manifest, the shuttle impact hypervelocity database has over 2800 entries. The data is currently divided into tables for crew module windows, payload bay door radiators and thermal protection system regions, with window impacts compromising just over half the records. In general, the database provides dimensions of hypervelocity impact damage, a component level location (i.e., window number or radiator panel number) and the orbiter mission when the impact occurred. Additional detail on the type of particle that produced the damage site is provided when sampling data and definitive analysis results are available. The paper will provide details and insights on the contents of the database including examples of descriptive statistics using the impact data. A discussion of post flight impact damage inspection and sampling techniques that were employed during the different observation campaigns will be presented. Future work to be discussed will be possible enhancements to the database structure and availability of the data for other researchers. A related database of ISS returned surfaces that are under development will also be introduced.

  12. Cumulative Risks of Foster Care Placement for Danish Children

    PubMed Central

    Fallesen, Peter; Emanuel, Natalia; Wildeman, Christopher

    2014-01-01

    Although recent research suggests that the cumulative risk of foster care placement is far higher for American children than originally suspected, little is known about the cumulative risk of foster care placement in other countries, which makes it difficult to gauge the degree to which factor foster care placement is salient in other contexts. In this article, we provide companion estimates to those provided in recent work on the US by using Danish registry data and synthetic cohort life tables to show how high and unequally distributed the cumulative risk of foster care placement is for Danish children. Results suggest that at the beginning of the study period (in 1998) the cumulative risk of foster care placement for Danish children was roughly in line with the risk for American children. Yet, by the end of the study period (2010), the risk had declined to half the risk for American children. Our results also show some variations by parental ethnicity and sex, but these differences are small. Indeed, they appear quite muted relative to racial/ethnic differences in these risks in the United States. Last, though cumulative risks are similar between Danish and American children (especially at the beginning of the study period), the age-specific risk profiles are markedly different, with higher risks for older Danish children than for older American children. PMID:25299657

  13. Cumulative risks of foster care placement for Danish children.

    PubMed

    Fallesen, Peter; Emanuel, Natalia; Wildeman, Christopher

    2014-01-01

    Although recent research suggests that the cumulative risk of foster care placement is far higher for American children than originally suspected, little is known about the cumulative risk of foster care placement in other countries, which makes it difficult to gauge the degree to which factor foster care placement is salient in other contexts. In this article, we provide companion estimates to those provided in recent work on the US by using Danish registry data and synthetic cohort life tables to show how high and unequally distributed the cumulative risk of foster care placement is for Danish children. Results suggest that at the beginning of the study period (in 1998) the cumulative risk of foster care placement for Danish children was roughly in line with the risk for American children. Yet, by the end of the study period (2010), the risk had declined to half the risk for American children. Our results also show some variations by parental ethnicity and sex, but these differences are small. Indeed, they appear quite muted relative to racial/ethnic differences in these risks in the United States. Last, though cumulative risks are similar between Danish and American children (especially at the beginning of the study period), the age-specific risk profiles are markedly different, with higher risks for older Danish children than for older American children.

  14. Liberalization in the Danish waste sector: an institutional perspective.

    PubMed

    Kørnøv, Lone; Hill, Amanda Louise; Busck, Ole; Løkke, Søren

    2016-12-01

    The push for creating a more competitive and liberalized system for traditional public services, including waste management, has been on the European agenda since the late 1980s. In 2008, changes were made in EU waste legislation allowing source-separated industrial/commercial waste that is suitable for incineration to be traded within the European market. This change has had broad implications for the Danish waste sector, which is characterized by institutionalized municipal control with all streams of waste and municipal ownership of the major treatment facilities allowing the municipal sector to integrate combustible waste in local heat and power generation. This article, applying an institutional approach, maps the institutions and actors of the Danish waste sector and analyses how the regulatory as well as normative pressure to liberalize has been met and partly neutralized in the institutional and political context. The new Danish regulation of 2010 has thus accommodated the specific requirement for liberalization, but in fact only represents a very small step towards a market-based waste management system. On the one hand, by only liberalizing industrial/commercial waste, the Danish Government chose to retain the main features of the established waste system favouring municipal control and hence the institutionalized principles of decentralized enforcement of environmental legislation as well as welfare state considerations. On the other hand, this has led to a technological and financial deadlock, particularly when it comes to reaching the recycling targets of EU, which calls for further adjustments of the Danish waste sector.

  15. VIEWCACHE: An incremental database access method for autonomous interoperable databases

    NASA Technical Reports Server (NTRS)

    Roussopoulos, Nick; Sellis, Timoleon

    1991-01-01

    The objective is to illustrate the concept of incremental access to distributed databases. An experimental database management system, ADMS, which has been developed at the University of Maryland, in College Park, uses VIEWCACHE, a database access method based on incremental search. VIEWCACHE is a pointer-based access method that provides a uniform interface for accessing distributed databases and catalogues. The compactness of the pointer structures formed during database browsing and the incremental access method allow the user to search and do inter-database cross-referencing with no actual data movement between database sites. Once the search is complete, the set of collected pointers pointing to the desired data are dereferenced.

  16. Open Geoscience Database

    NASA Astrophysics Data System (ADS)

    Bashev, A.

    2012-04-01

    Currently there is an enormous amount of various geoscience databases. Unfortunately the only users of the majority of the databases are their elaborators. There are several reasons for that: incompaitability, specificity of tasks and objects and so on. However the main obstacles for wide usage of geoscience databases are complexity for elaborators and complication for users. The complexity of architecture leads to high costs that block the public access. The complication prevents users from understanding when and how to use the database. Only databases, associated with GoogleMaps don't have these drawbacks, but they could be hardly named "geoscience" Nevertheless, open and simple geoscience database is necessary at least for educational purposes (see our abstract for ESSI20/EOS12). We developed a database and web interface to work with them and now it is accessible at maps.sch192.ru. In this database a result is a value of a parameter (no matter which) in a station with a certain position, associated with metadata: the date when the result was obtained; the type of a station (lake, soil etc); the contributor that sent the result. Each contributor has its own profile, that allows to estimate the reliability of the data. The results can be represented on GoogleMaps space image as a point in a certain position, coloured according to the value of the parameter. There are default colour scales and each registered user can create the own scale. The results can be also extracted in *.csv file. For both types of representation one could select the data by date, object type, parameter type, area and contributor. The data are uploaded in *.csv format: Name of the station; Lattitude(dd.dddddd); Longitude(ddd.dddddd); Station type; Parameter type; Parameter value; Date(yyyy-mm-dd). The contributor is recognised while entering. This is the minimal set of features that is required to connect a value of a parameter with a position and see the results. All the complicated data

  17. ARTI Refrigerant Database

    SciTech Connect

    Calm, J.M.

    1992-04-30

    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. The database provides bibliographic citations and abstracts for publications that may be useful in research and design of air- conditioning and refrigeration equipment. The complete documents are not included, though some may be added at a later date. The database identifies sources of specific information on R-32, R-123, R-124, R- 125, R-134a, R-141b, R142b, R-143a, R-152a, R-290 (propane), R-717 (ammonia), ethers, and others as well as azeotropic and zeotropic blends of these fluids. It addresses polyalkylene glycol (PAG), ester, and other lubricants. It also references documents addressing compatibility of refrigerants and lubricants with metals, plastics, elastomers, motor insulation, and other materials used in refrigerant circuits.

  18. The PROSITE database

    PubMed Central

    Hulo, Nicolas; Bairoch, Amos; Bulliard, Virginie; Cerutti, Lorenzo; De Castro, Edouard; Langendijk-Genevaux, Petra S.; Pagni, Marco; Sigrist, Christian J. A.

    2006-01-01

    The PROSITE database consists of a large collection of biologically meaningful signatures that are described as patterns or profiles. Each signature is linked to a documentation that provides useful biological information on the protein family, domain or functional site identified by the signature. The PROSITE database is now complemented by a series of rules that can give more precise information about specific residues. During the last 2 years, the documentation and the ScanProsite web pages were redesigned to add more functionalities. The latest version of PROSITE (release 19.11 of September 27, 2005) contains 1329 patterns and 552 profile entries. Over the past 2 years more than 200 domains have been added, and now 52% of UniProtKB/Swiss-Prot entries (release 48.1 of September 27, 2005) have a cross-reference to a PROSITE entry. The database is accessible at . PMID:16381852

  19. Medical database security evaluation.

    PubMed

    Pangalos, G J

    1993-01-01

    Users of medical information systems need confidence in the security of the system they are using. They also need a method to evaluate and compare its security capabilities. Every system has its own requirements for maintaining confidentiality, integrity and availability. In order to meet these requirements a number of security functions must be specified covering areas such as access control, auditing, error recovery, etc. Appropriate confidence in these functions is also required. The 'trust' in trusted computer systems rests on their ability to prove that their secure mechanisms work as advertised and cannot be disabled or diverted. The general framework and requirements for medical database security and a number of parameters of the evaluation problem are presented and discussed. The problem of database security evaluation is then discussed, and a number of specific proposals are presented, based on a number of existing medical database security systems.

  20. Mouse genome database 2016

    PubMed Central

    Bult, Carol J.; Eppig, Janan T.; Blake, Judith A.; Kadin, James A.; Richardson, Joel E.

    2016-01-01

    The Mouse Genome Database (MGD; http://www.informatics.jax.org) is the primary community model organism database for the laboratory mouse and serves as the source for key biological reference data related to mouse genes, gene functions, phenotypes and disease models with a strong emphasis on the relationship of these data to human biology and disease. As the cost of genome-scale sequencing continues to decrease and new technologies for genome editing become widely adopted, the laboratory mouse is more important than ever as a model system for understanding the biological significance of human genetic variation and for advancing the basic research needed to support the emergence of genome-guided precision medicine. Recent enhancements to MGD include new graphical summaries of biological annotations for mouse genes, support for mobile access to the database, tools to support the annotation and analysis of sets of genes, and expanded support for comparative biology through the expansion of homology data. PMID:26578600